Cognitive Brain Research Unit Department of Psychology University of Helsinki, Finland BioMag Laboratory, HUSLAB Helsinki University Central Hospital, Finland

Neurochemical regulation of auditory information processing studied with EEG/MEG: application to schizophrenia

Milena Korostenskaja

DOCTORAL DISSERTATION

To be presented, with the permission of the Faculty of Behavioural Sciences of the University of Helsinki, for public examination in Auditorium (Luentosali) 3, Helsinki University Central Hospital (Meilahden sairaala), Haartmaninkatu 4 on the 3rd of October, 2008 at 12:00 noon.

Helsinki, 2008

1 Supervisor

Seppo Kähkönen, M.D., Ph.D., Docent Cognitive Brain Research Unit, Department of Psychology, Faculty of Behavioural Sciences, University of Helsinki, Finland; BioMag Laboratory, HUSLAB, Helsinki University Central Hospital, Finland

Reviewers

Judith M. Ford, Ph.D., Professor of Psychiatry Co-Director, Laboratory of Clinical and Cognitive Neuroscience, University of California, San-Francisco, California, USA

Jyrki Ahveninen, Ph.D., Docent Instructor in Radiology, Athinoula A. Martinos Center for Biomedical Imaging, MGH/MIT/Harvard Medical School, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA

Opponent

Heikki Hämäläinen, Ph.D., Professor Department of Psychology, University of Turku, Turku, Finland

Cover page illustration made by Ruslan Korostenskij

ISBN 978-952-10-4930-9 (paperback) ISBN 978-952-10-4931-6 (PDF) (http://ethesis.helsinki.fi) Printed in UAB “Biznio masinu kompanija”, Vilnius, Lithuania Helsinki 2008

2 To my mother Liudmila Grigorjevna Grishina To my father Gennadij Andrejevich Grishin With love, gratitude and respect

3 ABSTRACT

Cognitive impairments of attention, memory and executive functions are a fundamental feature of the pathophysiology of schizophrenia. The neurophysiological and neurochemical changes in the auditory cortex are shown to underlie cognitive impairments in schizophrenia patients. Functional state of the neural substrate of auditory information processing could be objectively and non-invasively probed with auditory event-related potentials (ERPs) and event-related fields (ERFs). In the current work, we explored the neurochemical effect on the neural origins of auditory information processing in relation to schizophrenia. By means of ERPs/ERFs we aimed to determine how neural substrates of auditory information processing are modulated by antipsychotic medication in schizophrenia spectrum patients (Studies I, II) and by neuropharmacological challenges in healthy human subjects (Studies III, IV). First, with auditory ERPs we investigated the effects of olanzapine (Study I) and risperidone (Study II) in a group of patients with schizophrenia spectrum disorders. After 2 and 4 weeks of treatment, olanzapine has no significant effects on mismatch negativity (MMN) and P300, which, as it has been suggested, respectively reflect preattentive and attention-dependent information processing. After 2 weeks of treatment, risperidone has no significant effect on P300, however risperidone reduces P200 amplitude. This latter effect of risperidone on neural resources responsible for P200 generation could be partly explained through the action of dopamine. Subsequently, we used simultaneous EEG/MEG to investigate the effects of memantine (Study III) and methylphenidate (Study IV) in healthy subjects. We found that memantine modulates MMN response without changing other ERP components. This could be interpreted as being due to the possible influence of memantine through the NMDA receptors on auditory change-detection mechanism, with processing of auditory stimuli remaining otherwise unchanged. Further, we found that methylphenidate does not modulate the MMN response. This finding could indicate no association between catecholaminergic activities and electrophysiological measures of preattentive auditory discrimination processes reflected in the MMN. However, methylphenidate decreases the P200 amplitudes. This could be interpreted as a modulation of auditory information processing reflected in P200 by dopaminergic and noradrenergic systems. Taken together, our set of studies indicates a complex pattern of neurochemical influences produced by the antipsychotic drugs in the neural substrate of auditory information processing in patients with schizophrenia spectrum disorders and by the pharmacological challenges in healthy subjects studied with ERPs and ERFs.

4 TIIVISTELMÄ

Kuuloinformaation käsittelyn neurokemiallinen säätely terveillä ja skitsofreniapotilailla. MEG/EEG tutkimus

Skitsofreniapotilailla on usein psykoottisten oireiden ohella kognitiivisia ongelmia esimerkiksi muistissa ja tarkkavaisuudessa, joihin vanhemmilla psykoosilääkkeillä ei ole vaikutusta. Viime vuosina on kehitetty uusia psykoosilääkkeitä, joiden on arveltu parantavan kognitiivisia oireita. Tässä työssä haluttiin selvittää uusien psykoosilääkkeiden vaikutuksia aivosähköisiin kognitiivisiin mittareihin elektroenkefalografia (EEG)- menetelmällä skitsofreniaspektrin potilailla. 4-viikon mittaisilla risperidoni- ja olantsapiinihoidoilla ei ollut vaikutusta mismatch negatiivisuus - eli MMN - ja P3- vasteisiin, jotka heijastavat tarkkaavaisuusprosessien eri vaiheita. Kuitenkin risperidoni pienensi P2-vastetta, mikä voi heijastaa muutosta potilaiden kognitiivisissa toiminnoissa. Yhdistetyllä MEG/EEG-menetelmällä tutkittiin terveillä koehenkilöillä metyylifenidaatin ja memantiinin vaikutuksia MMN-vasteeseen, jotta saataisiin selvyyttä tarkkaavaisuuden neurokemiallisesta säätelystä. Kerta-annos metyylifenitaaattia ei vaikuttanut MMN- vasteeseen, mutta se pienensi P2-vastetta. Kerta-annos memantiinia suurensi MMN- vastetta EEG:ssä, muttei magnetoenkefalografiassa. Kiihdyttävä glutamaattivälittäjäaine saattaa osallistua tarkkaavaisuuden säätelyyn etuaivokuorella. Risperidonilla, muttei olantsapiinillä oli vaikutuksia aivosähköisiin kognitiivisiin mittareihin lyhyen hoidon jälkeen, mikä voi välittyä dopamiinin kautta.

5 ACKNOWLEDGEMENTS

This collaborative research work was carried out in the BioMag Laboratory, HUSLAB, Helsinki University Central Hospital, Finland and Laboratory of Electrophysiological Investigations, Republican Vilnius Psychiatric Hospital, Lithuania. I would like to express my gratitude to my supervisor Doc. Dr. Seppo Kähkönen for providing me with the opportunity to undertake this research and for his encouragement throughout. I’m grateful to both my reviewers Prof. Judith Ford and Dr. Jyrki Ahveninen for the best reviews I’ve ever had. I express my warmest thanks to Acad. Prof. Risto Näätänen for providing me with the opportunity to come to the Cognitive Brain Research Unit and to start my first MMN research, for his genuine interest in our neuropsychopharmacological and schizophrenia MMN studies, and also for ‘going through sentence by sentence’ and making valuable comments on my Thesis. I’m grateful to both Dr. Juha Montonen and Doc. Dr. Jyrki Mäkelä for their support and care during my work at the BioMag Laboratory. Special thanks for Pirjo Kari. I express my sincere gratitude to the Director of the Republican Vilnius Psychiatric Hospital Dr. Valentinas Mačiulis, to Kastytis Dapšys and to Prof. Osvaldas Ruksenas for their overall support throughout the course of my research work for my Thesis in Lithuania. I furthermore wish to acknowledge the outstanding library facilities at Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, USA. The exceptional resources and staff enabled me to extend my work in a multitude of ways. For these facilities I have been particularly grateful. I am deeply indebted to the following people who believed in me, shared their expertise with me and supported, assisted and stimulated me during different stages of my Dissertation:

Ala Sheredega Gediminas Žukauskas Pantelis Lioumis Aldona Šiurkutė Ivan Korostenskij Pat Michie Anke Sambeth Irina Anourova Petr Golovač Anna Shestakova Jolanta Lisauskienė Piiu Lehmus Anne-Mari Viitikainen Kimberly Edelstein Pirjo Kari Antony G Robson Lena Kotik Ranjit Kumar Aušra Daugirdienė Lena Somkina Silvija Saunoriūtė-Kerbelienė Bogdanov Sergej Liudmila Baziliuk Suvi Heikkilä Darja Osipova Maria Pardos Svetlana Khaslavskaja Dubravko Kičić Marja Junnonaho Valentina Gumenyuk Elina Pihko Nijolė Menčinskienė Valentina Syščikova Fran Golovač Nikolaj Novitskij Viktor Gnezditskij

The research conducted in this Dissertation was carried out with the support of the Republican Vilnius Psychiatric Hospital, Lithuania; the Centre of Excellence viz. Helsinki Brain Research Centre, Finland; the Centre for International Mobility (CIMO), Finland; Personal Grants from the Cognitive Brain Research Unit, University of Helsinki; Scholarship from the Graduate School of Helsinki University; Personal Grant from Biomedicum, Helsinki; Scientific award from Lundbeck Company, Turku. Last, but not least, I wish to thank Prof. Heikki Hämäläinen for his consent to act as my opponent at the public defence of this Dissertation and to Prof. Kimmo Alho and Prof. Teija Kujala for their help in organizational matters.

6 LIST OF ORIGINAL PUBLICATIONS

This thesis is based on the following original publications:

I. Korostenskaja, M., Dapsys, K., Siurkute, A., Maciulis, V., Ruksenas, O. & Kähkönen, S. (2005). Effects of olanzapine on auditory P300 and MMN in schizophrenia spectrum disorders. Progress in Neuropsychopharmacology and Biological Psychiatry, 29, 543-548.

II. Korostenskaja, M., Dapsys, K., Siurkute, A., Maciulis, V., Ruksenas, O. & Kähkönen, S. (2006). Effects of risperidone on auditory information processing in neuroleptic-naive patients with schizophrenia spectrum disorders. Acta Neurobiologiae Experimentalis, 66, 139-144.

III. Korostenskaja, M., Nikulin, V.V., Kicic, D., Nikulina, A.V. & Kähkönen, S. (2007). Effects of NMDA receptor antagonist memantine on mismatch negativity. Brain Research Bulletin, 72, 275-283.

IV. Korostenskaja, M., Kicic, D. & Kähkönen, S. (2008). Effects of methylphenidate on auditory information processing in healthy volunteers. Psychopharmacology (Berl.), 197, 475-486.

The publications are referred to in the text by their roman numerals.

7 CONTENTS

ABSTRACT ...... 4 TIIVISTELMÄ ...... 5 ACKNOWLEDGEMENTS ...... 6 LIST OF ORIGINAL PUBLICATIONS ...... 7 ABBREVIATIONS ...... 9 1. INTRODUCTION ...... 11 1 .1 . Information processing in schizophrenia and related disorders . . . . . 11 1 .2 . Non-invasive methods for studying neural correlates of information processing ...... 14 1 .3 . ERPs and ERFs in schizophrenia and other types of schizophrenia spectrum disorders ...... 20 1 .4 . Neurochemical imbalance and its effect on cognitive functioning and treatment in schizophrenia ...... 25 1 .5 . Effects of antipsychotic drugs on ERPs ...... 31 1 .6 . Neurochemical regulation of ERPs and ERFs ...... 33 2. THE MAIN PURPOSES AND OBJECTIVES OF THE STUDY ...... 39 3. METHODS ...... 40 3 .1 . Subjects ...... 40 3 .2 . Study design and data acquisition ...... 43 3 .3 . Data analysis and statistics ...... 47 4. RESULTS ...... 51 5. DISCUSSION ...... 62 6. CONCLUSIONS ...... 82 7. REFERENCES ...... 83

8 ABBREVIATIONS

5-HT serotonin (-ergic) ACh acetylcholine AEFs auditory evoked fields ANOVA analysis of variance ADHD attention deficit and hyperactivity disorder ATD acute tryptophan depletion BAEP brain stem auditory evoked potentials BOLD blood oxygen level-dependent CPT Continuous Performance Test CNS central nervous system CT computer tomography DA dopamine (-ergic) DSM-IV-TR American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders DTI diffusion tensor imaging ECD equivalent current dipole EEG electroencephalography EOG electro-oculogram EPS extrapyramidal symptoms ERFs event-related fields ERPs event-related potentials fMRI functional magnetic resonance imaging GABA gamma-amino-butyric acid HVA homovanillic acid ICD-10 International Statistical Classification of Diseases and Related Health Problems IFG inferior frontal gyrus ISI interstimulus interval

9 LORETA Low Resolution Electromagnetic Tomography LSD lysergic acid diethylamine LTD long-term depression LTP long-term potentiation MAEF middle-latency auditory evoked fields MEG magnetoencephalography MMN mismatch negativity MPH methylphenidate MRI magnetic resonance imaging NA noradrenaline NMDA N-methil-D-aspartate PANSS Positive and Negative Syndrome Scale PCP phencyclidine PET positron-emission tomography PN processing negativity PT planum temporale RON reorienting negativity RT reaction time RVPH Republican Vilnius Psychiatric Hospital SCL-90 Multidimensional Inventory Check List of Symptoms SEPs somatosensory evoked potentials SPL sound pressure level SQUID superconducting quantum interference device SSP signal-space projection SSRI selective serotonin reuptake inhibitor SSDs schizophrenia spectrum disorders STG superior temporal gyrus VAS visual analogue scale VEPs visual evoked potentials VM verbal memory

10 1. INTRODUCTION

1.1. Information processing in schizophrenia and related disorders

Schizophrenia is a devastating disorder affecting approximately 1% of world population (Jablensky et al. 1992), i.e. about 60 million people. Schizophrenia is associated with highly increased morbidity and mortality. This severe disease causes substantial socio- economic costs to the individual and society, it impairs the lives and functioning of numerous individual families and society as a whole (Schultz et al. 2007). Moreover, this disease is usually incurable, and its management depends primarily on well-chosen therapy. The early and objective diagnosis of schizophrenia is the key factor for the successful management of the disease.

Positive (e.g., hallucinations, delusions) and negative (e.g., flattening of effect, apathy, poverty of speech) are the main symptoms observed in schizophrenia disorder, which is usually diagnosed and classified by the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders (Flaum and Andreasen 1991) (current version being DSM-IV-TR), and the World Health Organization’s International Statistical Classification of Diseases and Related Health Problems (currently the ICD-10) (Kay et al. 1987). However, in addition to the observed behavioural, positive and negative symptoms of the disorder, patients with schizophrenia also exhibit robust cognitive impairments in attention, language, memory, learning and executive functions (e.g., ability to inhibit irrelevant stimuli) (Crespo-Facorro et al. 2007). Memory and information processing are considered the primary cognitive deficits in schizophrenia (Braff 1993; Nuechterlein and Dawson 1984; O’Donnell 2007). For example, all subtypes of schizophrenia (negative, disorganized, paranoid, Schneiderian, and mild) in the study by Hill et al. (2001) displayed a neuropsychological profile with prevalent impairment in learning, memory, and attention. More severe deficits were observed in learning and memory related to executive skills (ability to control and inhibit behaviour, and to use memory for guidance of future behaviour). These and a number of other findings reflect bilateral frontal-temporal dysfunction in schizophrenia patients. Inadequate frontal- and temporal-lobe connection

11 functioning seems to be a prominent pathophysiological finding in schizophrenia (Dolan et al. 1999; Saykin et al. 1991). Pathology in controlled and automatic information processing, associated with impairments in fronto-temporal connection, was shown in the study by Moelter and Hill (Moelter et al. 2001). As for auditory verbal memory (VM), which is usually indicated as a primary neuropsychological deficit present early in the course of schizophrenia, it was shown to be disrupted (Menon et al. 2000) and associated with impairments in the left temporal-hippocampal system (Saykin et al. 1994). The findings demonstrate specific sensory-perceptual deficits or even a general attentional dysfunction in schizophrenia patients (Bredgaard and Glenthoj 2000). Hence, these patients perform poorly in tasks involving information processing and attention, such as Continuous Performance Test (CPT) (Cornblatt and Malhotra 2001). Moreover, a relationship between chronically impaired attention and deficient social skills has been found (Cornblatt and Keilp 1994). All these above- mentioned cognitive impairments are proving to be a fundamental mark of the psychopathology of schizophrenia (Dickinson et al. 2004; Green 1996).

Studies of auditory information processing as far as schizophrenia patients are concerned are of particular importance. Areas involved in auditory processing are shown to be abnormal in schizophrenia. Structural and metabolic abnormalities of the auditory cortices are observed. For example, Dierks et al. (1999) found an increased blood oxygen level- dependent (BOLD) signal in Heschl’s gyrus during the hallucinations of schizophrenia patients, thereby providing evidence of the involvement of primary auditory areas in auditory verbal hallucinations. Further, Kasai et al. (2003a; 2003b) in magnetic resonance imaging (MRI) longitudinal studies, showed progressive neocortical grey matter volume loss in the left superior temporal gyrus 1.5 years after the initial scan in patients with first-episode schizophrenia. Moreover, Seok et al. (2007), in their diffusion tensor imaging (DTI) and MRI study, demonstrated that abnormalities in frontal and temporal white matter brain areas in schizophrenia patients were closely associated with auditory hallucinations. The vanishing of the left temporal lesion in the DTI and MRI study by Kho et al. (2007), resulting in the disappearance of psychosis, supports current theories on the role of the left temporal lobe in psychosis. Moreover, in MRI studies, a reversal of the normal asymmetry in planum temporale (PT) surface was found in 13 out of 14 right- handed schizophrenia patients, compared with healthy controls (Petty et al. 1995).

12 Particular relationships between left inferior frontal and right postcentral gyri reductions and the severity of auditory hallucinations were observed in a magnetic resonance voxel- based morphometry study by Garcia-Marti et al. (2007).

Schizophrenia is considered a disease with a high heritability level. Patients with schizophrenia spectrum disorders (SSDs) (cluster of disorders identified in ICD – 10 as F20-F29) (World Health Association 1992) share some common phenomenological, genetic, and cognitive abnormalities (Siever and Davis 2004). Furthermore, patients with different types of SSDs show genetic vulnerability for the development of schizophrenia (Bredgaard and Glenthoj 2000). Genetic and family studies suggest a biological relationship between chronic schizophrenia and schizotypal personality disorder (Kendler and Diehl 1993). Similarities in performance measurements of attention and information processing are also found (Kremen et al. 1994). Some authors describe neurochemical similarities in these groups (Siever et al. 1993). Phenotypic similarities among schizophrenia spectrum disorders include personality features (Lenzenweger 1994; Lenzenweger and Korfine 1994), neuropsychological deficits (Kremen et al. 1994), and psychophysiological deficits (Matthysse et al. 1986). Difficulties in attention, concentration and memory are shown to precede the onset of psychosis in these patients (Yung and McGorry 1996). Impaired attention is commonly observed among schizophrenia patients and those at genetic risk for the disease (Cornblatt and Keilp 1994). Findings indicate that the deficits in verbal and spatial attentional processing evaluated with CPT are heritable and predict future spectrum disorders in the at-risk offspring of schizophrenia patients (Cornblatt and Malhotra 2001). Patients with SSDs appear to possess temporal processing deficits as well (Davalos et al. 2003).

Therefore, in order to obtain a better understanding of the pathophysiology of the disorder, there is a pressing need for investigations of brain mechanisms that would underpin at least some of the cognitive deficits exhibited by patients with SSDs.

13 1.2. Non-invasive methods for studying neural correlates of information processing

Electroencephalography (EEG) and magnetoencephalography (MEG) The EEG and MEG are non-invasive neurophysiological techniques, which allow detection of changes in human brain activity with millisecond temporal resolution. The EEG response represents spontaneous electrical activity, produced by large populations of neurons, and is usually recorded by means of silver-chloride electrodes placed on the scalp. Because of the electrical conductive features of the brain tissues, electrical signals, even from the deep brain structures, can be recorded at the surface of the human head. Hans Berger, who was the first to record the non-invasive EEG in humans in 1926, aimed to use the EEG for the diagnosis of psychiatric disorders; however, at the present time, the EEG is used as the most powerful tool in identifying brain epileptic activity. Both the EEG and MEG are generated with the same neuronal mechanism; however, they can detect some different aspects of the electromagnetic field. Electric currents produced by synchronized neuronal currents are measurable with the EEG, whereas MEG measures magnetic fields produced by electrical currents. These produced magnetic fields are very weak. As a result, in order to record the brain’s magnetic responses, special superconductive devices must be used. Specially constructed electrically shielded rooms, specifically designed gradiometers measuring the magnetic field gradient, advanced superconducting quantum interference devices (SQUIDs), and the markedly increased sensitivity of the MEG method, led to the start of MEG research in the late 1970s (for review, see Makela et al. 2006). The localization of the MEG brain activity sources is less affected by the distortions caused by the skull and tissues than the EEG source localization (Banaschewski and Brandeis 2007). Simultaneous EEG/ MEG recording has more advantages than single EEG or MEG recordings (Sharon et al. 2007). For example, Liu et al. (2002), in their Monte Carlo stimulation study, showed that combination of the EEG/MEG provides better localization accuracy than the use of the EEG or MEG alone. Clinically oriented studies with epilepsy patients confirm these results (Bast et al. 2007; Yoshinaga et al. 2002). At the moment, the application of the MEG, as is the case with the EEG (brain-stem auditory evoked potentials – BAEPs, somatosensory evoked potentials – SEPs, visual evoked potentials – VEPs, and others), is related to the neurological evaluation; however, the MEG is most popularly

14 used to assist in the localization of epileptic activity, and is becoming an especially valuable procedure before epilepsy surgery. These two techniques could be used in combination to study how brain regions communicate with each other within a time resolution of milliseconds. The EEG and MEG are able to track such rapid changes of neuronal communication. New horizons are opening up with studies of high-frequency (up to 1000 Hz) oscillations (Worrell et al. 2008). Moreover, new spatial frequency analysis techniques (e.g. use of beamformer) make MEG analysis in time-frequency domain possible (see also even-related beamforming - ERB, Cheyne et al. 2007), thus improving spatial resolution of the MEG (Brookes et al. 2004; Fawcett et al. 2004). Further, signal averaging and other even-related algorithms help to extract cognitive events related to a particular stimulus from the general spontaneous brain and other activity, in this way allowing the investigation of information processing in response to different kinds of environmental stimulation.

Event-related potentials (ERPs) and event-related fields (ERFs) Brain event related potentials (ERPs) and brain event-related fields (ERFs) comprise a group of research methods which could serve as objective neurophysiological measures of the brain function. Defined as time-locked changes to external or internal stimuli in EEG and MEG activity, ERPs and ERFs, respectively, could provide an objective index of information processing in the human brain. Although the usefulness of electrophysiological examinations in patients with psychiatric disorders is a debated issue, according to the wide-ranging notion in most cases it could serve as an important tool which should complement clinical assessment (Pogarell et al. 2007). ERPs could also be included in the routine examinations of psychiatric patients. Auditory ERPs, such as mismatch negativity (MMN) and P300, can be used for studying different aspects of neural bases of dysfunction in auditory information processing and cognitive functions (Gene-Cos et al. 1999).

Mismatch negativity (MMN) The MMN, which can also be detected magnetically (MMNm), was first reported by Näätänen et al. (1978) (see also, Naatanen and Michie 1979). It is a negative ERP component elicited by any change (in frequency, duration, intensity, location) in some repetitive auditory stimulation, which peaks at about 100-200 ms from change onset (for

15 review, see Kujala et al. 2007b). It is suggested that the MMN represents a sensory memory trace formation process related to the evaluation of presented stimuli. The MMN could provide information about the amount of neuronal resources participating in automatic (involuntary) change-detection attentional processes (Haenschel et al. 2005). Interestingly, MMN can be recorded in neonates (Ceponiene et al. 2002), premature newborns (Cheour et al. 1998) and even in foetuses. Hence, Draganova et al. (2007) showed that at the 28-39 week gestational age group, the discriminative MMN-like responses to frequency change could be detected as early as 28 weeks. As a result, the MMN was considered the ontologically first cognitive component presented in the human brain (for review, see Naatanen et al. 2007).

According to prevailing MMN theory, it is assumed that there exist specific populations of change-detection neurons that produce MMN response (Naatanen et al. 1978; Tiitinen et al. 1994). Supporting this view, brain regions responsible for MMN generation were identified. The number of studies using EEG, MEG, functional MRI (fMRI) (Schall et al. 2003), positron-emission tomography (PET) (Muller et al. 2002) and even optical imaging (Tse et al. 2006) showed that MMN is generated in supratemporal cortices. However, additional parietal components are presented as well. Based on scalp current density maps, additional confirmations of the existence of a frontal MMN generator were presented (Deouell et al. 1998; Giard et al. 1990; Rinne et al. 2000; Yago et al. 2001a). MMN studies with intracranial recordings are of particular interest. Hence, a recent study by Rosburg et al. (2007), performed with patients during epilepsy surgery, showed MMN responses in the rhinal cortex. It seems that the pre-conscious discrimination of stimulus change in the auditory cortex elicits the supratemporal MMN and this in turn initiates a sequence of brain events that are associated with involuntary shifting of attention, orientation, and conscious detection of this change (Naatanen et al. 1992). This initiation of involuntary attention shifting is supposed to be reflected in the frontal MMN subcomponent (Giard et al. 1990; Naatanen et al. 1992). Rinne et al. (2000) showed that the “centre of gravity” of the MMN source current distribution shifts from the temporal to the frontal cortex as a function of time, supporting the theory (Naatanen and Alho 1995) that the frontal MMN subcomponent is generated slightly after the supratemporal subcomponent. Other observations from human-lesion (Alain et al. 1998; Alho et al. 1994) and imaging studies (Dittmann-

16 Balcar et al. 2001; Jemel et al. 2002; Muller et al. 2002; Opitz et al. 2002; Schall et al. 2003; Tse et al. 2006) support the theory of temporo-frontal MMN generation. Moreover, MMNs with different alteration types in auditory stimulation have different localization patterns. Indeed, the right inferior frontal gyrus (IFG) was activated in the frequency change condition, whereas the left IFG was activated in the duration change condition (Molholm et al. 2005). This difference in lateralization corresponds to the notion that the right hemisphere is involved in the processing of tonal information (frequency differences), while the left hemisphere is more involved in the processing of temporal information (duration differences) (Belin and Zatorre 2000; Zatorre and Belin 2001; Zatorre et al. 1994). Frontal MMN sources could not be well detected with the MEG; however they are well reflected in the EEG. Meanwhile, temporal MMN sources are visible and well detected in the MEG (Huotilainen et al. 1998; Rinne et al. 2000). An alternative explanation (“adaptation hypothesis”) (Jaaskelainen et al. 2004; May et al. 1999) of MMN origins should be mentioned as well. The hypothesis states that there is no specific population of neurons responsible for MMN generation. Moreover, the MMN component is here seen as a derivation of delayed N1 response, when the N1 is suppressed (adapted) because of a chain of similar events. Therefore, MMN generation origins are considered to be the same as for the N1 response. According to this view, during the adaptation of neurons in the posterior auditory cortex responsible for N1 generation, the centre of gravity of the electromagnetic N1 response shifts, creating an illusion of other loci of MMN generation (Jaaskelainen et al. 2004), which are different from the NI. This theory is supported by some animal studies as well (Ulanovsky et al. 2003).

For clinical research purposes, MMN recording is useful first of all because it is elicited even without the subject’s active attention. MMN can be registered in comatose patients (Fischer and Luaute 2005; Fischer et al. 2004; Fischer et al. 2006). Moreover, a high number of clinically oriented research studies determined clear MMN changes in populations with, for example, schizophrenia (for review, see Javitt et al. 2008; Umbricht and Krljes 2005), autism (Dunn et al. 2008), and dyslexia (Bonte et al. 2007). A potential field of application of MMN involves newborns and young infants (Carroll et al. 2007; Kaipio et al. 2000) as well as prematurely born children (Gomot et al. 2007; Mikkola et al. 2007). A number of studies show a potential for MMN application in the investigation of ageing

17 (Pekkonen 2000), and of Parkinson’s (Pekkonen et al. 1995) and Alzheimer’s diseases (Pekkonen et al. 1994). MMN recording could provide a non-invasive tool for exploring the neurophysiological functional deficits related to chronic alcoholism (Ahveninen et al. 2000a; Marco-Pallares et al. 2007) and drug abuse (Kivisaari et al. 2007). As MMN represents the earliest cognitive component registered from the human brain (Draganova et al. 2007), abnormalities in MMN generation could represent core cognitive dysfunction in the human brain, thus leading to dysfunction in further higher cognitive processing as a whole.

P300 potential The P300 first described by Sutton et al. (1965) is a positive potential occurring at an approximate latency of 300 ms and is evoked by the presentation of a novel target stimulus embedded among irrelevant stimuli, while the subject is actively reacting (pressing a button or mentally counting) to the target stimuli (Polich 2004). Classical P300 response usually embodies two subcomponents. The first one, which is elicited automatically by an infrequent stimulus novelty, has fronto-central scalp maximum and is called P3a, whereas the second one, which requires positive response to the infrequent stimulus of an “odd-ball” task, has a parietal scalp maximum, and is called P3b (Squires et al. 1975). A specially designed “distraction” paradigm uses novel (distractive) stimuli to elicit P3a response (Escera et al. 2001; Schroger and Wolff 1998b), which is considered to reflect the orienting of attention towards the distracting stimuli. P300 is usually interpreted as an electrophysiological correlate of active attentional processes and working memory (Karakas and Basar 2006). The latency of P300 could correspond to the speed of cognitive processing or to that of stimulus classification (Magliero et al. 1984). It is notable that P300 latency is negatively correlated with mental function in normal subjects, such that shorter latencies are related to superior cognitive performance (Polich et al. 1985). A number of studies showed an increase in P300 latency with age (Korostenskaja et al. 2003a; Korostenskaja et al. 2000; Pfefferbaum et al. 1984a). This dependence was linear and in some studies associated with ability to concentrate on particular stimuli (O’Donnell et al. 1992). As far as P300 amplitude is concerned, it is proposed that it mainly corresponds to the allocation of attention and activation of the immediate memory (Polich and Kok 1995). This view of P300 amplitude is supported by studies demonstrating that greater P300

18 amplitudes are associated with superior memory performance in healthy subjects (Fabiani et al. 1990). There is a tendency for P300 amplitude to decrease with age (Korostenskaja et al. 2003a; Korostenskaja et al. 2000; Pfefferbaum et al. 1984a). This seems to be related to the decrease of neural resources participating in the response to the presented stimuli. In elderly subjects, the reduction of the amplitude was associated with clinical changes in the orienting behavior (Kok 2000).

A number of studies (intracranial recordings, lesion, lobotomy and animal studies) provide evidence that the P300 represents the activity arising from different brain generators (for review, see Linden 2005). Some experimental findings indicate the local origin of the P300 in the limbic system (Tarkka et al. 1995), although studies with both scalp and intracranial recordings indicate that the limbic system is not obligatory for the generation of the P300 component (Fushimi et al. 2005). The inferior parietal lobe generated the largest P300 response in an intracranial research study by Smith et al. (1990). The correlations between magnetic resonance imaging and P300 amplitudes (Ford et al. 1994) raise the possibility that the temporal cortices are important areas for modulating and triggering the P300. Also, investigations point to the importance of the medial temporal lobe structures for P300 generation (Fell et al. 2004). A classic P300 generator was found to be located in the temporo-parietal junction using intracranial recordings (Smith et al. 1990). Generally, the integrity of the temporo-parietal junction is considered to be necessary for P300 generation (for review, see Soltani and Knight 2000). In conclusion, the P300 is not related to a single genesis and is associated with multiple cognitive processes. It seems to be directly generated in widespread cortical areas of the lateral pre-frontal cortex, temporo-parietal junction and in parietal cortices. Nevertheless, some indirect influences of subcortical structures, like the limbic system, have to be considered in explanations of P300 generation.

Potential applications of the P300 response in clinical practice are very broad. The P300 component has been widely used in studies of age-related cognitive dysfunction, because it reflects cognitive processes related to attention and memory function (for review, see Polich and Herbst 2000). P300 latency increases as cognitive capability decreases in dementia illness, e.g., Alzheimer’s disease or vascular dementia (Muscoso et al. 2006). The P300 could also be used in the monitoring of changes in cognitive functions during

19 a certain type of therapy. Thus, Paci et al. (2006) demonstrated that neuropsychological score considerably improved and P300 latency decreased after donepezil treatment in patients with vascular type dementia and Alzheimer’s disease.

1.3. ERPs and ERFs in schizophrenia and other types of schizophrenia spectrum disorders

MMN in schizophrenia Over recent years, both MMN and MMNm have proved to be particularly valuable in schizophrenia research (for review, see Umbricht and Krljes 2005; Umbricht et al. 2006) (Table 1). The first report concerning MMN deficiency in schizophrenia was made by Shelley et al. (1991). Schizophrenia patients show abnormal both MMN and MMNm responses (for review, see Michie 2001; Umbricht and Krljes 2005) and the most significant finding is the reduction of the MMN amplitude (Javitt 2000; Michie 2001). This is also shown in the magnetic MMN counterpart (Kreitschmann-Andermahr et al. 1999). It was shown that in patients with schizophrenia, the MMN is lower over the left hemisphere (Hirayasu et al. 1998b; Kreitschmann-Andermahr et al. 1999). This corresponds well with MRI studies showing that schizophrenic patients have structural brain abnormalities with reduced grey matter density in the left posterior superior temporal gyrus, the medial temporal lobe structures (Hirayasu et al. 1998c), the left inferior parietal lobule, the cingulate gyrus, the left middle frontal gyrus, the left hippocampal gyrus and the right superior frontal cortex (Wolf et al. 2008). Moreover, the MMN amplitude in patients with schizophrenia correlates with the volume of primary auditory cortex (Heschl gyrus) (Salisbury et al. 2007). In addition, several studies reported correlations between negative symptoms and the MMN amplitude (Catts et al. 1995; Javitt 2000).

All these abnormalities of MMN in schizophrenia are thought to be associated with cognitive dysfunction and are interpreted as a reflection of the impairment of early preattentive auditory processing (Hirayasu et al. 1998b; Javitt et al. 1998; Shelley et al. 1991), abnormal auditory trace formation and temporal summation (Todd et al. 2000). Moreover, Light and Braff (2005a) showed a high association between MMN deficit and poor everyday functioning in schizophrenia patients. The authors proposed that MMN deficit could reflect a core neurophysiological dysfunction in schizophrenia (Light and Braff 2005b).

20 Table 1. Summary of main findings on MMN changes in schizophrenic patients

Findings Authors

MMN and MMNm amplitude reduction. Javitt et al. (2000); Kreitschmann-Andermahr et al. (1999); Michie (2001);

MMN reduction is more robust over the left Hirayasu et al. (1998b); hemisphere. Kreitschmann-Andermahr et al. (1999)

MMN reduction in duration change condition is Michie et al. (2000a); Michie more prominent than that in frequency change (2001) condition.

MMN reduction correlates with negative Catts et al. (1995); Javitt et al. symptoms. (2000)

MMN latency could also be prolonged. Kathmann et al. (1995)

MMN amplitude reduction is not changed under Schall et al. (1999); Umbricht et antipsychotic medication. al. (1998; 1999)

Relationship between MMN amplitude reduction Ahveninen et al. (2006); Jessen et and genetic predisposition to schizophrenia is al. (2001); Magno et al. (2008); uncertain. Michie et al. (2002)

MMN amplitude does not depend on Javitt et al. (1998; 1997) interstimulus intervals (ISIs).

MMN amplitude depends on the probability of Javitt et al. (1998) the deviant stimuli.

MMN reduction correlates with P300 and N2b Javitt et al. (1995a); Kasai et al. reduction. (1999)

Both frontal and temporal MMN generators Baldeweg et al. (2002); Oknina found to be affected in schizophrenia. et al. (2005); Oades et al. (2006); Saint-Amour et al. (2007); Todd et al. (2003)

MMN amplitude could provide an index for the Umbricht et al. (2002) functional state of the NMDA receptor system.

21 Notably, MMN changes in schizophrenia differ from those in patients with other disorders such as dyslexia or autism. Hence, in persons with schizophrenia, contrary to children with dyslexia, MMN to duration change is more affected than that to frequency change (Michie 2001; Michie et al. 2000a). These results are interpreted as particular deficits of schizophrenia patients in the processing of the temporal properties of auditory stimuli (Michie et al. 2000a). MMN changes have a different profile in other vulnerable populations. One of the recent studies by Mikkola et al. (2007) showed that MMN to frequency deviant was greater in pre-term than in control children. Enhanced MMN may be due to hypersensitivity to auditory change. Increased, but not decreased, MMN has, as in schizophrenia patients, been reported in patients with a closed head injury (Kaipio et al. 2000) and in autistic children sensitive to certain types of sounds (Lepisto et al. 2005). Moreover, adults with Asperger syndrome show an enhanced MMN for deviant sounds with a gap or shorter duration and speeded latencies in frequency change condition (Kujala et al. 2007a) and enhanced MMN amplitudes, particularly for pitch and duration deviants, indicating enhanced sound-discrimination abilities (Lepisto et al. 2007).

Observed abnormalities in MMN amplitude for schizophrenia patients include both long and short interstimulus intervals (ISIs) (Javitt et al. 1998), contrary to the changes in patients with Alzhemer’s or Parkinson’s diseases (Pekkonen 2000; Pekkonen et al. 1994). Contrary to the pattern obtained with ISIs, MMN amplitudes differ between schizophrenics and controls, depending on the probability of deviant stimulus, deficits of MMN generation being greatest at the lowest levels of probability (Javitt et al. 1998).

Javitt et al. (1995a) found that MMN reduction correlated significantly with deficient P300 generation. This was interpreted as a contribution of deficits in preattentive stimulus processing to significant subsequent deficits in attention-dependent processing. In a dichotic listening task, a significant correlation between reduced MMN and N2b amplitudes within the schizophrenia patients’ group was found (Kasai et al. 1999). However, in schizophrenia, it is not only the amplitude that is abnormal, but also the increase in MMN latency. As an example, in a group of stabilized, chronic schizophrenia patients, an increased peak latency of MMN to frequency change, but no decrease in the MMN amplitude, was found by Kathmann et al. (1995).

It seems that both frontal and temporal MMN generators are affected in schizophrenia (Baldeweg et al. 2002; Oknina et al. 2005). Interestingly, younger schizophrenia patients showed more dorsal location of the right temporal MMN source than healthy controls;

22 whereas older patients had deficient MMN generation in the left temporal lobe structures, with MMN source located more medially than controls (Oknina et al. 2005). In the same study, the right mid-frontal MMN source was shown to be more ventral in the older patients compared with healthy subjects.

MMN in schizophrenia spectrum disorders NMDA receptor gene abnormalities in schizophrenia were reported in several studies (Ohtsuki et al. 2001; Riley et al. 1997) and it was also clearly shown that NMDA receptors are responsible for MMN generation (Javitt et al. 1995b). Therefore, it would be possible to suggest a genetic predisposition to MMN changes in schizophrenia spectrum. However, MMN studies of patients within the whole schizophrenia spectrum, as opposed to only patients with schizophrenia, are quite rare. The only study Michie et al. (2002) until recently demonstrated that patients with schizophrenia spectrum disorders have abnormal MMN and P3a responses. Other studies try to explore the question by investigating MMN changes in relatives of patients with schizophrenia. Significant reduction in MMN amplitude was observed in healthy first-degree relatives of individuals with schizophrenia (Jessen et al. 2001; Michie et al. 2002), raising the possibility that MMN may index certain aspects of the pathophysiology that predisposes individuals to the development of this illness. Interestingly, in their twins study Ahveninen et al. (2006) did not find MMN abnormalities in co-twins of patients with schizophrenia. This latter observation points towards MMN being a consequence of schizophrenia, rather than an initial reflection of the schizophrenia endophenotype.

P300 in schizophrenia Patients with schizophrenia also show reduction of P300 amplitude, particularly in an auditory task (Ford et al. 1994; Juckel et al. 1996; Molina et al. 2005). Roth and Cannon (1972) were the first to report a reduction of P300 amplitude relative to healthy controls. Since that time, the reduction of P300 amplitude has been demonstrated in various experimental paradigms in acute, remitted, medicated and medicationfree patients (Ford et al. 1992; Ford et al. 1994; Hirayasu 2007; Kawasaki et al. 2007; Sumich et al. 2008). Patients with schizophrenia also exhibit an increased P300 latency (Araki et al. 2006a; Pfefferbaum et al. 1984b). These effects were robust and independent of medication, gender, or clinical state at the time of testing. A positive correlation between the duration of schizophrenia illness and P300 latency was demonstrated (Mori et al. 2007). A parietal P300 amplitude reduction in schizophrenia patients was related to a poorer performance

23 in neuropsychological tests of memory, whereas frontal P300 amplitude reduction was linked to impaired selective attention (Nieman et al. 2002).

P300 in schizophrenia spectrum disorders P300 amplitude heritability was estimated at 69% in healthy monozygotic and dizygotic twin pairs, thus giving rise to the possibility of using P300 as an endophenotype for psychiatric research (Hall et al. 2006b). Abnormal auditory P300 responses in patients with different disorders within the schizophrenia spectrum have confirmed similarities with schizophrenia (Kimble et al. 2000; Michie et al. 2002). Further, Trestman et al. (1996) showed that changes in the auditory N1, P2, N2 and P300 components in patients with schizotypal personality disorder were halfway between those of patients with schizophrenia and healthy subjects. Moreover, the P300 latency and amplitude changes distinguished the borderline personality disorder and schizophrenic groups from healthy control subjects, those with major depressive disorder, and those with non-borderline personality disorders in study by Kutcher et al. (1987). The authors interpreted these findings as meaning that although some patients with borderline personality disorder may have depressive symptomatology, they share with schizophrenics a dysfunction of auditory neurointegration (Kutcher et al. 1989). Both first degree relatives and schizophrenic patients showed a lower P300 amplitude than that of controls in a study by Kidogami et al. (1991). Further, a number of studies have reported an association between catechol- O-methyltransferase (COMT) gene Val158Met polymorphism and neuropsychological traits in patients with schizophrenia and their relatives and in schizophrenia - related disorders (for review, see Lewandowski 2007). The P300 data has been correlated with the activation induced by Val158Met polymorphism (Golimbet et al. 2006).

Using multivariate genetic model - fitting analytic techniques, Hall et al. (2006a) were able to show that MMN and P300 can be used to evaluate different brain information processing functions and, further, that these differences may have distinct neurobiological mechanisms which are influenced by different sets of genes (Hall et al. 2006a); there is some evidence that deficient MMN generation in schizophrenic patients could contribute to subsequent neurophysiological dysfunction, later manifested in deficient P300 generation. Thus, a reduction in MMN amplitude correlated significantly with the reduction of P300 amplitude in a study by Javitt et al. (1995a). Therefore, a combined study of the MMN and P300 that would aim at providing information on auditory dysfunction at different stages, viz., pre-attentive (involuntary change-detection mechanism) and attention-dependent (processing of behaviourally relevant target stimuli), would be of great value.

24 1.4. Neurochemical imbalance and its effect on cognitive functioning and treatment in schizophrenia

The first hypothesis concerning neurochemical alterations in schizophrenia was dopaminergic (DA) hypothesis. The DA neurotransmitter system was put forward as the main system responsible for pathological changes in schizophrenia (for review, see Stone et al. 2007). Subsequently, several other hypotheses were put forward, such as GABA- ergic, serotoninergic and glutamatergic. The former became the most prominent in the last few decades.

Dopamine

DA is involved in a variety of cognitive functions such as learning, attention, memory and auditory information processing (Briand et al. 2007; Thiel 2007). This involvement has been demonstrated in studies with experimental animals (Castner et al. 2004), human patients (for review, see Nieoullon 2002), and healthy volunteers (Clark and White 1987). Changes in DA neurotransmission are involved and affect cognitive functioning (attention, working memory) not only in schizophrenia (for review, see Goto and Grace 2007), but also in a variety of other disorders such as attention deficit hyperactivity disorder (ADHD) (Solanto 2002), Parkinson’s and Alzheimer’s diseases (El-Ghundi et al. 2007), and autism (for review, see McPartland et al. 2004; Nieoullon 2002).

The most widely accepted hypothesis concerning the neurochemical abnormality present in schizophrenia is the dopamine hypothesis, which states that this disease is the result of an imbalance of dopaminergic activity in certain brain areas (for review, see Stone et al. 2007). The main evidence supporting this theory is that antipsychotic drugs (especially first generation of antipsychotics, e.g., haloperidol) mainly act through the DA system. Some DA antagonists improve cognitive deficits evident in schizophrenia (for review, see Nieoullon and Coquerel 2003). Moreover, genes shown to be responsible for schizophrenia (e.g., DRD2, DRD3, DARPP-32, BDNF or COMT) are closely related to the functioning of the DA system (Lang et al. 2007). Furthermore, psychostimulant d-amphetamine, believed to act primarily on the dopaminergic system, has served in the modelling of attentional dysfunction in schizophrenia (Feldon and Weiner 1991; Peleg-Raibstein et al. 2006). It is proposed that subcortical hyperstimulation of DA receptors (mostly D2)

25 underlies positive symptoms in schizophrenia, whereas cortical DA hypofunction is responsible for cognitive disturbances and negative symptoms (for review, see Guillin et al. 2007). Further, plasma concentrations of homovanillic acid (HVA, a major dopamine metabolite measured in various body fluids; measured in blood plasma, it is used to assess brain dopamine neuronal activity) correlate with symptom severity in unmedicated schizophrenia patients (Davis et al. 1985). Moreover, various changes in the plasma HVA have a high correlation with the therapeutic response to neuroleptic drugs (Davis et al. 2002).

From another point of view, increasing evidence indicates that the pathophysiology of mental disorders, including schizophrenia, could be a consequence of the deregulation of synaptic plasticity (Gratacos et al. 2007). Moreover, DA seems to affect synaptic plasticity induced within the circuits of certain brain regions (Goto and Grace 2007). In this way, disturbances in DA neurotransmission impair cognitive functions such as memory and information processing, which are considered the primary cognitive deficits in schizophrenia (Braff 1993; Nuechterlein and Dawson 1984; O’Donnell 2007).

Animal studies show long-term effects of antipsychotic drugs on the dopamine D2 receptor family, which is implicated in the pathophysiology of schizophrenia. For example, olanzapine and risperidone significantly increased D2 binding in the medial prefrontal cortex in a study by Tarazi et al. (2001). A number of studies show the negative effect of typical antipsychotics (especially haloperidol) on cognitive functioning in schizophrenia patients. Longitudinal studies in humans show impairments in cognitive performance, related to vigilance and attention tasks, associated with antipsychotic treatment (for review, see Cassens et al. 1990). Moreover, extra-pyramidal symptoms (EPS), produced by typical and some atypical antipsychotic drugs through the blockade of D2 receptors in striatum, could also have negative consequences on procedural learning (Bedard et al. 2000) and psychomotor performance (e.g. impairments in driving skills could occur) (Rapoport and Banina 2007). Studying schizophrenia patients, Purdon et al. (2003) observed that impairment in procedural learning resulted from the use not only of haloperidol, but also of risperidone. Ramaerkers et al. (1999) found that haloperidol significantly impairs psychomotor and cognitive performance in healthy volunteers.

Dopaminergic involvement in schizophrenia gives rise to the possibility of dopaminergic deregulation in schizotypal personality disorder as well (Siever et al. 1993). Preliminary

26 studies suggest that this disorder has dopaminergic dysfunction. Like patients with schizophrenia, schizotypal patients demonstrate clinical improvement in response to neuroleptics such as thiothixene and haloperidol (Goldberg et al. 1986; Siever et al. 1993). Schizotypal patients also have a significantly higher mean plasma HVA concentration than healthy control subjects (Siever et al. 1991). Moreover, in the study by Siever et al. (1991), plasma HVA concentration positively correlated with “psychotic-like” schizotypal symptoms. Results were interpreted as possible modulation of the psychotic- like symptoms of schizotypal personality disorder by the dopamine system.

Glutamate

Glutamate plays a major role in fast excitatory synaptic transmission (Feldman et al. 1997). It is crucially involved in the learning and memory processes (McEntee and Crook 1993; Morris et al. 1986), mediating a physiological analog of memory – long-term potentiation (LTP) (Bliss and Collingridge 1993). The blocking of glutamate N-methyl-D-aspartate (NMDA) receptors prevents the induction of LTP (Barcal et al. 2007; Collingridge 1987). The loss of NMDA receptors may cause memory impairment (Myhrer and Paulsen 1992) and impaired acquisition and retention in a visual-discrimination task in rats (Collingridge 1987). Both competitive and noncompetitive NMDA antagonists produce consistent impairments across a wide variety of memory-related tasks in animals (for review, see Bischoff and Tiedtke 1992; Whishaw and Auer 1989). Neuropsychological studies indicated that ketamine, by blocking NMDA receptors, impairs working memory in healthy subjects (Krystal et al. 2000; Lofwall et al. 2006).

In the auditory cortex, glutamate also acts partly through NMDA receptors (Metherate and Ashe 1995). In-vitro studies demonstrated that NMDA receptor-mediated LTP (Kudoh and Shibuki 1994) and long-term depression (LTD) (Kudoh et al. 2002) are observed in the rodent auditory cortex. Further, extensive auditory training induced changes in NMDA gene expression in the rat auditory cortex, in a study by Sun et al. (2005). Moreover, Schicknick and Tischmeyer (2006), in a study with adult male gerbils, showed that the NMDA receptor is essential for long-term memory consolidation in auditory cortex- dependent learning.

27 Evidence concerning abnormal neurochemical changes in schizophrenia points towards the disruption of corticostriatal glutamatergic circuits (Stone et al. 2007). In his review, Coyle (2006) proposed that impairments in NMDA receptor activity could contribute to the pathophysiology of schizophrenia. A number of studies demonstrated that the administration of NMDA-receptor antagonists, such as phencyclidine (PCP) or ketamine, produces psychotomimetic effects (symptoms similar to those observed in schizophrenia) in healthy subjects (Krystal et al. 1994). Some NMDA antagonists, such as ketamine, MK-801, or PCP, acting at the NMDA recognition binding sites in rats, cause memory impairments, reflected in a lower counting efficacy without altering sensorimotor function (Willmore 2003), and impairment of working-memory function (Wozniak et al. 1990). MK-801, a noncompetitive NMDA channel blocker, as well as the glycine/ NMDA receptor antagonist HA-966, markedly impairs the visual recognition memory in rhesus monkeys (Matsuoka and Aigner 1996; Ogura and Aigner 1993), suggesting an important role of NMDA receptors in the cognitive function of nonhuman primates. The glutamatergic theory is extensively supported by significant findings in genes regulating the glutamatergic system (e.g., SLC1A6, SLC1A2 GRIN1, GRIN2A, GRIA1, NRG1, ErbB4, DTNBP1, DAAO, G72/30, GRM3) (Lang et al. 2007).

Based on the glutamate deficiency theories, one approach has been to enhance glutamatergic function using agonists of the NMDA-linked glycine site (Deakin et al. 1997). Adjunctive glutamate antagonist therapy is used in the treatment of catatonic syndromes (for review, see Carroll et al. 2007). Furthermore, the glutamatergic hypothesis concerning schizophrenia resulted in the first successful mGlu2/3 receptor agonistic drug (Patil et al. 2007). Moreover, it would appear from a preliminary study by Krivoy et al. (2008) that non-competitive low-affinity NMDA receptor antagonist memantine, used as an add-on therapy to ongoing psychiatric treatment in schizophrenia patients with residual symptoms, seems to improve the clinical status of those patients who are in negative subscale. Finally, memantine and another weak NMDA receptor antagonist amantadine, used as an adjunctive therapy, are shown to be potent in improving catatonic signs in some patients who fail to respond to already established treatment, including electroconvulsive therapy (Carroll et al. 2007).

28 Other neurotransmitters involved in the pathophysiology of schizophrenia

Gamma-aminobutyric acid (GABA)

A preliminary but growing body of literature suggests a pivotal role of GABA in the pathophysiology of schizophrenia. GABAA receptors affecting agents commonly used because of their anaesthetic properties cause substantial memory impairments (for review, see Bonin and Orser 2008). GABA-ergic interneurons exert both inhibitory and disinhibitory modulation of cortical and hippocampal circuits involving gaiting of sensory mechanisms, discriminative information processing, and other functions that are abnormal in schizophrenia (for review, see Daskalakis et al. 2007). An increasing body of post-mortem data is consistent with abnormalities in the GABA system in cortical and subcortical areas which are of relevance to schizophrenia, for example, abnormalities of GABA synthesis and reuptake are clearly observed in the prefrontal cortex (Barbas and Zikopoulos 2007; Volk et al. 2001) as well as the loss of GABA- ergic interneurons (Reynolds and Harte 2007). The presynaptic markers of both GABA synthesis and reuptake are decreased in the cerebral cortex (especially in left temporal cortex) of schizophrenic subjects, providing evidence for GABA involvement in the cerebral atrophy of schizophrenia (Simpson et al. 1989). At the same time, the density of postsynaptic GABAA receptors was increased in the prefrontal cortex in a study by Benes et al. (1992). Of specific relevance to the amelioration of the symptoms of schizophrenia is the apparent role of GABA in modulating dopaminergic activity in the mesocortical and mesolimbic dopaminergic tracts. It has been postulated that GABA modulates the pathophysiology of schizophrenia which is represented by the involvement of genes like GABRA1, GABRP, GABRA6 and Reelin (Lang et al. 2007).

The GABA-modulating drugs differentially affect the working-memory performance and brain function in schizophrenia. Considering that cognitive impairment in schizophrenia may reflect abnormal inhibitory function, it may be possible to use drugs targeting GABA neurotransmission for schizophrenia treatment (Menzies et al. 2007).

29 5-Hydroxytryptamine (5-HT; serotonin)

The first hypothesis concerning the involvement of 5-HT in schizophrenia was based on the observation that lysergic acid diethylamide (LSD, structurally related to 5-HT), and its antagonists acting at brain 5-HT receptors, produce psychotomimetic effects in healthy subjects (Gaddum and Hameed 1954). It was hypothesized that serotonergic activity might be decreased in schizophrenia. However, the main effect produced by LSD was visual hallucinations, which are relatively rare in schizophrenia (the most common perceptual disturbance in schizophrenia being auditory hallucinations (Abraham et al. 1996)). Additionally, the wide range of cognitive impairments characteristic of schizophrenia, such as those in working memory and semantic memory, are generally absent during LSD intoxication (Aghajanian and Marek 2000). However, support for the 5-HT deficiency hypothesis comes from the fact that atypical antipsychotics such as clozapine, risperidone, olanzapine, sertindole, and ziprasidone are antagonists at multiple 5-HT receptors. Moreover, these antipsychotics have some advantages over selective DA receptor antagonists such as haloperidol or fluphenazine (Keefe et al. 1999).

The treatment of schizophrenia depends on the modulation of all neurotransmitter systems mentioned heretofore. At the moment, the most widely used atypical antipsychotic drugs mainly involve modulation of DA and 5-HT neurochemistry. However, the pattern of pharmacological effect of these drugs is, in fact, more complex and includes interactions with numerous other receptors, e.g. histaminergic, adrenergic, muscarinic acetylcholine and others (for review, see Nasrallah 2008). On the other hand, the pattern of interactions between the different neurochemical factors causing disturbances in schizophrenia is also very complex. As new views and theories are developed, new treatment possibilities surface, which could be used either alone or in conjunction with conventional treatment (Lavoie et al. 2007). Despite their pronounced effects on the psychotic symptoms of schizophrenia patients, conventional neuroleptics do not usually have a major impact on neurocognitive deficits. Moreover, they could negatively affect processing speed, motor skills and procedural learning (for review, see Woodward et al. 2007). Compared with typical neuroleptics, atypical neuroleptics seem to be more effective in ameliorating cognitive impairments (Karow et al. 2006; Keefe et al. 1999; Meltzer and McGurk 1999). Currently, the assessment of cognitive deficits plays no role in the choice of therapeutic options for patients. It is possible to predict that further advances in the treatment of this debilitating disorder might be achieved with a shift from treatments targeting symptoms

30 to treatments targeting the underlying pathophysiology. As a result, there is an urgent need to introduce new objective methods to investigate changes in neural substrates of cognitive function in patients with schizophrenia, when under the effect of antipsychotic medication. The current state of affairs requires that more studies be undertaken, in order to determine the effects of atypical antipsychotics on the different phases of information processing in schizophrenia and related disorders.

1.5. Effects of antipsychotic drugs on ERPs

Neuroleptics and MMN

Although the number of studies investigating the effects of antipsychotic medication on the MMN in schizophrenia is rather small, the results demonstrate a lack of significant MMN changes under the effect of antipsychotics administered. For instance, MMN studies with clozapine and risperidone in schizophrenia patients found the treatment had no significant effects on MMN latencies and amplitudes (Umbricht et al. 1998; 1999). The lack of a significant correlation between reported MMN amplitudes and the dose of antipsychotics administered to schizophrenic patients is observed (Kasai et al. 1999; Kasai et al. 2003b; Michie et al. 2000b; Todd and Michie 2000).

Neuroleptics and P300

Typical antipsychotics Results concerning P300 changes under the effect of antipsychotic treatment are not very consistent. Usually, a typical antipsychotic medication does not change P300 amplitudes and latencies in schizophrenia patients (Coburn et al. 1998; Ford et al. 1994; Umbricht et al. 1998). Ford et al. (1994) found no significant changes on P300 amplitudes and latencies after 1 week on placebo and after 4 weeks on medication. Furthermore, Coburn et al. (1998) in at least 1 week prior to testing drug-free schizophrenics found that haloperidol and remoxipride did not normalize P300 amplitude. These results were confirmed in a study by Niznikiewicz et al. (2005), who showed that as opposedto clozapine, chlorporomazine did not increase P300 amplitudes in schizophrenia patients relative to the baseline. Further, there were no significant differences in P300 amplitude

31 between the neuroleptic-naive and previously- treated schizophrenic groups (Hirayasu et al. 1998a). In a study by Asato et al. (1999), the auditory P300 amplitudes increased under the effect of typical neuroleptics, however patients still had smaller P300 amplitudes than those of the controls, even after the treatment. As concerns studies with healthy subjcts, some typical antipsychotics seem to reduce P300 amplitude. For instance, 2 mg/day of flupenthixol reduced P300 amplitude after a 4-day treatment in healthy volunteers (Rosler et al. 1985), suggesting a negative effect on attention-dependent processes is reflected in the P300. Interesting results were provided by Tekeshita and Ogura (1994), who showed that sulpiride increased P300 amplitudes in subjects with low P300 amplitudes and decreased them in high P300 amplitude subjects.

Atypical antipsychotics Atypical antipsychotics have been claimed to improve cognitive functions in schizophrenia (Keefe et al. 2006; Meltzer and McGurk 1999; Purdon 1999). However, the effects of these drugs on the neural aspects of cognitive dysfunction have not been consistent. Risperidone treatment produced a significant P300-latency reduction (Iwanami et al. 2001; Umbricht et al. 1999). Further, clozapine increased P300 amplitudes (Umbricht et al. 1998). A P300-amplitude increase at left temporal electrodes was reported during treatment with clozapine by Niznikiewicz et al. (2005). Olanzapine normalized frontal P300 amplitudes, however parietal P300 amplitudes still remained smaller in schizophrenic patients compared with healthy controls (Gonul et al. 2003). Follow-up by Sumiyoshi et al. (2006) after 6 months of olanzapine treatment observed a recovered left-dominant pattern of electrical density in the Heschl gyrus compared with the baseline in a Low Resolution Electromagnetic Tomography (LORETA) study. Further, olanzapine enhances neuropsychological performance in schizophrenia (Harvey et al. 2006). At the same time the P300 was shown to be related to neuropsychological performance in schizophrenia (Nieman et al. 2002). Nevertheless, the lack of significant effects on P300 parameters was apparent in the olanzapine study by Molina et al. (2004). Moreover, Gallinat et al. (2001) could not find changes in P300 latency and amplitude during olanzapine and clozapine therapy. Furthermore, perospiron, a new antipsychotic drug with D2/5-HT2A antagonistic and partial 5-HT1A agonistic properties, failed to change P300 amplitude in schizophrenia patients after a switch from previous antipsychotic medication (Araki et al. 2006b).

Generally, both typical and atypical neuroleptics do not have an influence on MMN response. Typical neuroleptics also seem to have no effect on P300 response, whereas

32 atypical neuroleptics do. Further investigations are needed to clarify the influence of new- generation drugs on P300 response. Risperidone and olanzapine are atypical antipsychotic drugs, sharing some pharmacological properties with clozapine (for review, see Horacek et al. 2006). According to a number of studies (Meltzer and McGurk 1999; Meltzer and Sumiyoshi 2003; Purdon 1999), they appear to be superior to typical antipsychotics in the improvement of cognitive functions. However, the effect of both these antipsychotics on neural substrates of auditory information processing in schizophrenia patients and other types of schizophrenia spectrum disorders has not yet been substantially investigated, especially at the early stage of the drug effect, e.g. after 2 weeks of treatment initialisation. This could be done by means of the ERPs.

1.6. Neurochemical regulation of ERPs and ERFs

Neurochemical MMN regulation

Previous studies indicate that MMN and MMNm are well-suited for investigating the effects of pharmacologically induced changes in attention (for review, see Kahkonen and Ahveninen 2002). However, the neurochemical bases of MMN are not fully known.

Glutamate (Glu) In monkeys, MMN generation has been linked to the NMDA receptor subtype of excitatory glutamate neurotransmission (Javitt et al. 1996). A number of drug-challenge studies in healthy volunteers investigated the relationship between NMDA receptors and MMN modulation. It was shown that ketamine, which has been used for studies of NMDA receptor modulation related to the glutamate system in humans (Lahti et al. 2001), significantly diminishes MMN amplitude to frequency and duration changes, but does not alter other sensory ERPs with a similar latency, such as the N1 and P2, in healthy volunteers (Umbricht et al. 2000). Further, Kreitschman-Andermahr et al. (2001) demonstrated in a test-retest type study that ketamine significantly increased the MMNm latency and decreased the dipole moment of the MMNm without affecting the latency and dipole moment of the N1m. Furthermore, Umbricht et al. (2002) analyzed correlations between the MMN recorded before ketamine administration and at the follow-up. Smaller MMNs to both frequency and duration deviants were significantly correlated to stronger effects during ketamine administration. Moreover, glycine, which augments NMDA

33 receptor function via stimulation of the glycine modulatory site of the NMDA receptor, significantly attenuated the duration MMN amplitude (Leung et al. 2008). In contrast to all these results, Oranje et al. (2000) found no changes in MMN amplitudes or latencies in dichotic listening tasks under the effect of ketamine. Although these studies suggest an important role for NMDA receptors in MMN generation in humans, they do not provide information about the effects of NMDA receptors on different MMN generators.

Serotonin (5-HT) Studies with acute tryptophan depletion (ATD), which reduces serotonin synthesis in the brain, showed increased MMN amplitudes in EEG and decreased latency in MEG, indicating that serotonin may be involved in MMN generation (Kahkonen et al. 2005). Further, the highly selective serotonin reuptake inhibitor (SSRI) escitalopram significantly increased the MMN response compared to placebo in healthy volunteers (Oranje et al. 2007). However, Umbricht et al. (2002) found no correlation between the MMN recorded before and after the administration of 5-HT2a agonist psilocybin. Moreover, in their subsequent study, although psilocybin administration induced significant performance deficits in the ‘AX’-type-CPT, it did not significantly reduce MMN amplitudes (Umbricht et al. 2003).

Acetilcholine (Ach) As the reduction in MMNm amplitude after scopolamine administration suggests, the cholinergic system could modulate MMN (Pekkonen et al. 2001; Pekkonen et al. 2005). The transdermal (Inami et al. 2005) and oral (Baldeweg et al. 2006) administration of nicotine successfully accelerated MMN. Dunbar et al. (2007) showed an increase in MMN amplitude and a shortening of MMN latency after the administration of the selective nicotinic receptors agonist AZD3480. Knott et al. (2006), however, found no relation between acetylcholine nicotinic receptors and MMN generation.

γ - aminobutyric acid (GABA) The relation between GABA and MMN was shown by Rosburg et al. (2004), who reported an increase in MMN latency under the effect of lorazepam. However, Smolnik et al. (1998), demonstrated only a nonsignificant increase in MMN amplitude following the administration of benzodiazepine antagonist flumazenil.

34 Dopamine (DA), adrenalin, noradrenalin (NA) Mervaala et al. (1993) studied the effects of the acute modulation of central noradrenergic α neurotransmission on MMN in healthy subjects, using a specific 2-antagonist atipamezole. Although atipamezole produced evident noradrenergic overactivity, it failed to modulate α MMN. The 2-adrenoreceptor antagonist clonidine also showed no effect on MMN (Duncan and Kaye 1987). Furthermore, Hansenne et al. (2003) demonstrated the lack of implication of DA and NA activities, as indirectly assessed by growth hormone response to apomorphine and clonidine, for the generation or modulation of MMN. Moreover, recently Leung et al. (2007) failed to show any significant effect of dopamine D2 and D1/ D2 receptor stimulants bromocriptine and pergolide, respectively, on MMN generation in healthy subjects. The only investigation so far (Kahkonen et al. 2001a) has shown that, in a dichotic listening task, haloperidol, a dopamine-2-receptor antagonist, increased MMN amplitudes in EEG, but not in MEG, suggesting some involvement of DA in MMN generation. However, differences in stimulation paradigms may explain the results.

In conclusion, it seems that the main excitatory glutamate system (in particular NMDA receptors) and the main inhibitory GABA system are involved in MMN generation in humans, although other neurotransmitter systems could affect MMN as well. This interaction should be further investigated.

Neurochemical P300 regulation

As P300 represents activity of multiple overlapping sources (hippocampus and amygdala, medial temporal areas, frontal and posterior parietal cortex) (for review, see Linden 2005) which possibly have different neurochemical modulation, it becomes evident that the neurochemical pattern of P300 generation could be very complex. Indeed, various neurochemical influences on P300 generation were found and numerous attempts were made to use P300 as an indicator for disturbances in the different neurochemical systems (for review, see Frodl-Bauch et al. 1999a). However, these studies are still highly inconsistent and the neurochemical mechanisms of P300 generation are still unclear (for review, see Polich and Criado 2006). Generally, it seems that dopaminergic/noradrenergic influence in the case of P300 generation is more robust than in MMN generation. Theα -2 noradrenergic influences in P300 generation were supported by primate studies (Pineda et al. 1989; Pineda and Westerfield 1993).

35 Glutamate Contrary to the Glu and MMN situation, there is no consistency in reports of the connection between Glu and P300. Frodl-Bauch et al. (1999a) proposed that glutamate triggers P300 response generation. Thus, the reduced amplitude of P300 in schizophrenics could stem from disturbances in the glutamatergic system. However, only one study up until recently (Oranje et al. 2000), showing that ketamine reduced P300 amplitude, has supported the suggestion put forward by Frodl-Bauch et al. (1999a). No other direct evidence supporting Glu involvement in P300 generation has been presented up to now.

Serotonin The effects of serotonin on P300 generation are few and inconsistent. ATD produced a significant reduction in the amplitude of the auditory P300 component in patients with bipolar disorder (Young et al. 2002). A significant negative correlation between P300 amplitude and serotonergic activity (assessed by prolactin response) in response to flesinoxan (a 5-HT1A agonist) was observed in major depressive inpatients (Hansenne and Ansseau 1999). However, the P300 component of autistic children was not affected by fenfluramine, although the drug significantly lowered blood concentrations of serotonin (Pritchard et al. 1987). The antidepressant citalopram increased the N1 and P3b source strengths in multiple brain regions specifically in the left prefrontal cortex, a brain region in which reduced blood flow and metabolism was found in depressed patients (Anderer et al. 2002). Similar increases were observed after intravenous administration of S-adenosyl-L-methionine in young healthy subjects and an even more pronounced increase was observed in elderly healthy subjects (Anderer et al. 2002).

Acetylcholine The amplitude of the Macaca radiata monkey P300-like component was significantly enhanced following the administration of muscarinic agonist AF102B (O’Neill et al. 2000). As with primate studies, human research shows the influence of the cholinergic system on P300 generation (Callaway et al. 1985; Hammond et al. 1987; Meador et al. 1987). Moreover, a genetic linkage and associated findings were reported (Jones et al. 2006), implicating the gene encoding of the muscarinic acetylcholine receptor M2 (CHRM2) in the modulation of a scalp-recorded electrophysiological P300 phenotype. The attenuated amplitudes and prolonged latencies of the P300 in dementia (Bennys et al. 2007) could serve as indirect evidence of the relationship between the P300 and the cholinergic system. However, some studies (Blackwood and Christie 1986; van Gool

36 et al. 1991) failed to find an effect of central cholinesterase inhibitors on the P300 in Alzheimer’s patients.

γ-aminobutyric acid Sedative drugs primarily acting through the GABA system tend to alter P300 parameters. In this way, P300 amplitude was reduced after the administration of benzodiazepine clonazepam in healthy volunteers (Reinsel et al. 1991; Rockstroh et al. 1991). Furthermore, P300 latency was delayed after the application of GABA-ergic drugs midazolam (Domino et al. 1989) and diazepam (Ray et al. 1992). In addition, oxazepam reduced P300 amplitude in a dose-dependent manner (van Leeuwen et al. 1995). The tranquillizer lorazepam prolonged P300 latency (Anderer et al. 2002). GABA-mimetic drug sodium valproate (VPA) increased P300 amplitude in low P300 amplitude subjects and decreased it in high P300 amplitude subjects (Urasaki et al. 1994).

Dopamine, adrenaline, noradrenaline The evidence concerning catecholaminergic P300 modulation is the most abundant (for review, see Polich and Criado 2006). A number of investigations confirm DA participation in P300 response. First, Anderer et al. (2002), using acute haloperidol administration, found reduced dipole strength of the P300 component. In addition, Kähkönen et al. (2001a) found a decrease in P3a amplitudes in haloperidol versus placebo conditions. Studies exploring the effect of clonidine on ERPs (Duncan and Kaye 1987; Joseph and Sitaram 1989) found clonidine to reduce P300 amplitude. Further, Cooper et al. (2005) showed that the amplitude of P300 to background stimuli was increased and the latency of P300 to target stimuli reduced after the administration of psychostimulant methylphenidate (MPH), which affects both DA and NA systems. In addition, MPH increased the P300 source strength in brain regions with major P3b generators (Anderer et al. 2002). Also, the neuroleptic haloperidol decreased the P300 source strength predominantly in brain regions not involved in the generation of these components, suggesting a shift of resources (Anderer et al. 2002). However, some discrepancy exists. As an example, Shelley et al.

(1997) showed that the dopamine D2-receptor antagonist droperidol has no significant auditory P300 effects. No changes on P300 after a single dose of olanzapine were reported by Hubl et al. (2001). Neither clonidine nor yohimbine affected the latencies and amplitudes of P3b in the study of Turetsky and Fein (2002).

37 Polich and Criado (2006) proposed that different neurochemical activities are responsible for the generation of separate P300 components. According to this proposal, dopaminergic/ frontal processes are connected with the generation of the P3a component, whereas P3b is more related to changes in locus-coeruleus – norepinephrine/parietal activity. The involvement of catecholamines in P300 modulation is indirectly supported by the observation that P300 is deficient in Parkinson’s patients (Hansch et al. 1982; Stanzione et al. 1991), who have abnormally decreased DA level, and in ADHD patients with both DA and NA imbalance.

The studies of neurochemical modulation of auditory information processing in schizophrenics with ERPs are obscured by many factors – for example, complementary drug (benzodiazepines, SSRIs, etc.) effects. Alongside the necessity to understand the neurochemical influences of antipsychotic drugs on cognition in patients with schizophrenia, there is a need to study healthy subjects and to determine the effects of different neurochemical modulators on the neurophysiological correlates of their auditory information processing, attention and memory.

Consequently, the purposes and objectives of the study were formulated as follows:

38 2. THE MAIN PURPOSES AND OBJECTIVES OF THE STUDY

The main purpose of the current study is to explore the neurochemical influences on neural bases of auditory information processing in relation to schizophrenia by employing the auditory event-related potentials (ERPs) and event-related fields (ERFs) techniques. The objectives of the current study are as follows:

• To determine the effects of olanzapine on neural substrates of auditory information processing in patients with schizophrenia spectrum disorder by using auditory ERPs (MMN and P300) (Study I). • Using auditory ERPs, to determine the effects of risperidone on neural substrates of auditory information processing in patients with schizophrenia spectrum disorder who have never been exposed to antipsychotic drug treatment (Study II). • To determine the effects of memantine on neural substrates of auditory information processing in healthy subjects by recording electric and magnetic MMN responses (Study III). • To determine the effects of methylphenidate on neural substrates of auditory information processing in healthy subjects by recording electric and magnetic MMN responses (Study IV).

39 3. METHODS

3.1. Subjects

Patients Patients with schizophrenia spectrum disorders (Studies I, II) were recruited from the Republican Vilnius Psychiatric Hospital (see Table 2). Exclusion criteria for psychiatric patients were an organic pathology of the central nervous system (e.g., tumours) and a history of alcohol dependence. Clinical symptoms were evaluated with PANSS (Kay et al. 1987). Diagnoses in all cases were made according to the ICD-10 (World Health Association 1992) by clinicians using all information available. The number of patients in Study II is rather small; however, the group of subjects studied is unique – these patients had never been exposed to any antipsychotic medication prior to this, their first, hospitalization. Usually, it takes a time to recruit patients like this. The main information concerning the patients’ diagnoses and medication is summarized in Table 3. It is known that for a large number of schizophrenia patients satisfactory treatment response is not achieved with antipsychotic treatment alone. In these cases, additional medication (adjunctive therapy) is used, for example, benzodiazepines. These could be prescribed for a variety of reasons, e.g. as hypnotics, to alleviate anxiety symptoms or to treat negative symptoms (for review, see Volz et al. 2007). This explains why, in Study I, some patients were receiving additional treatment with the benzodiazepines clonazepam and lorazepam. Further, a proportion of our studied patients was diagnosed with schizoaffective disorder, depressive type, and had pronounced depressive symptoms. This is why, in addition to olanzapine, they were given the antidepressant drug citalopram (belonging to the class of selective serotonin reuptake inhibitors - SSRIs), which is also used as an add-on therapy in the treatment of negative symptoms in schizophrenia (for review, see Sepehry et al. 2007). Finally, several patients, before being switched to olanzapine, were treated with typical neuroleptics such as haloperidol and trifluoperazine, known to produce tardive dyskinesia (type of extrapyramidal symptoms - involuntary, repetitive movements) as a side effect. In order to alleviate these symptoms, patients were given the antiparkinson drug trihexyphenidyl, which is often used to treat EPS side effects produced by antipsychotic drugs (for review, see Gao et al. 2008).

40 Table 2. Age and gender for all participants in Studies I-IV

Study Subjects Number Averaged Age Gender age ± SD, range, (females / years years males)

Study I schizophrenia 11 31.9±11.3 18–55 5/6 spectrum disorders

healthy controls 15 34.7±10.7 23–55 7/8

Study II schizophrenia 9 26 ± 8 18–39 2/7 spectrum disorders

healthy controls 9 28 ± 10 18–41 3/6

Study III healthy volunteers 13 27±5 22-32 5/8

Study IV healthy volunteers 13 26±3 23-29 8/5

Healthy controls Healthy controls (Studies I-IV) (Table 2) had no known neurological or psychiatric disorders. In the case of the study with CNS drugs such as methylphenidate and memantine (Studies III, IV), before being included, subjects underwent a medical examination to exclude physical health problems by using the Multidimensional Inventory Check List of Symptoms (SCL-90) (Derogatis et al. 1973). All subjects reported having used no drugs for at least 2 weeks before the study. They were instructed to avoid alcohol for at least 48 hours prior to the MEG recordings. All participants were non-smokers. There could be some overlap in subjects participating in memantine and in methylphenidate studies, and also in healthy controls participating in olanzapine and risperidone studies.

41 Table 3. Main information about patients from Studies I, II

Study I Study II

Diagnosis schizotypal disorder F21 (N = 2) schizotypal schizoaffective disorder, depressive type F25.1 disorder F21.0 (N = 7) (N = 5) schizoaffective disorder, mixed type F25.2 paranoid (N = 1) schizophrenia delusional disorder F22.0 (N = 1) F20.0 (N = 4)

History of neuroleptic naive (N = 2) neuroleptic naive antipsychotic neuroleptic free (N = 7; 1 for at least half a patients treatment year, and 6 for at least 1 month) treated with other antipsychotics before the switch to olanzapine (N = 2; 1 patient with trifluoperazine 30 mg/d; 1 patient with haloperidol decanoate 50 mg)

Medication 5-10 mg/d of olanzapine 2.5±1 mg/day of at 4 weeks of risperidone follow-up

Additional benzodiazepines (5 received clonazepam no additional treatment 2-4 mg/d, 3 – lorazepam 2-4 mg/d) therapy citalopram (4 patients – 20 mg/d) trihexyphenidyl (3 patients – 4 mg/d)

Before the EEG/MEG measurements, the subjective levels of anxiety, mood, and arousal were measured with the visual analogue scales (VAS). The VAS allows the quantification of small changes over time and there is a good subject/observer agreement for this method (Hornblow and Kidson 1976; Hotopf et al. 1999; Lundberg 1980). The VAS was presented in the form of a 10-cm line. The anchor statements were “not at all” and “very much so”. Two experimental sessions were separated by one week.

Studies were performed at the Republican Vilnius Psychiatric Hospital (Vilnius, Lithuania) (Studies I, II) and at the BioMag Laboratory, at the Helsinki University Central Hospital (Helsinki, Finland) (Studies III, IV). The studies were approved by the Ethic Committees of the Hospitals. Subjects gave their written informed consent to participate in the study.

42 3.2. Study design and data acquisition

Study design

ERP recordings were performed at the baseline and at follow-up in Studies I, II. We used random, double-blind, cross-over design in Studies III, IV; VAS was employed immediately prior to the EEG/MEG measurements. The main study design is summarized in Table 4.

Table 4. Design of the studies

Study First recording Subsequent recording

Study I baseline (before olanzapine treatment) at 2 and 4 weeks’ follow-up

Study II baseline (before risperidone treatment) at 2 weeks’ follow-up

Study III four hours after the administration of 30 mg after 1 week of memantine or a placebo

Study IV four hours after the administration of 40 mg after 1 week of methylphenidate or a placebo

Data acquisition

Studies I, II

All data were acquired in an electrically shielded room. The recording sessions were always carried out between 9 a.m. and 2 p.m. The main recording parameters are presented in Table 5. The ERPs were recorded with a 32- channel EEG device (Galileo NT, by EBNeuro, Italy) (passband 0.01–30 Hz) from F3, Fz, F4, C3, Cz, C4, and Pz sites (according to the 10/20 International system) using Ag/AgCl electrodes. Ear electrodes served as a reference for all electrodes and the ground electrode was attached to the forehead. ERPs were acquired during active and passive auditory oddball paradigms. The signal-rejection threshold was set for an amplitude of more than 100 µV. The active

43 paradigm was set before the passive paradigm. Each paradigm consisted of two blocks with 1- min interval.

P300 recording In the P300 recording paradigm, pure tones were binaurally presented via headphones at an intensity of 60dB. The standard tone had a frequency of 1000 Hz and duration of 50 ms. Deviant tones had the same duration but they were of 2000 Hz. The probability of tones was 80% for standards and 20% for deviants. During the recording, at least 30 deviant stimuli were presented. Subjects were asked to silently count all deviant stimuli and then to report the number. To ensure counting accuracy subjects were asked to count the stimuli out loud at the beginning of the trial. In this way, we were able to make sure that subjects understood the procedure. Afterwards, subjects were allowed to count the stimuli silently; however, with the interval of 2-10 stimuli the subjects were periodically checked by being asked to report the calculated number. Only when we were completely sure of the subjects’ required accuracy did we start the actual recording. Meanwhile, the subjects were aware that they were participating in the actual recording. Consequently, the subjects were ready to report the number at any time and stayed alert throughout the entire procedure, anticipating our possible checks on them. Subjects were motivated by the fact that we explained that a precise calculation of the final number was of utmost importance to the interpretation of the results of the entire procedure. Most of the time subjects performed very accurately. There were no significant differences between schizophrenia and healthy control groups in the reported number of calculated deviants. The ISI was 1500 ms. The analysis period was 1000 ms.

MMN recording During the MMN recording, subjects were reading a self-selected text. They were instructed not to attend to tones (for more details, see Kraus et al. 1992; Naatanen et al. 1978). Pure tones were binaurally presented via headphones at an intensity of 60dB. The standard tone was 1000 Hz and 75 ms in duration. Deviant tones had a frequency of 1000 Hz and they were of 25 ms in duration. The probability for standards was 90% and for deviants 10%. During the recording, at least 60 deviant tones were presented with an ISI of 1 s. The analysis period was 500 ms.

44 Studies III, IV

The main recording parameters are presented in Table 5. During the MEG/EEG recordings, each subject sat in a comfortable chair located in an electromagnetically shielded room (Euroshield, Finland) with their head inside a helmet. During the recording, contact with the subjects was maintained with on-line video monitoring.

MMN recording ERPs were recorded with a 60-channel EEG using an electrode cap (Virtanen et al. 1996) and an amplifier (Virtanen et al. 1997) specifically designed and built for simultaneous EEG and MEG measurements.

MMNm recording The ERFs were recorded with a 306-channel MEG Neuromag Vectorview system (Elekta-Neuromag, Helsinki, Finland) consisting of 204 planar gradiometers and 102 magnetometers. Only gradiometer sensor-pairs were used in the following analysis. The subjects watched a silent video and were instructed to pay no attention to the tones presented monaurally to the left ear through a plastic tube and an earpiece. Left monaural stimulation elicits MEG responses over both the right and left auditory cortices (Kahkonen et al. 2001a; Pekkonen et al. 1995). Moreover, this kind of stimulation seems to be especially useful in clinically oriented MEG research as was shown in studies into ageing (Pekkonen et al. 1995).

Each two-channel gradiometer sensor unit measured two independent magnetic field ∂ ∂ ∂ ∂ gradient components Bz/ x and Bz/ y, with the z-axis being normalised at the local helmet surface. The position of the subject’s head relative to the recording instrument was determined by measuring the magnetic fields produced by marker coils in relation to the cardinal points on the head (nasion, left and right pre-auricular points), determined before the experiment using an Isotrak 3D-digitizer (Polhemus, Colchester, VT, U.S.A.).

45 Table 5. Main ERP and ERF recording parameters

Parameters P300 recording MMN recording MMN and MMNm recording

Type of change between frequency duration change duration change frequency deviant and standard stimuli change change Nr. of study Studies I, II Study I Studies III, IV Analysis epoch 1000 ms 500 ms 750 ms (including 100 ms prestimulus baseline) Minimum number of 30 60 100 100 averages without artifacts Number of recording sessions 2 2 1 1 (with 2 min. interval) Stimulation type left and right ears left and right ears only left ear only left ear Interstimulus interval 1500 ms 1000 ms 1000 ms 1000 ms Stimulus type auditory auditory auditory auditory Stimulus frequency: Deviant tone 2000 Hz 1000 Hz 700 600 Standard tone 1000 Hz 1000 Hz 700 700 Stimulus occurrence probability: Deviant stimulus 20% 10% 20 20 Standard stimulus 80% 90% 80 80 Deviant/standard stimulus ratio 1:4 1:9 1:4 1:4 Stimulus intensity: Deviant tone 60 dB SPL 60 dB SPL 60 dB over the subjective stimulus threshold Standard tone 60 dB SPL 60 dB SPL 60 dB over the subjective stimulus threshold Stimulus duration: Deviant stimulus 50 ms 25 ms 25 50 Standard stimulus 50 ms 75 ms 50 50 Montage monopolar Active electrodes/channels F3, Fz, F4, C3, Cz, C4, Pz (10/20 64 active EEG electrodes system) + 306 MEG channels (204 planar gradiometers and 102 magnetometers) Ground electrode Fpz (lobe) cheek cheek Reference A1, A2 (ears) nose nose Artefact rejection >100 µV epochs containing EOG, EEG, or MEG changes exceeding 100 µV, 150 µV or 3,000 fT/ cm, respectively, as well as the responses to the first few stimuli Registration conditions: Position of the subject sitting in the sitting in the chair sitting in the chair and watching chair and reading self- self-selected movie selected text Eyes closed* open open open Task To silently count To read the text To watch the movie and not to target (deviant) and not to attend attend to the tones stimuli to the tones

*In case of increased alfa- activity, the subject was asked to open his/her eyes.

46 3.3. Data analysis and statistics

Data analysis

The main analysis parameters for all studies are summarized in Table 6. Digital filters were applied off-line. The MMN response was obtained by subtracting the standard response from that to deviant stimulus. Amplitudes of all components in Studies I, II were calculated as peak-to-peak voltage differences.

Table 6. Summary of the ERP analysis parameters

Study Component Electrode sites Passband Latency window (filter), Hz post-stimulus, ms

I MMN F3, Fz, F4 0.15–30 100–300

N200, P300 Fz, Cz, Pz 200–500

II N100 Cz 0.01–30 70–150

P200 150–300

P300 200–500

III P50 frontal: F3, F1, Fz, F2, F4; 5–40 25–80 central: C3, C1, Cz, C2, C4; N100 parietal: P3, P1, Pz, P2, P4 1–30 50–150

MMN F1, Fz, F2, FC1, FCz, FC2, 1–20 130–250 C1, Cz, C2, CP1, CPz, CP2, P1, Pz, P2

IV N100 frontal: F3, F1, Fz, F2, F4; 1–30 50–150 central: C3, C1, Cz, C2, C4; 1–30 P200 parietal: P3, P1, Pz, P2, P4 120–250 MMN 1–20 130–250

In Studies III, IV, averaged responses were baseline-corrected off-line in relation to the mean amplitude at the 100-ms pre-stimulus interval. The analysis period for the averaged epochs was 750 ms. For the EEG, the peak latencies of different components were

47 measured from the channel with the largest deflection. The electrode sites used for the EEG analysis corresponded to the electrode positions in a 10/20 system. As the MMN amplitudes were largest at the right frontocentral electrodes, the average amplitude of 15 EEG channels (F1, Fz, F2, FC1, FCz, FC2, C1, Cz, C2, CP1, CPz, CP2, P1, Pz, P2) was determined in Study III. The P50 and N100 latencies were determined at the Cz, from responses to standard tones. At these latencies, the amplitudes of the P50 and N100 peaks were determined from three subsets of EEG channels (frontal: F3, F1, Fz, F2, F4; central: C3, C1, Cz, C2, C4; parietal: P3, P1, Pz, P2, P4). In Study IV, the N100 and P200 latencies were determined at the Cz from responses to standard tones. At these latencies, the peak amplitudes of the N100, P200 and MMN were determined from three subsets of EEG channels (frontal: F3, F1, Fz, F2, F4; central: C3, C1, Cz, C2, C4; parietal: P3, P1, Pz, P2, P4).

For the MEG, in addition to the temporal filtering, signal-space projection (SSP) was applied to suppress external magnetic noise (Tesche et al. 1995; Uusitalo and Ilmoniemi 1997). The Peak latencies and amplitudes of the ERFs were measured from channel- ∂ ∂ 2 pairs showing the highest amplitude over the left and right temporal areas ([ Bz/ x] + ∂ ∂ 2 ½ [ Bz/ y] ) . The sources of the P50m, N100m, MMNm (Study III), and P100m, P200m and MMNm (Study IV) were estimated with single equivalent current dipoles (ECD), found by a least-squares fit, using a fixed subset of 34 channels over the auditory cortex separately for each subject’s left and right hemispheres (Hamalainen et al. 1993). A spherical head model was used. The peak latencies and ECD amplitudes as well as the degree of “fit” were determined from the time-course curves of the sources. The ECD that had a local maximum in source strength, Q, or, in its absence, a local maximum in the degree of fit, was chosen as representative of the source. Dipole fits with at least 60% (Study III) and 70% (Study IV) residual variance were considered successful. The estimate of the “centre of gravity” of the cortical activation was based on a coordinate system in which the x-axis goes from the left to right preauricular point, the y-axis is perpendicular to the x-axis and passes through the nasion, and the z-axis points upwards. The centre of symmetry in the head model was at {x, y, z }= {0, 0, 50 mm}.

48 Statistics

Inter-group comparison Statistical comparisons of the data were made using t-tests (in case of normal distribution of variables) or Mann-Whitney U-test (in case of nonparametric distribution) and analyses of variance (ANOVA/MANOVA). An alpha level of 0.05 was used for all the statistical tests. Study I As we were interested in comparison between peak latencies and amplitudes of all three ERP components (N200, P300, MMN) between healthy controls and patients at each electrode site, we decided to use unpaired t-tests. The effects of olanzapine treatment on the peak latencies and amplitudes of different ERP components were assessed by a method similar to repeated-measurement analysis of variances (ANOVA) (we use the term “repeated measurement” in order better to describe the design of measurements for the schizophrenia group), with a diagnostic group as the inter-subject factor, and electrode site (F3, Fz, F4 for MMN and Fz, Cz, Pz for N200, P300) and session (baseline, 2 week follow-up, 4 week follow up) as intra-subject factors. We also made an assumption that the control group measurements did not change over time and used their baseline values as proxies (substitutes) for weeks 2 and 4. In this way, we made a comparison of the schizophrenia group with healthy controls at both these points in time. Study II Comparisons of peak latencies and amplitudes of three ERP components (N100, P200, P300) were performed between healthy controls and patients at baseline, between healthy controls and patients after the 2-week follow-up and between the patients at the baseline and after 2-week follow-up. The Mann-Whitney U-test was used for comparison. Study III The statistical analysis for the MEG data was carried out with a two-factor (drug: memantine, placebo; hemisphere: contralateral, ipsilateral side of stimulated ear) repeated- measurement analysis of variance (ANOVA). The amplitudes of the P50 and N100 were also analyzed with a two-factor (drug: memantine, placebo; electrode site: frontal, central, and parietal) repeated-measurement analysis (ANOVA). Study IV We used paired t-tests to analyze the amplitudes and latencies of N100 and P200 at Cz, and MMN at Fz. The statistical analysis of the MEG data was carried out by repeated-

49 measurement analysis of variance (ANOVA) with two-factors: drug: methylphenidate vs. placebo and hemisphere: the contralateral vs. ipsilateral side of the stimulated ear.

Permutation test We used the permutation (or randomization) test, first proposed by Blair and Karniski (1993), to evaluate the overall differences between the scalp distributions of brain electrical potentials (60 EEG electrodes) under different experimental conditions - placebo and drug (Galan et al. 1997; Kahkonen et al. 2001c; Karniski et al. 1994) (Studies III, IV).

Correlation analysis The correlation coefficients between ERPs and PANSS were calculated by the Pearson (Study I) and Spearman (Study II) correlation analysis. The extent of drug-induced effects (subjective, measured with VAS) was correlated with the amplitudes and latencies of the ERPs using Spearman’s correlation coefficient(Studies III, IV).

50 4. RESULTS

Effects of olanzapine on active and passive attention measured with ERPs (Study I)

Psychopathology Olanzapine decreased all PANSS, total psychopathology, positive symptom and negative symptom scales (Table 7).

Table 7. PANSS scores before and after olanzapine treatment

Baseline After olanzapine treatment

PANSS 90.6±16.3 56.7±10.1**

positive symptom scale 16.9±4.6 10.9±1.9**

negative symptom scale 21.4±4.5 16.4±4.1*

total psychopathology scale 51.9±10.7 30.3±4.7**

* P<0.05; ** P<0.01.

Active paradigm

The mean amplitudes and latencies of P300 components at baseline and after 2 and 4 weeks of olanzapine treatment are presented in Table 8. Overall average ERP waveforms for the active paradigm are presented in Fig. 1a.

Comparison at baseline of patients and healthy controls Patients presented smaller amplitudes of both the N200 and P300 components than controls. However, only the P300 amplitude differences had any statistical significance (Fz: t=2.86, P<0.01; Cz: t=3.37, P=0.03; Pz: t=3.98, P=0.04; df for all electrodes = 24). No differences in latencies between the patients and controls were observed.

51 Effects of olanzapine treatment A repeated-measurement ANOVA demonstrated no significant group effect or group × session or group × electrode site interactions for either the N200 or the P300 amplitudes (main effects for N200: F(2,28)=0.51, P=0.61; interaction effect for N200: F(4,56)=0.59, P=0.67; main effects for P300: F(2,28)=0.08, P=0.92; interaction effect for P300: F(4,56)=0.4, P=1.0). ANOVA did not reveal significant group main effects and/or group×session or group×electrode site interactions for either the N200 or the P300 latencies (main effects for N200: F(2,28)=0.93, P=0.41; interaction effect for N200: F(4,56)=0.44, P=0.78); main effects for P300: F(2,28)=0.61; P=0.55; interaction effect for P300: F(4,56)=2.18; P=0.08). At the 4-week follow-up, patients still had significantly smaller P300 amplitudes compared with controls. (Fz: t=3.16, df=22, P=0.004; Cz: t=2.92, df=23, P=0.008; Pz: t=2.57, df=23, P=0.017).

Figure 1. Grand-average of (a) P300 and (b) Mismatch Negativity in healthy controls and patients after 2 and 4 weeks of treatment.

52 Passive paradigm

The mean amplitudes and latencies of the MMN component at the baseline, after 2 and after 4 weeks of olanzapine treatment are presented in Table 8. Grand-averaged ERP waveforms for the active paradigm are presented in Fig. 1b.

Comparison of patients at baseline vs. healthy controls The MMN latency and amplitude did not differ between patients and healthy controls (for latency: t=1.7, df=24, P=0.1; for amplitude: t=0.26, df=24, P=0.8).

Effects of olanzapine treatment A repeated-measurement ANOVA with MMN latencies (at F3, Fz, F4 electrodes) demonstrated no significant effects of session and no significant session×electrode site interactions (main effect: F(2,26)=0.94; P=0.4; interaction effect: F(4,52)=0.88; P=0.48). ANOVA did not reveal significant group main effects and/or group×session or session×electrode site interactions for the MMN amplitudes (main effect: F(2,26)=0.43; P=0.65; interaction effect: F(4,52)=0.9; P=0.47).

Table 8. Latencies and amplitudes of ERP components (± SD) of healthy controls and patients at baseline, 2 weeks (Patients F2) and 4-weeks (Patients F4) of follow-up.

Components MMN P300

Locations of electrodes F3 Fz F4 Fz Cz Pz

Latency, ms

Healthy controls, N=15 145.1±13.8 144.6±13.6 146.7±14.4 325.3±27.9 327.2±26.1 326.9±26.1

Patients at baseline, N=11 149.8±11.8 151.9±12.9 150.4±11.6 332.6±40.5 336±39 339.1±39.8

Patients F2, N=11 144.5±14.6 143.5±14 142.4±7.3 329.7±49.2 334.6±53.2 336.7±53.6

Patients F4, N=9, for MMN 145.3±21 147.1±21.2 143±18.6 321.2±36.2 325.7±39.1 328.7±39.2 N=7

53 Amplitude, µV

Healthy controls, N=15 5.7±2.2 5.3±2.2 5.7±1.8 17.6±9.3 17.2±8.6 17.4±8.9

Patients at baseline, N=11 4.9±2 5.3±3.3 5±2.8 10.5±3.7** 9.5±4.3* 9.7±4*

Patients F2, N=11 5.4±1.3 5±1.2 5.2±1.3 8.5±3.7 8.4±3.8 8.6±3.8

Patients F4, N=9, for MMN 4.9±1.1 4.5±1.5 4.7±1.8 8.6±1.4** 9.6±4.6** 10.1±5.3* N=7

*P<0.05, **P<0.01; healthy controls compared to patients at baseline

Relationship between psychopathology, effect of treatment and ERPs There were no significant correlations between the latencies and amplitudes of N200, P300 and MMN and clinical scores measured by PANSS scale at baseline and follow-up periods.

Summary In the current study, the effect of the antipsychotic drug olanzapine on the neural bases of auditory information processing was explored by means of auditory ERPs in patients with schizophrenia-spectrum disorders. ERPs were recorded during active and passive auditory “oddball”-paradigms before, after 2 weeks of, and after 4 weeks of, olanzapine treatment. Before the treatment, patients showed significantly reduced P300 amplitudes compared with healthy controls. Clinical signs measured with PANSS improved significantly after the olanzapine treatment. However, olanzapine had no significant effects on the latencies and amplitudes of MMN and P300 during 4 weeks of treatment. As MMN is considered to be an index of involuntary change-detection mechanism, and P300 could reflect attention- dependent processes, we assume that olanzapine does not influence the neural substrates of these processes measured by MMN and P300 after 4 weeks of treatment.

Effects of risperidone on active attention measured with ERPs (Study II)

Psychopathology Risperidone decreased all PANSS, total psychopathology, positive symptom and negative symptom scales (Table 9).

54 Table 9. PANSS before and after risperidone treatment

Baseline After risperidone treatment PANSS, scores 97.4±14.9 67.4±9.5* positive symptom scale, scores 22.1±5 14.1±2.3* negative symptom scale, scores 20.2±3.9 16.3±4* total psychopathology scale, scores 57.1±15.2 37±5.7*

* P<0.05, patients at baseline compared to follow-up

Effects of risperidone treatment The mean amplitudes and latencies of N100, P200 and P300 components at baseline and after 2 weeks of risperidone treatment are presented in Table 10. Grand-average ERP waveforms are presented in Fig. 2. At the baseline, patients showed significantly longer P300 latencies than those of controls (U=17, Z=-2.03, P=0.04). No significant differences in the baseline N100 and P200 amplitudes or latencies between patients and controls were observed (P>0.05). Risperidone treatment did not change P300 amplitudes or latencies (P>0.05). After the treatment, patients still had longer P300 latencies than those of controls (U=2.5, Z=-3.07, P=0.002). A significant decrease in P200 amplitude after risperidone treatment was observed (U=12, Z=2.06, P=0.04). Risperidone did not affect the N100 amplitudes and latencies or the P200 latencies (P>0.05).

Table 10. The average peak latencies and amplitudes (±SD) of the P200 and P300 components in healthy controls and patients with schizophrenia spectrum disorders at baseline and after two weeks of treatment.

Latency, ms Amplitude, µV Components P200 P300 P200 P300 Healthy controls 191.8±13.7 319.8±28.6 16.5±8.4 21.7±13.1 Patients at baseline 185.8±30 347.8±24.4* 17±9 11.8±8.6 Patients after 186.6±17.5 358.3±25.9* 9.4±6.4§ 16.4±7.4 treatment

*P<0.05, patients at baseline and at the follow-up compared with healthy controls; § P<0.05, patients at follow-up compared with patients at baseline.

55 Relationship between psychopathology and ERPs There were no significant correlations between the latencies and amplitudes of N100, P200, P300 and clinical scores measured with PANSS at baseline and follow-up.

Figure 2. Grand-average of ERPs in healthy controls, patients at baseline and patients after 2 weeks of risperidone treatment.

Summary In the current study, the effects of two-week risperidone treatment on neural bases of auditory information processing were explored with ERPs in a small sample of neuroleptic naive patients with schizophrenia spectrum disorders. ERPs were elicited during the active auditory “oddball” paradigm and were recorded before and after the two weeks of treatment. Baseline P300 latencies were significantly delayed in the patient group. Risperidone treatment did not change the P300 amplitudes and latencies. However, the P200 amplitudes were reduced in parallel with the clinical improvement measured by Positive and Negative Syndrome Scale. The results of this study indicate that risperidone did not have early effects on attention-dependent processes related to P300 generation. However, the reduction of P200 amplitude suggests that risperidone (possibly through the

56 effect on the DA system) may modulate the neuronal population activity responsible for auditory information processing reflected in P200 in patients with schizophrenia spectrum disorders who have never been exposed to antipsychotics.

Effects of NMDA receptor antagonist memantine on mismatch negativity (Study III)

VAS results Memantine significantly decreased the arousal level (VAS scores 35.7±20.5 vs. 55.5±28.6 in memantine and placebo conditions, respectively; P<0.05), and increased the speed of thinking (48.7±22.7 vs. 31.2±29.6; P<0.05), whereas mood and anxiety were not significantly affected.

MEG It was observed that the drug produced no significant main effects or drug x hemisphere interactions for P50m, N100m, and MMNm amplitudes or latencies in response to duration and frequency changes. Further, ANOVA did not reveal significant effects for source activities of P50m, N100m, and MMNm in response to duration and frequency changes. Also, memantine did not change the locations of the sources.

EEG The MMN amplitudes to frequency changes were significantly greater after memantine administration than after placebo (t=2.32; P=0.038) (Table 11, Fig. 3). Whereas the memantine did not change the MMN latencies, ANOVA revealed no significant main effects of the drug, or drug x electrode interactions, on the P50 and N100 amplitudes and latencies. The permutation test, used to assess differences between scalp voltage distributions, revealed that the MMN response to frequency change was nearly significantly (P=0.08) affected by memantine, but no differences were observed in other ERP components between the memantine and placebo conditions. There was no significant correlation between the latencies and the amplitudes of MMN and the extent of VAS changes in the memantine as compared with the placebo condition.

57 Table 11. Mean±SD peak latencies (ms) and amplitudes (µV) of electric MMN responses

Duration change condition Frequency change condition

Placebo Memantine Placebo Memantine

MMN Latency (at Fz) 170.6±26.6 182.1±22 177.9±43.5 162.7±37.4

Amplitude -1.71±1.14 -1.48±1.06 -0.98±1.05 -1.89±1.05*

*P<0.05.

Figure 3. (a) Grand-average MMN waves to frequency change in memantine and placebo conditions. (b) Grand-average potential maps, estimated at the peak latency of MMN in each condition. Topographic distribution of the differences between placebo and memantine conditions revealed by paired t-test. Note the low P-values in the right fronto- temporal area. The nose is upwards.

58 Summary We aimed to determine whether a single dose of memantine would affect neural substrates of auditory information processing reflected in MMN/MMNm in healthy subjects studied with simultaneous electroencephalography (EEG) and magnetoencephalography (MEG). Monaural left-ear auditory stimuli were presented in a passive oddball paradigm with infrequent deviant tones differing in frequency and duration. Neuronal activity was recorded in 13 healthy subjects after oral administration of 30 mg of memantine or placebo in a randomized, double-blind, cross-over design. MMNm was analyzed using equivalent current dipoles. MMN was evaluated from fronto-central electrodes. Memantine lowered subjects’ arousal level as measured by visual analog scales, and enhanced the amplitude of MMN in the EEG. No differences in MMN latency were observed in the MEG or EEG. Memantine did not affect the location, strength, amplitude or latency of the MMNm, P50m, and N100m components. No changes in amplitude or latency were observed for P50 and N100 peaks. These results indicate that memantine (possibly through NMDA receptors), without otherwise changing auditory stimulus processing, affects neuronal resources, postulated to be responsible for involuntary change-detection reflected in MMN. Memantine-induced changes in the electrical MMN component alone could reflect modulation of the putative frontal MMN subcomponent that is more clearly observed in EEG than MEG.

The effect of methylphenidate on auditory information processing in healthy volunteers: a combined EEG/MEG (Study IV)

VAS Methylphenidate significantly increased the arousal level (VAS scores 63.4±16.2 vs. 39.4±25.3 in MPH and placebo conditions, respectively; P<0.01), speed of thinking (74.5±15.3 vs. 59.1±18.7; P<0.05), and raised the general mood level (76.2±14.0 vs. 62.2±19.7; P<0.05), but did not significantly affect the anxiety level.

MEG We observed no significant main effects of the drug or drug x hemisphere interactions for N100m, P200m and MMNm amplitudes or latencies in response to duration and frequency changes. ANOVA revealed no significant effects on the source activities of N100m, P200m and MMNm in response to duration and frequency changes. MPH did not change the locations of the sources.

59 EEG While comparing two scalp distributions, the permutation test revealed that the MPH significantly (P<0.05) reduced the P200 response amplitude in both frequency- and duration-change MMN paradigms (Fig. 4), but no differences were observed between the MPH and placebo conditions in other ERP components. The paired t-test also revealed that the P200 amplitudes in response to frequency change were significantly smaller after the administration of MPH than after that of placebo (P<0.01) (see Table 12), whereas MPH did not change the P200 latencies. We observed no significant correlation between the latencies and the amplitudes of P200 and the extent of VAS changes in MPH in comparison to the placebo condition.

Figure 4. Top: grand average EEG waves of 13 healthy subjects from responses to standard tones during placebo and methylphenidate in duration and frequency change conditions (negativity upwards). Bottom: grand average EEG potential maps on a spherical head model, estimated at the peak latency of P200 under each condition; the nose is upward.

60 Table 12. Mean ± SD peak latencies (ms) and amplitudes (µV) of electric P200 and MMN responses in methylphenidate and placebo conditions

Duration change Frequency change condition condition Placebo MPH Placebo MPH P200 Latency (at Cz) 160.6±28.5 157.5±28.4 162.1±26.4 158.4±21.7 Amplitude Frontal 1.3±0.9 1.0±0.9 1.3±1.0 1.1±1.0 Central 0.9±0.6 0.6±0.7 1.0±0.6 0.6±0.7* Parietal 0.8±0.6 0.4±0.6 0.9±0.5 0.5±0.7 MMN Latency (at Fz) 190.5±33 178.3±19 158.3±24.4 159.3±19.9 Amplitude Frontal -1.9±0.9 -2.3±1.1 -2.0±1.0 -2.2±0.9 Central -0.9±0.5 -1.3±0.9 -0.8±0.7 -0.7±0.7 Parietal -0.7±0.7 -0.9±1.3 -0.1±1.1 -0.6±0.8

*P<0.01; paired t-test between methylphenidate and placebo conditions.

Summary We investigated neural mechanisms of MPH action on sensory information processing, aiming to determine whether a single dose of MPH affects neural substrates of passive attention in healthy adults studied with simultaneous whole-head magnetoencephalography (MEG) and electroencephalography (EEG). Monaural left-ear auditory stimuli were presented in an oddball paradigm, with infrequent deviant tones differing in frequency and duration from standard. Neuronal activity was recorded with simultaneous whole-head MEG and EEG in 13 healthy subjects (5 females; aged 27 ± 5 years) after oral administration of 40 mg MPH or placebo in a randomized, double-blind, cross-over design. We analyzed both electric and magnetic N100, P200 and mismatch negativity (MMN) components. MPH increased arousal levels in Visual Analogue Scales, whereas it had no effect on the dipole strength of MMN or MMNm in either frequency or duration deviations. MPH did reduce P200 amplitudes in EEG, however. Therefore, we could suggest that MPH through the modulation of NA and DA systems, affects auditory information processing reflected in P200. However, there is no strong relationship between DA and preattentive auditory processes reflected in MMN.

61 5. DISCUSSION

Cognitive impairments are common features in schizophrenia patients. The neuro­ physiological and neurochemical changes in the auditory cortex are shown to underlie cognitive impairments in schizophrenia. Neurochemical modulation (e.g. antipsychotic medication) is used to improve clinical status and cognitive functioning in schizophrenia. We used auditory ERPs and ERFs to explore how neurochemical modulation, produced by antipsychotic drugs olanzapine and risperidone, affects the neural basis of auditory information processing in patients with schizophrenia spectrum disorders (Studies I, II). We determined that after 2 and 4 weeks of treatment, olanzapine has no significant effects on the MMN and P300, which, it has been proposed, reflect preattentive and attention-dependent information processing, respectively. After 2 weeks of treatment, risperidone has no significant effect on P300; however, risperidone reduces the P200 amplitude. This latter effect of risperidone on auditory information processing could be partly explained through the dopamine modulation of the P200-related neural response. However, observed effects could not be properly interpreted because of the obscuring factors such as the effect of other add-on drugs on the same neural substrates. With a view to understanding the possible role of main neurochemical agents involved in the pathophysiology of schizophrenia (glutamate, dopamine) in modulation of auditory information processing and to excluding any contaminating factors mentioned above, we decided to use pharmacological challenges such as memantine and methylphenidate in healthy subjects (Studies III, IV). We observed a complex pattern of neurochemical influences produced by both antipsychotics and pharmacological challenges. Neuronal populations responsible for the generation of different ERP components could be selectively modulated by different neurotransmitter systems.

Auditory information processing in patients with schizophrenia spectrum disorders

Deficient P300 generation in patients with schizophrenia spectrum disorders (reduction of the P300 amplitude) Although a reduced P300 amplitude in schizophrenia is a well established phenomenon and is replicated in a large number of studies (Blackwood et al. 1987; Braff 1993; Duncan

62 1988; Kutcher et al. 1987; Ogura et al. 1991; Pass et al. 1980; Roth and Cannon 1972), the question remains as to whether this abnormality in the P300 response is also evident in patients with other types of disorders in the schizophrenia spectrum. We found that patients with schizophrenia spectrum, in comparison with healthy controls, showed reduced P300 amplitude (Study I). In a number of previous studies there were no significant P300 differences observed in schizotypal personality disorder (Squires-Wheeler et al. 1997; Trestman et al. 1996) or in a group of schizophrenic and schizoaffective disorder patients (Alain et al. 2001) when compared with healthy control subjects. However, Kutcher et al. (1989) reported that the P300 latency was prolonged in schizotypal personality disorder. Moreover, Weisbrod et al. (1999) found significant reduction of P300 amplitude in a group of patients with schizophrenia and schizoaffective psychosis. Our results are in line with these latter findings, confirming deficient P300 generation in patients with schizophrenia spectrum. The P300 amplitude decrease observed in the present study could serve as an index of decreased attention-dependent resources in patients with schizophrenia spectrum disorders.

P300 changes in first-episode patients with schizophrenia spectrum disorders P300 studies with unmedicated patients are quite rare. We found that the P300 latency was significantly delayed in a “never-medicated” patients’ group with schizophrenia spectrum disorders, compared with healthy control subjects (Study II). Previous reports indicated a prolongation of the P300 latency in drug-naive schizophrenia patients (for review, see Jeon and Polich 2003), although this observation is not as consistent as the reduction of the P300 amplitude. The same pattern of P300 changes is observed in patients with other types of schizophrenia spectrum as well - in previous studies, significant changes in the P300 amplitude, but not latency, were more often reported in patients with schizophrenia spectrum disorders. For example, Salisbury et al. (1996) showed a left-lateralized P300-amplitude abnormality in a sample of unmedicated patients with schizotypal personality disorder and confirmed their results in a subsequent study (Salisbury et al. 1998). However, it seems that neuroleptic naive first-episode patients do have prolonged latencies more often than reduced amplitudes. The present P300-latency prolongation in neuroleptic-naive patients is in line with the study of Demiralp et al (2002), who found a clear prolongation of the P300 latency in first-episode schizophrenia. The observation of a delayed P300 latency in our Study II indicates that attention-dependent processes reflected in P300 component are already slowed down in the early stages in patients with schizophrenia spectrum disorders.

63 MMN in schizophrenia spectrum disorders By contrast with the P300 results, we did not observe any significant differences in MMN response between the group of schizophrenia spectrum patients and healthy controls (Study I). In their meta-analysis, Umbricht and Krljes (2005) summarized the results on MMN changes in schizophrenia patients from about 40 published studies, starting with the original investigation by Shelley et al. (1991) and going up to the end of 2003. Results indicated a strong association between a deficient MMN generation and chronic schizophrenia (overall effect size was 0.99). Previous studies showed that MMN to stimuli differing in duration is more impaired than MMN to frequency change (Michie et al. 2000a; Umbricht and Krljes 2005). Further, a recent study (Fisher et al. 2008) of schizophrenia patients with the multi-feature paradigm (Naatanen et al. 2004), which tests MMN changes in response to five different types of physically deviant tones, showed specific changes only in duration and intensity of MMN responses (see also Todd et al. 2008). In our study, MMN elicited by frequency deviants was used. This could explain the absence of significant differences between MMN responses in the schizophrenia spectrum group and healthy volunteers. Another aspect should also be taken into consideration. Even though in the present study conventional parameters such as the amplitude and latency did not allow discrimination between the schizophrenia spectrum and healthy controls groups, other parameters such as the slope of the ascending MMN wave or the MMN area could improve discrimination accuracy (Korostenskaja et al. 2003b).

Further, only one study until now clearly demonstrated MMN changes in a group of schizophrenia spectrum patients (MMN was evoked by duration increments) (Michie et al. 2002). Significant reduction in MMN amplitude was observed in healthy first-degree relatives of individuals with schizophrenia (Jessen et al. 2001; Michie et al. 2002). However, a study by Jessen et al. (2001) is rather inconclusive – in this study, no differences between patients and healthy controls were observed. Moreover, sample size used in the study is relatively small. This could suggest that the findings might be false and/or related to some other factor than predisposition to schizophrenia. And even more controversy exists. For instance, Bramon et al. (2004a) reported unchanged MMN among the unaffected relatives of schizophrenia patients. A twin’s study, which provides a better control for separation of environmental and genetic factors, did not show any significant differences in MMN responses between unaffected co-twins of schizophrenia patients and healthy controls, while at the same time showing similar N50 and N100 responses in unaffected co-twins and those with schizophrenia (Ahveninen et al. 2006). In addition, Salisbury et al. (2002)

64 found that the pitch-deviant MMN reduction that is present in patients with chronic schizophrenia is absent in patients at their first hospitalization. This provides evidence that MMN changes are related to the progress of the disease. Finally, Magno et al. (2008) did not observe any MMN deficiency in first-degree biological relatives of schizophrenia patients, or in first-episode schizophrenia patients, compared with healthy controls. At the same time, Weisbrod et al. (1999) observed a clear reduction in P300 amplitudes both in twins with schizophrenia and their non-affected co-twins (see also Turetsky et al. 2000). Overall, it seems that whereas MMN deficits in schizophrenia patients are progressive (Salisbury et al. 2002), and not present at illness onset, abnormalities in P300 response are already discernible in first-episode patients (our Study II) and are not significantly influenced by the duration of the illness (see also meta-analysis of Bramon et al. 2004b).

Relation of ERPs to the clinical pathology of schizophrenia We observed no significant correlation between the P300 parameters and clinical pathology measured with PANSS (Study I, II). At the present time, the relationship between the clinical symptomatology of schizophrenia and P300 abnormalities still needs to be determined. The results of previous studies investigating this question are very inconsistent. For example, a number of reports have shown a significant correlation between the P300 and psychotic symptoms, e.g., reduced amplitudes with negative symptoms (Eikmeier et al. 1992; Ford et al. 1999; Liu et al. 2004; Pfefferbaum et al. 1989; Pritchard 1986; Strik et al. 1993; Ward et al. 1991), positive symptoms (Egan et al. 1994; Higashima et al. 2003; Kawasaki et al. 1997; Laurent et al. 1993; McCarley et al. 1989) or both (Frodl-Bauch et al. 1999b; Mathalon et al. 2000). However, several further studies (Barrett et al. 1986; Blackwood et al. 1987; Coburn et al. 1998; Laurent et al. 1993; Shenton et al. 1989b) do not reveal any association between the P300 and the psychotic symptoms of schizophrenia. These latter observations are in accordance with the results of our study. We found no published results relating the clinical pathology (PANSS) to P300 parameters in a group of schizophrenia spectrum disorders.

Reports relating MMN measurements with clinical symptomatology in schizophrenia are not consistent either. Some studies (Catts et al. 1995; Javitt et al. 2000; Kasai et al. 2002) found associations between MMN amplitude and negative symptom severity, whereas most studies reported no significant relationship between the PANSS and MMN parameters. Only one previous study (Park et al. 2002) has reported a significant correlation between MMN measurements, such as the left ECD power of the MMN generator, and positive

65 scores in PANSS. Generally, it seems that precisely localized MMN/P300 responses have stronger correlations with measurements of clinical symptomatology (Higashima et al. 2003; Kawasaki et al. 2007; Pae et al. 2003) than traditional measurements. Our study shows that, as with the schizophrenia group, patients with different types of schizophrenia spectrum disorders do not show a significant relationship between MMN parameters and clinical symptoms. This could also be due to the heterogeneity of studied groups. Notably,a recent study by Fisher et al (2008) showed MMN reductions only in hallucinating patients. This argues for a symptom-specific approach in the future.

It should also be mentioned that in previous studies Mathalon et al. (2000) showed that P300 amplitude fluctuates in accordance with the clinical state of the patient, with decrease occurring with worsening of the symptoms and increase with their improvement. This means that when the clinical status of the patient changes, his/her P300 amplitude changes as well. In this case, if an increase in P300 amplitude during olanzapine or risperidone treatment were to be observed, it would be difficult to identify the cause of the increase – i.e. would this change in amplitude be attributable to the change in clinical status or to the change in cognition? In our studies, we could not distinguish between these two changes. Although in our current Studies I and II we did not observe a relationship between symptomatology and changes in ERPs, in order for future research to use ERPs such as MMN and P300 in monitoring the effect of antipsychotic treatment and making the evaluation of cognitive patient status more objective, it would be necessary to distinguish between wheather ERPs reflected an improvement in clinical state or an improvement in cognition. This should be the future approach for this kind of investigation.

Effect of antipsychotic medication on ERPs

There is inconsistency and considerable variability in the reporting of the effects of neuroleptics on ERPs in schizophrenia patients. No studies to date have investigated the effects of antipsychotic drugs in patients with schizophrenia- related disorders. In both of the present Studies I and II we observed no significant effect of olanzapine on MMN and P300 latencies and amplitudes (Study I) and of risperidone on the P300 (Study II) in patients with schizophrenia spectrum disorders.

66 Antipsychotics and P300 Olanzapine To date, several studies (Gallinat et al. 2001; Gonul et al. 2003; Higuchi et al. 2008; Molina et al. 2004; Sumiyoshi et al. 2006) investigating the effect of olanzapine on the P300 response in schizophrenia patients have been conducted. Our results are in line with those shown in the studies by Gallinat et al. (2001) and Molina et al. (2004). Neither of these studies found that treatment with olanzapine had any effect on P300 amplitudes and latencies. The patients studied showed smaller baseline P300 amplitudes compared with healthy controls. The 4 week follow-up period in our study is the same as that of Gallinat et al. (2001). Our results showing unaffected P300 amplitude are partly in line with those of Gonul et al. (2003), who showed that olanzapine treatment does not change the P300 amplitudes at the Pz electrode. However, these authors observed that the P300 amplitude was increased in frontal electrodes. The differences in the results could be partly explained by the differences in the experiment design and conditions. Firstly, they observed in their study a significant delay of P300 latency at the baseline, with a reduction of P300 amplitude in patients with schizophrenia. Secondly, a larger number of subjects was studied and the patient sample was more homogeneous, including more severe forms of schizophrenia. Thirdly, the follow-up period of Gonul et al. (2003) was longer (6 weeks). However, the relationship between treatment duration and changes in P300 response is rather speculative. For instance, Molina et al. (2004), who observed no significant P300 changes under olanzapine treatment, used a 6 month drug follow-up period. However, after the same treatment period, Sumiyoshi et al. (2006) found that the anatomical configuration of the P300 generator was changed (recovery of the left dominant pattern was observed) in schizophrenia patients. The sample size in that study was limited to 5 subjects and could be biased by type-I and type-II errors. However, a subsequent study by the same research group (Higuchi et al. 2008) confirmed their previous results, by showing that six-month olanzapine treatment significantly increased the P300 source density in the left superior temporal gyrus (STG). Interestingly, in the study by Hubl et al. (2001) with healthy subjects, no differences in the P300 responses were found after the 3h, 6h and 9h administration of olanzapine. The lack of the effect of olanzapine on the P300 in our study could also be partly explained by a wash-out period having occurred in several patients during the switch from other neuroleptics to olanzapine treatment.

67 Risperidone To date, only two studies (Iwanami et al. 2001; Umbricht et al. 1999) investigating the effect of risperidone on P300 response in schizophrenia patients have been conducted. In these studies, risperidone significantly reduced P300 latency after 4 weeks (Iwanami et al. 2001) and 6–9 weeks (Umbricht et al. 1999) of treatment. Contrary to these results, our study showed no changes in P300 amplitude and latency. However, in our study, patients received a low dose of risperidone (2.5±1 mg/day) for two weeks, whereas Umbricht et al. (1999) and Iwanami et al. (2001) used higher doses (4–6 mg/day) (Iwanami et al. 2001; Umbricht et al. 1999). It is possible that different doses of risperidone lead to different treatment responses. Finally, patients included in our study had different psychopathologies from the above-mentioned studies. In the present study, these factors may in part explain the absence of an early effect of risperidone on attention.

Antipsychotics and MMN We found that olanzapine had no significant effect on the MMN response after 4 weeks of treatment (Study I). Our results are in agreement with MMN studies of the effects of other atypical antipsychotics, such as clozapine and risperidone, on schizophrenia patients, which found no effects on MMN latencies and amplitudes (Umbricht et al. 1998). However, our patient sample is not fully comparable with those used in other studies, because our patients did not show baseline differences in MMN amplitudes and latencies. This may be due to differences in diagnosis, including less severe forms of schizophrenia spectrum disorders. Or, differences might be partly explained by the different paradigms used. In conclusion, duration of follow-up, dosage of antipsychotic medication, pathophysiology, diagnostic group, and sample size could affect results of the studies.

Taken as a whole, the majority of published data shows that olanzapine has no significant influence on P300 response in schizophrenia patients. Our results suggest that this is also true for patients with schizophrenia spectrum disorders. Risperidone seems to modify the P300 component in patients with schizophrenia, although this is not evident in the group of schizophrenia spectrum disorders. Perospirone, which, unlike risperidone, has a high affinity for 5-HT1A receptors, failed to produce any significant effects on P300 in a group of schizophrenia patients, even after 10 months of treatment (Araki et al. 2006b). It is possible that olanzapine and risperidone have different action profiles on P300 response as well. This suggestion is supported by results obtained by Nieman et al. (2002), who found that patients on risperidone treatment demonstrated P300 changes different from those in

68 patients on olanzapine treatment (Nieman et al. 2002). Moreover, although olanzapine has a receptor profile very similar to that of clozapine, their respective effects on the P300 seem to differ substantially. A review of all the studies conducted up to the present time shows that clozapine has the most stable effect on P300 generation, the amplitude and/ or latency of which was affected in a number of consecutive studies (Galletly et al. 2005; Pallanti et al. 1999; Schall et al. 1998; Umbricht et al. 1998). Further, the onset of action on neurocognitive deficits may vary in timescale between different atypical antipsychotics. This view is also supported in our recent preliminary study on atypical antipsychotic quetiapine in a group of patients with schizoaffective disorder (Korostenskaja et al. 2008, under review). We observed reduction in P300 latency compared with baseline after only two weeks of quetiapine treatment.

Another question that should be addressed is whether adjunctive therapy such as benzodiazepines, used for the treatment of schizophrenia patients in Study I, could have influenced the studied ERP measurements. Drug-challenge studies showed an increase in MMN latency Rosburg et al. (2004) and decrease in MMN amplitude (Nakagome et al. 1998) after the administration of lorazepam and triazolam, respectively, in healthy volunteers. However, studying patients with schizophrenia, Murakami et al. (2002) demonstrated that benzodiazepines do not have a significant influence on MMN response. As the effect of benzodiazepines on ERP responses could differ between healthy and diseased populations, according to the study by Murakami et al. (2002), it would be possible to assume that benzodiazepines did not have effect on MMN in our Study I. Further, a number of findings indicate that benzodiazepines tend to reduce P300 amplitude (Reinsel et al. 1991; Rockstroh et al. 1991) or prolong its latency (Domino et al. 1989). Thus, it would be possible to anticipate the influence of benzodiazepines on the P300 in Study I.

Taken as a whole, results from current and previously- conducted studies, show that, whereas the influence of antipsychotics on the P300 cannot be ruled out, they seem to have no effect on MMN generation in patients with schizophrenia. This is the stage currently reached by researchers.

69 Neurochemical origins of MMN generation in humans

In our combined MEG and EEG Study III, MMN amplitudes were increased in response to a frequency change and the level of arousal was decreased after the administration of memantine. Other EPR and EPF components were unaffected by memantine. In Study IV, statistically significant changes in the subjective test scale (VAS) indicated the effect of MPH on arousal level and speed of thinking. However, in this study, we found that MPH had no significant effect on either electrical or magnetic MMN components. Furthermore, we also found that MPH had a significant effect on P200 components.

Frontal but not temporal MMN components Our findings (Study III) demonstrated that the MMN amplitude, after the introduction of memantine, was increased in the EEG at the right fronto-central electrodes, but not in the MEG. This observation suggests that the frontal MMN component was affected by NMDA receptor modulation. The preconscious discrimination of stimulus change in the auditory cortex eliciting the supratemporal MMN, which is selectively detected by MEG, initiates a sequence of brain events that are associated with involuntary shifting of attention, orienting, and conscious detection of this change (Naatanen 1992). The initiation of involuntary attention shifting is probably reflected by the frontal MMN subcomponent (Escera et al. 1998; Schroger and Wolff 1998a), which is generated later than the supratemporal MMN (Rinne et al. 2000; Tse et al. 2006). The frontal subcomponent might be radially oriented, judging by the fact that it is not detected by the MEG (Rinne et al. 2000). Memantine-induced changes in MMN amplitude are in line with other studies showing that antagonists of NMDA receptors can change MMN amplitude. In the EEG study by Umbricht et al. (2000), ketamine decreased MMN amplitudes in response to duration and frequency changes. Oranje et al. (2000) were, however, unable to confirm these results, showing no effect of ketamine infusion on MMN in a dichotic listening task. Unfortunately, these EEG studies do not allow for distinction between the contribution made by different MMN sources to the memantine effect.

Memantine-induced changes in electrical MMN response alone may reflect modulation of the putative frontal MMN subcomponent that is more clearly observed in EEG than MEG. Based on scalp current density maps, a frontal MMN generator was shown to exist (Deouell et al. 1998; Giard et al. 1990; Rinne et al. 2000; Yago et al. 2001b). These observations receive support from human lesion studies (Alain et al. 1998; Alho et al.

70 1994) and imaging studies (Dittmann-Balcar et al. 2001; Muller et al. 2002; Opitz et al. 2002; Schall et al. 2003; Tse et al. 2006). The right IFG was activated in the frequency- change condition, whereas the left IFG was activated in the duration-change condition (Molholm et al. 2005). This difference in lateralization corresponds to the notion that the right hemisphere is involved in the processing of tonal information (frequency differences), while the left hemisphere is more involved in the processing of temporal information (duration differences) (Belin and Zatorre 2000; Zatorre and Belin 2001; Zatorre et al. 1994). Taken together, these data suggest that the prefrontal cortex subserves auditory deviance detection at a later stage of processing, possibly by top-down modulation of early deviance processing. Memantine may affect later phases of deviance processing, but not deviance detection.

However, this explanation should be considered with great caution. The involvement of the auditory cortex cannot be eliminated. Firstly, preliminary PET evaluation of the memantine-derivative radiotracer in a rhesus monkey demonstrated good uptake and prolonged retention in the NMDA receptor-rich regions (frontal cortex, striata, and temporal cortex) (Samnick et al. 1998). Secondly, there is a lot of evidence supporting the notion that NMDA antagonists block MMN generated in the auditory cortex, e.g. direct recording from the primary auditory cortex in monkeys by Javitt et al. (1996). Moreover, a decrease in magnetic MMN source activity was also reported by Kreitschmann-Andermahr et al. (2001) after the administration of ketamine. However, it should be mentioned that in that study, a test-retest design was used, possibly affecting the results. The same group (Rosburg et al. 2004) showed MMNm source activity in repeated measurements undergoing a significant adaptation, resulting in a decrease of the MMNm dipole strength. An alternative explanation of our observed effect in EEG also exists. Our observed EEG effect could be explained by the fact that the EEG will pool together auditory cortex activity from both hemispheres and from radially oriented sources (Hamalainen et al. 1993). It is possible that the same tangential sources, which were not visible with MEG due to the weak signal, were visible with EEG, because it was more sensitive to detecting weak overall modulations in the voltage fluctuations of auditory cortex activity, by pooling together memantine effects from a wider area of auditory cortex.

71 Frequency and duration change MMN We found that MMN to frequency, but not to duration, deviation was affected by memantine. From a number of studies, it becomes evident that MMN to different stimulus changes could be differentially modified in certain types of condition or disease. In a study on Landau-Kleffner syndrome, different MMN types were used (Honbolygo et al. 2006). MMN responses to phoneme and stress differences were recorded. Surprisingly, an abnormal MMN pattern was found in response to the stress difference, but not to the phoneme difference. This was in agreement with neuropsychological examination showing a dissociation between verbal and nonverbal functions. With a new multi-feature MMN paradigm (Naatanen et al. 2004; Pakarinen et al. 2007), which allows 5 different MMNs (duration, frequency, intensity, silent gap and location) to be registered at the same time, it appears evident that each clinical group is likely to have its own MMN-change pattern. In adults with Asperger syndrome, Kujala et al. (2007a) found an enhanced MMN in response to deviants to gap or shorter duration, and a speeded MMN in response to frequency changes. The same research team (Kujala et al. 2006), in their study of adult dyslexics, showed diminished pitch- and enhanced location- MMN. It is also of great interest that, in a study into psychological stress (Simoens et al. 2007), only MMN responses to duration change were affected by stress manipulation. Recently, the first study into schizophrenia using an “Optimal” (multi-feature) MMN paradigm was undertaken by Thoennessen et al. (2007), who showed that patients demonstrated significantly smaller MMNm responses to all deviants over both the left and right auditory cortices, with the only exceptions being MMN responses to location and gap deviance over the right hemisphere. The multi- feature paradigm opened new perspectives for studying schizophrenia. The Fisher et al. (2008) study clearly demonstrated that MMN was diminished in response to duration and intensity deviations in hallucinating schizophrenia patients to a greater degree than in non-hallucinating patients. This is in line with previously-made observations (Michie et al. 2000a) concerning the prevalence of the duration MMN response abnormality in schizophrenia.

Different MMN-change profiles are also made evident from studies of neurochemical MMN regulation. Thus, only the MMNm elicited by intensity deviants, but not by frequency and duration deviants, showed significantly increased latency after lorazepam administration (Rosburg et al. 2004). Furthermore, scopolamine had a differential impact on MMN responses to frequency and duration deviants (Pekkonen et al. 2001). In addition, haloperidol did not alter MMN response to duration change, whereas it affected MMNm

72 response to frequency change (Pekkonen et al. 2002). Frodl-Bauch et al. (1997) found that the locations of the frequency and duration MMN-dipoles were separate within the auditory cortex, with an anterior and caudal location for the frequency MMN-dipoles.

In humans, auditory information is transmitted from each ear to both auditory cortices via two ascending neural pathways. The majority of fibres cross the midline in the brainstem and reach the contralateral auditory cortex, whereas a smaller proportion of fibres ascend to the ipsilateral auditory cortex (Kelly and Judge 1994). It is possible that these fibres are differentially sensitive to neurochemical modulation. This could explain the differential effects of neurotransmitters on certain MMN types. A further explanation could be the greater consistency and reliability of the duration MMN. In a study, Kathmann et al. (1999) used MMN elicited by frequency and duration changes in test and retest sessions in 45 subjects. The MMN amplitude was greater for duration deviants. The individual replicability of the MMN amplitudes was generally better when duration deviants were used than when frequency deviants were used. By contrast, Frodl-Bauch et al. (1997) found that test-retest reliability was not as good for the duration MMN as it was for the frequency MMN. It is also known that tonal information (frequency differences) in the auditory system is processed differently from temporal information (duration differences) (Belin and Zatorre 2000; Zatorre and Belin 2001; Zatorre et al. 1994). The different effects of neurotransmitters under certain conditions could lead to dissociation between these two systems.

It should be pointed out that the above-mentioned neuropharmacological studies (Pekkone et al. 2002; Pekkonen et al. 2001) were not specifically designed to test differences in neurochemical modulation of MMN to duration versus frequency deviants, and thus the degree of difficulty in detecting the different types of deviants was not always monitored. It is also noteworthy that a number of current cellular level neurophysiological studies (Fritz et al. 2003; Fritz et al. 2007) provide evidence for the existence of complex spectrotemporal receptive fields even in the primary auditory cortex. In other words, the neurons seem to have parallel representations for both sound duration and frequency in auditory cortices. There is also psychophysical evidence (Wright 2005), suggesting that sound duration is not processed independently of sound frequency.

73 Increase but not decrease of the MMN amplitude A number of studies in anaesthetized rats (Tikhonravov et al. 2008), anaesthetized mice (Ehrlichman et al. 2008), monkeys (Javitt et al. 1996) and healthy human subjects (Heekeren et al. 2008; Kreitschmann-Andermahr et al. 2001; Umbricht et al. 2000) showed that the MMN (or MMN-like) response is reduced under the effect of NMDA-antagonists such as ketamine, MK-801 or PCP. Moreover, NMDA receptor antagonist nitrous oxide (N2O) was found to significantly attenuate MMN amplitude in healthy volunteers (Pang and Fowler 1999). The results of these studies suggest that MMN response could reflect activation of the NMDA receptors. Memantine is known as an NMDA receptor antagonist (for review, see Parsons et al. 2007). We therefore hypothesized that memantine would attenuate MMN amplitude. Contrary to our original hypothesis, we found an increase in MMN amplitude after memantine administration. As MMN is assumed to represent a reflection of auditory change-detection mechanism, enhancement of MMN amplitude could be interpreted as an improvement of change-detection under the effect of memantine. In this way, our findings contradict the results of the above- mentioned studies. Why were our findings different?

First of all, memantine seems to be unique in its pharmacological properties, differing from other NMDA antagonists. Memantine has a lower affinity and therefore a faster kinetics and voltage tendency than ketamine (for review, see Danysz et al. 2000a; Danysz et al. 2000b; Frankiewicz and Parsons 1999; Parsons et al. 1999). A recent study by Parsons et al. (2008) demonstrated that memantine does not block the NMDA receptor from the intracellular compartment, thereby providing further support for claims for its good clinical tolerability. Blanpied et al. (1997) suggested that memantine can be trapped by the NMDA channel more easily than PCP or MK-801. Consistently with this, Jones et al. (2001) showed that memantine “filters” non-physiological activity, whilst leaving normal synaptic events relatively untouched, which could contribute to its more favourable clinical action. Ketamine has a different effect from memantine on hormones: ketamine increases serum cortisol (Krystal et al. 1994), whereas memantine does not have such an effect (Hergovich et al. 2001). Born et al. (1987) showed that cortisol administration reduces MMN amplitude. Therefore, the differences in pharmacological properties and hormonal effects between these substances could in part explain the different effects on MMN.

74 Secondly, different pharmacological properties make memantine a more favourable agent in terms of its effects on cognition. For example, ketamine can produce psychotic-like experiences in healthy subjects (Krystal et al. 1994; Lahti et al. 2001), whereas memantine, at therapeutic doses, rarely produces such side-effects (Bresink et al. 1995; Parsons et al. 1995). Moreover, there is evidence of memantine having beneficial effects on information processing, especially in patients with Alzheimer disease. For example, Minkeviciene et al. (2004) showed that the oral administration of memantine significantly improves learning in a transgenic mouse model of Alzheimer disease. Moreover, in a subsequent study, the same research group (Minkeviciene et al. 2008) reported improved cognition in normal mice after memantine administration. Further, pre-training administration of memantine facilitated a dose-dependent enhancement of long-term memory in mice (Zoladz et al. 2006). Controlled clinical trials in humans also showed memantine to be efficient in improving cognitive symptoms in patients with mild to moderate vascular dementia (Ditzler 1991) and Alzheimer disease (Peskind et al. 2006; Winblad et al. 2007). These findings are in agreement with those of our study, in which memantine increased thinking speed, as measured with VAS. Thus, the effect we observed on MMN may have been facilitated by improved cognition after memantine.

This facilitating effect on cognition could also be explained by the therapeutic memantine dose used in our experiment. A number of studies (Higgins et al. 2005; Mondadori et al. 1989) have, for example, concluded that a low-level blockade of NMDA receptors may have beneficial effects on cognition. For instance, in a study by Mondadory et al. (1989) of rats, the administration of MK-801 facilitated the learning of passive avoidance tasks. Moreover, Higgins et al. (2005) found an improvement in task performance and learning after the administration of the nonselective NMDA antagonist dizocilpine. And, by contrast, a high dose of the amino acid glycine, which is supposed to facilitate NMDA receptor function through the stimulation of the NMDA glycine modulatory site, produced a significant decrease, rather than an increase, in MMN amplitude in a study by Leung et al. (Leung et al. 2008).

Thirdly, the glutamatergic system is closely linked to other neurotransmitter systems, such as those of dopamine, serotonin, and nicotine (Gu 2002; Marino and Conn 2002). Memantine also has effects on other neurotransmitter systems; it can, for instance, block

5-HT3 and nicotinic receptors (Buisson and Bertrand 1998; Loscher et al. 2003; Rammes et al. 2001). The synergetic properties of memantine on these receptor types could

75 contribute to its ability to improve cognitive functions (Rammes et al. 2001). MMN could also be affected by non-glutamatergic transmitter systems. For instance, Kahkonen et al. (2005) showed that ATD, which reduces serotonin synthesis in the brain, increased MMN amplitude in the EEG, indicating that serotonin may be involved in MMN generation. Moreover, Oranje et al. (2008) found that the acute challenge of SSRI escitalopram, known for its serotonin transporter blocking properties, significantly enhanced MMN amplitude, contrary to the authors’ anticipated results. Further, haloperidol, a dopamine- 2-receptor antagonist, increased MMN amplitude in the EEG, but not in the MEG, in a dichotic listening task, suggesting some involvement of dopamine in MMM generation (Kahkonen et al. 2001a). Finally, Inami et al. (2005) showed that transdermal administration of nicotine can accelerate MMN. Taken together, these results indicate that the increase in MMN amplitudes after memantine administration may be mediated through indirect effects of aminergic modulation on the NMDA receptors.

Finally, other explanations should be taken into consideration. It seems that the relation between the change in MMN amplitude and cognition could be more complex than previously thought. It is possible that an enhanced MMN does not always correspond to improved cognitive functioning. Support for this view can be found in a number of clinical and neuropsychopharmacological MMN studies. One recent study (Mikkola et al. 2007) showed that MMN response to frequency change was greater in amplitude in pre-term children than in control children. This MMN response to frequency change correlated significantly with verbal intelligence quotient and NEPSY language domain verbal fluency in pre-term children of 5 years of age. Further, an increased MMN amplitude has been reported in autistic children sensitive to certain types of sounds (Lepisto et al. 2005). Children with Asperger syndrome have an enhanced MMN response to speech- pitch changes. Further, adults with Asperger syndrome showed enhanced MMN response to gap or shorter duration deviants (Kujala et al. 2007a). And adult dyslexic individuals showed an enhanced location MMN response(Kujala et al. 2006). In addition, a later phase of MMN response was shown to be enhanced in alcoholics in a study by Ahveninen et al. (2000b). This increase in MMN amplitude significantly correlated with pronounced reaction time-lag (RT) and was interpreted as the inability of alcoholics to inhibit the frontal-temporal neural network. As regards neuropsychopharmacological MMN studies, contrary to expected results, the amplitudes of the frequency and duration MMN responses were increased following ATD. At the same time, ATD induced depressive mood. Similarly, contrary to the expected effect, the acute administration of haloperidol

76 increased MMN amplitude (Kahkonen et al. 2001a). An enhanced MMN response may be due to hypersensitivity to auditory change, derived from hyper-excited specific areas of the auditory sensory cortex. This phenomenon is well recognised in epilepsy. Epilepsy patients, who have a diminished sensory excitation threshold, exhibit enhanced EPs – so-called “giant evoked responses” (Kubota et al. 2000; Sinha et al. 2007). This type of response was also reported in Rett syndrome (Yamanouchi et al. 1993). It is possible that the excitation threshold of the auditory change-detection mechanism in patients is affected, producing enhanced MMN responses. Notably, Kaipio et al. (2000) reported a clear tendency for enhanced MMN amplitudes with a significant increase in consequent P3a component in patients with closed-head injury, compared with healthy controls. These findings were interpreted as evidence of increased distractability distractibility after this kind of injury. In conclusion, as is evident from a number of different studies, an enhanced MMN may arise due to hypersensitivity to auditory change and/or lack of the inhibitory mechanisms underlying change-detection.

Weak/absent association between catecholamines and MMN generation

In Study IV, we found that methylphenidate had no significant effect on either electrical or magnetic MMN components.

A number of studies exploring the effects of catecholamine agonists and of antagonists on MMN generation in healthy volunteers support the view of the weak/absent association between catecholamines and MMN generation. Mervaala et al. (1993) studied the effects of the acute modulation of central noradrenergic neurotransmission on MMN α in healthy subjects, using a specific 2-antagonist atipamezole. Although atipamezole produced evident noradrenergic overactivity, it failed to modulate MMN. In addition, α the 2-adrenoreceptor antagonist clonidine also showed no effect on MMN (Duncan and Kaye 1987). Furthermore, Hansenne et al. (2003) indirectly demonstrated the lack of implication of DA and NA activities, as assessed by growth-hormone response to apomorphine and clonidine, in the generation or modulation of MMN. Moreover, a study by Leung et al. (2007) failed to show any significant effect of dopamine D2 and D1/D2 receptor stimulants bromocriptine and pergolide on MMN generation, in healthy subjects. The only investigation to have been carried out so far into this aspect, that undertaken by Kähkönen et al. (2001a), showed that, in a dichotic listening task, haloperidol, a dopamine-2-receptor antagonist, increased MMN amplitudes in the EEG, but not in the

77 MEG, suggesting some involvement of DA in MMN generation (Kahkonen et al. 2001a). However, differences in stimulation paradigms may explain the results.

Taking into account the catecholaminergic action (mostly by increasing the concentration of catecholamines in the synaptic cleft) of MPH (for review, see Solanto 1998), the lack of the effect observed could stem from the weak relationship between MMN generation and changes in DA and NA neurotransmission.

P200 and dopaminergic neurotransmission Our Study IV showed a significant reduction in the P200 amplitudes of subjects under the effect of MPH. We observed significant P200 changes in both schizophrenia patients (Study II) and healthy- volunteers (Study IV). Because DA and NA are the main neurotransmitters involved in MPH action, the reduction in P200 amplitude could result from the effects of MPH on at least one of these two neurotransmitter systems. Indeed, studies with healthy subjects showed that sulpiride, a selective antagonist at postsynaptic D2-receptors (known for its antipsychotic properties), shortened the P200 latency to the standard stimuli in the odd-ball paradigm (Takeshita and Ogura 1994). Further, results shown by Turetsky and Fein (2002) demonstrated that in the NA system the acting drugs clonidine and yohimbine had significant opposing effects on P200 latency, with yohimbine accelerating and clonidine slowing the peak latency. By contrast, neither clonidine nor yohimbine affected the latencies of N250 or overlapping P300b (Turetsky and Fein 2002). Consistently with this, we observed this effect only on the P200, but not on other ERP components, which suggests that P200 may reflect neuronal population activity directly modulated by NA and DA. Our results also find partial support from our Study II, which found that in patients with schizophrenia spectrum disorders, only the P200 was reduced under the effect of the antipsychotic drug risperidone.

Neurochemical effects on later versus earlier stages of information processing Another possible explanation for the results from our Study IV is that NA and DA are responsible for the modulation of the later stages of information processing. Our results, thus, agree with those of Kähkönen and Ahveninen (2002), who suggested that different neurotransmitter systems modulate different stages of attentional processing, with dopamine having an influence on later, but not on earlier, stages of this processing. Hence, investigating early information-processing stages occurring at about 20-70 ms from stimulus onset with middle-latency auditory-evoked magnetic fields (MAEF), Kähkönen

78 et al. (2001b), using haloperidol as a challenge, and Kudoh and Matsuki (1999), using droperidol during total intravenous anaesthesia, found no differences in MAEF either before or after administration of the drugs. Furthermore, haloperidol administration did not affect sound detection representing N100/N100m components in healthy volunteers (Kahkonen et al. 2002). Further, Abduljawad et al. (1999) failed to show changes in the amplitudes or latencies of the auditory N100/P200 complex after the administration of haloperidol and bromocriptine. However, both haloperidol (Kahkonen et al. 2001a) and droperidol (Shelley et al. 1997) appeared to modulate processing negativity (PN), peaking at around 300-500 ms, and possibly reflecting selective attention. In previous studies on the effect of clonidine on ERPs, the drug reduced the amplitude of the P300 component (Duncan and Kaye 1987; Joseph and Sitaram 1989). Later, Anderer et al. (2002), using acute haloperidol administration, found that the dipole strength of the P300 component was attenuated. Further, Cooper et al. (2005) showed that, together with enhancements in the speed of processing and omission errors in CPT, P300 measurements were improved after the introduction of MPH. Finally, in the study by Kähkönen et al. (2002) of haloperidol versus placebo, the P3a exhibited decreased amplitudes, whereas the reorienting negativity (RON) (slow negativity evoked after 400-600 ms of stimulus onset (for more information, see Schroger and Wolff 1998a)) showed decreased amplitudes and increased latencies.

Clinical implications of the current results Results from clinical studies show, as I have already mentioned, that patients with schizophrenia consistently demonstrate diminished MMN and MMNm responses (Catts et al. 1995; Kreitschmann-Andermahr et al. 1999). Moreover, Catts et al. (1995) and Javitt et al. (1995a) found that there was no significant difference in MMN amplitude between medicated and neuroleptic-free patients. Our Study I and other results (Catts et al. 1995; Umbricht et al. 1998; 1999) indicate that neuroleptics have no effect on MMN amplitude in schizophrenia. Although these findings do not rule out the possibility of DA involvement in MMN response, they nonetheless provide additional support for the notion that no relationship exists between changes in MMN generation and alterations in DA transmission. It seems that MMN changes with the development of disease and reflects disease progression, rather than changes, under the different effects of medication (Salisbury et al. 2002). A number of studies in healthy volunteers (Kreitschmann- Andermahr et al. 2001; Umbricht et al. 2000), including our Study III, suggest an important role is played by NMDA receptors in MMN generation in humans. Hence, it

79 appears that MMN generators are more sensitive to glutamatergic than to dopaminergic modulation.

As for the P200 component, its physiological significance is currently under reconsideration (for review, see Crowley and Colrain 2004). P200 may reflect early stimulus evaluation and correspond to information inhibition processes in cortical and subcortical structures (Catts et al. 1986; Chiarenza et al. 1985; Oades et al. 1996). The idea that the NE and DA neurotransmitter systems may modulate P200 elucidates several findings concerning ERP abnormalities in schizophrenia and ADHD. The P200 latency has been observed to occur earlier and with a higher amplitude in patients with schizophrenia than that in healthy controls. These studies have shown that P200 abnormalities may be physiological markers for a positive-symptom subtype (Hegerl et al. 1988; Schwarzkopf et al. 1990) of schizophrenia. Thus, Roth et al. (1981) demonstrated a negative correlation between P200 latency to frequency tones and the delusion/hallucination score, and Laurent et al. (1999) showed a negative correlation between P200 latency and the PANSS positive syndrome score, whereas Shenton et al. (1989a) found that reduced P200 amplitudes correlated significantly with a negative-symptom subtype. In addition, ERP studies into ADHD showed an enhanced P200 amplitude or a reduced P200 latency, or both, compared with those of healthy controls. Thus, ADHD children exhibited enhanced P200 amplitudes relative to those of controls (Oades et al. 1996), with differences tending to ameliorate after MPH medication (Broyd et al. 2005). Moreover, Sunohara et al. (1999) showed that the ADHD group at baseline was more impulsive and inattentive than the controls, and showed shorter initial P200 latencies, which increased after a higher dosage of MPH. Garcia-Larrea et al. (1992) suggested that changes in P200 could result from a progressive deficit in an individual’s capacity to withdraw attentional resources from stimuli.Therefore, our results may suggest that MPH selectively affects physiological processes underlying the evaluation of stimuli, in this way increasing the inhibition of auditory information reflected in the P200 and modulated by DA and/or NA. This supports the suggestion by Turetsky and Fein (2002) that there exists a “noradrenergically modulated physiological mechanism that ‘tunes’ the CNS towards the selective attendance of potentially important alterations in ongoing background stimulation” (page 154). The question is whether the effect observed by us is likely to be a direct effect of MPH on neurons in the auditory cortex. Although the information about the effects of DA/NA on single-cell responses in the auditory cortex to simple auditory stimuli is not very well documented, studies of the distributions of DA receptors show that dopamine D2-receptors are rich in the basal

80 ganglia, with sparse density in the auditory cortex (Goldsmith and Joyce 1996). Thus, it seems that the observed effect is more likely to be due to the indirect MPH action on the auditory cortex, mediated by afferents from other regions to the auditory cortex. Hence, neurons of ventral tegmental area are activated by auditory events (Horvitz et al. 1997). This interpretation gains support from the study by Krause et al. (2003), showing that DA/NA stimulant amphetamine affects auditory sensory processing in the thalamic reticular nucleus.

We found no significant changes in the parameters of the magnetic counterpart of the P200 component under the effect of MPH. It is well established that the MEG detects tangentially oriented sources of cortical brain activity, rather than radially oriented sources (Hamalainen et al. 1993). Therefore, sources of electrical brain activity localized in the temporal cortex could be well detected in the MEG. With their MEG and EEG data from depth electrodes, Godey et al. (2001) showed that P200 generators were localized in the PT also seen in the Broadmann Area 22. However, the P200 appears at least partly to reflect the auditory-driven output of the mesencephalic reticular activating system, which responds to input from all sensory modalities (Rif et al. 1991). Thus, the P200m peak may arise from multiple sources, with contributions to a centre of activity close to Heschl’s gyrus. The main effect of MPH in ADHD patients is usually prominent in the prefrontal areas (Berridge et al. 2006) and the striatum (Dodds et al. 2008; Udo de Haes et al. 2005), which suggests that this effect may be better reflected in the EEG (sensitive to both radial and tangential sources of electrical activity) than in the MEG. The lack of the sensitivity of the P200m component to MPH may also be linked to the different localizations of DA receptors in the auditory cortex (Goldsmith and Joyce 1996). Consequently, the lack of MPH effect on the magnetic P200 component is likely to be due to the lack of significant changes in dopaminergic and noradrenergic neurotransmission in the temporal areas of the brain.

81 6. CONCLUSIONS

1. In a group of schizophrenia spectrum disorder patients, after 2 and 4 weeks of treatment, olanzapine was found to have no significant effects on MMN and P300, which have been proposed to respectively reflect involuntary change-detection mechanism and attention-dependent information processing.

2. In neuroleptic-naive patients with schizophrenia spectrum disorders, after two weeks of treatment, risperidone was found to have no significant effect on P300 response, which has been proposed to reflect attention-dependent processes. However, risperidone reduces P200 amplitude, and this could be partly explained through the dopamine effect on the neural sources responsible for P200 generation.

3. In healthy adult subjects, memantine increases MMN amplitude without modulation of other ERP components. This could suggest that a possible influence of memantine through the NMDA receptors on preattentive processes is reflected in MMN without otherwise changing the processing of auditory stimuli. Memantine-induced changes in only electrical MMN response may reflect modulation of the putative frontal MMN subcomponent, an effect that is more clearly observed in EEG than in MEG.

4. In healthy adult subjects, methylphenidate reduces P200 amplitude, suggesting that dopamine and noradrenaline neurotransmitter systems could be responsible for the modulation of the auditory information processing reflected in P200. Furthermore, methylphenidate has no effect on MMN, suggesting the absence of a strong association between dopaminergic and noradrenergic activities and MMN.

82 7. References

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