Introduction to Infant EEG and Event-Related Potentials

Total Page:16

File Type:pdf, Size:1020Kb

Introduction to Infant EEG and Event-Related Potentials Introduction to infant EEG and event-related potentials Michelle de Haan Institute of Child Health, University College London, UK It is many decades since investigators first employed the electroencephalo- gram (EEG) to study the function of infants’ central nervous systems (for reviews see Bell, 1998; Schmidt & Fox, 1998). While initially investigators focused on how changes in the ongoing EEG related to the behavioural states of sleep and wakefulness (Lindsely, 1939; Smith, 1938), in subsequent years they also began to study event-related activity including evoked (e.g., Galambos & Despland, 1980; Sokol & Dobson, 1976) and endogenous responses (e.g., Courchesne, Ganz, & Norcia, 1981; Vaughan, 1975). In recent years, with the growing interest in understanding the neural bases of human perception, cognition, and emotion, there has been increased interest in use of EEG and event-related potentials (ERPs) to study these processes as they develop in human infants. This is because EEG and ERPs are among the only ways to study brain activity in healthy infants (see Meek, 2002, for discussion of another method that can be used with healthy infants, optical imaging). Other brain-imaging methods commonly used with adults and older children pose significant risks or would require sedation in young infants, making them unsuitable unless required for clinical purposes. That there is now a sufficient body of literature in the field of infant EEG and ERPs to warrant an entire volume on this topic is testament to how quickly the field has grown in the last few years. This is in spite of the fact that these data can be quite challenging to collect from young infants. Cooper- ation with placement of the electrodes and leaving them in place for the duration of the experiment, minimising movement during the experiment to prevent artefacts, and ensuring that the baby participates in the experiment as needed (e.g., by attending to visual stimuli) can all represent challenges (see DeBoer et al., Chapter 1, for discussion of practical aspects of recording infant EEG and ERPs). Once these challenges are overcome, others present themselves in analysis and interpretation of the data, as in many instances the relationship between components observed in infant ERPs and those known in adults is not obvious. The chapters in this volume demonstrate that these challenges can be overcome and reliable EEG and ERP data can be recorded from infants in a variety of paradigms and ages. Chapter 1 (DeBoer et al.) provides an 2 De Haan overview of methods for recording and analysing EEG and ERP, with an emphasis on the special issues related to using these techniques with infants. Chapters 2–4 focus on visual potentials, from visual evoked responses (McCulloch, Chapter 2) to face-sensitive components (de Haan et al., Chapter 3) and components related to visual attention and memory (de Haan, Chapter 4). In Chapter 2, McCulloch outlines techniques for recording visual evoked potentials (VEPs) and describes the picture they provide of the development of the visual system in infancy, in both typical and atypical development. In Chapter 3, de Haan, Johnson, and Halit describe ERP components related to infants’ processing of faces, how these relate to com- ponents in the adult ERP, and how developmental changes in these com- ponents inform theories of the development of face processing. In Chapter 4, de Haan focuses on ERP components related to infant recognition memory and attention, describing the development of the negative central (Nc) component and various slow waves. Chapters 5–7 focus on auditory potentials, including those related to audi- tory recognition (deRegnier, Chapter 5), the mismatch negativity (Cheour, Chapter 6), and those related to speech and language (Molfese et al., Chapter 7). In Chapter 5, de Regnier outlines the brain circuits involved in auditory recognition memory and presents data demonstrating differences in ERP response to the mother’s vs a stranger’s voice in neonates. When the same auditory recognition paradigm is used with infants at risk for later memory impairment, there is evidence of atypical auditory ERP memory responses very early in life. In Chapter 6, Cheour describes what is perhaps one of the most well-studied ERP components, mismatch negativity (MMN). She discusses issues in identifying the infant MMN, and its differences from and similarities to the adult component, as well as its usefulness in detecting cognitive impairment early in life. In Chapter 7, Molfese, Molfese, and Pratt discuss the use of infant ERPs to predict later language and reading devel- opment. They present impressive findings indicating that ERPs to speech and non-speech sounds in neonates and young infants can predict a sizeable amount of the variance in language and reading skills at school age. Chapters 8–10 focus on other aspects of the EEG, with Chapter 8 (Marshall & Fox) examining ERP and EEG emotion-related responses, Chapter 9 (Stroganova & Orekhova) focusing on EEG and infants’ states, particularly different states of wakefulness, and Chapter 10 (Csibra & Johnson) reporting on event-related oscillations in perceptual-cognitive tasks. In Chapter 8, Marshall and Fox report on individual differences in both EEG and ERP responses and how they relate to individual differences in emotion and tem- perament. Their findings suggest that temperamental differences among infants may be an important factor to consider in interpreting results from ERP group studies. In Chapter 9, Stroganova and Orekhova discuss devel- opment of the EEG in relation to infant states, raising important questions regarding variations in the EEG during wakefulness and definition of infant EEG rhythms (e.g., alpha) in relation to those observed in adults. In Introduction 3 Chapter 10, Csibra and Johnson described a relatively recent approach to analysing infant brain activity, event-related oscillations, and describe how these have been used to study the neural correlates of perceptual binding and memory for hidden objects in infancy. Several questions and themes run throughout these chapters, including the usefulness of infant EEG/ERP in early detection of impairments in percep- tion and cognition, and how best to define infant brain activity with respect to adult brain activity, and these and other themes are discussed further in Chapter 11 (de Haan). A glossary of terms is also provided at the end of the book, with the hope that it will make the chapters more accessible to those less familiar with the field and its terminology. The main purpose of creating this volume was to provide a reference useful to both those active in the field and those new to it. For those already involved in infant EEG and ERP research, the chapters in this book will provide a very useful reference drawing together numerous studies, and may also help to broaden their outlook, as often researchers tend to focus on a particular type of ERP and may not be fully aware of work that is related but carried out in another domain. For those new to the field, it is hoped that the introduction provided by Chapter 1 and the glossary will form the back- ground for informed reading of the remaining chapters devoted to more specific topics. Ideally, the exciting findings reported here will recruit new researchers into the field and help to take the field forward in the decades to come. REFERENCES Bell, M. A. (1998). The ontogeny of the EEG during infancy and childhood: Implications for cognitive development. In B. Barreau (Ed.), Neuroimaging in child neuropsychiatric disorders (pp. 97–111) Berlin: Springer. Courchesne, E., Ganz, L., & Norcia, A. M. (1981). Event-related brain potentials to human faces in infants. Child Development, 52, 804–811. Galambos, R., & Despland, P. A. (1980). The auditory brainstem response (ABR) evaluates risk factors for hearing loss in the newborn. Pediatric Research, 14, 159–163. Lindsely, D. B. (1939) A longitudinal study of the occipital alpha rhythm in normal children: Frequency and amplitude standards. Journal of Genetic Psychology, 55, 197–213. Meek, J. (2002). Basic principles of optical imaging and application to the study of infant development. Developmental Science, 5, 371–380. Schmidt, L. A., & Fox, N. A. (1998). Electrophysiological indices I: Quantitative elec- troencephalography. In C. E. Coffey & R. A. Brumback (Eds.), Textbook of pediatric neuropsychiatry (pp. 315–329). Washington, DC: American Psychiatric Press. Smith, J. R. (1938). The electroencephalogram during normal infancy and childhood: I Rhythmic activities present in the neonate and their subsequent development. Journal of Genetic Psychology, 53, 431–453. 4 De Haan Sokol, S., & Dobson, V. (1976). Pattern reversal visually evoked potentials in infants. Investigative Ophthalmology, 15, 58–62. Vaughan, H. G. Jr. (1975). Electrophysiologic analysis of regional cortical maturation. Biological Psychiatry, 10, 513–526. 1 Methods for acquiring and analyzing infant event-related potentials Tracy DeBoer University of Minnesota, USA Lisa S. Scott University of Colorado at Boulder, USA Charles A. Nelson University of Minnesota, USA A primary goal of developmental cognitive neuroscience is to elucidate the relation between brain development and cognitive development (see Nelson & Luciana, 2001). The study of this relation in children older than 5–6 years lends itself to many of the same tools used in the adult, such as functional magnetic resonance imaging (fMRI). However, in children younger than this, limitations in motor and linguistic abilities,
Recommended publications
  • Visual Cortex in Humans 251
    Author's personal copy Visual Cortex in Humans 251 Visual Cortex in Humans B A Wandell, S O Dumoulin, and A A Brewer, using fMRI, and we discuss the main features of the Stanford University, Stanford, CA, USA V1 map. We then summarize the positions and proper- ties of ten additional visual field maps. This represents ã 2009 Elsevier Ltd. All rights reserved. our current understanding of human visual field maps, although this remains an active field of investigation, with more maps likely to be discovered. Finally, we Human visua l cortex comprises 4–6 billion neurons that are organ ized into more than a dozen distinct describe theories about the functional purpose and functional areas. These areas include the gray matter organizing principles of these maps. in the occi pital lobe and extend into the temporal and parietal lobes . The locations of these areas in the The Size and Location of Human Visual intact human cortex can be identified by measuring Cortex visual field maps. The neurons within these areas have a variety of different stimulus response proper- The entirety of human cortex occupies a surface area 2 ties. We descr ibe how to measure these visual field on the order of 1000 cm and ranges between 2 and maps, their locations, and their overall organization. 4 mm in thickness. Each cubic millimeter of cortex contains approximately 50 000 neurons so that neo- We then consider how information about patterns, objects, color s, and motion is analyzed and repre- cortex in the two hemispheres contain on the order of sented in these maps.
    [Show full text]
  • The Davida Teller Award Lecture, 2016 Visual Brain Development: A
    Journal of Vision (2017) 17(3):26, 1–24 1 The Davida Teller Award Lecture, 2016 Visual Brain Development: A review of ‘‘Dorsal Stream Vulnerability’’—motion, mathematics, amblyopia, actions, and attention # Janette Atkinson University College London, London, UK $ Research in the Visual Development Unit on ‘‘dorsal stream vulnerability’ (DSV) arose from research in two Introduction somewhat different areas. In the first, using cortical milestones for local and global processing from our neurobiological model, we identified cerebral visual Emerging cortical function and infant cortical impairment in infants in the first year of life. In the impairment second, using photo/videorefraction in population refractive screening programs, we showed that infant The work discussed at the beginning of this review spectacle wear could reduce the incidence of strabismus arose out of the first twenty years of my research with and amblyopia, but many preschool children, who had Oliver Braddick and our team in the Visual Develop- been significantly hyperopic earlier, showed visuo-motor ment Unit in Cambridge, particularly John Wattam- and attentional deficits. This led us to compare Bell and Shirley Anker (Atkinson, 2000). We began by developing dorsal and ventral streams, using sensitivity devising new methods, both behavioral (automated to global motion and form as signatures, finding deficits forced-choice preferential looking) and electrophysio- in motion sensitivity relative to form in children with logical (steady-state VEP/VERP—Visual Evoked Po- Williams syndrome, or perinatal brain injury in tential/Visual Event Related Potential) to measure the hemiplegia or preterm birth. Later research showed that normal visual capacities of infants such as acuity and this DSV was common across many disorders, both ‘‘ ’’ contrast sensitivity, over the first years of life (Atkin- genetic and acquired, from autism to amblyopia.
    [Show full text]
  • VISUAL NEUROSCIENCE Spring 2019
    PSYC/BIBB/VLST 217 VISUAL NEUROSCIENCE Spring 2019 Spring 2019 Lecture: MWF 9-10a, Leidy Labs 10 Prerequisites: PSCY 1, BIBB 109, VLST 101, or COGS 001 Synopsis: An introduction to the scientific study of vision, with an emphasis on the biological substrate and its relation to behavior. Topics will typically include physiological optics, transduction of light, visual thresholds, color vision, anatomy and physiology of the visual pathways, and the cognitive neuroscience of vision. Instructor: Alan A. Stocker, Ph.D. Office: Goddard Labs Rm 421, 3710 Hamilton Walk Phone: (215) 573 9341 Email: [email protected] Office hour: W 12-1p Teaching Assistant: Lingqi Zhang Email: [email protected] Office hour: T 5-6p, TR 5-6p Office hour location: Goddard Labs Rm 420, 3710 Hamilton Walk Course Website (CANVAS): The course has a dedicated CANVAS site. Lecture slides, homework assignments, and reading assignments/material will be posted there. Also, check the site frequently for posted announcements and Q & As on the discussion board. In general, this is the place to go first if you have any question or are in need of any information regarding the course. Requirements: Homework1-3 posted on canvas Midterm Exam 1 February 15 (in class) Midterm Exam 2 March 29 (in class) Midterm Exam 3 April 26 (in class) Final Exam (cumulative) May 13, 12-2p Policy on homework assignments: Homework assignments are essential for a proper understanding of the material. There will be three homework assignments, meant in part as preparation for each midterm exam. Assignments and due dates will be posted on CANVAS.
    [Show full text]
  • Perception, As You Make It
    Perception, As You Make It Behavioral & Brain Sciences commentary on Chaz Firestone & Brian Scholl, “Cognition does not affect perception: Evaluating the evidence for ‘top-down’ effects" David W. Vinson, University of California, Merced, Drew H. Abney, University of California, Merced Dima Amso, Brown University Anthony Chemero, University of Cincinnati James E. Cutting, Cornell University Rick Dale, University of California, Merced Jonathan B. Freeman, New York University Laurie B. Feldman, The University at Albany, SUNY Karl J. Friston, University College London Shaun Gallagher, University of Memphis J. Scott Jordan, Illinois State University Liad Mudrik, Tel Aviv University Sasha Ondobaka, University College London Daniel C. Richardson, University College London Ladan Shams, University of California, Los Angeles Maggie Shiffrar, California State University, Northridge Michael J. Spivey, University of California, Merced Abstract: The main question F&S pose is whether “what and how we see is functionally independent from what and how we think, know, desire, act, etc.” We synthesize a collection of concerns from an interdisciplinary set of co-authors regarding F&S’s assumptions and appeals to intuition, resulting in their treatment of visual perception as context-free. No perceptual task takes place in a contextual vacuum. How do we know that an effect is one of perception qua perception that does not involve other cognitive contributions? Experimental instructions alone involve various cognitive factors that guide task performance (Roepstorff & Frith, 2004). Even a request to detect simple stimulus features requires participants to understand the instructions (“language, memory”), keep track of them (“working memory”), become sensitive to them (“attention”), and pick up the necessary information to become appropriately sensitive (“perception”).
    [Show full text]
  • Principles of Image Representation in Visual Cortex
    In: The Visual Neurosciences, L.M. Chalupa, J.S. Werner, Eds. MIT Press, 2003: 1603-1615. Principles of Image Representation in Visual Cortex Bruno A. Olshausen Center for Neuroscience, UC Davis [email protected] 1 Introduction data. Neuroscientists are interested in understand- ing how the cortex extracts certain properties of the The visual cortex is responsible for most of our con- visual environment—surfaces, objects, textures, mo- scious perception of the visual world, yet we remain tion, etc.—from the data stream coming from the largely ignorant of the principles underlying its func- retina. Similarly, engineers are interested in design- tion despite progress on many fronts of neuroscience. ing algorithms capable of extracting structure con- The principal reason for this is not a lack of data, tained in images or sound—for example, to identify but rather the absence of a solid theoretical frame- and label parts within the body from medical imag- work for motivating experiments and interpreting ing data. These problems at their core are one in the findings. The situation may be likened to trying same, and progress in one domain will likely lead to to understand how birds fly without knowledge of new insights in the other. the principles of aerodynamics: no amount of ex- The key difficulty faced by both sides is that the perimentation or measurements made on the bird core principles of pattern analysis are not well un- itself will reveal the secret. The key experiment— derstood. No amount of experimentation or techno- measuring air pressure above and below the wing as logical tinkering alone can overcome this obstacle.
    [Show full text]
  • Do We Know What the Early Visual System Does?
    The Journal of Neuroscience, November 16, 2005 • 25(46):10577–10597 • 10577 Mini-Symposium Do We Know What the Early Visual System Does? Matteo Carandini,1 Jonathan B. Demb,2 Valerio Mante,1 David J. Tolhurst,3 Yang Dan,4 Bruno A. Olshausen,6 Jack L. Gallant,5,6 and Nicole C. Rust7 1Smith-Kettlewell Eye Research Institute, San Francisco, California 94115, 2Departments of Ophthalmology and Visual Sciences, and Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, Michigan 48105, 3Department of Physiology, University of Cambridge, Cambridge CB2 1TN, United Kingdom, Departments of 4Molecular and Cellular Biology and 5Psychology and 6Helen Wills Neuroscience Institute and School of Optometry, University of California, Berkeley, Berkeley, California 94720, and 7Center for Neural Science, New York University, New York, New York 10003 We can claim that we know what the visual system does once we can predict neural responses to arbitrary stimuli, including those seen in nature. In the early visual system, models based on one or more linear receptive fields hold promise to achieve this goal as long as the models include nonlinear mechanisms that control responsiveness, based on stimulus context and history, and take into account the nonlinearity of spike generation. These linear and nonlinear mechanisms might be the only essential determinants of the response, or alternatively, there may be additional fundamental determinants yet to be identified. Research is progressing with the goals of defining a single “standard model” for each stage of the visual pathway and testing the predictive power of these models on the responses to movies of natural scenes.
    [Show full text]
  • The Visual Analysis of Emotional Actions
    SOCIAL NEUROSCIENCE, 2006, 1(1) 63Á/74 The visual analysis of emotional actions Arieta Chouchourelou Rutgers University Á/ Newark Campus, Newark, NJ, USA Toshihiko Matsuka Stevens Institute of Technology, W.J. Howe School of Technology Management, Hoboken, NJ, USA Kent Harber and Maggie Shiffrar Rutgers University Á/ Newark Campus, Newark, NJ, USA Is the visual analysis of human actions modulated by the emotional content of those actions? This question is motivated by a consideration of the neuroanatomical connections between visual and emotional areas. Specifically, the superior temporal sulcus (STS), known to play a critical role in the visual detection of action, is extensively interconnected with the amygdala, a center for emotion processing. To the extent that amygdala activity influences STS activity, one would expect to find systematic differences in the visual detection of emotional actions. A series of psychophysical studies tested this prediction. Experiment 1 identified point-light walker movies that convincingly depicted five different emotional states: happiness, sadness, neutral, anger, and fear. In Experiment 2, participants performed a walker detection task with these movies. Detection performance was systematically modulated by the emotional content of the gaits. Participants demonstrated the greatest visual sensitivity to angry walkers. The results of Experiment 3 suggest that local velocity cues to anger may account for high false alarm rates to the presence of angry gaits. These results support the hypothesis that the visual analysis of human action depends upon emotion processes. Human observers demonstrate impressive visual 1988), emotional state (Atkinson, Dittrich, Gem- sensitivity to the actions of other people. This was mell, & Young, 2004) and gender (Troje, 2002).
    [Show full text]
  • 1 What Do Models of Visual Perception Tell Us About Visual Phenomenology?
    What do models of visual perception tell us about visual phenomenology? Rachel N. Denison1, Ned Block2, Jason Samaha3 1 Department of Psychology and Center for Neural Science, New York University 2 Department of Philosophy, New York University 3 Department of Psychology, University of California, Santa Cruz 1 Abstract Computational models of visual processing aim to provide a compact, explanatory account of the complex neural processes that underlie visual perception and behavior. But what, if anything, do current modeling approaches say about how conscious visual experience arises from neural processing? Here, we introduce the reader to four commonly used models for understanding visual computations, neural activity, and behavior: signal detection theory, drift diffusion, probabilistic population codes, and sampling. In an attempt to bridge these modeling approaches with experimental and philosophical work on the neural basis of conscious visual perception, we lay out possible relationships between the components of the models and the contents of phenomenal visual experience. We find no unique relation between model components and phenomenal experience in any model; rather, there are multiple logically possible mappings from models to experience. Going forward, we suggest that there are scientific opportunities to develop models that predict and explain a variety of subjective reports and philosophical opportunities to consider what aspects of phenomenal experience are promising scientific targets. Keywords: vision, perception, consciousness, subjective report, computational model 2 1 Introduction The science of visual perception has a long history of developing quantitative, computational models to explain and predict visual performance on a variety of tasks. These models have typically been developed to account for objective visual performance—like observer’s accuracy, reaction time, or perceptual sensitivity in discriminating different visual stimuli.
    [Show full text]
  • Unspecific Hypervigilance and Spatial Attention in Early Visual Perception
    Social Cognitive and Affective Neuroscience Advance Access published May 24, 2013 doi:10.1093/scan/nst044 SCAN (2013) 1 of 7 Timing the fearful brain: unspecific hypervigilance and spatial attention in early visual perception Mathias Weymar,1,2 Andreas Keil,2 and Alfons O. Hamm1 1Department of Biological and Clinical Psychology, University of Greifswald, 17487 Greifswald, Germany and 2Center for the Study of Emotion and Attention (CSEA), University of Florida, Gainesville, FL 32611, USA Numerous studies suggest that anxious individuals are more hypervigilant to threat in their environment than nonanxious individuals. In the present event-related potential (ERP) study, we sought to investigate the extent to which afferent cortical processes, as indexed by the earliest visual component C1, are biased in observers high in fear of specific objects. In a visual search paradigm, ERPs were measured while spider-fearful participants and controls searched for discrepant objects (e.g. spiders, butterflies, flowers) in visual arrays. Results showed enhanced C1 amplitudes in response to spatially directed target stimuli in spider-fearful participants only. Furthermore, enhanced C1 amplitudes were observed in response to all discrepant targets and distractors in spider-fearful compared with non-anxious participants, irrespective of fearful and non-fearful target contents. This pattern of results is in line with theoretical notions of heightened sensory sensitivity (hypervigilance) to external stimuli in high-fearful individuals. Specifically, the findings suggest that fear facilitates afferent cortical processing in the human visual cortex in a non-specific and temporally sustained fashion, when Downloaded from observers search for potential threat cues. Keywords: emotion; hypervigilance; spatial attention; C1; event-related potentials (ERPs) http://scan.oxfordjournals.org/ INTRODUCTION in specific object fear should show sensory facilitation when expecting Voluntary attention to a specific location in the environment results in to confront the feared object.
    [Show full text]
  • VISUAL NEUROSCIENCE Spring 2020
    PSYC/BIBB/VLST 217 VISUAL NEUROSCIENCE Spring 2020 Spring 2020 Lecture: MWF 9-10a, Leidy Labs 10 Prerequisites: PSCY 1, BIBB 109, VLST 101, COGS 001, PSYC 149/BIBB 249 Synopsis: An introduction to the scientific study of vision, with an emphasis on the biological substrate and its relation to behavior. Topics will typically include physiological optics, transduction of light, visual thresholds, color vision, anatomy and physiology of the visual pathways, and the cognitive neuroscience of vision. Instructor: Alan A. Stocker, Ph.D. Office: Goddard Labs Rm 421, 3710 Hamilton Walk Phone: (215) 573 9341 Email: [email protected] Office hour: W 12-1p Teaching Assistant: Jiang Mao Email: [email protected] Office hour: T 4-5p, TR 4-5p Office hour location: Goddard Labs Rm 420, 3710 Hamilton Walk Course Website (CANVAS): The course has a dedicated CANVAS site. Lecture slides, homework assignments, and reading assignments/material will be posted there. Also, check the site frequently for posted announcements and Q & As on the discussion board. In general, this is the place to go first if you have any question or are in need of any information regarding the course. Requirements: Homework1-3 posted on canvas Midterm Exam 1 February 21 (in class) Midterm Exam 2 March 27 (in class) Midterm Exam 3 April 24 (in class) Final Exam (cumulative) May 7, 12-2p Policy on homework assignments: Homework assignments are essential for a proper understanding of the material. There will be three homework assignments, meant in part as preparation for each midterm exam. Assignments and due dates will be posted on CANVAS.
    [Show full text]
  • Visual Perception & Visual Neuroscience
    Short tutorial: Visual Perception & Visual Neuroscience Organization of visual system Organization: lateral geniculate nucleus Ipsilateral: 2,3,5 Contralateral: 1,4,6 • Parvocellular: small cells, form • Magnocellular: large cells, motion Visual cortex • Primary visual cortex (striate cortex, V1) • Extrastriate visual areas • Retinotopic mapping in humans with fMRI Multiple visual areas: reality Macaque: about 50% of cortex is related to vision Physiology Example: direction selectivity in V1 V1 physiology Simple cells: Complex cells: • orientation selective • orientation selective • some are direction selective • some are direction selective • some are disparity selective • some are disparity selective • monocular or binocular • nearly all are binocular • separate ON and OFF • no separate ON and OFF subregions subregions • length summation • length summation (best response to long bar) Hypercomplex cells: end-stopping (best response to short bar) Brightness perception • Simultaneous brightness contrast – Effect of center- surround RF in the retina? Adelson’s checker shadow illusion See http://web.mit.edu/persci/people/adelson/checkershadow_illusion.html Color perception • Trichromacy • Opponent processes – R-G, B-Y, B-W – Opponent cells (center- surround opponency) Cortical basis of color perception • Evidence of a dedicated ‘color module’ in the human brain – Cerebral achromatopsia Mr. I. could hardly bear the changed appearances of people ("like animated gray statues") any more than he could bear his own changed appearance in the mirror: he shunned social intercourse and found sexual intercourse impossible. He saw people's flesh, his wife's flesh, his own flesh, as an abhorrent gray; "flesh-colored" now appeared "rat-colored" to him. This was so even when he closed his eyes, for his preternaturally vivid ("eidetic") visual imagery was preserved but now without color, and forced on him images, forced him to "see" but see internally with the wrongness of his achromatopsia.
    [Show full text]
  • Neuropsychiatry Review Series: Disorders of Visual Perception. Dominic Ffytche, Jan Dirk Blom, Marco Catani
    Neuropsychiatry Review series: Disorders of Visual perception. Dominic Ffytche, Jan Dirk Blom, Marco Catani To cite this version: Dominic Ffytche, Jan Dirk Blom, Marco Catani. Neuropsychiatry Review series: Disorders of Visual perception.. Journal of Neurology, Neurosurgery and Psychiatry, BMJ Publishing Group, 2010, 81 (11), pp.1280. 10.1136/jnnp.2008.171348. hal-00587980 HAL Id: hal-00587980 https://hal.archives-ouvertes.fr/hal-00587980 Submitted on 22 Apr 2011 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Disorders of visual perception Dr Dominic H ffytche1,4* Dr JD Blom2,3 4 Dr M Catani 1 Department of Old Age Psychiatry, Institute of Psychiatry, King’s College London, UK 2 Parnassia Bavo Group, The Hague, the Netherlands 3 Department of Psychiatry, University of Groningen, Groningen, the Netherlands 4 Natbrainlab, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, King’s College London, UK *Address for Correspondence Dr D H ffytche Department of Old Age Psychiatry, Institute of Psychiatry PO70, King’s College
    [Show full text]