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Human Cortical Oscillations: a Neuromagnetic View Through the Skull

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Human Cortical Oscillations: a Neuromagnetic View Through the Skull R EVIEW R. Hari and R. Salmelin – Human cortical rhythms VA -IN S I N V Human cortical oscillations: a O E N I neuromagnetic view through the skull M G AG I N Riitta Hari and Riitta Salmelin The mammalian cerebral cortex generates a variety of rhythmic oscillations, detectable directly from the cortex or the scalp. Recent non-invasive recordings from intact humans, by means of neuromagnetometers with large sensor arrays, have shown that several regions of the healthy human cortex have their own intrinsic rhythms, typically 8–40 Hz in frequency, with modality- and frequency-specific reactivity. The conventional hypotheses about the functional significance of brain rhythms extend from epiphenomena to perceptual binding and object segmentation. Recent data indicate that some cortical rhythms can be related to periodic activity of peripheral sensor and effector organs. Trends Neurosci. (1997) 20, 44–49 EURONES IN THE HUMAN BRAIN, especially in signals can be identified easily. By contrast, MEG (and Nthalamic nuclei and in the cerebral cortex, ex- EEG) sensors pick up signals from extensive brain hibit intrinsic oscillations1–3, which probably form the regions, which might be even several centimetres basis for macroscopic rhythms, detectable with electro- away from the sensor. Therefore the sites of active encephalography (EEG) and magnetoencephalography neuronal populations have to be deduced from the (MEG). Analysis of cortical rhythms forms an essential measured signal distribution. Although this ‘inverse part of clinical EEG evaluation, which relies on corre- problem’ does not have a unique solution in the gen- lations between the signal phenomenology and brain eral case6,9, modelling the generators of MEG signals as disorders. However, despite extensive animal experi- current dipoles allows identification of the most prob- ments2–4, the functional significance of cortical rhythms able source areas. A current dipole describes a local has remained largely unknown. active cortical area well, and can also be used to rep- Interest in human brain rhythms started to increase resent the centre of gravity of an extended active brain with the development of neuromagnetometers with region8. For elicited responses, sources are typically extended sensor arrays. MEG (Refs 5–9), although modelled during peaks of the responses to benefit closely related to EEG, benefits from the transparency from the best signal-to-noise ratio. Owing to the of the skull and the scalp to magnetic fields: the MEG spatial complexity and temporal overlap of active signals, which arise mainly from synaptic currents in cortical areas, magnetic field patterns of brain fissural cortex, can be picked up outside the head rhythms might be strictly dipolar only during 1–3% of undisturbed by tissue inhomogeneities. MEG thus typical analysis intervals, selected on the basis of visu- provides a non-invasive view ‘through the skull’ on ally identifiable oscillatory activity11,22. temporospatial activation patterns of the human cer- Figure 1A (right) illustrates a source cluster for the ebral cortex (Fig. 1). Early attempts to localize the sources posterior 10 Hz rhythm, obtained by determining the of spontaneous brain rhythms already offered some model parameters at 5–10 ms intervals over several insights into the function of the active brain regions12–14, tens of seconds; the cluster gives an estimate for the but were handicapped by the small coverage of the MEG active brain region, but it is also affected by noise and sensor arrays. Only the recent emergence of whole- thus has to be considered as a statistical representation scalp magnetometers has made studies of spontaneous of the most probable source areas. In this figure, the activity of the whole human neocortex feasible. sources have been projected to the surface of the brain The best known electric oscillations of the human for illustrative purposes; the current orientations, brain are the alpha rhythm, detected with EEG over typically perpendicular to the course of cortical the posterior parts of the brain15–17, and the mu fissures, are not shown. Sources can also be defined rhythm, recorded over the rolandic regions18,19. Both readily in frequency domain23–25, although the rhythms are seen clearly in MEG recordings (see Fig. 1) approach is only selectively applicable for physiologi- and display modality-specific reactivity: the posterior cal studies of brain oscillations, which are not strictly Riitta Hari rhythm is dampened by opening the eyes, and the periodic and typically occur in brief bursts. A recent and Riitta Salmelin rolandic rhythm is dampened by limb movements review9 can be consulted for detailed description of are at the Brain and tactile stimulation. A third modality-specific MEG the MEG data interpretation. Research Unit, rhythm, ‘tau’, has been recorded from the supra- Sources and reactivity of the alpha rhythm Low Temperature temporal auditory cortex. It increases during drowsi- Laboratory, Helsinki ness and is occasionally dampened by sounds8,20,21. Sources of the posterior 10 Hz alpha rhythm con- University of centrate predominantly in the parieto–occipital region Source modelling Technology, and, to a smaller extent, in the occipital areas. The 02150 Espoo, The invasive microelectrode recordings have the two subclusters differ both by their sites and current Finland. advantage that the neuronal structure generating the orientations, and suggest that the strongest activity 44 TINS Vol. 20, No. 1, 1997 Copyright © 1997, Elsevier Science Ltd. All rights reserved. 0166 - 2236/97/$17.00 PII: S0166-2236(96)10065-5 R. Hari and R. Salmelin – Human cortical rhythms R EVIEW A Measurement Sources Signal detection Measurement coil Signal coil → → B ext Bcoupl SQUID B C Spectra 11.5 Reactivity α µ √ –1 9.3 10 fT (cm Hz) 17.9 22.6 21.8 Eyes closed µ Eyes open Move left α Move right 10 20 30 40 Hz 0 10 20 30 40 Hz Fig. 1. Recording and displaying of magnetoencephalographic rhythms. (A) (Left) The subject sits in a magnetically shielded room, with his head under a whole-scalp neuromagnetometer, which houses 122 superconducting SQUIDs (superconducting quantum interference devices) on a helmet- like sensor array10. (Middle) The external magnetic flux, generated by currents flowing in the human brain, penetrates the superconducting flux transformers. The resulting currents in the coils then couple the signal magnetically to the SQUID. (Right) A source cluster of the posterior 10 Hz oscillations superimposed on the surface rendering of the subject’s brain, constructed from the magnetic resonance images. (B) Amplitude spectra of one subject calculated from a 1 min period of spontaneous activity when the subject was resting with the eyes closed. Each sensor unit records the changes of the radial magnetic field in two orthogonal directions along the plane of the helmet. (C) Reactivity of the parieto–occipital (‘alpha’) and rolandic (‘mu’) rhythms to opening of the eyes and to movements of the left and right hand. The MEG data are adapted from Ref. 11. occurs in the parieto–occipital sulcus with less activity In addition to the physical features of the stimuli, the in the calcarine sulcus22,26. Even within these sub- reactivity also depends on the subject’s performance clusters, several single sources with independent time and effort. For example, the phasic alpha suppression behaviour might be active simultaneously11, thereby during passive viewing of pictures is intensified con- supporting previous studies that suggest a multitude siderably when the subject is asked to name the pic- of distinct sources for the electric and magnetic alpha tures, either silently or aloud32. oscillations27,28. The observed dominance of the Interestingly, changes very similar to those elicited parieto–occipital magnetic activity seems to contrast by visual stimuli can also be produced by visual with the animal data29, which emphasize the role of imagery. Figure 3 shows changes of the 10 Hz alpha the visual projection cortex in the generation of alpha rhythm during a visual letter-imagery task when the activity. We assume that either the human calcarine subject kept her eyes closed; the suppression reached region produces considerably less alpha-range activity its maximum within 1 s after the auditory presen- than the parieto–occipital sulcus region, or the oppo- tation of a letter that the subject was to view in her site orientations of source currents in the walls of mind’s eye22. The suppression was strong also when calcarine fissures result in cancellation of the external the subject subsequently inspected the mental image magnetic field. The present data do not allow a dis- to answer a probe question about its visual properties. tinction between these two possibilities. In this type of experiment, the inter-individual vari- The level of the posterior 10 Hz alpha rhythm ability is large, both in the brain’s reactivity and in the decreases during and after visual stimulation (Fig. 2). subject’s capability to form mental images. Whereas stimulus-locked elicited responses typically These results suggest strong involvement of non- concentrate within a time window of 0.5 s, cortical primary visual areas in the vicinity of the parieto– rhythms are modulated over periods of a few seconds. occipital sulcus in generation and inspection of mental TINS Vol. 20, No. 1, 1997 45 R EVIEW R. Hari and R. Salmelin – Human cortical rhythms various visual stimuli35 and in association with volun- tary eye blinks36 and saccades37. Anatomically, this Original area could be the human homologue of the monkey V6/V6A region, influenced by, for example, saccades and eye position, and hypothesized to be related to Stimulus spatial coding of extrapersonal visual space and to visuomotor integration38,39. Segregation of the 10 Hz and 20 Hz somatomotor Filtered rhythms (8 –13 Hz) The well-known ‘comb-like’ shape of the somato- motor mu rhythm implies that the rhythm consists of Rectified two or three frequency components with a nearly har- monic relationship.
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