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The large multicomponent K-complex (KC) and the rhythmic spindle are the hallmarks of non-rapid eye movement (NREM)-2 sleep stage. We studied with magnetoencephalography (MEG) the progress of light sleep (NREM-1 and NREM-2) and emergence of KCs and spindles. Seven periods of interest (POI) were analyzed: wakefulness, the two quiet “core” periods of light sleep (periods free from any prominent phasic or oscillatory events) and four periods before and during spindles and KCs. For each POI, eight 2-s (1250 time slices) segments were used. We employed magnetic field tomography (MFT) to extract an independent tomographic estimate of brain activity from each MEG data sample. The spectral power was then computed for each voxel in the brain for each segment of each POI. The sets of eight maps from two POIs were contrasted using a voxel-by-voxel t-test. Only increased spectral power was identified in the four key contrasts between POIs before and during spindles and KCs versus the NREM2 core. Common increases were identified for all four subjects, especially within and close to the anterior cingulate cortex (ACC). These common increases were widespread for low frequencies, while for higher frequencies they were focal, confined to specific brain areas. For the pre-KC POI, only one prominent increase was identified, confined to the theta/alpha bands in a small area in the dorsal caudal part of ACC (dcACC). During KCs, the activity in this area grows in intensity and extent (in space and frequency), filling the space between the areas that expanded their low frequency activity (in the delta band) during NREM2 compared to NREM1. Our main finding is that prominent spectral power increases before NREM2 graphoelements are confined to the dcACC, and only for KCs, sharing common features with changes of activity in dcACC of the well-studied error related negativity (ERN). ERN is seen in awake state, in perceptual conflict and situations where there is a difference between expected and actual environmental or internal events. These results suggest that a KC is the sleep side of the awake state ERN, both serving their putative sentinel roles in the frame of the saliency network.

Introduction This project aims to monitor human volunteers as they switch from heavy (>10 cigarette/day) tobacco smoking to electronic cigarette (EC) use. Monitoring of markers will comprise expired carbon monoxide, DNA methylation, oxytocin, cortisol, nicotine cotinine and tobacco specific nitrosamine levels in urine and saliva together with psychometric data. In addition electroencephalography will be used to search for electrical changes in the brain correlated with changes in the above markers after transition to EC use. Methods Volunteers were recruited and consented at St George’s University of London. Volunteers were allowed to select their own EC and e-fluid including nicotine concentration. Blood, saliva, urine and buccal cell samples and questionnaire data (nicotine dependence, withdrawal, anxiety, depression, mood, quality of life and sleep quality) were collected at baseline (day-2 and day-1) and throughout the 28-day EC trial (days 3,21,28) and EEG data (eyes open-eyes fixed-eyes closed, each 3 x 30s) were collected at baseline (day-1) and on EC day 21. Nicotine, cotinine, NNK, NNAL and NNN were determined by UHPLC-HESI-HRMS, 5methyl cytosine by HPLC and oxytocin and cortisol by ELISA. Results Urinary and salivary nicotine, cotinine and tobacco specific nitrosamines and expired carbon monoxide decrease significantly following transition to EC. Behavioural data have revealed modest changes in nicotine craving, nicotine withdrawal symptoms, social anxiety and sleep quality following the transition to e-cigarettes. Preliminary comparison of regional spectral power extracted from EEG data collected pre- and post- transition to e-cigarettes use has identified significant changes in specific spectral bands across the brain. Conclusions Switching to EC quickly induces beneficial changes in exposure to toxicants and psychometrics. Changes in regional spectral power observed by EEG vary will be correlated to these other biomarkers. Funding This work is supported by H2020 funding from the European Union and by a PHE-funded PhD studentship.

In recent years, parallel developments in disparate disciplines have focused on what has come to be termed connectivity; a concept used in understanding and describing complex systems. Conceptualisations and operationalisations of connectivity have evolved largely within their disciplinary boundaries, yet similarities in this concept and its application among disciplines are evident. However, any implementation of the concept of connectivity carries with it both ontological and epistemological constraints, which leads us to ask if there is one type or set of approach(es) to connectivity that might be applied to all disciplines. In this review we explore four ontological and epistemological challenges in using connectivity to understand complex systems from the standpoint of widely different disciplines. These are: (i) defining the fundamental unit for the study of connectivity; (ii) separating structural connectivity from functional connectivity; (iii) understanding emergent behaviour; and (iv) measuring connectivity. We draw upon discipline-specific insights from Computational Neuroscience, Ecology, Geomorphology, Neuroscience, Social Network Science and Systems Biology to explore the use of connectivity among these disciplines. We evaluate how a connectivity-based approach has generated new understanding of structural-functional relationships that characterise complex systems and propose a ‘common toolbox’ underpinned by network-based approaches that can advance connectivity studies by overcoming existing constraints.

In normal viewing conditions, many objects are often hidden or occluded by others, therefore restricting the information that enters the eye. One ability that the human visual system has developed to compensate for this visual limitation is to relate the surrounding elements to globally interpret the whole scene. The appearance of illusory figures (IF) based on surrounding elements also relies on this similar function. In the present study, we hypothesized that different mechanisms may be used by the brain to process IF from the center and periphery of the visual field. We compared magnetoencephalo- graphic responses to IFs presented at different parts of the visual field under three task loads. For cen- tral presentation, IF specific responses peaked first in V1/V2 (96-101 ms), and then in the lateral occipi- tal complex (LOC; 132-141 ms), independent of task. For peripheral presentation, the relative modula- tion towards IF was markedly reduced in V1/V2 and LOC while prominent activation peaks now shifted to the Fusiform Gyrus (from 200 ms onwards). Additionally, the type of task influenced proc- essing at early stages beginning in V1/V2 (87 ms). Our results show that retinal eccentricity plays a crucial role in IF processing: figural completion at the center of the visual field is achieved in an 'auto- matic' and seemingly effortless fashion whereas peripheral stimulus locations necessitate higher-order object completion stages which rely more heavily on attentional demands. Hum Brain Mapp 29:1313- 1326, 2008. V V C 2007 Wiley-Liss, Inc.

Epilepsy and sleep are characterized by spontaneously occurring large graphoelements in electroencephalography (EEG) and magnetoencephalography (MEG) recordings, such as ictal and interictal epileptiform discharges in epilepsy and K-complexes (KC) in sleep. Localization of the neural sources of these graphoelements, which is of immense clinical and research importance, requires application of electromagnetic source analysis methods. A number of such methods are available; however their ability to localize widespread synchronous cortical sources, such as the sources of KCs and widespread epileptiform discharges, is contested. Here, we used KC as an exemplar of large graphoelements with such sources to test the performance of a diverse set of commonly employed source analysis methods. We analyzed segments of sleep MEG data with clear KCs using equivalent current dipole models, beamformer methods, linear distributed source methods, and a non-linear distributed source method—magnetic field tomography (MFT). MFT provided the most robust and steady localization across KCs, which was also highly consistent with the intracranial findings: strong and widespread activations were reliably found in superior aspects of bilateral frontal cortex. Conversely, the localizations provided by the other methods were very variable across KCs and were all inconsistent with the intracranial findings: in many cases, the KCs were incorrectly localized in deep medial brain structures. Our current and earlier results showing the excellent localization accuracy of MFT for focal as well as extended brain sources and the smart uses of MEG and EEG in epilepsy, demonstrate that the MFT analysis of MEG signals may be a powerful tool for the studies of epilepsy, epilepsy monitoring and in pre-surgical evaluation of patients.

We investigated the process of amodal completion in a same-different experiment in which test pairs were preceded by sequences of two figures. The first of these could be congruent to a global or local completion of an occluded part in the second figure, or a mosaic interpretation of it. We recorded and analyzed the magnetoencephalogram for the second figures. Compared to control conditions, in which unrelated primes were shown, occlusion and mosaic primes reduced the peak latency and amplitude of neural activity evoked by the occlusion patterns. Compared to occlusion primes, mosaic ones reduced the latency but increased the amplitude of evoked neural activity. Processes relating to a mosaic interpretation of the occlusion pattern, therefore, can dominate in an early stage of visual processing. The results did not provide evidence for the presence of a functional “mosaic stage” in completion per se, but characterize the mosaic interpretation as a qualitatively special one that can rapidly emerge in visual processing when context favors it.

Cortical activity evoked by repeated identical sensory stimulation is extremely variable. The source of this variability is often assigned to "random ongoing background activity" which is considered to be irrelevant to the processing of the stimuli and can therefore be eliminated by ensemble averaging. In this work, we studied the single-trial variability in neuromagnetic responses elicited by circular checkerboard pattern stimuli with radii of 1.8 degrees, 3.7 degrees, and 4.5 degrees. For most of the MEG sensors over the occipital areas, the averaged signal showed a clear early (N70m) response following the stimulus onset and this response was modulated by the checkerboard size. A data-driven spatial filter was used to extract one of the many possible composite time courses of single-trial activity corresponding to the complex of N70m generators. Pattern analysis principles were then employed to analyze, classify, and handle the extracted temporal patterns. We explored whether these patterns correspond to distinct response modes, which could characterize the evoked response better than the averaged signal and over an extended range of latencies around N70m. A novel scheme for detecting and organizing the structure in single-trial recordings was utilized. This served as a basis for comparisons between runs with different checkerboard sizes and provided a causal interpretation of variability in terms of regional dynamics, including the relatively weak activation in primary visual cortex. At the level of single trial activity, the polymorphic response to a simple stimulus is generated by a coupling of polymodal areas and cooperative activity in striate and extrastriate areas. Our results suggest a state-dependent response with a wide range of characteristic time scales and indicate the ongoing activity as a marker of the responsiveness state.

Somatosensory stimulation of primary somatosensory cortex (SI) using frequency discrimination offers a direct, well-defined and accessible way of studying cortical decisions at the locus of early input processing. Animal studies have identified and classified the neuronal responses in SI but they have not yet resolved whether during prolonged stimulation the collective SI response just passively reflects the input or actively participates in the comparison and decision processes. This question was investigated using tomographic analysis of single trial magnetoencephalographic data. Four right-handed males participated in a frequency discrimination task to detect changes in the frequency of an electrical stimulus applied to the right-hand digits 2+3+4. The subjects received approximately 600 pairs of stimuli with Stim1 always at 21 Hz, while Stim2 was either 21 Hz (50%) or varied from 22 to 29 Hz in steps of 1 Hz. Both stimuli were 1 s duration, separated by a 1 s interval of no stimulation. The left-SI was the most consistently activated area and showed the first activation peak at 35-48 ms after Stim1 onset and sustained activity during both stimulus periods. During the Stim2 period, we found that the left-SI activation started to differ significantly between two groups of trials (21 versus 26-29 Hz) within the first 100 ms and this difference was sustained and enhanced thereafter (approximately 600 ms). When only correct responses from the above two groups were used, the difference was even higher at later latencies (approximately 650 ms). For one subject who had enough trials of same perception to different input frequencies, e.g. responded 21 Hz to Stim2 at 21 Hz (correct) and 26-29 Hz (error), we found the sustained difference only before 650 ms. Our results suggest that SI is involved with the analysis of an input frequency and related to perception and decision at different latencies.

The echoic memory trace (EMT) refers to neuronal activity associated with the short-term retention of stimulus-related information, especially within the primary and association auditory cortex. Using magnetoencephalography it is possible to determine quantitatively the lifetime of the EMT. Previous studies assumed that each new stimulus drives the EMT to its full strength, which then passively decays. In this study we show the limitations of this assumption using trains of auditory stimuli designed specifically for computing the EMT lifetime and its contextual sensitivity. We estimated a time-dependent EMT using a data-driven approach, which allows contributions from a relatively wide area around the auditory cortex in our quantitative measures. We identified: (1) internally generated cortical activations during the silent period between stimuli well separated in time from each other, which had influence on the morphology of the neuromagnetic response to the next external stimulus; and (2) EMTs with different lifetimes that modulate the amplitude of the evoked responses at different latencies, suggesting the existence of multiple neural delay lines. Long EMT lifetimes were observed on the descending part of the M100 complex, which showed handedness and gender-dependent interhemispheric asymmetry. Specifically, all subjects showed longer EMT lifetimes on the left hemisphere, except left-handed males. Distributed source analysis of the data for one left- and one right-handed male subject identified a secondary generator in the right-handed subject, which was located posterior to the early primary generator and dominated the auditory response at late latencies, where EMT lifetime asymmetry was high. The identified multiple neural delay lines and their laterality may provide a link between macroneuronal activity and left hemisphere specialization for processing linguistic material.

The tomographic localization of activity within human primary visual cortex (striate cortex or V1) was examined using whole-head magnetoencephalography (MEG) and 4-T functional magnetic resonance imaging (fMRI) in four subjects. Circular checkerboard pattern stimuli with radii from 1.8 to 5.2 degrees were presented at eccentricity of 8 degrees and angular position of 45 degrees in the lower quadrant of the visual field to excite the dorsal part of V1 which is distant from the V1/V2 border and from the fundus of the calcarine sulcus. Both fMRI and MEG identified spatially well-overlapped activity within the targeted area in each subject. For MEG, in three subjects a very precise activation in V1 was identified at 42 ms for at least one of the two larger stimulus sizes (radii 4.5 and 5.2 degrees ). When this V1 activity was present, it marked the beginning of a weak wave of excitations in striate and extrastriate areas which ended at 50 ms (M50). The beginning of the next wave of activations (M70) was also marked by a brief V1 activation, mainly between 50 and 60 ms. The mean separation between V1 activation centers identified by fMRI and the earliest MEG activation was 3-5 mm.

In current clinical practice the degree of paraplegia or quadriplegia is objectively determined with transcranial magnetic stimulation (TMS) and somatosensory-evoked potentials (SSEP). We measured the MEG signal following electrical stimulation of upper and lower limbs in two normal and three clinically complete paraplegic subjects. From the MEG signal we computed distributed estimates of brain activity and identified foci just behind the central sulcus consistent in location with primary somatosensory (SI) for arm and foot and secondary somatosensory (SII) areas. Activation curves were computed from regions of interest defined around these areas. Activation of the SI foot area was observed in normal and paraplegic subjects when the upper limb was stimulated. Surprisingly, for each paraplegic subject, stimulation below the lesion was followed by cortical activations. These activations were weak, only loosely time-locked to the stimulus and were seen intermittently behind the central sulcus and nearby cortical areas. Statistical analysis of tomographic solutions and activation curves showed consistent responses following foot stimulation in one paraplegic (PS1) and intermittently in another paraplegic subject. We repeated the same experiment for PS1 in a different laboratory and the results from the analysis of foot stimulation from both laboratories revealed statistically significant focal cortical response only in the contralateral SI foot area.

The magnetoencephalography (MEG) signal was recorded while subjects watched a video containing separate blocks of affective and cognitive advertisements and recalled slides extracted from the video a day later. An earlier behavioural study using the same video material showed that the affective advertisements were better recalled and that administration of propranolol (a beta-adrenergic blocker) abolished this effect. Magnetic field tomography (MFT) was used to extract tomographic estimates of activity millisecond by millisecond from the continuous MEG signal. Statistically significant differences between affective and cognitive blocks were identified in posterior and prefrontal areas. Cognitive blocks produced stronger activity in posterior parietal areas and superior prefrontal cortex in all three subjects. Affective blocks modulated activity in orbitofrontal and retrosplenial cortex, amygdala and brainstem. Individual contributions to the statistical maps were traced in real time from milliseconds to many seconds. Time-locked responses from the recall session were used to compare average and single trial MFT solutions and to combine activations from all subjects into a common anatomical space. The last step produced statistically significant increases in occipital and inferior ventral cortex between 100 and 200 ms compared to a prestimulus baseline.

MEG correlates of the recognition of facial expressions of emotion were studied in four healthy volunteers. Subjects performed a facial emotion recognition task and a control task involving recognition of complex objects including faces. Facial emotion recognition activated inferior frontal cortex, amygdala and different parts of temporal cortex in a relatively consistent time sequence. The characteristics of these activations were clearly different from those recorded during the control task. Most interesting was the fact that faces evoked different MEG responses as a function of task demands, i.e., the activations recorded during facial emotion recognition were different from those recorded during simple face recognition in the control task. These findings support the assumption that MEG is able to specifically identify the activation pattern of the brain when recognition of the emotional expression of a face is performed.

In an earlier experiment, we have used the BTi twin MAGNES system (2 × 37 channels) to record the evoked magnetic field from five healthy right-handed male volunteers using two tasks: visual recognition of complex objects including faces and facial expressions of emotion. We have repeated the experiment with one of the five subjects using the BTi whole head system (148 channels). Magnetic field tomography (MFT) was used to extract 3D estimates of brain activity millisecond by millisecond from the recorded magnetoencephalographic (MEG) signals. Results from the MFT analysis of the average signals of the five subjects have been reported elsewhere (Streit et al. 1997; Streit et al. 1999). In this paper, we present results of the detailed single trial analysis for the subject recorded from the whole head system. We found activations in areas extending from the occipital pole to anterior areas. Regions of interest (ROIs) were defined entirely on functional criteria and confirmed independently by the location of the maximum activity on the MRI. Activation curves for each ROI were computed and objective statistical measures (Kolmogorov-Smirnov test) were then used to identify time segments for which the ROI activity showed significant differences both within the same and across different object/emotion categories. Emphasis is placed on the quantification of the activity from two ROIs, fusiform gyrus (FG) and amygdala (AM), which have been best studied in the context of processing of faces and facial expressions of emotion, respectively. We found no face-specific area as such, but instead areas like the FG was activated by all complex objects at roughly similar latencies and varying strengths. The amygdala activity was significantly different between 150 and 180 ms for fearful expression, and even earlier for happy expression.

Auditory evoked magnetic fields were recorded from five human subjects using the BTi whole head system (148 channels). The stimuli were simple tone bursts with different inter-stimulus intervals (ISI). The magnetic field was also recorded from the same subjects in place without stimulation to provide baseline 'noise' measurements. Magnetic field tomography (MFT) was applied to the average data and activation curves were computed from well circumscribed regions of interest (ROI). Objective statistical measures (Kolmogorov-Smirnov test) were then used to identify latency segments with distribution significantly different from the baseline distribution. For latency segments with significant activations the dependence of the activation strength on ISI was modeled by an exponentially saturating function. In earlier studies, the characteristic time (tau) in this function was interpreted as a measure of a memory trace for auditory tones. Our analysis identified distinct levels for tau: all subjects had the same lower two levels (0.50 s and 0.69 s). Attention modulation introduced considerably higher tau values in most subjects but it did not change the two 'ground state' tau levels. To our knowledge, this is the first demonstration of quantization effects in the macro-properties of brain activity, which were universal amongst the subjects we studied.

Auditory evoked magnetic fields were recorded from 5 human subjects, simultaneously over each hemisphere, using the BTi twin MAGNES system (2×37 channel). Accurate placing of each probe and the use of optimally designed linear sums of signals allow the estimation of the millisecond by millisecond history of activation of the complex of generators responsible for the M100 response in each single trial. Thus it can be shown in much greater detail than any study so far, how the average signal around the M100 period is built up by events in single trials. We found consistent features across subjects, defining a dynamic baseline from which the stimulus related activity can be differentiated. Our analysis indicates that prior to the stimulus onset the activity in each auditory cortex proceeds more or less independently. The onset of the stimulus establishes a binding of activity in the two hemispheres, probably through a common input. The coordinated activity is well described by an exponentially saturating function with a characteristic time constant in the `magic' 15–30 ms range.

The spatiotemporal profiles of visual processing are normally distributed in two temporal phases, each lasting about 100 ms. Within each phase, cortical processing begins in V1 and traverses the visual cortical hierarchy. However, the causal role of V1 in starting each of these two phases is unknown. Here we used magnetoencephalography to study the spatiotemporal profiles of visual processing and the causal contribution of V1 in three neurologically intact participants and in a rare patient (GY) with unilateral destruction of V1, in whom residual visual functions mediated by the extra-geniculostriate pathways have been reported. In healthy subjects, visual processing in the first 200 ms post-stimulus onset proceeded in the two usual phases. Normally perceived stimuli in the left hemifield of GY elicited a spatiotemporal profile in the intact right hemisphere that closely matched that of healthy subjects. However, stimuli presented in the cortically blind hemifield produced no detectable response during the first phase of processing, indicating that the responses in extrastriate visual areas during this phase are determined by the feedforward progression of activity initiated in V1. The first responses occurred during the second processing phase, in the ipsilesional high-level visual areas. The activity then spread forward toward higher-level areas and backward toward lower-level areas. However, in contrast to responses in the intact hemisphere, the back-propagated activity in the early visual cortex did not exhibit the classic retinotopic organization and did not have well-defined response peaks.

How the brain works is nowadays synonymous with how different parts of the brain work together and the derivation of mathematical descriptions for the functional connectivity patterns that can be objectively derived from data of different neuroimaging techniques. In most cases static networks are studied, often relying on resting state recordings. Here, we present a quantitative study of dynamic reconfiguration of connectivity for event-related experiments. Our motivation is the development of a methodology that can be used for personalized monitoring of brain activity. In line with this motivation, we use data with visual stimuli from a typical subject that participated in different experiments that were previously analyzed with traditional methods. The earlier studies identified well-defined changes in specific brain areas at specific latencies related to attention, properties of stimuli, and tasks demands. Using a recently introduced methodology, we track the event-related changes in network organization, at source space level, thus providing a more global and complete view of the stages of processing associated with the regional changes in activity. The results suggest the time evolving modularity as an additional brain code that is accessible with noninvasive means and hence available for personalized monitoring and clinical applications.

All sleep stages contain epochs with high-amplitude electrophysiological phasic events, alternating with quieter "core periods." High-amplitude and core state properties cannot be disentangled with PET and fMRI. Here from high temporal resolution magnetoencephalography data, regional changes in neuronal activity were extracted during core periods in different frequency bands for each sleep stage and waking. We found that gamma-band activity increases in precuneus during light sleep (stages 1/2) and in the left dorso-medial prefrontal cortex (L-DMPFC) during deep sleep (stages 3/4). The L-DMPFC activated area expands laterally during rapid eye movement (REM) sleep, into a volume of about 5 cm(3) bounded by regions attributed to Theory of Mind (ToM) and default systems, both involved in introspection. Gamma band activity in this area was higher during REM sleep than other sleep stages and active wakefulness. There is a tantalizing correspondence between increased wide-band activity (dominated by low frequencies) in early non-REM (NREM) sleep stages and increases in gamma-band activity in late NREM and REM periods that we attribute to a lateral disinhibition mechanism. The results provide a description of regional electrophysiological changes in awake state, light and deep sleep, and REM sleep. These changes are most pronounced in the L-DMPFC and the other areas around the dorsal midline that are close to, but do not overlap with areas of the default and ToM systems, suggesting that the DMPFC, particularly in the left hemisphere, plays an important role in late NREM stages, in REM and possibly in dreaming.

The visual system rapidly completes a partially occluded figure. We probed the completion process by using priming in combination with neuroimaging techniques. Priming leads to more efficient visual processing and thus a reduction in neural activity in relevant brain areas. These areas were studied with high spatial resolution and temporal accuracy with focus on early perceptual processing. We recorded magnetoencephalographic responses from 10 human volunteers in a primed same-different task for test figures. The test figures were preceded by a sequence of two figures, a prime or control figure followed by an occluded figure. The prime figures were one of three possible interpretations of the occluded figures: global and local completions and mosaic interpretation. A significant priming effect was evident: in primed trials as compared with control trials, subjects responded faster and the latency was shorter in the magnetoencephalographic signal for the largest peak between 50 and 300 ms after the occluded figure onset. Tomographic and statistical parametric mapping analyses revealed stages of activation in occipitotemporal areas during occluded figure processing. Notably, we found significantly reduced activation in the right fusiform cortex between 120 and 200 ms after occluded figure onset for primed trials as compared with control trials. We also found significant spatiotemporal differences of local, global and mosaic interpretations for individual subjects but not across subjects. We conclude that modulation of activity in the right fusiform cortex may be a neural correlate of priming in the interpretation of an occluded figure, and that this area acts as a hub for different occluded figure interpretations in this early stage of perception.

With sufficiently fast data sampling, ubiquitous sharp transients appear in magnetoencephalography (MEG) data. Initially, no known collective neuronal activity could explain MEG signal generation well above 100 Hz, so it was assumed that these transients were entirely composed of background electronic noise that could be eliminated by filtering and averaging. Recent studies at the cellular level provided evidence for synchronous synaptic input to dendrites and volleys of near-simultaneous action potentials. MEG studies have also identified high-frequency oscillations well above 200 Hz after averaging large number of somatosensory evoked responses. In this study, we searched for evidence of high-frequency neuronal activity in the raw MEG signal using the highest sampling rate available with our hardware. Two human subjects participated in three experiments using visual cues to define planning, preparation, and execution or inhibition of saccades. Tomographic analysis identified “MEG spikes” that were widely distributed across the cortex, cerebellum, and brainstem during cue presentations and saccades. Here we demonstrate how these MEG spikes can be recorded and localized in real time and show that task demands influence their properties. The MEG spikes were organized into feedforward and corollary discharge sequences that could, when combined with the slower activity-linked processing in discrete brain areas over long periods, lasting hundreds of milliseconds. Preparation for impending saccade began as soon as relevant information became available. Cues providing partial information initiated competing motor programs for as yet undecided future actions that were maintained until cues with new information resolved the uncertainty.

Most neuroimaging studies on face processing used centrally presented images with a relatively large visual field. Images presented in this way activate widespread striate and extrastriate areas and make it difficult to study spatiotemporal dynamics and connectivity pattern differences from various parts of the visual field. Here we studied magnetoencephalographic responses in humans to centrally and peripherally presented faces for testing the hypothesis that processing of visual stimuli with facial expressions of emotions depends on where the stimuli are presented in the visual field. Using our tomographic and statistical parametric mapping analyses, we identified occipitotemporal areas activated by face stimuli more than by control conditions. V1/V2 activity was significantly stronger for lower than central and upper visual field presentation. Fusiform activity, however, was significantly stronger for central than for peripheral presentation. Both the V1/V2 and fusiform areas activated earlier for peripheral than for central presentation. Fast responses in the fusiform were found at 70–80 ms after image onset, as well as a response at 130–160 ms. For peripheral presentation, contralateral V1/V2 and fusiform activated earlier (10 ms and 23 ms, respectively) and significantly stronger than their ipsilateral counterparts. Mutual information analysis further showed linked activity from bilateral V1/V2 to fusiform for central presentation and from contralateral V1/V2 to fusiform for lower visual field presentation. In the upper visual field, the linkage was from fusiform to V1/V2. Our results showed that face stimuli are processed predominantly in the hemisphere contralateral to the stimulation and demonstrated for the first time early fusiform activation leading V1/V2 activation for upper visual field stimulation.

Attentional effects in the striate and extrastriate cortex have been the subject of intense research interest in many recent studies using single unit recordings in animals and neuroimaging methods in humans. The consensus emerging from these studies places attentional effects first in extrastriate areas. Attentional influence in this view is reaching V1 rather late, some 150 ms after stimulus onset, well after the main N1/P1 complex which peaks about 50 ms earlier. We show here that an earlier wave of attentional effects is present in V1 beginning soon after 50 ms and reaching a peak between 90 and 100 ms after stimulus onset. This effect is identified in a comparison of passive viewing of stimuli and an active GO/NOGO task using the same stimuli. The effect was best seen in the tomographic analysis of single trial magnetoencephalographic (MEG) data, designed to cope with simultaneous activations throughout the brain at each timeslice. This early attentional modulation might still be interpreted as a modulation of the striate cortex from extrastriate areas because attention related changes are present in the prestimulus period in both dorsal and ventral extrastriate areas.

Old ideas about attention and consciousness seemed to be irrelevant today. We re-evaluated them here in the light of recent neuroimaging data, data from pathological conditions where attentional mechanisms are impaired and the knowledge that activity following a stimulus spreads rapidly very widely. We present the case that the multiple systems both cortical and subcortical involved in attentional processes can best be studied using tomographic, millisecond by millisecond single trial analysis of magnetoencephalographic data.

Magnetic field tomography (MFT) was used to extract estimates for distributed source activity from average and single trial MEG signals recorded while subjects identified objects (including faces) and facial expressions of emotion. Regions of interest (ROIs) were automatically identified from the MFT solutions of the average signal for each subject. For one subject the entire set of MFT estimates obtained from unaveraged data was also used to compute simultaneous time series for the single trial activity in different ROIs. Three pairs of homologous areas in each hemisphere were selected for further analysis: posterior calcarine sulcus (PCS), fusiform gyrus (FM), and the amygdaloid complex (AM). Mutual information (MI) between each pair of the areas was computed from all single trial time series and contrasted for different tasks (object or emotion recognition) and categories within each task. The MI analysis shows that through feed‐forward and feedback linkages, the “computation” load associated with the task of identifying objects and emotions is spread across both space (different ROIs and hemispheres) and time (different latencies and delays in couplings between areas)—well within 200 ms, different objects separate first in the right hemisphere PCS and FG coupling while different emotions separate in the right hemisphere FG and AM coupling, particularly at latencies after 200 ms. Hum. Brain Mapping 11:77–92, 2000. © 2000 Wiley‐Liss, Inc.

In both MEG and EEG studies, single epoch analysis has become increasingly popular [1, 2]. In EEG the relationship between generators and signal is blurred by the high resistivity and inhomogeneity of the skull, making single trial analysis problematic because of low signal-to-noise ratio. For MEG, the signal-to-noise ratio in single trials is high, in the sense that, contributions from small cortical regions are easily detectable, although not easily distinguished from other contributions. In addition, single trial analysis of MEG signals incurs a high computational burden and produces huge amount of output. In our earlier work [3, 4], we have addressed these problems by introducing a vector signal transformation called V3, which is the MEG analogue of the well-known Laplacian method of EEG. We have tested the accuracy of the V3 based estimates with Computer generated data and compared the results with the ones obtained from Magnetic Field Tomography (MFT) analysis of the same data. These tests have shown that the V3 based estimates are remarkably accurate when superficial generators are involved [4]. Estimators constructed from correlational measures based on the V3 and integrated over a period of time and/or a region, can be used to scan quickly and efficiently through all single trials. The V3 analysis has already been applied to the identification and quantification of auditory cortex activation and the investigation of gamma-band activity in single trials [4, 5]. Further correlation analysis of spatio-temporal V3 templates, has enabled us to describe qualitatively and quantitatively how patterns observed in the average signal are represented in single trials [6]: we showed conclusively that the average is a superposition of histories each reflected in different subsets of the epochs. In this paper, we will show another related application of the V3: it can be used as the basis for easy and fast inspection of data, and for identification of correlations in activity, in space and time, within the same hemisphere or across the hemispheres.

A general method for obtaining continuous solutions to the biomagnetic inverse problem was first presented during the 1989 Biomagnetism conference. From the outset, the method was developed for three-dimensional source spaces [1, 2] but, partly to reduce computational demands and partly for ease of presentation, the first major publication of the method [3] used two-dimensional reconstructions. Soon afterwards the algorithms were ported to a transputer, making possible the analysis of large sets of MEG data. The output (estimates of the primary current density in a three-dimensional source space) was displayed by taking slices (tomes) through the source space leading to a series of MFT (Magnetic Field Tomographie) images. Later forms of representation included time integrals and activation curves, describing the evolution of activity within specified Regions of Interest (ROI). Animations run on the transputer array and recorded on video, were by far the most effective presentation tool, showing in colour-coded form the changes in the activity against a background of coregistered MRI slices[4]. Early reconstructions used averaged data but the emphasis has recently shifted to analysis of single trial or continuous data [5, 6]. Each three-dimensional study was underpinned by thorough tests with Computer generated data which, however, have been only superficially reported because of space limitations. We have previously described our philosophy and method [3], the transputer based implementation [7] and the logic in the various algorithmic steps [8]. However, the lack of published material on the background tests must be the cause of misrepresentations of MFT in some recent publications dealing with distributed source analysis, e.g. [9]. The present paper makes good this omission and uses computer-generated data to illustrate the power and limitations of MFT as a 3D imaging method, using realistic sensor configurations and signals that are neurophysiologically realistic in terms of location and temporal characteristics.

A method of analysing biomagnetic signals is presented which focuses attention on activity in a specific region of interest. The method is based on the construction of virtual sensors, corresponding to linear combinations of lead fields that are optimally localized within the region of interest. This method is fast and stable. It is tested against physiologically plausible computer generated signals and also against more elaborate analysis of real data. The results show that the method can be very effective as a fast scanning tool identifying activity from pre-defined regions of interest.

The real-time, single-trial activity in the human auditory cortex was extracted from magnetoencephalographic signals. A predictor of single-trial activity was defined as the sum of the average response and a mean-free base level computed over a range of base times. For simple stimuli the residual (predicted–actual) activity had a stimulus-independent oscillatory (10 Hz) component. This component was larger and more durable in trained subjects, reaching saturation only in the most trained of the five subjects studied (S1). Changes in variability and associated reduction of the absolute value and duration of the oscillations were evident in experiments with stimuli loaded with information, saliency, or task contingency. Repetition reintroduces stimulus-independent oscillations very slowly. For S1, after training, the stimulus-independent oscillations were reestablished in the auditory cortices to the level seen for simple stimuli, except for the time periods and in the hemisphere associated with the combination of task demands and stimulus processing.

Our understanding of the link between electrical events in the brain and behaviour is based on indirect measures. Positron Emission Tomography (PET) and functional Magnetic Resonance Imaging (fMRI) rely on haemodynamic processes which are slower by two to three orders of magnitude than the processes characterizing normal and pathological brain function. Direct invasive measurements of the electrical activity on the other hand produce too local a view which fails to show the large scale coherence which sustains awareness and cognition. On the opposite extreme, gross measures of the electrical activity like Electroencephalography (EEG) and single or few channel Magetoencephalography (MEG) had until recently to rely on simplistic point like models extracted from the averages of many repetitions of physiologically irrelevant stimuli. The introduction of multichannel probes with over 30 channels (Hämälainen et al. 1993), and the use of distributed source analysis (Ioannides et al. 1990a) opened up for the first time the possibility to study the response of single trials. In this work we address directly the question how representative is the description of events extracted from the analysis of the average signal. We use the simplest possible example: the cortical response to a simple 1 kHz tone, focusing on the early and by general admission "automatic" response around 100 ms after stimulus onset. To avoid the confounding inter-subject variability we have studied the responses over the left and right cortical areas to ipsi- and contralateral stimulation in a single subject; for testing reproducibility, we have used both the eyes open and eyes closed conditions. Since the computational demands involved in extracting a full three dimensional description from each trial are too great, we have complemented the distributed source analysis with special techniques, which allow us to scan through each and every single trial and identify each cortical activation similar to the ones picked out in the average signal. We are thus able to show conclusively that the sequence of events suggested by the analysis of the average signal is not representative of what is happening in individual trials. The sequence is made up of events which occurred in different trials reflecting probably the existence of many parallel routes each of which leads from the input at the ear to a final "computation".

Background Identifying eye movement related areas in the frontal lobe has a long history, with microstimulation in monkeys producing the most clear-cut results. For humans, however, there is still no consensus about the location and the extent of the frontal eye field (FEF). There is also no simple non-invasive method for unambiguously defining the FEF in individual subjects, a prerequisite for clinical applications. Here we explore the use of magnetoencephalography (MEG) for the non-invasive identification and characterization of FEF activity in an individual subject. Methods We mapped human brain activity before, during and after saccades by applying tomographic analysis to MEG data. Statistical parametric maps and circular statistics produced plausible FEF loci, but no unambiguous definition for individual subjects. Here we first computed the spectral decomposition and correlation with electrooculogram (EOG) of the tomographic brain activations. For each of these two measures statistical comparisons were made between different saccades. Results In this paper, we first review the frontal cortex activations identified in earlier animal and human studies and place the putative human FEFs in a well-defined anatomical framework. This framework is then used as reference for describing the results of new Fourier analysis of the tomographic solutions comparing active saccade tasks and their controls. The most consistent change in the dorsal frontal cortex was at the putative left FEF, for both saccades to the left and right. The asymmetric result is consistent with the 1-way callosal traffic theory. We also showed that the new correlation analysis had its most consistent change in the contralateral putative FEF. This result was obtained for EOG latencies before saccade onset with delays of a few hundreds of milliseconds (FEF activity leading the EOG) and only for visual cues signaling the execution of a saccade in a previously defined saccade direction. Conclusions The FEF definition derived from microstimulation describes only one of the areas in the dorsal lateral frontal lobe that act together to plan, prepare and execute a saccade. The definition and characterization of these areas in an individual subject can be obtained from non-invasive MEG measurements.