Timing and connectivity in the human somatosensory cortex from single trial mass electrical activity

First activity and interactions in thalamus and cortex using raw single-trial EEG and MEG elicited by somatosensory stimulation

Introduction

One of the primary motivations for studying the human brain is to comprehend how external sensory input is processed and ultimately perceived by the brain. A good understanding of these processes can promote the identification of biomarkers for the diagnosis of various neurological disorders; it can also provide ways of evaluating therapeutic techniques. In this work, we seek the minimal requirements for identifying key stages of activity in the brain elicited by median nerve stimulation.

Methods

We have used a priori knowledge and applied a simple, linear, spatial filter on the electroencephalography and magnetoencephalography signals to identify the early responses in the thalamus and cortex evoked by short electrical stimulation of the median nerve at the wrist. The spatial filter is defined first from the average EEG and MEG signals and then refined using consistency selection rules across ST. The refined spatial filter is then applied to extract the timecourses of each ST in each targeted generator. These ST timecourses are studied through clustering to quantify the ST variability. The nature of ST connectivity between thalamic and cortical generators is then studied within each identified cluster using linear and non-linear algorithms with time delays to extract linked and directional activities. A novel combination of linear and non-linear methods provides in addition discrimination of influences as excitatory or inhibitory.

Results

Our method identifies two key aspects of the evoked response. Firstly, the early onset of activity in the thalamus and the somatosensory cortex, known as the P14 and P20 in EEG and the second M20 for MEG. Secondly, good estimates are obtained for the early timecourse of activity from these two areas. The results confirm the existence of variability in ST brain activations and reveal distinct and novel patterns of connectivity in different clusters.

Discussion

It has been demonstrated that we can extract new insights into stimulus processing without the use of computationally costly source reconstruction techniques which require assumptions and detailed modeling of the brain. Our methodology, thanks to its simplicity and minimal computational requirements, has the potential for real-time applications such as in neurofeedback systems and brain-computer interfaces.

The sequence of cortical activity inferred by response latency variability in the human ventral pathway of face processing

Variability in neuronal response latency has been typically considered caused by random noise. Previous studies of single cells and large neuronal populations have shown that the temporal variability tends to increase along the visual pathway. Inspired by these previous studies, we hypothesized that functional areas at later stages in the visual pathway of face processing would have larger variability in the response latency. To test this hypothesis, we used magnetoencephalographic data collected when subjects were presented with images of human faces. Faces are known to elicit a sequence of activity from the primary visual cortex to the fusiform gyrus. Our results revealed that the fusiform gyrus showed larger variability in the response latency compared to the calcarine fissure. Dynamic and spectral analyses of the latency variability indicated that the response latency in the fusiform gyrus was more variable than in the calcarine fissure between 70 ms and 200 ms after the stimulus onset and between 4 Hz and 40 Hz, respectively. The sequential processing of face information from the calcarine sulcus to the fusiform sulcus was more reliably detected based on sizes of the response variability than instants of the maximal response peaks. With two areas in the ventral visual pathway, we show that the variability in response latency across brain areas can be used to infer the sequence of cortical activity.

Current and Emerging Potential of Magnetoencephalography in the Detection and Localization of High-Frequency Oscillations in Epilepsy

Up to one-third of patients with epilepsy are medically intractable and need resective surgery. To be successful, epilepsy surgery requires a comprehensive preoperative evaluation to define the epileptogenic zone (EZ), the brain area that should be resected to achieve seizure freedom. Due to lack of tools and methods that measure the EZ directly, this area is defined indirectly based on concordant data from a multitude of presurgical non-invasive tests and intracranial recordings. However, the results of these tests are often insufficiently concordant or inconclusive. Thus, the presurgical evaluation of surgical candidates is frequently challenging or unsuccessful. To improve the efficacy of the surgical treatment, there is an overriding need for reliable biomarkers that can delineate the EZ. High-frequency oscillations (HFOs) have emerged over the last decade as new potential biomarkers for the delineation of the EZ. Multiple studies have shown that HFOs are spatially associated with the EZ. Despite the encouraging findings, there are still significant challenges for the translation of HFOs as epileptogenic biomarkers to the clinical practice. One of the major barriers is the difficulty to detect and localize them with non-invasive techniques, such as magnetoencephalography (MEG) or scalp electroencephalography (EEG). Although most literature has studied HFOs using invasive recordings, recent studies have reported the detection and localization of HFOs using MEG or scalp EEG. MEG seems to be particularly advantageous compared to scalp EEG due to its inherent advantages of being less affected by skull conductivity and less susceptible to contamination from muscular activity. The detection and localization of HFOs with MEG would largely expand the clinical utility of these new promising biomarkers to an earlier stage in the diagnostic process and to a wider range of patients with epilepsy. Here, we conduct a thorough critical review of the recent MEG literature that investigates HFOs in patients with epilepsy, summarizing the different methodological approaches and the main findings. Our goal is to highlight the emerging potential of MEG in the non-invasive detection and localization of HFOs for the presurgical evaluation of patients with medically refractory epilepsy (MRE).

Timing of Cortical Events Preceding Voluntary Movement

We studied magnetic signals from the human brain recorded during a second before a self-paced finger movement. Sharp triangular peaks were observed in the averaged signals about 0.7 second before the finger movement. The amplitude of the peaks varied considerably from trial to trial, which indicated that the peaks were concurrent with much longer oscillatory processes. One can cluster trials into distinct groups with characteristic sequences of events. Prominent short trains of pulses in the beta frequency band were identified in the premovement period. This observation suggests that during preparation of the intended movement, cortical activity is well organized in time but differs from trial to trial. Magnetoencephalography can capture these processes with high temporal resolution and allows their study in fine detail.

MEG reveals a fast pathway from somatosensory cortex to occipital areas via posterior parietal cortex in a blind subject

Cross-modal activity in visual cortex of blind subjects has been reported during performance of variety of non-visual tasks. A key unanswered question is through which pathways non-visual inputs are funneled to the visual cortex. Here we used tomographic analysis of single trial magnetoencephalography (MEG) data recorded from one congenitally blind and two sighted subjects after stimulation of the left and right median nerves at three intensities: below sensory threshold, above sensory threshold and above motor threshold; the last sufficient to produce thumb twitching. We identified reproducible brain responses in the primary somatosensory (S1) and motor (M1) cortices at around 20 ms post-stimulus, which were very similar in sighted and blind subjects. Time-frequency analysis revealed strong 45-70 Hz activity at latencies of 20-50 ms in S1 and M1, and posterior parietal cortex Brodmann areas (BA) 7 and 40, which compared to lower frequencies, were substantially more pronounced in the blind than the sighted subjects. Critically, at frequencies from α-band up to 100 Hz we found clear, strong, and widespread responses in the visual cortex of the blind subject, which increased with the intensity of the somatosensory stimuli. Time-delayed mutual information (MI) revealed that in blind subject the stimulus information is funneled from the early somatosensory to visual cortex through posterior parietal BA 7 and 40, projecting first to visual areas V5 and V3, and eventually V1. The flow of information through this pathway occurred in stages characterized by convergence of activations into specific cortical regions. In sighted subjects, no linked activity was found that led from the somatosensory to the visual cortex through any of the studied brain regions. These results provide the first evidence from MEG that in blind subjects, tactile information is routed from primary somatosensory to occipital cortex via the posterior parietal cortex.

Source space analysis of event-related dynamic reorganization of brain networks

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.

Frequency-dependent functional connectivity within resting-state networks: an atlas-based MEG beamformer solution

The brain consists of functional units with more-or-less specific information processing capabilities, yet cognitive functions require the co-ordinated activity of these spatially separated units. Magnetoencephalography (MEG) has the temporal resolution to capture these frequency-dependent interactions, although, due to volume conduction and field spread, spurious estimates may be obtained when functional connectivity is estimated on the basis of the extra-cranial recordings directly. Connectivity estimates on the basis of reconstructed sources may similarly be affected by biases introduced by the source reconstruction approach.

Here we propose an analysis framework to reliably determine functional connectivity that is based around two main ideas: (i) functional connectivity is computed for a set of atlas-based ROIs in anatomical space that covers almost the entire brain, aiding the interpretation of MEG functional connectivity/network studies, as well as the comparison with other modalities; (ii) volume conduction and similar bias effects are removed by using a functional connectivity estimator that is insensitive to these effects, namely the Phase Lag Index (PLI).

Our analysis approach was applied to eyes-closed resting-state MEG data for thirteen healthy participants. We first demonstrate that functional connectivity estimates based on phase coherence, even at the source-level, are biased due to the effects of volume conduction and field spread. In contrast, functional connectivity estimates based on PLI are not affected by these biases. We then looked at mean PLI, or weighted degree, over areas and subjects and found significant mean connectivity in three (alpha, beta, gamma) of the five (including theta and delta) classical frequency bands tested. These frequency-band dependent patterns of resting-state functional connectivity were distinctive; with the alpha and beta band connectivity confined to posterior and sensorimotor areas respectively, and with a generally more dispersed pattern for the gamma band. Generally, these patterns corresponded closely to patterns of relative source power, suggesting that the most active brain regions are also the ones that are most-densely connected.

Our results reveal for the first time, using an analysis framework that enables the reliable characterisation of resting-state dynamics in the human brain, how resting-state networks of functionally connected regions vary in a frequency-dependent manner across the cortex.

BA3b and BA1 activate in a serial fashion after median nerve stimulation: direct evidence from combining source analysis of evoked fields and cytoarchitectonic probabilistic maps

This study combines source analysis imaging data for early somatosensory processing and the probabilistic cytoarchitectonic maps (PCMs). Human somatosensory evoked fields (SEFs) were recorded by stimulating left and right median nerves. Filtering the recorded responses in different frequency ranges identified the most responsive frequency band. The short-latency averaged SEFs were analyzed using a single equivalent current dipole (ECD) model and magnetic field tomography (MFT). The identified foci of activity were superimposed with PCMs. Two major components of opposite polarity were prominent around 21 and 31 ms. A weak component around 25 ms was also identified. For the most responsive frequency band (50-150 Hz) ECD and MFT revealed one focal source at the contralateral Brodmann area 3b (BA3b) at the peak of N20. The component ~25 ms was localised in Brodmann area 1 (BA1) in 50-150 Hz. By using ECD, focal generators around 28-30 ms located initially in BA3b and 2 ms later to BA1. MFT also revealed two focal sources - one in BA3b and one in BA1 for these latencies. Our results provide direct evidence that the earliest cortical response after median nerve stimulation is generated within the contralateral BA3b. BA1 activation few milliseconds later indicates a serial mode of somatosensory processing within cytoarchitectonic SI subdivisions. Analysis of non-invasive magnetoencephalography (MEG) data and the use of PCMs allow unambiguous and quantitative (probabilistic) interpretation of cytoarchitectonic identity of activated areas following median nerve stimulation, even with the simple ECD model, but only when the model fits the data extremely well.

MEG's ability to localise accurately weak transient neural sources

OBJECTIVE

To investigate the accurate localisation of weak, transient, neural sources under conditions of varying difficulty.

METHODS

Multiple dipolar sources placed within a head-shaped phantom at superficial and deep locations were driven separately or simultaneously by a short-lasting current with varied amplitudes. Artificial MEG signals that were very similar to the human High Frequency Oscillations (HFO) were produced. MEG signals of HFO were also recorded from median nerve stimulation. Different inverse techniques were used to localise the phantom dipoles and the human HFO generators.

RESULTS

The human HFO were measured around 200 and 600Hz by using only 120 trials. The 200Hz HFO were localised to BA3b. The superficial phantom's source was localised with an accuracy of 2-3mm by all inverse techniques (120 trials). The 'subcortical' source was localised with an error of approximately 5mm. Localisation of deeper 'thalamic' sources required more trials.

CONCLUSION

MEG can detect and localise weak transient activations and the human HFO with an accuracy of a few mm at cortical and subcortical regions even when a small number of trials are used.

SIGNIFICANCE

Localizing HFO to specific anatomical structures has high clinical utility, for example in epilepsy, where discrete HFO appears to be generated just before focal epileptic activity.

Magnetoencephalography (MEG)

Magnetoencephalography (MEG) encompasses a family of non-contact, non-invasive techniques for detecting the magnetic field generated by the electrical activity of the brain, for analyzing this MEG signal and for using the results to study brain function. The overall purpose of MEG is to extract estimates of the spatiotemporal patterns of electrical activity in the brain from the measured magnetic field outside the head. The electrical activity in the brain is a manifestation of collective neuronal activity and, to a large extent, the currency of brain function. The estimates of brain activity derived from MEG can therefore be used to study mechanisms and processes that support normal brain function in humans and help us understand why, when and how they fail.

Dynamic functional connectivity

Recent studies show that anatomical and functional brain networks exhibit similar small-world properties. However, the networks that are compared often differ in what the nodes represent (e.g. sensors or brain areas), what kind of connectivity is measured, and what temporal and spatial scales are probed. Here, I review studies of large-scale connectivity and recent results from a variety of real-time recording techniques, which together suggest that an adequate description of brain organization requires a hierarchy of networks rather than the single, binary networks that are currently in vogue. Pattern analysis methods now offer a principled way for constructing such network hierarchies. As shown at the end of this review, a correspondence principle can be formulated to guide the interpretation across network levels and to relate nodes to well defined anatomical entities.

Magnetoencephalography as a research tool in neuroscience: state of the art

Magnetoencephalography (MEG) is a noninvasive neuroimaging method for detecting, analyzing, and interpreting the magnetic field generated by the electrical activity in the brain. Modern hardware can capture the MEG signal at hundreds of points around the head in a snapshot lasting only a fraction of a millisecond. The sensitivity of modern hardware is high enough to permit the extraction of a clean signal generated by the brain well above the noise level of the MEG hardware. It is possible to identify signatures of superficial and often deep generators in the raw MEG signal, even in snapshots of data. In a more quantitative way, tomographic images of the electrical current density in the brain can be extracted from each snapshot of MEG signal, providing a direct correlate of coherent collective neuronal activity. A number of recent studies have scrutinized brain function in the new spatiotemporal window that real-time tomographic analysis of MEG signals has opened. The results have allowed the variability in a single area to be seen in the context of activity in other areas and background rhythmic activity. In this view, normal brain function is seen as a cascade of extremely fast events and the unfolding of specialized processes, segregated in space and time and organized into well-defined stages of processing.

Posing for success: clenching a fist facilitates approach

A clenched fist is a gesture often seen both within and outside sports that seems to communicate success or to function in self-encouragement or the encouragement of others. This "encouragement gesture" involves the contraction of forearm flexors, similar to the grasping action that is part of acquisitive approach actions. This gesture may be part of a physiological feedback mechanism that functions to increase or sustain levels of approach in challenging situations by signaling the sufficiency of resources (muscle strength). Here we show that for pleasant but not unpleasant words, subjects were faster in categorizing words while contracting their forearm flexors rather than their forearm tensors. This effect dissipated during the first minute of performance, which may reflect habituation of interoceptive feedback. The data further suggest that the effect is larger when experimenter and subject are of opposite sexes. The facilitated responding to pleasant stimuli suggests that contraction of the forearm flexors promotes approach.

Magnetoencephalographic study of vibrotactile evoked transient and steady-state responses in human somatosensory cortex

Somatosensory responses to vibrotactile stimulation applied to the index fingertip were recorded with whole-head MEG in eleven healthy young adult participants. Stimulus trains were produced by a pneumatically driven membrane oscillating at 22 Hz for a trial duration of 1 s, separated by interstimulus intervals (ISIs) of 0.5, 1.0, 3.0, and 7.0 s. Data analysis was performed in two frequency bands. Transient onset responses in the lower frequency band (<20 Hz) contained a clearly expressed P50 component. The higher frequency band (18-30 Hz) revealed a gamma-band response (GBR) within the first 200 ms followed by rhythmic activity at the stimulus frequency that continued throughout the stimulus duration, known as the steady-state response (SSR). Dipoles associated with the transient responses and SSRs were localized in two distinct regions within the primary somatosensory cortex (SI), with transient responses located on average 3 mm more medial and inferior than the SSRs. The transient and GBR peak amplitudes increased with ISI, whereas the SSR amplitude showed no ISI dependence. These results may reflect functionally and spatially distinct neural populations. Further investigations are required to assess the implications of these findings for probing the somatosensory system using other functional neuroimaging methods such as fMRI.

Clustering of early cortical responses to median nerve stimulation from average and single trial MEG and EEG signals

Median nerve electrical stimulation (MNES) produces early and strong averaged magnetoencephalography (MEG) or electroencephalography (EEG) signals, despite considerable single trial (ST) variability, demonstrated in separate MEG and EEG studies. Here, simultaneous MEG/EEG recordings are used to assess whether same or different aspects of ST variability are influencing EEG and MEG. Clustering techniques provided groupings for the ST timeseries for cortical responses to MNES derived from one modality. These groupings were applied to the corresponding ST timeseries derived from the other modality to quantify the similarity in variability captured by MEG and EEG signals. Estimates of early cortical activity elicited by MNES derived from MEG and EEG signals were very similar, provided ongoing mu rhythm was removed. Similarity between EEG and MEG estimates included both results based on average signals and measures of ST variability. Either MEG or EEG can provide a robust measure of the early cortical activity elicited by MNES as well as of its variability. Reliable indices of early cortical responses to MNES can be derived from either MEG or EEG data. These indices can be based on average signals, as is routinely done with clinical EEG, but it could also rely on hitherto little utilized measures of ST variability.

Time-efficient localization of the human secondary somatosensory cortex by functional magnetic resonance imaging

Standardized, robust and time-efficient localization of the human secondary somatosensory cortex (S2) is a challenge in clinical blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI). A fully automated tactile stimulation was optimized in seven right-handed volunteers at 1.5 T for minimum scan time, high BOLD signals and robust localization of S2 by systematically varying the applied block-design. All volunteers had six different fMRI measurements of five stimulation-baseline-cycles (sbc) each with equal block duration that was changed between the measurements from 6 s to 30 s. Additional data sets of 4, 3 and 2 cycles were generated post hoc resulting in a total of 168 data sets that were evaluated individually for BOLD-signal intensity (dS%), correlation to the hemodynamic reference function (r) and Euclidean coordinates (x, y, z). Using different block-designs the S2 activation was highly variable regarding the localization rate (lr), the hemispheric symmetry and the BOLD-signals. The protocol with 3 cycles, a block duration (dp) of 15 s and a total scan time (dt) of 105 s most robustly localized S2 (contralateral: lr=71.4%, r=0.65, dS=1.01%; ipsilateral: lr=100%, r=0.6, dS=1.14%) whereas the most time-efficient protocol to localize SI (sbc=5, dp=6 s, dt=66 s) provided no robust localization of S2. Compared to other published fMRI protocols a scan time reduction up to 86% was achieved.

Assessing linear time-invariance in human primary somatosensory cortex with BOLD fMRI using vibrotactile stimuli

The assumption of linear time-invariance (LTI) in the human primary somatosensory cortex (SI) is assessed for fMRI signals generated by variable-duration vibrotactile stimuli. Predictions based on time-shifted summation (TSS) of responses to 2 s stimuli overestimate observed BOLD signal amplitudes in response to longer-duration stimuli, in agreement with previous findings in other primary sensory cortices. To interpret these results, we undertook an alternative approach for LTI assessment by characterizing BOLD signals using two biophysical models. The first model assumes that the input stimulus envelope is proportional to neural activity. The second assumes that neural activity exhibits both transient and steady-state components, consistent with extensive electrophysiological data, and fits the experimental data better. Although nonlinearity remains evident for short stimulus durations, the latter model shows that the TSS procedure to assess LTI overestimates the BOLD signal because the temporal characteristics of neural activity have not been considered adequately. Further research to investigate the BOLD response to time-varying neural activity is required.

The human primary somatosensory cortex response contains components related to stimulus frequency and perception in a frequency discrimination task

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.

Single-trial variability in early visual neuromagnetic responses: an explorative study based on the regional activation contributing to the N70m peak

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.

Surface visualization of electromagnetic brain activity

Advances in hardware and software have made possible the reconstruction of brain activity from non-invasive electrophysiological measurements over a large part of the brain. The appreciation of the information content in the data is enhanced when relevant anatomical detail is also available for visualization. Different neuroscientific questions give rise to different requirements for optimal superposition of structure and function. Most available software deal with scalar measures of activity, especially hemodynamic changes. In contrast, the electrophysiological observables are generated by electrical activity, which depends on the synchrony of neuronal assemblies and the geometry of the local cortical surface. We describe methods for segmentation and visualization of spatio-temporal brain activity, which allow the interplay of geometry and scalar as well as vector properties of the current density directly in the representations. The utility of these methods is demonstrated through displays of tomographic reconstructions of early sensory processing in the somatosensory and visual modality extracted from magnetoencephalography (MEG) data. The activation course characteristic to a specific area could be observed as current density or statistical maps independently and/or contrasted to the activity in other areas or the whole brain. MEG and functional magnetic resonance imaging (fMRI) activations were simultaneously visualized. Integrating and visualizing complementary functional data into a single environment helps evaluating analysis and understanding structure/function relationships in normal and diseased brain.

Consistent and precise localization of brain activity in human primary visual cortex by MEG and fMRI

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.

Semantic geodesic maps: a unifying geometrical approach for studying the structure and dynamics of single trial evoked responses

OBJECTIVES

A general framework for identifying and describing structure in a given sample of evoked response single-trial signals (STs) is introduced. The approach is based on conceptually simple geometrical ideas and enables the convergence of pattern analysis and non-linear time series analysis.

METHODS

Classical steps for analyzing the STs by waveform are first employed and the ST-analysis is transferred to a multidimensional space, the feature space, the geometry of which is systematically studied via multidimensional scaling (MDS) techniques giving rise to semantic maps. The structure in the feature space characterizes the trial-to-trial variability and this is utilized to probe functional connectivity between two brain areas. The underlying dynamic process responsible for the emerged structure can be described by a multidimensional trajectory in the feature space. This in turn enables the detection of dynamical interareal coupling as similarity between the corresponding trajectories.

RESULTS AND CONCLUSIONS

The utility of semantic maps was demonstrated using magnetoencephalographic data from a simple auditory paradigm. The coupling of ongoing activity and evoked response is vividly demonstrated and contrasted with the apparent deflection from zero baseline that survives averaging. Prototypes are easily identified as the end points of distinct paths in the semantic map representation, and their neighborhood is populated by STs with distinct properties not only in the latencies where the evoked response is expected to be strong, but also and very significantly in the prestimulus period. Finally our results provide evidence for interhemispheric binding in the (4-8 Hz) range and dynamical coupling at faster time scales.