Neuromagnetic Recordings Research Articles

Artificial embodiment displaces cortical neuromagnetic somatosensory responses

Integrating artificial limbs as part of one's body involves complex neuroplastic changes resulting from various sensory inputs. While somatosensory feedback is crucial, plastic processes that enable embodiment remain unknown. We investigated this using somatosensory evoked fields (SEFs) in the primary somatosensory cortex (S1) following the Rubber Hand Illusion (RHI), known to quickly induce artificial limb embodiment. During electrical stimulation of the little finger and thumb, 19 adults underwent neuromagnetic recordings before and after the RHI. We found early SEF displacement, including an illusion-brain correlation between extent of embodiment and specific changes to the first cortical response at 20 ms in Area 3b, within S1. Furthermore, we observed a posteriorly directed displacement at 35 ms towards Area 1, known to be important for visual integration during touch perception. That this second displacement was unrelated to extent of embodiment implies a functional distinction between neuroplastic changes of these components and areas. The earlier shift in Area 3b may shape extent of limb ownership, while subsequent displacement into Area 1 may relate to early visual-tactile integration that initiates embodiment. Here we provide evidence for multiple neuroplastic processes in S1—lasting beyond the illusion—supporting integration of artificial limbs like prostheses within the body representation.

Localization accuracy of a common beamformer for the comparison of two conditions

The linearly constrained minimum variance beamformer is frequently used to reconstruct sources underpinning neuromagnetic recordings. When reconstructions must be compared across conditions, it is considered good practice to use a single, “common” beamformer estimated from all the data at once. This is to ensure that differences between conditions are not ascribable to differences in beamformer weights. Here, we investigate the localization accuracy of such a common beamformer. Based on theoretical derivations, we first show that the common beamformer leads to localization errors in source reconstruction. We then turn to simulations in which we attempt to reconstruct a (genuine) source in a first condition, while considering a second condition in which there is an (interfering) source elsewhere in the brain. We estimate maps of mislocalization and assess statistically the difference between “standard” and “common” beamformers. We complement our findings with an application to experimental MEG data. The results show that the common beamformer may yield significant mislocalization. Specifically, the common beamformer may force the genuine source to be reconstructed closer to the interfering source than it really is. As the same applies to the reconstruction of the interfering source, both sources are pulled closer together than they are. This observation was further illustrated in experimental data. Thus, although the common beamformer allows for the comparison of conditions, in some circumstances it introduces localization inaccuracies. We recommend alternative approaches to the general problem of comparing conditions.

A Tactile Virtual Reality for the Study of Active Somatosensation.

Natural exploration of textures involves active sensing, i.e., voluntary movements of tactile sensors (e.g., human fingertips or rodent whiskers) across a target surface. Somatosensory input during moving tactile sensors varies according to both the movement and the surface texture. Combining motor and sensory information, the brain is capable of extracting textural features of the explored surface. Despite the ecological relevance of active sensing, psychophysical studies on active touch are largely missing. One reason for the lack of informative studies investigating active touch is the considerable challenge of assembling an appropriate experimental setup. A possible solution might be in the realm of virtual tactile reality that provides tactile finger stimulation depending on the position of the hand and the simulated texture of a target surface. In addition to rigorous behavioral studies, the investigation of the neuronal mechanisms of active tactile sensing in humans is highly warranted, requiring neurophysiological experiments using electroencephalography (EEG), magnetoencephalography (MEG) and/or functional magnetic resonance imaging (fMRI). However, current neuroimaging techniques impose specific requirements on the tactile stimulus delivery equipment in terms of compatibility with the neurophysiological methods being used. Here, we present a user-friendly, MEG compatible, tactile virtual reality simulator. The simulator consists of a piezo-electric tactile stimulator capable of independently protruding 16 plastic pistons of 1 mm diameter arranged in a 4 × 4 matrix. The stimulator delivers a spatial pattern of tactile stimuli to the tip of a finger depending on the position of the finger moving across a 2-dimensional plane. In order to demonstrate the functionality of the tactile virtual reality, we determined participants’ detection thresholds in active and passive touch conditions. Thresholds in both conditions were higher than reported in the literature. It could well be that the processing of the piston-related stimulation was masked by the sensory input generated by placing the finger on the scanning probe. More so, the thresholds for both the active and passive tasks did not differ significantly. In further studies, the noise introduced by the stimulator in neuromagnetic recordings was quantified and somatosensory evoked fields for active and passive touch were recorded. Due to the compatibility of the stimulator with neuroimaging techniques such as MEG, and based on the feasibility to record somatosensory-related neuromagnetic brain activity the apparatus has immense potential for the exploration of the neural underpinnings of active tactile perception.

Objective assessment of automatic language comprehension mechanisms in the brain: Novel E/MEG paradigm.

Assessing the brain activity related to language comprehension is required in a range of situations. Particularly in cases when subjects' cooperation with instructions cannot be guaranteed (e.g., in neurological patients), a protocol is needed that could be independent from attention and behavioral tasks. In this study, we aimed at designing a novel approach for neuromagnetic recordings of brain activity which could allow for probing the neural foundations underpinning three key levels of speech comprehension: lexical, semantic, and (morpho)syntactic, without requiring active attention on speech input or any active task, while keeping the recording session duration as short as possible. To this end, we designed two different auditory paradigms using the same set of single word-based lexical, semantic, and syntactic contrasts: a modified version of the multifeature oddball paradigm and an equiprobable design. Combined magnetoencephalography/electroencephalography data were recorded form young, healthy participants, presented with these stimuli while watching a silent movie. Data from the equiprobable design yielded significant activations in temporal and inferior frontal areas associated with the lexical, semantic, and morphosyntactic contrasts. In turn, neural dissociations observed in the multifeature paradigm emerged mainly in temporal cortices, and were confined to the lexical and semantic conditions with a striking lack of any statistically significant effects for syntactic violations. Our findings indicate that, by employing the equiprobable design, a comprehensive range of key linguistic processes could be assessed in a passive, attention-free manner within a relatively short time (here, ~27min), thus making this paradigm a time-efficient and patient-friendly tool.

How to Build a Functional Connectomic Biomarker for Mild Cognitive Impairment From Source Reconstructed MEG Resting-State Activity: The Combination of ROI Representation and Connectivity Estimator Matters.

Our work aimed to demonstrate the combination of machine learning and graph theory for the designing of a connectomic biomarker for mild cognitive impairment (MCI) subjects using eyes-closed neuromagnetic recordings. The whole analysis based on source-reconstructed neuromagnetic activity. As ROI representation, we employed the principal component analysis (PCA) and centroid approaches. As representative bi-variate connectivity estimators for the estimation of intra and cross-frequency interactions, we adopted the phase locking value (PLV), the imaginary part (iPLV) and the correlation of the envelope (CorrEnv). Both intra and cross-frequency interactions (CFC) have been estimated with the three connectivity estimators within the seven frequency bands (intra-frequency) and in pairs (CFC), correspondingly. We demonstrated how different versions of functional connectivity graphs single-layer (SL-FCG) and multi-layer (ML-FCG) can give us a different view of the functional interactions across the brain areas. Finally, we applied machine learning techniques with main scope to build a reliable connectomic biomarker by analyzing both SL-FCG and ML-FCG in two different options: as a whole unit using a tensorial extraction algorithm and as single pair-wise coupling estimations. We concluded that edge-weighed feature selection strategy outperformed the tensorial treatment of SL-FCG and ML-FCG. The highest classification performance was obtained with the centroid ROI representation and edge-weighted analysis of the SL-FCG reaching the 98% for the CorrEnv in α1:α2 and 94% for the iPLV in α2. Classification performance based on the multi-layer participation coefficient, a multiplexity index reached 52% for iPLV and 52% for CorrEnv. Selected functional connections that build the multivariate connectomic biomarker in the edge-weighted scenario are located in default-mode, fronto-parietal, and cingulo-opercular network. Our analysis supports the notion of analyzing FCG simultaneously in intra and cross-frequency whole brain interactions with various connectivity estimators in beamformed recordings.

Aberrant resting-state functional brain networks in dyslexia: Symbolic mutual information analysis of neuromagnetic signals

Neuroimaging studies have identified a variety of structural and functional connectivity abnormalities in students experiencing reading difficulties. The present study adopted a novel approach to assess the dynamics of resting-state neuromagnetic recordings in the form of symbolic sequences (i.e., repeated patterns of neuromagnetic fluctuations within and/or between sensors).Participants were 25 students experiencing severe reading difficulties (RD) and 27 age-matched non-impaired readers (NI) aged 7–14 years. Sensor-level data were first represented as symbolic sequences in eight conventional frequency bands. Next, dominant types of sensor-to-sensor interactions in the form of intra and cross-frequency coupling were computed and subjected to graph modeling to assess group differences in global network characteristics.As a group RD students displayed predominantly within-frequency interactions between neighboring sensors which may reflect reduced overall global network efficiency and cost-efficiency of information transfer. In contrast, sensor networks among NI students featured a higher proportion of cross-frequency interactions. Brain-reading achievement associations highlighted the role of left hemisphere temporo-parietal functional networks, at rest, for reading acquisition and ability.

Data-Driven Topological Filtering Based on Orthogonal Minimal Spanning Trees: Application to Multigroup Magnetoencephalography Resting-State Connectivity.

In the present study, a novel data-driven topological filtering technique is introduced to derive the backbone of functional brain networks relying on orthogonal minimal spanning trees (OMSTs). The method aims to identify the essential functional connections to ensure optimal information flow via the objective criterion of global efficiency minus the cost of surviving connections. The OMST technique was applied to multichannel, resting-state neuromagnetic recordings from four groups of participants: healthy adults (n = 50), adults who have suffered mild traumatic brain injury (n = 30), typically developing children (n = 27), and reading-disabled children (n = 25). Weighted interactions between network nodes (sensors) were computed using an integrated approach of dominant intrinsic coupling modes based on two alternative metrics (symbolic mutual information and phase lag index), resulting in excellent discrimination of individual cases according to their group membership. Classification results using OMST-derived functional networks were clearly superior to results using either relative power spectrum features or functional networks derived through the conventional minimal spanning tree algorithm.

Attention to Color Sharpens Neural Population Tuning via Feedback Processing in the Human Visual Cortex Hierarchy.

Attention can facilitate the selection of elementary object features such as color, orientation, or motion. This is referred to as feature-based attention and it is commonly attributed to a modulation of the gain and tuning of feature-selective units in visual cortex. Although gain mechanisms are well characterized, little is known about the cortical processes underlying the sharpening of feature selectivity. Here, we show with high-resolution magnetoencephalography in human observers (men and women) that sharpened selectivity for a particular color arises from feedback processing in the human visual cortex hierarchy. To assess color selectivity, we analyze the response to a color probe that varies in color distance from an attended color target. We find that attention causes an initial gain enhancement in anterior ventral extrastriate cortex that is coarsely selective for the target color and transitions within ∼100 ms into a sharper tuned profile in more posterior ventral occipital cortex. We conclude that attention sharpens selectivity over time by attenuating the response at lower levels of the cortical hierarchy to color values neighboring the target in color space. These observations support computational models proposing that attention tunes feature selectivity in visual cortex through backward-propagating attenuation of units less tuned to the target.SIGNIFICANCE STATEMENT Whether searching for your car, a particular item of clothing, or just obeying traffic lights, in everyday life, we must select items based on color. But how does attention allow us to select a specific color? Here, we use high spatiotemporal resolution neuromagnetic recordings to examine how color selectivity emerges in the human brain. We find that color selectivity evolves as a coarse to fine process from higher to lower levels within the visual cortex hierarchy. Our observations support computational models proposing that feature selectivity increases over time by attenuating the responses of less-selective cells in lower-level brain areas. These data emphasize that color perception involves multiple areas across a hierarchy of regions, interacting with each other in a complex, recursive manner.

Greater Repertoire and Temporal Variability of Cross-Frequency Coupling (CFC) Modes in Resting-State Neuromagnetic Recordings among Children with Reading Difficulties.

Cross-frequency, phase-to-amplitude coupling (PAC) between neuronal oscillations at rest may serve as the substrate that supports information exchange between functionally specialized neuronal populations both within and between cortical regions. The study utilizes novel algorithms to identify prominent instantaneous modes of cross-frequency coupling and their temporal stability in resting state magnetoencephalography (MEG) data from 25 students experiencing severe reading difficulties (RD) and 27 age-matched non-impaired readers (NI). Phase coherence estimates were computed in order to identify the prominent mode of PAC interaction for each sensor, sensor pair, and pair of frequency bands (from δ to γ) at successive time windows of the continuous MEG record. The degree of variability in the characteristic frequency-pair PACf1−f2 modes over time was also estimated. Results revealed a wider repertoire of prominent PAC interactions in RD as compared to NI students, suggesting an altered functional substrate for information exchange between neuronal assemblies in the former group. Moreover, RD students showed significant variability in PAC modes over time. This temporal instability of PAC values was particularly prominent: (a) within and between right hemisphere temporo-parietal and occipito-temporal sensors and, (b) between left hemisphere frontal, temporal, and occipito-temporal sensors and corresponding right hemisphere sites. Altered modes of neuronal population coupling may help account for extant data revealing reduced, task-related neurophysiological and hemodynamic activation in left hemisphere regions involved in the reading network in RD. Moreover, the spatial distribution of pronounced instability of cross-frequency coupling modes in this group may provide an explanation for previous reports suggesting the presence of inefficient compensatory mechanisms to support reading.

Task-sensitive reconfiguration of corticocortical 6-20 Hz oscillatory coherence in naturalistic human performance.

Electrophysiological oscillatory coherence between brain regions has been proposed to facilitate functional long‐range connectivity within neurocognitive networks. This notion is supported by intracortical recordings of coherence in singled‐out corticocortical connections in the primate cortex. However, the manner in which this operational principle manifests in the task‐sensitive connectivity that supports human naturalistic performance remains undercharacterized. Here, we demonstrate task‐sensitive reconfiguration of global patterns of coherent connectivity in association with a set of easier and more demanding naturalistic tasks, ranging from picture comparison to speech comprehension and object manipulation. Based on whole‐cortex neuromagnetic recording in healthy behaving individuals, the task‐sensitive component of long‐range corticocortical coherence was mapped at spectrally narrow‐band oscillatory frequencies between 6 and 20 Hz (theta to alpha and low‐beta bands). This data‐driven cortical mapping unveiled markedly distinct and topologically task‐relevant spatiospectral connectivity patterns for the different tasks. The results demonstrate semistable oscillatory states relevant for neurocognitive processing. The present findings decisively link human behavior to corticocortical coherence at oscillatory frequencies that are widely thought to convey long‐range, feedback‐type neural interaction in cortical functional networks. Hum Brain Mapp 36:2455–2469, 2015. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc..

Predicting the Semantic Category of Internally Generated Words from Neuromagnetic Recordings

In this study, we explore the possibility to predict the semantic category of words from brain signals in a free word generation task. Participants produced single words from different semantic categories in a modified semantic fluency task. A Bayesian logistic regression classifier was trained to predict the semantic category of words from single-trial MEG data. Significant classification accuracies were achieved using sensor-level MEG time series at the time interval of conceptual preparation. Semantic category prediction was also possible using source-reconstructed time series, based on minimum norm estimates of cortical activity. Brain regions that contributed most to classification on the source level were identified. These were the left inferior frontal gyrus, left middle frontal gyrus, and left posterior middle temporal gyrus. Additionally, the temporal dynamics of brain activity underlying the semantic preparation during word generation was explored. These results provide important insights about central aspects of language production.

The emerging perceptual representation of faces decoded from human neuromagnetic recordings.

Event Abstract Back to Event The emerging perceptual representation of faces decoded from human neuromagnetic recordings. Thomas Carlson1* and Steven Dakin2 1 Macquarie University, Cognitive Sciences, Australia 2 University College London, U.K. As highly social creatures, face perception is essential to daily human life. From the moment we turn our gaze to an individual, our brain begins to form a perceptual representation of the individual's face to promote recognition and ultimately guide our social interactions. In the present study we used a generative model of face perception, human behaviour, and a magnetoencephalography (MEG) decoding approach to study when and how the brain constructs a perceptual representation of a face. We first generated 18 individual face exemplars using a generative model of face perception that encodes faces using a range of metric features, e.g. eye width. In a behavioural experiment, we then measured the human capacity to discriminate faces for all possible pairwise comparisons between face exemplars. The behavioural data was then used to estimate a perceptual geometry of the face stimuli, which is described quantitatively in a dissimilarity matrix (DSM). Next, in a MEG experiment, we used a sliding window decoding approach to measure the neural discriminability between the face stimuli as a function of time (100Hz temporal resolution). The decoding analysis produced a set of time varying DSMs, which describe the brain's emerging representational geometry of the stimuli. To determine when the brain forms a perceptual representation of a face, we compared the perceptual geometry (from behaviour) to the time varying representational geometry of the stimuli in the brain. Our analysis found a significant correspondence between perception and the brain's representation 80ms after stimulus onset that peaked at 100ms. Our results show that the brain rapidly constructs a perceptual representation of a face; and the extremely short latency further suggests this representation is constructed using feed forward mechanisms. This early (fast) representation might underlie our capacity to rapidly recognize individuals and their emotional state, and to guide social interactions. Keywords: MEG, Decoding, face perception, social perception, multivariate pattern analysis Conference: XII International Conference on Cognitive Neuroscience (ICON-XII), Brisbane, Queensland, Australia, 27 Jul - 31 Jul, 2014. Presentation Type: Oral Presentation Topic: Sensation and Perception Citation: Carlson T and Dakin S (2015). The emerging perceptual representation of faces decoded from human neuromagnetic recordings.. Conference Abstract: XII International Conference on Cognitive Neuroscience (ICON-XII). doi: 10.3389/conf.fnhum.2015.217.00001 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 19 Feb 2015; Published Online: 24 Apr 2015. * Correspondence: Dr. Thomas Carlson, Macquarie University, Cognitive Sciences, Sydney, Australia, thomas.carlson@mq.edu.au Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Thomas Carlson Steven Dakin Google Thomas Carlson Steven Dakin Google Scholar Thomas Carlson Steven Dakin PubMed Thomas Carlson Steven Dakin Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.

Artemis 123: development of a whole-head infant and young child MEG system

Background: A major motivation in designing the new infant and child magnetoencephalography (MEG) system described in this manuscript is the premise that electrophysiological signatures (resting activity and evoked responses) may serve as biomarkers of neurodevelopmental disorders, with neuronal abnormalities in conditions such as autism spectrum disorder (ASD) potentially detectable early in development. Whole-head MEG systems are generally optimized/sized for adults. Since magnetic field produced by neuronal currents decreases as a function of distance2 and infants and young children have smaller head sizes (and thus increased brain-to-sensor distance), whole-head adult MEG systems do not provide optimal signal-to-noise in younger individuals. This spurred development of a whole-head infant and young child MEG system – Artemis 123.Methods:In addition to describing the design of the Artemis 123, the focus of this manuscript is the use of Artemis 123 to obtain auditory evoked neuromagnetic recordings and resting-state data in young children. Data were collected from a 14-month-old female, an 18-month-old female, and a 48-month-old male. Phantom data are also provided to show localization accuracy.Results:Examination of Artemis 123 auditory data showed generalizability and reproducibility, with auditory responses observed in all participants. The auditory MEG measures were also found to be manipulable, exhibiting sensitivity to tone frequency. Furthermore, there appeared to be a predictable sensitivity of evoked components to development, with latencies decreasing with age. Examination of resting-state data showed characteristic oscillatory activity. Finally, phantom data showed that dipole sources could be localized with an error less than 0.5 cm.Conclusions:Artemis 123 allows efficient recording of high-quality whole-head MEG in infants four years and younger. Future work will involve examining the feasibility of obtaining somatosensory and visual recordings in similar-age children as well as obtaining recordings from younger infants. Thus, the Artemis 123 offers the promise of detecting earlier diagnostic signatures in such neurodevelopmental disorders.

Representational dynamics of object vision: The first 1000 ms

Human object recognition is remarkably efficient. In recent years, significant advancements have been made in our understanding of how the brain represents visual objects and organizes them into categories. Recent studies using pattern analyses methods have characterized a representational space of objects in human and primate inferior temporal cortex in which object exemplars are discriminable and cluster according to category (e.g., faces and bodies). In the present study we examined how category structure in object representations emerges in the first 1000 ms of visual processing. In the study, participants viewed 24 object exemplars with a planned categorical structure comprised of four levels ranging from highly specific (individual exemplars) to highly abstract (animate vs. inanimate), while their brain activity was recorded with magnetoencephalography (MEG). We used a sliding time window decoding approach to decode the exemplar and the exemplar's category that participants were viewing on a moment-to-moment basis. We found exemplar and category membership could be decoded from the neuromagnetic recordings shortly after stimulus onset (<100 ms) with peak decodability following thereafter. Latencies for peak decodability varied systematically with the level of category abstraction with more abstract categories emerging later, indicating that the brain hierarchically constructs category representations. In addition, we examined the stationarity of patterns of activity in the brain that encode object category information and show these patterns vary over time, suggesting the brain might use flexible time varying codes to represent visual object categories.

Clinical Application of Neuromagnetic Recordings: From Functional Imaging to Neural Decoding

Magnetoencephalography (MEG) measures very weak neuromagnetic signals using SQUID sensors. Standard MEG analyses include averaged waveforms, isofield maps and equivalent current dipoles. Beamforming MEG analyses provide us with frequency-dependent spatiotemporal information about the cerebral oscillatory changes related to not only somatosensory processing but also language processing. Language dominance is able to be evaluated using laterality of power attenuation in the low γ band in the frontal area. Neuromagnetic signals of the unilateral upper movements are able to be decoded using a support vector machine. key words: magnetoencephalography, oscillation, neuroimaging, beamformer, neural decoding

Adaptive changes in the neuromagnetic response of the primary and association somatosensory areas following repetitive tactile hand stimulation in humans

Cortical adaptation in the primary somatosensory cortex (SI) has been probed using different stimulation modalities and recording techniques, in both human and animal studies. In contrast, considerably less knowledge has been gained about the adaptation profiles in other areas of the cortical somatosensory network. Using magnetoencephalography (MEG), we examined the patterns of short-term adaptation for evoked responses in SI and somatosensory association areas during tactile stimulation applied to the glabrous skin of the hand. Cutaneous stimuli were delivered as trains of serial pulses with a constant frequency of 2 Hz and 4 Hz in separate runs, and a constant inter-train interval of 5 s. The unilateral stimuli elicited transient responses to the serial pulses in the train, with several response components that were separated by independent component analysis. Subsequent source reconstruction techniques identified regional generators in the contralateral SI and somatosensory association areas in the posterior parietal cortex (PPC). Activity in the bilateral secondary somatosensory cortex (i.e., SII/PV) was also identified, although less consistently across subjects. The dynamics of the evoked activity in each area and the frequency-dependent adaptation effects were assessed from the changes in the relative amplitude of serial responses in each train. We show that the adaptation profiles in SI and PPC areas can be quantitatively characterized from neuromagnetic recordings using tactile stimulation, with the sensitivity to repetitive stimulation increasing from SI to PPC. A similar approach for SII/PV has proven less straightforward, potentially due to the tendency of these areas to respond selectively to certain stimuli.

Diagnosis of incomplete conduction block of spinal cord from skin surface using spinal cord evoked magnetic fields

BackgroundWe previously reported the usefulness of neuromagnetic recordings for the diagnosis of disorders in peripheral nerves or the spinal cord. However, there have been no reports on incomplete conduction block of the spinal cord, which is clinically common in conditions such as cervical myelopathy. Here, we estimated the usefulness of measuring spinal cord evoked magnetic fi elds for evaluating incomplete conduction block. MethodsIncomplete conduction block models of the spinal cord of the rabbit were established using a Fogarty balloon catheter that was inserted into the epidural space of the cervical spine. Electrical stimuli were applied to the lower thoracic spinal cord with an epidural catheter electrode. Spinal cord evoked potentials were recorded using epidural electrodes. Spinal cord evoked magnetic fi elds were recorded over the skin surface of the neck using a biomagnetometer. ResultsThe decrease in the conduction velocity and amplitude at the compression site could be detected by spinal cord evoked potentials from the epidural space, confi rming the spinal cord lesion. The waveforms of the magnetic fi elds showed a biphasic confi guration. The distribution of magnetic fi elds showed a characteristic quadrupolar pattern propagating from caudal to cranial. After compression, the amplitude and the conduction velocity of the magnetic fi elds decreased, and the distribution of magnetic fi elds were attenuated and decelerated near the compression site especially in the trailing magnetic fi elds. Diagnosis of the incomplete conduction block was thus possible. ConclusionsWe report the fi rst measurement of the spinal cord evoked magnetic fi eld in the intact spinal cord from the skin surface and that it can be applied to incomplete conduction block of the injured spinal cord. The use of a biomagnetometer is promising as a less-invasive method for clinically evaluating spinal cord function.

The brain in time: insights from neuromagnetic recordings

The millisecond time resolution of magnetoencephalography (MEG) is instrumental for investigating the brain basis of sensory processing, motor planning, cognition, and social interaction. We review the basic principles, recent progress, and future potential of MEG in noninvasive tracking of human brain activity. Cortical activation sequences from tens to hundreds of milliseconds can be followed during, e.g., perception, motor action, imitation, and language processing by recording both spontaneous and evoked brain signals. Moreover, tagging of sensory input can be used to reveal neuronal mechanisms of binaural interaction and perception of ambiguous images. The results support the emerging ideas of multiple, hierarchically organized temporal scales in human brain function. Instrumentation and data analysis methods are rapidly progressing, enabling attempts to decode the four-dimensional spatiotemporal signal patterns to reveal correlates of behavior and mental contents.

The spatial profile of the focus of attention in visual search: Insights from MEG recordings

The spatial focus of attention has been suggested to resemble a spotlight, a zoom-lens, a simple gradient, or even a more complex center–surround profile. Here we review evidence from neuromagnetic recordings indicating that the spatial profile is not fixed but depends on the particular perceptual demands of the attention task. We show that visual search requiring spatial scrutiny for target discrimination produces a zone of neural attenuation in the target’s immediate surround, whereas search permitting target discrimination without spatial scrutiny is associated with a simple gradient. We provide new evidence indicating that increasing the demands on target discrimination without changing the spatial scale of discrimination does not influence surround attenuation, and that surround attenuation is also not influenced by the type of features involved in forward processing, that is whether the target location is defined by color or luminance contrast in visual search. An assessment of the time-course of attentional selection reveals that, when present, surround attenuation onsets with a substantial delay relative to the initial feed-forward sweep of processing in the visual system. The reported observations together suggest that the more complex center–surround profile arises as a consequence of top-down attentional selection in the visual system. The reviewed neuromagnetic evidence is discussed with respect to key notions of the Selective Tuning model of visual attention for which strong support is provided.

Cortical dynamics of selective attention to somatosensory events

Recent studies have shown evidence of somatosensory deficits in individuals with attentional difficulties yet relatively little is known about the role of attention in the processing of somatosensory input. Neuromagnetic imaging studies have shown that rhythmic oscillations within the human somatosensory cortex are strongly modulated by somatosensory stimulation and may reflect the normal processing of such stimuli. However, few studies have examined how attention influences these cortical oscillations. We examined attentional effects on human somatosensory oscillations during median nerve stimulation by conducting time–frequency analyses of neuromagnetic recordings in healthy adults. We found that selective attention modulated somatosensory oscillations in the alpha, beta, and gamma bands that were both phase-locked and non-phase-locked to the stimulus. In the primary somatosensory cortex (SI), directing the subject's attention toward the somatosensory stimulus resulted in increased gamma band power (30–55 Hz) that was phase-locked to stimulus onset. Directed attention also produced an initial suppression (desynchrony) followed by enhancement (synchrony) of beta band power (13–25 Hz) that was not phase-locked to the stimulus. In the secondary somatosensory cortex (SII), directing attention towards the stimulus increased phase-locked alpha (7–9 Hz) power approximately 30 ms after onset of phase-locked gamma in SI, followed by a non-phase-locked increase in alpha power. We suggest that earlier phase-locked oscillatory power may reflect the relay of input from SI to SII, whereas later non-phase-locked rhythms reflect stimulus-induced oscillations that are modulated by selective attention and may thus reflect enhanced processing of the stimulus underlying the perception of somatosensory events.