A method for spatiotemporal mapping of event-related modulation of cortical rhythmic activity

GABAergic inhibition shapes behavior and neural dynamics in human visual working memory

Neuronal inhibition, primarily mediated by GABAergic neurotransmission, is crucial for brain development and healthy cognition. Gamma-aminobutyric acid concentration levels in sensory areas have been shown to correlate with hemodynamic and oscillatory neuronal responses. How these measures relate to one another during working memory, a higher-order cognitive process, is still poorly understood. We address this gap by collecting magnetoencephalography, functional magnetic resonance imaging, and Flumazenil positron emission tomography data within the same subject cohort using an n-back working-memory paradigm. By probing the relationship between GABAA receptor distribution, neural oscillations, and Blood Oxygen Level Dependent (BOLD) modulations, we found that GABAA receptor density in higher-order cortical areas predicted the reaction times on the working-memory task and correlated positively with the peak frequency of gamma power modulations and negatively with BOLD amplitude. These findings support and extend theories linking gamma oscillations and hemodynamic responses to gamma-aminobutyric acid neurotransmission and to the excitation-inhibition balance and cognitive performance in humans. Considering the small sample size of the study, future studies should test whether these findings also hold for other, larger cohorts as well as to examine in detail how the GABAergic system and neural fluctuations jointly support working-memory task performance.

The relationship between electrophysiological and hemodynamic measures of neural activity varies across picture naming tasks: A multimodal magnetoencephalography-functional magnetic resonance imaging study

Different neuroimaging methods can yield different views of task-dependent neural engagement. Studies examining the relationship between electromagnetic and hemodynamic measures have revealed correlated patterns across brain regions but the role of the applied stimulation or experimental tasks in these correlation patterns is still poorly understood. Here, we evaluated the across-tasks variability of MEG-fMRI relationship using data recorded during three distinct naming tasks (naming objects and actions from action images, and objects from object images), from the same set of participants. Our results demonstrate that the MEG-fMRI correlation pattern varies according to the performed task, and that this variability shows distinct spectral profiles across brain regions. Notably, analysis of the MEG data alone did not reveal modulations across the examined tasks in the time-frequency windows emerging from the MEG-fMRI correlation analysis. Our results suggest that the electromagnetic-hemodynamic correlation could serve as a more sensitive proxy for task-dependent neural engagement in cognitive tasks than isolated within-modality measures.

Large-scale cortico-cerebellar computations for horizontal and vertical vergence in humans

Horizontal and vertical vergence eye movements play a central role in binocular coordination. Neurophysiological studies suggest that cortical and subcortical regions in animals and humans are involved in horizontal vergence. However, little is known about the extent to which the neural mechanism underlying vertical vergence overlaps with that of horizontal vergence. In this study, to explore neural computation for horizontal and vertical vergence, we simultaneously recorded electrooculography (EOG) and whole-head magnetoencephalography (MEG) while presenting large-field stereograms for 29 healthy human adults. The stereograms were designed to produce vergence responses by manipulating horizontal and vertical binocular disparities. A model-based approach was used to assess neural sensitivity to horizontal and vertical disparities via MEG source estimation and the theta-band (4 Hz) coherence between brain activity and EOG vergence velocity. We found similar time-locked neural responses to horizontal and vertical disparity in cortical and cerebellar areas at around 100–250 ms after stimulus onset. In contrast, the low-frequency oscillatory neural activity associated with the execution of vertical vergence differed from that of horizontal vergence. These findings indicate that horizontal and vertical vergence involve partially shared but distinct computations in large-scale cortico-cerebellar networks.

Picture naming yields highly consistent cortical activation patterns: Test-retest reliability of magnetoencephalography recordings

Reliable paradigms and imaging measures of individual-level brain activity are paramount when reaching from group-level research studies to clinical assessment of individual patients. Magnetoencephalography (MEG) provides a direct, non-invasive measure of cortical processing with high spatiotemporal accuracy, and is thus well suited for assessment of functional brain damage in patients with language difficulties. This MEG study aimed to identify, in a delayed picture naming paradigm, source-localized evoked activity and modulations of cortical oscillations that show high test-retest reliability across measurement days in healthy individuals, demonstrating their applicability in clinical settings. For patients with a language disorder picture naming can be a challenging task. Therefore, we also determined whether a semantic judgment task ('Is this item living?') with a spoken response ("yes"/"no") would suffice to induce comparably consistent activity within brain regions related to language production. The MEG data was collected from 19 healthy participants on two separate days. In picture naming, evoked activity was consistent across measurement days (intraclass correlation coefficient (ICC)>0.4) in the left frontal (400-800 ms after image onset), sensorimotor (200-800 ms), parietal (200-600 ms), temporal (200-800 ms), occipital (400-800 ms) and cingulate (600-800 ms) regions, as well as the right temporal (600-800 ms) region. In the semantic judgment task, consistent evoked activity was spatially more limited, occurring in the left temporal (200-800 ms), sensorimotor (400-800 ms), occipital (400-600 ms) and subparietal (600-800 ms) regions, and the right supramarginal cortex (600-800 ms). The delayed naming task showed typical beta oscillatory suppression in premotor and sensorimotor regions (800-1200 ms) but other consistent modulations of oscillatory activity were mostly observed in posterior cortical regions that have not typically been associated with language processing. The high test-retest consistency of MEG evoked activity in the picture naming task testifies to its applicability in clinical evaluations of language function, as well as in longitudinal MEG studies of language production in clinical and healthy populations.

Analysis of Functional Connectivity and Oscillatory Power Using DICS: From Raw MEG Data to Group-Level Statistics in Python

Communication between brain regions is thought to be facilitated by the synchronization of oscillatory activity. Hence, large-scale functional networks within the brain may be estimated by measuring synchronicity between regions. Neurophysiological recordings, such as magnetoencephalography (MEG) and electroencephalography (EEG), provide a direct measure of oscillatory neural activity with millisecond temporal resolution. In this paper, we describe a full data analysis pipeline for functional connectivity analysis based on dynamic imaging of coherent sources (DICS) of MEG data. DICS is a beamforming technique in the frequency-domain that enables the study of the cortical sources of oscillatory activity and synchronization between brain regions. All the analysis steps, starting from the raw MEG data up to publication-ready group-level statistics and visualization, are discussed in depth, including methodological considerations, rules of thumb and tradeoffs. We start by computing cross-spectral density (CSD) matrices using a wavelet approach in several frequency bands (alpha, theta, beta, gamma). We then provide a way to create comparable source spaces across subjects and discuss the cortical mapping of spectral power. For connectivity analysis, we present a canonical computation of coherence that facilitates a stable estimation of all-to-all connectivity. Finally, we use group-level statistics to limit the network to cortical regions for which significant differences between experimental conditions are detected and produce vertex- and parcel-level visualizations of the different brain networks. Code examples using the MNE-Python package are provided at each step, guiding the reader through a complete analysis of the freely available openfMRI ds000117 “familiar vs. unfamiliar vs. scrambled faces” dataset. The goal is to educate both novice and experienced data analysts with the “tricks of the trade” necessary to successfully perform this type of analysis on their own data.

Large-scale functional networks connect differently for processing words and symbol strings

Reconfigurations of synchronized large-scale networks are thought to be central neural mechanisms that support cognition and behavior in the human brain. Magnetoencephalography (MEG) recordings together with recent advances in network analysis now allow for sub-second snapshots of such networks. In the present study, we compared frequency-resolved functional connectivity patterns underlying reading of single words and visual recognition of symbol strings. Word reading emphasized coherence in a left-lateralized network with nodes in classical perisylvian language regions, whereas symbol processing recruited a bilateral network, including connections between frontal and parietal regions previously associated with spatial attention and visual working memory. Our results illustrate the flexible nature of functional networks, whereby processing of different form categories, written words vs. symbol strings, leads to the formation of large-scale functional networks that operate at distinct oscillatory frequencies and incorporate task-relevant regions. These results suggest that category-specific processing should be viewed not so much as a local process but as a distributed neural process implemented in signature networks. For words, increased coherence was detected particularly in the alpha (8-13 Hz) and high gamma (60-90 Hz) frequency bands, whereas increased coherence for symbol strings was observed in the high beta (21-29 Hz) and low gamma (30-45 Hz) frequency range. These findings attest to the role of coherence in specific frequency bands as a general mechanism for integrating stimulus-dependent information across brain regions.

Defining the Neural Substrate of the Adult Outcome of Childhood ADHD: A Multimodal Neuroimaging Study of Response Inhibition

OBJECTIVE

Understanding the neural processes tied to the adult outcome of childhood attention deficit hyperactivity disorder (ADHD) could guide novel interventions to improve its clinical course. It has been argued that normalization of prefrontal cortical activity drives remission from ADHD, while anomalies in subcortical processes are "fixed," present even in remission. Using multimodal neuroimaging of inhibitory processes, the authors tested these hypotheses in adults followed since childhood, contrasting remitted against persistent ADHD.

METHOD

Adult participants (persistent ADHD, N=35; remit-ted ADHD, N=47; never affected, N=99) were scanned with functional MRI (fMRI) (N=85), magnetoencephalography (N=33), or both (N=63) during a response inhibition task.

RESULTS

In fMRI analyses, during inhibition, right caudate anomalies reflected a childhood ADHD history and were present even among those who remitted. By contrast, differences related to adult outcome emerged in cortical (right inferior frontal and inferior parietal/precuneus) and cerebellar regions. The persistent ADHD group showed under-activation, whereas the remitted ADHD group did not differ significantly from the never-affected group. Magnetoencephalography showed that the association between adult symptom severity and prefrontal neuronal activity was confined to the time window covering the act of inhibition (300 ms-350 ms). Group differences in cerebellar and parietal neuronal activity occurred during the time window of performance monitoring processes (500 ms-600 ms).

CONCLUSIONS

By combining fMRI and magnetoencephalography, the location and time window of neuronal activity that underpins the adult outcome of ADHD was pinpointed. Thus, the cortico-cerebellar processes tied to the clinical course of ADHD are separated from the subcortical processes that are not.

Gamma oscillations in V1 are correlated with GABA(A) receptor density: A multi-modal MEG and Flumazenil-PET study

High-frequency oscillations in the gamma-band reflect rhythmic synchronization of spike timing in active neural networks. The modulation of gamma oscillations is a widely established mechanism in a variety of neurobiological processes, yet its neurochemical basis is not fully understood. Modeling, in-vitro and in-vivo animal studies suggest that gamma oscillation properties depend on GABAergic inhibition. In humans, search for evidence linking total GABA concentration to gamma oscillations has led to promising -but also to partly diverging- observations. Here, we provide the first evidence of a direct relationship between the density of GABA_A receptors and gamma oscillatory gamma responses in human primary visual cortex (V1). By combining Flumazenil-PET (to measure resting-levels of GABA_A receptor density) and MEG (to measure visually-induced gamma oscillations), we found that GABA_A receptor densities correlated positively with the frequency and negatively with amplitude of visually-induced gamma oscillations in V1. Our findings demonstrate that gamma-band response profiles of primary visual cortex across healthy individuals are shaped by GABA_A-receptor-mediated inhibitory neurotransmission. These results bridge the gap with in-vitro and animal studies and may have future clinical implications given that altered GABAergic function, including dysregulation of GABA_A receptors, has been related to psychiatric disorders including schizophrenia and depression.

Dynamic reconfiguration of the language network preceding onset of speech in picture naming

Language production is a complex neural process that requires the interplay between multiple specialized cortical regions. We investigated modulations in large-scale cortical networks underlying preparation for speech production by contrasting cortico-cortical coherence for overt and silent picture naming in an all-to-all connectivity analysis. To capture transient, frequency-specific changes in functional connectivity we analyzed the magnetoencephalography data in two consecutive 300-ms time windows. Within the first 300 ms following picture onset beta frequency coherence was increased for overt naming in a network of regions comprising the bilateral parieto-temporal junction and medial cortices, suggesting that overt articulation modifies selection processes involved in speech planning. In the late time window (300-600 ms after picture onset) beta-range coherence was enhanced in a network that included the ventral sensorimotor and temporal cortices. Coherence in the gamma band was simultaneously reduced between the ventral motor cortex and supplementary motor area, bilaterally. The results suggest functionally distinct roles for beta (facilitatory) and gamma (suppressive) band interactions in speech production, with strong involvement of the motor cortex in both frequency bands. Overall, a striking difference in functional connectivity between the early and late time windows was observed, revealing the dynamic nature of large-scale cortical networks that support language and speech. Our results demonstrate that as the naming task evolves in time, the global connectivity patterns change, and that these changes occur (at least) on the time-scale of a few hundred milliseconds. More generally, these results bear implications for how we view large-scale neural networks underlying task performance.

Volumetric imaging of brain activity with spatial-frequency decoding of neuromagnetic signals

BACKGROUND

The brain generates signals in a wide frequency range (∼2840 Hz). Existing magnetoencephalography (MEG) methods typically detect brain activity in a median-frequency range (1-70 Hz). The objective of the present study was to develop a new method to utilize the frequency signatures for source imaging.

NEW METHOD

Morlet wavelet transform and two-step beamforming were integrated into a systematic approach to estimate magnetic sources in time-frequency domains. A grid-frequency kernel (GFK) was developed to decode the correlation between each time-frequency representation and grid voxel. Brain activity was reconstructed by accumulating spatial- and frequency-locked signals in the full spectral data for all grid voxels. To test the new method, MEG data were recorded from 20 healthy subjects and 3 patients with verified epileptic foci.

RESULTS

The experimental results showed that the new method could accurately localize brain activation in auditory cortices. The epileptic foci localized with the new method were spatially concordant with invasive recordings.

COMPARISON WITH EXISTING METHODS

Compared with well-known existing methods, the new method is objective because it scans the entire brain without making any assumption about the number of sources. The novel feature of the new method is its ability to localize high-frequency sources.

CONCLUSIONS

The new method could accurately localize both low- and high-frequency brain activities. The detection of high-frequency MEG signals can open a new avenue in the study of the human brain function as well as a variety of brain disorders.

Multivariate analysis of correlation between electrophysiological and hemodynamic responses during cognitive processing

Animal and human studies have frequently shown that in primary sensory and motor regions the BOLD signal correlates positively with high-frequency and negatively with low-frequency neuronal activity. However, recent evidence suggests that this relationship may also vary across cortical areas. Detailed knowledge of the possible spectral diversity between electrophysiological and hemodynamic responses across the human cortex would be essential for neural-level interpretation of fMRI data and for informative multimodal combination of electromagnetic and hemodynamic imaging data, especially in cognitive tasks. We applied multivariate partial least squares correlation analysis to MEG-fMRI data recorded in a reading paradigm to determine the correlation patterns between the data types, at once, across the cortex. Our results revealed heterogeneous patterns of high-frequency correlation between MEG and fMRI responses, with marked dissociation between lower and higher order cortical regions. The low-frequency range showed substantial variance, with negative and positive correlations manifesting at different frequencies across cortical regions. These findings demonstrate the complexity of the neurophysiological counterparts of hemodynamic fluctuations in cognitive processing.

Interactions between visual and semantic processing during object recognition revealed by modulatory effects of age of acquisition

The age of acquisition (AoA) of objects and their names is a powerful determinant of processing speed in adulthood, with early-acquired objects being recognized and named faster than late-acquired objects. Previous research using fMRI (Ellis et al., 2006. Traces of vocabulary acquisition in the brain: evidence from covert object naming. NeuroImage 33, 958-968) found that AoA modulated the strength of BOLD responses in both occipital and left anterior temporal cortex during object naming. We used magnetoencephalography (MEG) to explore in more detail the nature of the influence of AoA on activity in those two regions. Covert object naming recruited a network within the left hemisphere that is familiar from previous research, including visual, left occipito-temporal, anterior temporal and inferior frontal regions. Region of interest (ROI) analyses found that occipital cortex generated a rapid evoked response (~75-200 ms at 0-40 Hz) that peaked at 95 ms but was not modulated by AoA. That response was followed by a complex of later occipital responses that extended from ~300 to 850 ms and were stronger to early- than late-acquired items from ~325 to 675 ms at 10-20 Hz in the induced rather than the evoked component. Left anterior temporal cortex showed an evoked response that occurred significantly later than the first occipital response (~100-400 ms at 0-10 Hz with a peak at 191 ms) and was stronger to early- than late-acquired items from ~100 to 300 ms at 2-12 Hz. A later anterior temporal response from ~550 to 1050 ms at 5-20 Hz was not modulated by AoA. The results indicate that the initial analysis of object forms in visual cortex is not influenced by AoA. A fastforward sweep of activation from occipital and left anterior temporal cortex then results in stronger activation of semantic representations for early- than late-acquired objects. Top-down re-activation of occipital cortex by semantic representations is then greater for early than late acquired objects resulting in delayed modulation of the visual response.

Reactivity of dogs' brain oscillations to visual stimuli measured with non-invasive electroencephalography

Studying cognition of domestic dogs has gone through a renaissance within the last decades. However, although the behavioral studies of dogs are beginning to be common in the field of animal cognition, the neural events underlying cognition remain unknown. Here, we employed a non-invasive electroencephalography, with adhesive electrodes attached to the top of the skin, to measure brain activity of from 8 domestic dogs (Canis familiaris) while they stayed still to observe photos of dog and human faces. Spontaneous oscillatory activity of the dogs, peaking in the sensors over the parieto-occipital cortex, was suppressed statistically significantly during visual task compared with resting activity at the frequency of 15-30 Hz. Moreover, a stimulus-induced low-frequency (~2-6 Hz) suppression locked to the stimulus onset was evident at the frontal sensors, possibly reflecting a motor rhythm guiding the exploratory eye movements. The results suggest task-related reactivity of the macroscopic oscillatory activity in the dog brain. To our knowledge, the study is the first to reveal non-invasively measured reactivity of brain electrophysiological oscillations in healthy dogs, and it has been based purely on positive operant conditional training, without the need for movement restriction or medication.

Neural interactions at the core of phonological and semantic priming of written words

Word processing is often probed with experiments where a target word is primed by preceding semantically or phonologically related words. Behaviorally, priming results in faster reaction times, interpreted as increased efficiency of cognitive processing. At the neural level, priming reduces the level of neural activation, but the actual neural mechanisms that could account for the increased efficiency have remained unclear. We examined whether enhanced information transfer among functionally relevant brain areas could provide such a mechanism. Neural activity was tracked with magnetoencephalography while subjects read lists of semantically or phonologically related words. Increased priming resulted in reduced cortical activation. In contrast, coherence between brain regions was simultaneously enhanced. Furthermore, while the reduced level of activation was detected in the same area and time window (superior temporal cortex [STC] at 250-650 ms) for both phonological and semantic priming, the spatiospectral connectivity patterns appeared distinct for the 2 processes. Causal interactions further indicated a driving role for the left STC in phonological processing. Our results highlight coherence as a neural mechanism of priming and dissociate semantic and phonological processing via their distinct connectivity profiles.

Spatiotemporal convergence of semantic processing in reading and speech perception

Retrieval of word meaning from the semantic system and its integration with context are often assumed to be shared by spoken and written words. How is modality-independent semantic processing manifested in the brain, spatially and temporally? Time-sensitive neuroimaging allows tracking of neural activation sequences. Use of semantically related versus unrelated word pairs or sentences ending with a semantically highly or less plausible word, in separate studies of the auditory and visual modality, has associated lexical-semantic analysis with sustained activation at approximately 200-800 ms. Magnetoencephalography (MEG) studies have further identified the superior temporal cortex as a main locus of the semantic effect. Nevertheless, a direct comparison of the spatiotemporal neural correlates of visual and auditory word comprehension in the same brain is lacking. We used MEG to compare lexical-semantic analysis in the visual and auditory domain in the same individuals, and contrasted it with phonological analysis that, according to models of language perception, should occur at a different time with respect to semantic analysis in reading and speech perception. The stimuli were lists of four words that were either semantically or phonologically related, or with the final word unrelated to the preceding context. Superior temporal activation reflecting semantic processing occurred similarly in the two modalities, left-lateralized at 300-450 ms and thereafter bilaterally, generated in close-by areas. Effect of phonology preceded the semantic effect in speech perception but not in reading. The present data indicate involvement of the middle superior temporal cortex in semantic processing from approximately 300 ms onwards, regardless of input modality.