Frédéric Roux

Neural synchrony and the development of cortical networks

Recent data indicate that the synchronisation of oscillatory activity is relevant for the development of cortical circuits as demonstrated by the involvement of neural synchrony in synaptic plasticity and changes in the frequency and synchronisation of neural oscillations during development. Analyses of resting-state and task-related neural synchrony indicate that gamma-oscillations emerge during early childhood and precise temporal coordination through neural synchrony continues to mature until early adulthood. The late maturation of neural synchrony is compatible with changes in the myelination of cortico-cortical connections and with late development of GABAergic neurotransmission. These findings highlight the role of neural synchrony for normal brain development as well as its potential importance for understanding neurodevelopmental disorders, such as autism spectrum disorders (ASDs) and schizophrenia.

Working memory and neural oscillations: alpha–gamma versus theta–gamma codes for distinct WM information?

Neural oscillations at different frequencies have recently been related to a wide range of basic and higher cognitive processes. One possible role of oscillatory activity is to assure the maintenance of information in working memory (WM). Here we review the possibility that rhythmic activity at theta, alpha, and gamma frequencies serve distinct functional roles during WM maintenance. Specifically, we propose that gamma-band oscillations are generically involved in the maintenance of WM information. By contrast, alpha-band activity reflects the active inhibition of task-irrelevant information, whereas theta-band oscillations underlie the organization of sequentially ordered WM items. Finally, we address the role of cross-frequency coupling (CFC) in enabling alpha-gamma and theta-gamma codes for distinct WM information.

The development of neural synchrony reflects late maturation and restructuring of functional networks in humans

Brain development is characterized by maturational processes that span the period from childhood through adolescence to adulthood, but little is known whether and how developmental processes differ during these phases. We analyzed the development of functional networks by measuring neural synchrony in EEG recordings during a Gestalt perception task in 68 participants ranging in age from 6 to 21 years. Until early adolescence, developmental improvements in cognitive performance were accompanied by increases in neural synchrony. This developmental phase was followed by an unexpected decrease in neural synchrony that occurred during late adolescence and was associated with reduced performance. After this period of destabilization, we observed a reorganization of synchronization patterns that was accompanied by pronounced increases in gamma-band power and in theta and beta phase synchrony. These findings provide evidence for the relationship between neural synchrony and late brain development that has important implications for the understanding of adolescence as a critical period of brain maturation.

Gamma-Band Activity in Human Prefrontal Cortex Codes for the Number of Relevant Items Maintained in Working Memory

Previous studies in electrophysiology have provided consistent evidence for a relationship between neural oscillations in different frequency bands and the maintenance of information in working memory (WM). While the amplitude and cross-frequency coupling of neural oscillations have been shown to be modulated by the number of items retained during WM, interareal phase synchronization has been associated with the integration of distributed activity during WM maintenance. Together, these findings provided important insights into the oscillatory dynamics of cortical networks during WM. However, little is known about the cortical regions and frequencies that underlie the specific maintenance of behaviorally relevant information in WM. In the current study, we addressed this question with magnetoencephalography and a delayed match-to-sample task involving distractors in 25 human participants. Using spectral analysis and beamforming, we found a WM load-related increase in the gamma band (60–80 Hz) that was localized to the right intraparietal lobule and left Brodmann area 9 (BA9). WM-load related changes were also detected at alpha frequencies (10–14 Hz) in Brodmann area 6, but did not covary with the number of relevant WM-items. Finally, we decoded gamma-band source activity with a linear discriminant analysis and found that gamma-band activity in left BA9 predicted the number of target items maintained in WM. While the present data show that WM maintenance involves activity in the alpha and gamma band, our results highlight the specific contribution of gamma band delay activity in prefrontal cortex for the maintenance of behaviorally relevant items.

The Phase of Thalamic Alpha Activity Modulates Cortical Gamma-Band Activity: Evidence from Resting-State MEG Recordings

Recent findings have implicated thalamic alpha oscillations in the phasic modulation of cortical activity. However, the precise relationship between thalamic alpha oscillations and neocortical activity remains unclear. Here we show in a large sample of healthy human participants (n = 45) using spatial filtering techniques and measures of phase amplitude coupling that the amplitude of gamma-band activity in posterior medial parietal cortex is modulated by the phase of thalamic alpha oscillations during eyes-closed resting-state recordings. In addition, our findings show that gamma-band activity in visual cortex was not modulated by thalamic alpha oscillations but coupled to the phase of strong cortical alpha activity. To overcome the limitations of electromagnetic source localization we estimated conduction delays using transfer entropy and found nonspurious information transfer from thalamus to cortex. The present findings provide novel evidence for magneto-encephalography-measured phase coupling between cortical gamma-band activity and thalamic alpha oscillations, which highlight the role of phasic inhibition in the coordination of cortical activity.

Adolescent brain maturation and cortical folding: evidence for reductions in gyrification

Evidence from anatomical and functional imaging studies have highlighted major modifications of cortical circuits during adolescence. These include reductions of gray matter (GM), increases in the myelination of cortico-cortical connections and changes in the architecture of large-scale cortical networks. It is currently unclear, however, how the ongoing developmental processes impact upon the folding of the cerebral cortex and how changes in gyrification relate to maturation of GM/WM-volume, thickness and surface area. In the current study, we acquired high-resolution (3 Tesla) magnetic resonance imaging (MRI) data from 79 healthy subjects (34 males and 45 females) between the ages of 12 and 23 years and performed whole brain analysis of cortical folding patterns with the gyrification index (GI). In addition to GI-values, we obtained estimates of cortical thickness, surface area, GM and white matter (WM) volume which permitted correlations with changes in gyrification. Our data show pronounced and widespread reductions in GI-values during adolescence in several cortical regions which include precentral, temporal and frontal areas. Decreases in gyrification overlap only partially with changes in the thickness, volume and surface of GM and were characterized overall by a linear developmental trajectory. Our data suggest that the observed reductions in GI-values represent an additional, important modification of the cerebral cortex during late brain maturation which may be related to cognitive development.

Thalamo-cortical communication, glutamatergic neurotransmission and neural oscillations:a unique window into the origins of ScZ?

The thalamus has recently received renewed interest in systems-neuroscience and schizophrenia (ScZ) research because of emerging evidence highlighting its important role in coordinating functional interactions in cortical-subcortical circuits. Moreover, higher cognitive functions, such as working memory and attention, have been related to thalamo-cortical interactions, providing a novel perspective for the understanding of the neural substrate of cognition. The current review will support this perspective by summarizing evidence on the crucial role of neural oscillations in facilitating thalamo-cortical (TC) interactions during normal brain functioning and their potential impairment in ScZ. Specifically, we will focus on the relationship between NMDA-R mediated (glutamatergic) neurotransmission in TC-interactions. To this end, we will first review the functional anatomy and neurotransmitters in thalamic circuits, followed by a review of the oscillatory signatures and cognitive processes supported by TC-circuits. In the second part of the paper, data from preclinical research as well as human studies will be summarized that have implicated TC-interactions as a crucial target for NMDA-receptor hypofunctioning. Finally, we will compare these neural signatures with current evidence from ScZ-research, suggesting a potential overlap between alterations in TC-circuits as the result of NMDA-R deficits and stage-specific alterations in large-scale networks in ScZ.

Chronset: An automated tool for detecting speech onset

The analysis of speech onset times has a longstanding tradition in experimental psychology as a measure of how a stimulus influences a spoken response. Yet the lack of accurate automatic methods to measure such effects forces researchers to rely on time-intensive manual or semiautomatic techniques. Here we present Chronset, a fully automated tool that estimates speech onset on the basis of multiple acoustic features extracted via multitaper spectral analysis. Using statistical optimization techniques, we show that the present approach generalizes across different languages and speaker populations, and that it extracts speech onset latencies that agree closely with those from human observations. Finally, we show how the present approach can be integrated with previous work (Jansen & Watter Behavior Research Methods, 40:744–751, 2008) to further improve the precision of onset detection. Chronset is publicly available online at www.bcbl.eu/databases/chronset.

Hippocampal synchrony and neocortical desynchrony cooperate to encode and retrieve episodic memories

Episodic memories hinge upon our ability to process a wide range of multisensory information and bind this information into a coherent, memorable representation. On a neural level, these two processes are thought to be supported by neocortical alpha/beta desynchronisation and hippocampal theta/gamma synchronisation, respectively. Intuitively, these two processes should interact to successfully build and retrieve episodic memories, yet this hypothesis has not been tested empirically. Here, we address this question by analysing human intracranial EEG data recorded during an associative memory task that involved the pairing of life-like, dynamic stimuli to verbal stimuli. Our findings indicate that neocortical alpha/beta (8-20Hz) desynchronisation reliably precedes and predicts hippocampal 9fast9 gamma (60-80Hz) synchronisation during episodic memory formation; during episodic memory retrieval however, hippocampal 9slow9 gamma (40-50Hz) synchronisation reliably precedes and predicts later neocortical alpha/beta desynchronisation. We speculate that this cooperation reflects the flow of information from neocortex to hippocampus during memory formation, and hippocampal pattern completion inducing information reinstatement in the neocortex during memory retrieval.Episodic memories hinge upon our ability to process a wide range of multisensory information and bind this information into a coherent, memorable representation. On a neural level, these two processes are thought to be supported by neocortical alpha/beta desynchronisation and hippocampal theta/gamma synchronisation, respectively. Intuitively, these two processes should couple to successfully create and retrieve episodic memories, yet this hypothesis has not been tested empirically. We address this by analysing human intracranial EEG data recorded during two associative memory tasks. We find that neocortical alpha/beta (8-20Hz) power decreases reliably precede and predict hippocampal “fast” gamma (60-80Hz) power increases during episodic memory formation; during episodic memory retrieval however, hippocampal “slow” gamma (40-50Hz) power increases reliably precede and predict later neocortical alpha/beta power decreases. We speculate that this coupling reflects the flow of information from neocortex to hippocampus during memory formation, and hippocampal pattern completion inducing information reinstatement in the neocortex during memory retrieval. Significance Statement Episodic memories detail our personally-experienced past. The formation and retrieval of these memories has long been thought to be supported by a division of labour between the neocortex and the hippocampus, where the former processes event-related information and the latter binds this information together. However, it remains unclear how the two regions interact. We uncover directional coupling between these regions, with power decreases in the neocortex that precede and predict power increases in the hippocampus during memory formation. Fascinatingly, this process reverses during memory retrieval, with hippocampal power increases preceding and predicting neocortical power decreases. These results suggest a bidirectional flow of information between the neocortex and hippocampus is fundamental to the formation and retrieval of episodic memories.

Data-driven re-referencing of intracranial EEG based on independent component analysis (ICA)

BACKGROUND Intracranial recordings from patients implanted with depth electrodes are a valuable source of information in neuroscience. They allow for the unique opportunity to record brain activity with high spatial and temporal resolution. A common pre-processing choice in stereotactic EEG (S-EEG) is to re-reference the data with a bipolar montage. In this, each channel is subtracted from its neighbor, to reduce commonalities between channels and isolate activity that is spatially confined. NEW METHOD We challenge the assumption that bipolar reference effectively performs this task. To extract local activity, the distribution of the signal source of interest, interfering distant signals, and noise need to be considered. Referencing schemes with fixed coefficients can decrease the signal to noise ratio (SNR) of the data, they can lead to mislocalization of activity and consequently to misinterpretation of results. We propose to use Independent Component Analysis (ICA), to derive filter coefficients that reflect the statistical dependencies of the data at hand. RESULTS We describe and demonstrate this on human S-EEG recordings. In a simulation with real data, we quantitatively show that ICA outperforms the bipolar referencing operation in sensitivity and importantly in specificity when revealing local time series from the superposition of neighboring channels. COMPARISON WITH EXISTING METHOD(S) We argue that ICA already performs the same task that bipolar referencing pursues, namely undoing the linear superposition of activity and will identify activity that is local. CONCLUSIONS When investigating local sources in human S-EEG, ICA should be preferred over re-referencing the data with a bipolar montage.