Cortical traveling waves reflect state-dependent hierarchical sequencing of local regions in the human connectome network

Recent human studies using electrocorticography have demonstrated that alpha and theta band oscillations form traveling waves on the cortical surface. According to neural synchronization theories, the cortical traveling waves may group local cortical regions and sequence them by phase synchronization; however these contributions have not yet been assessed. This study aimed to evaluate the functional contributions of traveling waves using connectome-based network modeling. In the simulation, we observed stable traveling waves on the entire cortical surface wherein the topographical pattern of these phases was substantially correlated with the empirically obtained resting-state networks, and local radial waves also appeared within the size of the empirical networks (< 50 mm). Importantly, individual regions in the entire network were instantaneously sequenced by their internal frequencies, and regions with higher intrinsic frequency were seen in the earlier phases of the traveling waves. Based on the communication-through-coherence theory, this phase configuration produced a hierarchical organization of each region by unidirectional communication between the arbitrarily paired regions. In conclusion, cortical traveling waves reflect the intrinsic frequency-dependent hierarchical sequencing of local regions, global traveling waves sequence the set of large-scale cortical networks, and local traveling waves sequence local regions within individual cortical networks.

Sequential propagation and routing of activity in a cortical network

Single spikes can trigger repeatable sequences of spikes in cortical networks. The mechanisms that support reliable propagation from such small events and their functional consequences for network computations remain unclear. We investigated the conditions in which single spikes trigger reliable and temporally precise sequences in a network model constrained by experimental measurements from turtle cortex. We examined the roles of connectivity, synaptic strength, and spontaneous activity in the generation of sequences. Sparse but strong connections support sequence propagation, while dense but weak connections modulate propagation reliability. Unsupervised clustering reveals that sequences can be decomposed into sub-sequences corresponding to divergent branches of strongly connected neurons. The sparse backbone of strong connections defines few failure points where activity can be selectively gated, enabling the controlled routing of activity. These results reveal how repeatable sequences of activity can be triggered, sustained, and controlled, with significant implications for cortical computations.

Hierarchical cortical networks of “voice patches” for processing voices in human brain

Humans have an extraordinary ability to recognize and differentiate voices. It is yet unclear whether voices are uniquely processed in the human brain. To explore the underlying neural mechanisms of voice processing, we recorded electrocorticographic signals from intracranial electrodes in epilepsy patients while they listened to six different categories of voice and nonvoice sounds. Subregions in the temporal lobe exhibited preferences for distinct voice stimuli, which were defined as “voice patches.” Latency analyses suggested a dual hierarchical organization of the voice patches. We also found that voice patches were functionally connected under both task-engaged and resting states. Furthermore, the left motor areas were coactivated and correlated with the temporal voice patches during the sound-listening task. Taken together, this work reveals hierarchical cortical networks in the human brain for processing human voices.

Assessment of Cortical Plasticity in Schizophrenia by Transcranial Magnetic Stimulation

Neural plasticity refers to the capability of the brain to modify its structure and/or function and organization in response to a changing environment. Evidence shows that disruption of neuronal plasticity and altered functional connectivity between distinct brain networks contribute significantly to the pathophysiological mechanisms of schizophrenia. Transcranial magnetic stimulation has emerged as a noninvasive brain stimulation tool that can be utilized to investigate cortical excitability with the aim of probing neural plasticity mechanisms. In particular, in pathological disorders, such as schizophrenia, cortical dysfunction, such as an aberrant excitatory-inhibitory balance in cortical networks, altered cortical connectivity, and impairment of critical period timing are very important to be studied using different TMS paradigms. Studying such neurophysiological characteristics and plastic changes would help in elucidating different aspects of the pathophysiological mechanisms underlying schizophrenia. This review attempts to summarize the findings of available TMS studies with diagnostic and characterization aims, but not with therapeutic purposes, in schizophrenia. Findings provide further evidence of aberrant excitatory-inhibitory balance in cortical networks, mediated by neurotransmitter pathways such as the glutamate and GABA systems. Future studies with combining techniques, for instance, TMS with brain imaging or molecular genetic typing, would shed light on the characteristics and predictors of schizophrenia.

Impact of inspiratory threshold loading on brain activity and cognitive performances in healthy humans

In healthy humans, inspiratory threshold loading deteriorates cognitive performances. This can result from motor-cognitive interference (activation of motor respiratory-related cortical networks vs. executive resources allocation), sensory-cognitive interference (dyspnea vs. shift in attentional focus), or both. We hypothesized that inspiratory loading would concomitantly induce dyspnea, activate motor respiratory-related cortical networks, and deteriorate cognitive performance. We reasoned that a concomitant activation of cortical networks and cognitive deterioration would be compatible with motor-cognitive interference, particularly in case of a predominant alteration of executive cognitive performances. Symmetrically, we reasoned that a predominant alteration of attention-depending performances would suggest sensory-cognitive interference. Twenty-five volunteers (12 men; 19.5-51.5 years) performed the Paced Auditory Serial Addition test (PASAT-A and B; calculation capacity, working memory, attention), the Trail Making Test (TMT-A, visuospatial exploration capacity; TMT-B, visuospatial exploration capacity and attention), and the Corsi block-tapping test (visuospatial memory, short-term and working memory) during unloaded breathing and inspiratory threshold loading in random order. Loading consistently induced dyspnea and respiratory-related brain activation. It was associated with deteriorations inPASAT A (52 [45.5;55.5] (median [interquartile range]) to 48 [41;54.5], p=0.01), PASAT B (55 [47.5;58] to 51 [44.5;57.5], p=0.01), and TMT B (44s [36;54.5] to 53s [42;64], p=0.01), but did not affect TMT-A and Corsi. The concomitance of cortical activation and cognitive performance deterioration is compatible with competition for cortical resources (motor-cognitive interference), while the profile of cognitive impairment (PASAT and TMT-B but not TMT-A and Corsi) is compatible with a contribution of attentional distraction (sensory-cognitive interference). Both mechanisms are therefore likely at play.

Human intracranial recordings reveal distinct cortical activity patterns during invasive and non-invasive vagus nerve stimulation

Vagus nerve stimulation (VNS) is being used increasingly to treat a wide array of diseases and disorders. This growth is driven in part by the putative ability to stimulate the nerve non-invasively. Despite decades of use and a rapidly expanding application space, we lack a complete understanding of the acute effects of VNS on human cortical neurophysiology. Here, we investigated cortical responses to sub-perceptual threshold cervical implanted (iVNS) and transcutaneous auricular (taVNS) vagus nerve stimulation using intracranial neurophysiological recordings in human epilepsy patients. To understand the areas that are modulated by VNS and how they differ depending on invasiveness and stimulation parameters, we compared VNS-evoked neural activity across a range of stimulation modalities, frequencies, and amplitudes. Using comparable stimulation parameters, both iVNS and taVNS caused subtle changes in low-frequency power across broad cortical networks, which were not the same across modalities and were highly variable across participants. However, within at least some individuals, it may be possible to elicit similar responses across modalities using distinct sets of stimulation parameters. These results demonstrate that both invasive and non-invasive VNS cause evoked changes in activity across a set of highly distributed cortical networks that are relevant to a diverse array of clinical, rehabilitative, and enhancement applications.

Analysis of cellular and synaptic mechanisms behind spontaneous cortical activity in vitro: Insights from optimization of spiking neuronal network models

Spontaneous network bursts, the intervals of intense network-wide activity interleaved with longer periods of sparse activity, are a hallmark phenomenon observed in cortical networks at postnatal developmental stages. Generation, propagation and termination of network bursts depend on a combination of synaptic, cellular and network mechanisms; however, the interplay between these mechanisms is not fully understood. We study this interplay in silico, using a new data-driven framework for generating spiking neuronal networks fitted to the microelectrode array recordings. We recorded the network bursting activity from rat postnatal cortical networks under several pharmacological conditions. In each condition, the function of specific excitatory and inhibitory synaptic receptors was reduced in order to examine their impact on global network dynamics. The obtained data was used to develop two complementary model fitting protocols for automatic model generation. These protocols allowed us to disentangle systematically the modeled cellular and synaptic mechanisms that affect the observed network bursts. We confirmed that the change in excitatory and inhibitory synaptic transmission in silico, consistent with pharmacological conditions, can account for the changes in network bursts relative to the control data. Reproducing the exact recorded network bursts statistics required adapting both the synaptic transmission and the cellular excitability separately for each pharmacological condition. Our results bring new understanding of the complex interplay between cellular, synaptic and network mechanisms supporting the burst dynamics. While here we focused on analysis of in vitro data, our approach can be applied ex vivo and in vivo given that the appropriate experimental data is available.