Pedreschi, N. | Search bioRxiv

bioRxiv2024

States of functional connectivity flow and their multiplex dynamics in human epilepsy and postictal aphasia

We present a methodological framework for analysing multi-frequency dynamic functional connectivity (dFC) in electrophysiological recordings. The approach characterises not only the magnitude of network reconfiguration over time, but also whether these changes are spatially random or, instead, spatially organised in ways that drive a slower reconfiguration of modular structure. We define a generative null model of multi-scale connectivity fluctuations that differ in their degree of spatiotemporal organisation, and we describe dFC flows through the joint assessment of (i) instantaneous reconfiguration speed and (ii) the extent and quality of ongoing modular reorganisation. Different combinations of these features delineate distinct "flow styles", ranging from more liquid to more frozen dynamics. As a case study, we apply this framework to SEEG recordings from epileptic patients. We identify transitions between dynamic "allegiance states", whose flow styles closely mirror those of the null model. Seizure onset is associated with a pronounced slowing of dFC-speed, while a specific post-ictal regime combines low speed with highly frozen allegiance, and aligns most strongly with clinician-annotated aphasia. These pilot results suggest that temporal multiplex network analyses can reveal transient, frequency-specific network regimes linked to symptom expression and offers a generalisable tool for dissecting fast network dynamics in intracranial recordings. Author SummaryCognitive functions rely on the brains capacity to continually reorganize interactions among neuronal populations. Capturing this flexibility requires describing not only average functional network structure but also how it evolves over time. Using time- and frequency-resolved coherence from intracranial recordings in epilepsy patients, we model dynamic functional connectivity as a temporal multiplex network spanning multiple frequency bands. We introduce a frame-work that distinguishes different "styles" of network reconfiguration--faster or slower, and more structured or more random.

neuroscience↗

bioRxiv2020

Dynamic core-periphery structure of information sharing networks in entorhinal cortex and hippocampus

Neural computation is associated with the emergence, reconfiguration and dissolution of cell assemblies in the context of varying oscillatory states. Here, we describe the complex spatio-temporal dynamics of cell assemblies through temporal network formalism. We use a sliding window approach to extract sequences of networks of information sharing among single units in hippocampus and enthorinal cortex during anesthesia and study how global and node-wise functional connectivity properties evolve along time and as a function of changing global brain state (theta vs slow-wave oscillations). First, we find that information sharing networks display, at any time, a core-periphery structure in which an integrated core of more tightly functionally interconnected units link to more loosely connected network leaves. However the units participating to the core or to the periphery substantially change across time-windows, with units entering and leaving the core in a smooth way. Second, we find that discrete network states can be defined on top of this continuously ongoing liquid core-periphery reorganization. Switching between network states results in a more abrupt modification of the units belonging to the core and is only loosely linked to transitions between global oscillatory states. Third, we characterize different styles of temporal connectivity that cells can exhibit within each state of the sharing network. While inhibitory cells tend to be central, we show that, otherwise, anatomical localization only poorly influences the patterns of temporal connectivity of the different cells. Furthermore, cells can change temporal connectivity style when the network changes state. Altogether, these findings reveal that the sharing of information mediated by the intrinsic dynamics of hippocampal and enthorinal cortex cell assemblies have a rich spatiotemporal structure, which could not have been identified by more conventional time- or state-averaged analyses of functional connectivity. AUTHOR SUMMARYIt is generally thought that computations performed by local brain circuits rely on complex neural processes, associated to the flexible waxing and waning of cell assemblies, i.e. ensemble of cells firing in tight synchrony. Although cell assembly formation is inherently and unavoidably dynamical, it is still common to find studies in which essentially "static" approaches are used to characterize this process. In the present study, we adopt instead a temporal network approach. Avoiding usual time averaging procedures, we reveal that hub neurons are not hardwired but that cells vary smoothly their degree of integration within the assembly core. Furthermore, our temporal network framework enables the definition of alternative possible styles of "hubness". Some cells may share information with a multitude of other units but only in an intermittent manner, as "activists" in a flash mob. In contrast, some other cells may share information in a steadier manner, as resolute "lobbyists". Finally, by avoiding averages over pre-imposed states, we show that within each global oscillatory state a rich switching dynamics can take place between a repertoire of many available network states. We thus show that the temporal network framework provides a natural and effective language to rigorously describe the rich spatiotemporal patterns of information sharing instantiated by cell assembly evolution.

neuroscience↗