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Dasilva, M.

Publications and source records attributed to Dasilva, M..

3 recordsLinked to original sources

Multiscale dynamics underlying neocortical slow oscillations

Slow oscillations in the sleeping and anesthetized brain invariantly emerge as an alternation between Up (high firing) and Down (almost quiescent) states. In cortex, they occur simultaneously in cell assemblies in different layers and propagate as traveling waves, a concerted activity at multiple scales whose interplay and role is still under debate. Slow oscillations have been reported to start in deep layers, more specifically in layer 5. Here, we studied the laminar organization of slow oscillations in the anesthetized rat cortex and we found that the activity leading to Up states actually initiates in layer 6, then spreads towards upper layers. Layer 5 cell assemblies have a threshold-like activation that can persist after layer 6 inactivation, giving rise to hysteresis loops like in "flip-flop" computational units. We found that such hysteresis is finely tuned by the columnar circuitry depending on the recent history of the local ongoing activity. Furthermore, thalamic inactivation reduced infragranular excitability without affecting the columnar activation pattern. We propose a role for layer 6 acting as a hub unraveling a hierarchy of cortical loops.

neuroscience↗

Slow waves form expanding, memory-rich mesostates steered by local excitability in fading anesthesia

During sleep and anesthesia, large groups of neurons throughout the entire cortex activate rhythmically producing wavefronts of activity referred to as slow-wave activity (SWA). In the arousal process, the brain restores its integrative and complex activity. The network mechanisms underlying this global state transition remain however to be elucidated. Here we investigated the network features shaping the SWA under fading anesthesia. Using electrocorticographical recordings of wide cortical areas of the mouse brain, we developed a quantitative measure of the anesthesia level based on slow-wave frequency and complexity. At deep anesthesia, we document a stringent alternation of posterior-anterior-posterior modes of propagation. With fading anesthesia, SWA evolves to produce a plethora of metastable spatiotemporal patterns. A network model of spiking neurons reproduced the data using short-range connectivity, subcortical input and a local activity-dependent adaptation. The emergence from deep anesthesia does not require modifying the connectivity, but small changes in the local excitability of cortical cell assemblies, further supporting the hypothesis of a tight bound between scales in the brain.

neuroscience↗

Characterization and remediation of sample index swaps by non-redundant dual indexing on massively parallel sequencing platforms

Here, we present an in-depth characterization of the index swapping mechanism on Illumina instruments that employ the ExAmp chemistry for cluster generation (HiSeqX, HiSeq4000, and NovaSeq). We discuss best practices for eliminating the effects of index swapping on data integrity by utilizing unique dual indexing for complete filtering of index swapped reads. We calculate mean swap rates across multiple sample preparation methods and sequencer models, demonstrating that different methods can have vastly different swap rates, and show that even non-ExAmp chemistry instruments display trace levels of index swapping. Finally, using computational methods we provide a greater insight into the mechanism of index swapping.

genomics↗