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Stacey, W. C.

Publications and source records attributed to Stacey, W. C..

3 recordsLinked to original sources

Visual speech differentially modulates beta, theta, and high gamma bands in auditory cortex

Speech perception is a central component of social communication. While principally an auditory process, accurate speech perception in everyday settings is supported by meaningful information extracted from visual cues (e.g., speech content, timing, and speaker identity). Previous research has shown that visual speech modulates activity in cortical areas subserving auditory speech perception, including the superior temporal gyrus (STG), potentially through feedback connections from the multisensory posterior superior temporal sulcus (pSTS). However, it is unknown whether visual modulation of auditory processing in the STG is a unitary phenomenon or, rather, consists of multiple temporally, spatially, or functionally distinct processes. To explore these questions, we examined neural responses to audiovisual speech measured from intracranially implanted electrodes within the temporal cortex of 21 patients undergoing clinical monitoring for epilepsy. We found that visual speech modulates auditory processes in the STG in multiple ways, eliciting temporally and spatially distinct patterns of activity that differ across theta, beta, and high-gamma frequency bands. Before speech onset, visual information increased high-gamma power in the posterior STG and suppressed beta power in mid-STG regions, suggesting crossmodal prediction of speech signals in these areas. After sound onset, visual speech decreased theta power in the middle and posterior STG, potentially reflecting a decrease in sustained feedforward auditory activity. These results are consistent with models that posit multiple distinct mechanisms supporting audiovisual speech perception and provide a crucial map for subsequent studies to identify the types of visual features that are encoded by these separate mechanisms.

neuroscience

Carbamazepine and GABA have distinct effects on seizure onset dynamics in mouse brain slices

Optimizing antiepileptic drug therapy is very challenging due to the absence of a reliable method to assess how brain activity changes between seizures. This work uses the Taxonomy of Seizure Dynamics (Saggio et al., 2020) to investigate how anticonvulsants influence seizure onset dynamotypes. The no Mg2+ /high K+ mouse brain-slice seizure model (N = 92) was used to generate consistent epileptiform onsets. We compared the onset bifurcations of controls with slices treated with either GABA or carbamazepine. Each anticonvulsant uniquely changed the types of bifurcations in the slices. This experiment provides proof-of-concept evidence that brain states exist on a "map" of seizure dynamics, and that antiepileptic drugs with different mechanisms can change the positioning of the brain states on the map. Impact statementAntiepileptic drugs modify underlying brain states and influence the pathway into seizure onset in brain slices.

bioinformatics

Epidynamics characterize and navigate the map of seizure dynamics

Seizures are a disruption of normal brain activity present across a vast range of species, diseases, and conditions. Here we introduce an organizing principle that leads to the first objective Taxonomy of Seizure Dynamics (TSD) based on bifurcation theory, and applied it to the analysis of EEG data. The "dynamotype" of a seizure is the part of its dynamic composition that defines its observable characteristics, including how it starts, evolves and terminates. Analyzing over 2000 focal-onset seizures recorded from 7 epilepsy centers on five continents, we find evidence of all 16 dynamotypes predicted in TSD. We demonstrate that patients dynamotypes evolve during their lifetime and display complex but systematic variations including hierarchy (certain dynamotypes are more common), non-bijectivity (a patient may display multiple dynamotypes) and pairing preference (multiple dynamotypes may occur during one seizure). TSD not only provides a way to stratify patients in complement to present practical classifications but also guides biophysically based mechanistic approaches and provides a language to describe the most critical features of seizure dynamics. Impact statementTaxonomy of Seizure Dynamics (TSD) provides a rigorous method for classifying and quantifying seizures and a principled framework for understanding seizure initiation and propagation.

bioinformatics