Biology subjects

Liegeois-Chauvel, C.

Publications and source records attributed to Liegeois-Chauvel, C..

3 recordsLinked to original sources

bioRxiv2022

Inter-Individual Variability in Dorsal Stream Dynamics During Word Production

The current standard model of language production involves a sensorimotor dorsal stream connecting areas in the temporo-parietal junction with those in the inferior frontal gyrus and lateral premotor cortex. These regions have been linked to various aspects of word production such as phonological processing or articulatory programming, primarily through neuropsychological and functional imaging group studies. Most if not all the theoretical descriptions of this model imply that the same network should be identifiable across individual speakers. We tested this hypothesis by quantifying the variability of activation observed across individuals within each dorsal stream anatomical region. This estimate was based on electrical activity recorded directly from the cerebral cortex with millisecond accuracy in awake epileptic patients clinically implanted with intracerebral depth electrodes for pre-surgical diagnosis. Each regions activity was quantified using two different metrics--intra-cerebral evoked related potentials and high gamma activity--at the level of the group, the individual, and the recording contact. Using picture naming task, the two metrics show simultaneous activation of parietal and frontal regions in line with models that posit interactive processing during word retrieval. They also reveal different levels of variability across brain regions and patients except in auditory and motor regions. The independence and non-uniformity of cortical activity according to the two metrics push the current model towards sub-second and sub-region explorations focused on individualized language speech production. Several hypotheses are considered for this within-region heterogeneity.

neuroscience↗

bioRxiv2019

Converging intracortical signatures of two separated processing timescales in human early auditory cortex.

Neural oscillations in auditory cortex are argued to support parsing and representing speech constituents at their corresponding temporal scales. Yet, how incoming sensory information interacts with ongoing spontaneous brain activity, what features of the neuronal microcircuitry underlie spontaneous and stimulus-evoked spectral fingerprints, and what these fingerprints entail for stimulus encoding, remain largely open questions. We used a combination of human invasive electrophysiology, computational modeling and decoding techniques to assess the information encoding properties of brain activity and to relate them to a plausible underlying neuronal microarchitecture. We analyzed intracortical auditory EEG activity from 10 patients while they were listening to short sentences. Pre-stimulus neural activity in early auditory cortical regions often exhibited power spectra with a shoulder in the delta range and a small bump in the beta range. Speech decreased power in the beta range, and increased power in the delta-theta and gamma ranges. Using multivariate machine learning techniques, we assessed the spectral profile of information content for two aspects of speech processing: detection and discrimination. We obtained better phase than power information decoding, and a bimodal spectral profile of information content with better decoding at low (delta-theta) and high (gamma) frequencies than at intermediate (beta) frequencies. These experimental data were reproduced by a simple rate model made of two subnetworks with different timescales, each composed of coupled excitatory and inhibitory units, and connected via a negative feedback loop. Modeling and experimental results were similar in terms of pre-stimulus spectral profile (except for the iEEG beta bump), spectral modulations with speech, and spectral profile of information content. Altogether, we provide converging evidence from both univariate spectral analysis and decoding approaches for a dual timescale processing infrastructure in human auditory cortex, and show that it is consistent with the dynamics of a simple rate model.\n\nAuthor summaryLike most animal vocalizations, speech results from a pseudo-rhythmic process that reflects the convergence of motor and auditory neural substrates and the natural resonance properties of the vocal apparatus towards efficient communication. Here, we leverage the excellent temporal and spatial resolution of intracranial EEG to demonstrate that neural activity in human early auditory cortical areas during speech perception exhibits a dual-scale spectral profile of power changes, with speech increasing power in low (delta-theta) and high (gamma - high-gamma) frequency ranges, while decreasing power in intermediate (alpha-beta) frequencies. Single-trial multivariate decoding also resulted in a bimodal spectral profile of information content, with better decoding at low and high frequencies than at intermediate ones. From both spectral and informational perspectives, these patterns are consistent with the activity of a relatively simple computational model comprising two reciprocally connected excitatory/inhibitory sub-networks operating at different (low and high) timescales. By combining experimental, decoding and modeling approaches, we provide consistent evidence for the existence, information coding value and underlying neuronal architecture of dual timescale processing in human auditory cortex.

neuroscience↗

bioRxiv2019

Asymmetric sampling in human auditory cortex reveals spectral processing hierarchy

Speech perception is mediated by both left and right auditory cortices, but with differential sensitivity to specific acoustic information contained in the speech signal. A detailed description of this functional asymmetry is missing, and the underlying models are widely debated. We analyzed cortical responses from 96 epilepsy patients with electrode implantation in left or right primary, secondary, and/or association auditory cortex. We presented short acoustic transients to reveal the stereotyped spectro-spatial oscillatory response profile of the auditory cortical hierarchy. We show remarkably similar bimodal spectral response profiles in left and right primary and secondary regions, with preferred processing modes in the theta ([~]4-8 Hz) and low gamma ([~]25-50 Hz) ranges. These results highlight that the human auditory system employs a two-timescale processing mode. Beyond these first cortical levels of auditory processing, a hemispheric asymmetry emerged, with delta and beta band ([~]3/15 Hz) responsivity prevailing in the right hemisphere and theta and gamma band ([~]6/40 Hz) activity in the left. These intracranial data provide a more fine-grained and nuanced characterization of cortical auditory processing in the two hemispheres, shedding light on the neural dynamics that potentially shape auditory and speech processing at different levels of the cortical hierarchy.\n\nAuthor summarySpeech processing is now known to be distributed across the two hemispheres, but the origin and function of lateralization continues to be vigorously debated. The asymmetric sampling in time (AST) hypothesis predicts that (1) the auditory system employs a two-timescales processing mode, (2) present in both hemispheres but with a different ratio of fast and slow timescales, (3) that emerges outside of primary cortical regions. Capitalizing on intracranial data from 96 epileptic patients we sensitively validated each of these predictions and provide a precise estimate of the processing timescales. In particular, we reveal that asymmetric sampling in associative areas is subtended by distinct two-timescales processing modes. Overall, our results shed light on the neurofunctional architecture of cortical auditory processing.

neuroscience↗