Biology subjects

Chaminade, T.

Publications and source records attributed to Chaminade, T..

5 recordsLinked to original sources

bioRxiv2024

Central Nervous System Control of breathing in Natural Conversational Turn-Taking

Discussion is a fundamental social activity requiring coordination of speech between interlocutors. Speech production is a complex human behaviour that involves several anatomo-physiological processes, including inspiration and expiration. The aim of the present study is to investigate the neurophysiological underpinnings of speech-related respiration events in conversational turn-taking. We made use of an existing corpus of natural conversations between a participant and its interlocutor (Human or Robot) focusing on synchronised (1) behavioural (conversation turn-taking), (2) respiratory (maxima of inspiration) and (3) neurophysiological (fMRI) data. Precisely timed conversation transcripts from 25 participants were used to categorise breathing maxima based on their timing relative to the participants speech onset. In agreement with the literature, the closest respiration time maximum to each speech turn occurred on average 200 ms prior to speech onset. The fMRI second-level contrast (pFWE < 0.05, extend k > 5 cm3) Resp+ (maximum respiration associated with speech) versus Resp-, exclusively masked to exclude speech related areas, revealed bilateral activations in the central sulcus, the brainstem and the cerebellum. The brainstem cluster comprises respiratory pattern generators, possibly the preBotzinger complex, that need to be inhibited to enslave breathing to speech production and not physiological needs, while the central sulcus cluster is likely to be located in the postcentral primary sensory cortex receiving upper torso inputs indicating that lungs are filled, and the cerebellum clusters could play a role in the timing of speech onset, 200 ms after a respiration maximum. These results show how cortical, cerebellar and brainstem coordinated control of breathing during conversational turn-taking is part of the intricate physiological mechanisms that contribute to natural communication dynamics.

neuroscience↗

bioRxiv2023

Social Context and Drug Cues Modulate Inhibitory Control in Cocaine Addiction: involvement of the STN evidenced through Functional Magnetic Resonance Imaging

BackgroundAddictions often develop in a social context, although the influence of social factors did not receive much attention in the neuroscience of addiction. Recent animal studies suggest that peer presence can reduce cocaine intake, an influence potentially mediated, among others, by the subthalamic nucleus (STN). However, there is to date no such neurobiological study in humans. MethodsThis study investigated the impact of social context and drug cues on brain correlates of inhibitory control in individuals with and without cocaine use disorder (CUD) using functional Magnetic Resonance Imaging (fMRI). Seventeen CUD participants and 17 healthy controls (HC) performed a novel fMRI Stop-Signal task in the presence and absence of an observer while being exposed to cocaine-related and neutral pictures as cues. ResultsThe results showed that CUD participants, while slower at stopping with neutral cues, recovered control level stopping abilities with cocaine cues, while HC did not show any difference. Neuroimaging revealed the involvement of frontal cortical regions and of the subthalamic nucleus (STN) in inhibitory control, which was modulated by both social context and drug cues in CUD participants but not in HC. ConclusionsThese findings highlight the impact of social context and drug cues on inhibitory control in CUD and suggest potential targets for intervention such as the STN, also emphasizing the importance of considering the social context in addiction research and treatment.

neuroscience↗

bioRxiv2021

Perceived facial happiness during conversation correlates with insular and hypothalamus activity for humans, not robots. An investigation of the somatic marker hypothesis applied to social interactions.

The somatic marker hypothesis posits that perceiving emotions entails reenacting markers of self emotions, in particular in the autonomous nervous system. Well studied in decision-making tasks, it has not been tested in a social cognitive neuroscience framework, and in particular for the automatic processing of positive emotions during natural interactions. Here, we address this question using a unique corpus of brain activity recorded during unconstrained conversations between participants and a human or a humanoid robot. fMRI recordings are used to test whether activity in the most important brain regions in relation to the autonomic system, the amygdala, hypothalamus and insula, is affected by the level of happiness expressed by the human and robot agents. Results indicate that for the hypothalamus and the insula, in particular the anterior agranular region strongly involved in processing social emotions, activity in the right hemisphere increases with the level of happiness expressed by the human, but not the robot. Results indicate that perceiving positive emotions in social interactions induces the local brain responses predicted by the somatic marker hypothesis, but only when the interacting agent is a real human.

neuroscience↗

bioRxiv2019

Inter-subject pattern analysis: a straightforward and powerful scheme for group-level MVPA.

Multivariate pattern analysis (MVPA) has become vastly popular for analyzing functional neuroimaging data. At the group level, two main strategies are used in the literature. The standard one is hierarchical, combining the outcomes of within-subject decoding results in a second-level analysis. The alternative one, inter-subject pattern analysis, directly works at the group-level by using, e.g, a leave-one-subject-out cross-validation. This study provides a thorough comparison of these two group-level decoding schemes, using both a large number of artificial datasets where the size of the multivariate effect and the amount of inter-individual variability are parametrically controlled, as well as two real fMRI datasets comprising respectively 15 and 39 subjects. We show that these two strategies uncover distinct significant regions with partial overlap, and that inter-subject pattern analysis is able to detect smaller effects and to facilitate the interpretation. The core source code and data are openly available, allowing to fully reproduce most of these results.

neuroscience↗

bioRxiv2018

Grammars of action in human behavior and evolution

Distinctive human behaviors from tool-making to language are thought to rely on a uniquely evolved capacity for hierarchical action sequencing. Unfortunately, testing of this idea has been hampered by a lack of objective, generalizable methods for measuring the structural complexity of real-world behaviors. Here we present a data-driven approach for quantifying hierarchical structure by extracting action grammars from basic ethograms. We apply this method to the evolutionarily-relevant behavior of stone tool-making by comparing sequences from the experimental replication of {small tilde}2.5 Mya Oldowan vs. more recent {small tilde}0.5 Mya Achuelean tools. Results show that, while using the same \"alphabet\" of elementary actions, Acheulean sequences are structurally more complex. Beyond its specific evolutionary implications, this finding illustrates the broader applicability of our method to investigate the structure of naturalistic human behaviors and cognition. We demonstrate one application by using our complexity measures to re-analyze data from an fMRI study of tool-making action observation.

neuroscience↗