First-person body view modulates the neural substrates of episodic memory and autonoetic consciousness: A functional connectivity study.

Episodic memory (EM) is classically conceived as a memory for events, localized in space and time, and characterized by autonoetic consciousness (ANC) allowing to mentally travel back in time and subjectively relive an event. Building on recent evidence that the first-person visual co-perception of one's own body during encoding impacts EM, we used a scene recognition task in immersive virtual reality (VR) and measured how first-person body view would modulate peri-encoding resting-state fMRI, EM performance, and ANC. Specifically, we investigated the impact of body view on post-encoding functional connectivity in an a priori network of regions related either to EM or multisensory bodily processing and used these regions in a seed-to-whole brain analysis. Post-encoding connectivity between right hippocampus (rHC) and right parahippocampus (rPHC) was enhanced when participants encoded scenes while seeing their body. Moreover, the strength of connectivity between the rHC, rPHC and the neocortex displayed two main patterns with respect to body view. The connectivity with a sensorimotor fronto-parietal network, comprising primary somatosensory and primary motor cortices, correlated with ANC after - but not before - encoding, depending on body view. The opposite change of connectivity was found between rHC, rPHC and the medial parietal cortex (from being correlated with ANC before encoding to an absence of correlation after encoding), but irrespective of body view. Linking immersive VR and fMRI for the study of EM and ANC, these findings suggest that seeing one's own body during encoding impacts the brain activity related to EM formation by modulating the connectivity between the right hippocampal formation and the neocortical regions involved in the processing of multisensory bodily signals and self-consciousness.

Sense of Agency during Encoding Predicts Subjective Reliving.

Autonoetic consciousness (ANC), the ability to re-experience personal past events links episodic memory and self-consciousness by bridging awareness of oneself in a past event (i.e., during its encoding) with awareness of oneself in the present (i.e., during the reliving of a past event). Recent neuroscience research revealed a bodily form of self-consciousness, including the sense of agency (SoA) and the sense of body ownership (SoO) that are based on the integration of multisensory bodily inputs and motor signals. However, the relation between SoA and/or SoO with ANC is not known. Here, we used immersive virtual reality technology and motion tracking and investigated the potential association of SoA/SoO with ANC. For this, we exposed participants to different levels of visuomotor and perspectival congruency, known to modulate SoA and SoO, during the encoding of virtual scenes and collected ANC ratings 1 week after the encoding session. In a total of 74 healthy participants, we successfully induced systematic changes in SoA and SoO during encoding and found that ANC depended on the level of SoA experienced during encoding. Moreover, ANC was positively associated with SoA, but only for the scene encoded with preserved visuomotor and perspectival congruency, and such SoA-ANC coupling was absent for SoO and control questions. Collectively, these data provide behavioral evidence in a novel paradigm that links a key subjective component of bodily self-consciousness during encoding, SoA, to the subjective reliving of those encoded events from one's past, ANC.

Out-of-body illusion induced by visual-vestibular stimulation.

Out-of-body experiences (OBEs) are characterized by the subjective feeling of being located outside one's physical body and perceiving one's own body from an elevated perspective looking downwards. OBEs have been correlated with abnormal integration of bodily signals, including visual and vestibular information. In two studies, we used mixed reality combined with a motion platform to manipulate visual and vestibular integration in healthy participants. Behavioral data and questionnaires show that congruent visual-vestibular stimulation in a self-centered reference frame induced an OBE-like illusion characterized by elevated self-location and feelings of disembodiment and lightness. The OBE-like illusion was also modulated by individuals' visual field dependency assessed by the Rod and Frame Test. These results show that the manipulation of visual-vestibular stimulation in the present study induces various aspects of OBEs and further link OBE to congruency mechanisms between visual and vestibular gravitational and self-motion cues.

Introducing HiBoP: a Unity-based visualization software for large iEEG datasets.

BACKGROUND: Intracranial EEG data offer a unique spatio-temporal precision to investigate human brain functions. Large datasets have become recently accessible thanks to new iEEG data-sharing practices and tighter collaboration with clinicians. Yet, the complexity of such datasets poses new challenges, especially regarding the visualization and anatomical display of iEEG. NEW METHOD: We introduce HiBoP, a multi-modal visualization software specifically designed for large groups of patients and multiple experiments. Its main features include the dynamic display of iEEG responses induced by tasks/stimulations, the definition of Regions and electrodes Of Interest, and the shift between group-level and individual-level 3D anatomo-functional data. RESULTS: We provide a use-case with data from 36 patients to reveal the global cortical dynamics following tactile stimulation. We used HiBoP to visualize high-gamma responses [50-150 Hz], and define three major response components in primary somatosensory and premotor cortices and parietal operculum. COMPARISON WITH EXISTING METHODS(S): Several iEEG softwares are now publicly available with outstanding analysis features. Yet, most were developed in languages (Python/Matlab) chosen to facilitate the inclusion of new analysis by users, rather than the quality of the visualization. HiBoP represents a visualization tool developed with videogame standards (Unity/C#), and performs detailed anatomical analysis rapidly, across multiple conditions, patients, and modalities with an easy export toward third-party softwares. CONCLUSION: HiBoP provides a user-friendly environment that greatly facilitates the exploration of large iEEG datasets, and helps users decipher subtle structure/function relationships.

Embodiment in episodic memory through premotor-hippocampal coupling.

Episodic memory (EM) allows us to remember and relive past events and experiences and has been linked to cortical-hippocampal reinstatement of encoding activity. While EM is fundamental to establish a sense of self across time, this claim and its link to the sense of agency (SoA), based on bodily signals, has not been tested experimentally. Using real-time sensorimotor stimulation, immersive virtual reality, and fMRI we manipulated the SoA and report stronger hippocampal reinstatement for scenes encoded under preserved SoA, reflecting recall performance in a recognition task. We link SoA to EM showing that hippocampal reinstatement is coupled with reinstatement in premotor cortex, a key SoA region. We extend these findings in a severe amnesic patient whose memory lacked the normal dependency on the SoA. Premotor-hippocampal coupling in EM describes how a key aspect of the bodily self at encoding is neurally reinstated during the retrieval of past episodes, enabling a sense of self across time.

Virtual reality intervention alleviates dyspnoea in patients recovering from COVID-19 pneumonia.

Background: Immersive virtual reality (iVR)-based digital therapeutics are gaining clinical attention in the field of pain management. Based on known analogies between pain and dyspnoea, we investigated the effects of visual respiratory feedback on persistent dyspnoea in patients recovering from coronavirus disease 2019 (COVID-19) pneumonia. Methods: We performed a controlled, randomised, single-blind, crossover proof-of-concept study (feasibility and initial clinical efficacy) to evaluate an iVR-based intervention to alleviate dyspnoea in patients recovering from COVID-19 pneumonia. Included patients reported persistent dyspnoea (≥5 on a 10-point scale) and preserved cognitive function (Montreal Cognitive Assessment score >24). Assignment was random and concealed. Patients received synchronous (intervention) or asynchronous (control) feedback of their breathing, embodied via a gender-matched virtual body. The virtual body flashed in a waxing and waning visual effect that could be synchronous or asynchronous to the patient's respiratory movements. Outcomes were assessed using questionnaires and breathing recordings. Results: Study enrolment was open between November 2020 and April 2021. 26 patients were enrolled (27% women; median age 55 years, interquartile range (IQR) 18 years). Data were available for 24 of 26 patients. The median rating on a 7-point Likert scale of breathing comfort improved from 1 (IQR 2) at baseline to 2 (IQR 1) for synchronous feedback, but remained unchanged at 1 (IQR 1.5) for asynchronous feedback (p<0.05 between iVR conditions). Moreover, 91.2% of all patients were satisfied with the intervention (p<0.0001) and 66.7% perceived it as beneficial for their breathing (p<0.05). Conclusion: Our iVR-based digital therapy presents a feasible and safe respiratory rehabilitation tool that improves breathing comfort in patients recovering from COVID-19 infection presenting with persistent dyspnoea. Future research should investigate the intervention's generalisability to persistent dyspnoea with other aetiologies and its potential for preventing chronification.

Corticostriatal response selection in sentence production: Insights from neural network simulation with reservoir computing.

Language production requires selection of the appropriate sentence structure to accommodate the communication goal of the speaker - the transmission of a particular meaning. Here we consider event meanings, in terms of predicates and thematic roles, and we address the problem that a given event can be described from multiple perspectives, which poses a problem of response selection. We present a model of response selection in sentence production that is inspired by the primate corticostriatal system. The model is implemented in the context of reservoir computing where the reservoir - a recurrent neural network with fixed connections - corresponds to cortex, and the readout corresponds to the striatum. We demonstrate robust learning, and generalization properties of the model, and demonstrate its cross linguistic capabilities in English and Japanese. The results contribute to the argument that the corticostriatal system plays a role in response selection in language production, and to the stance that reservoir computing is a valid potential model of corticostriatal processing.