Notice bibliographique
Résumé
When it comes to symptom emergence and treatment of disorders, psychiatry and neuroscience do not always find common ground. On the one hand, neuroscientific research approaches mental disorders through their biological correlates using brain recordings; on the other, clinical psychiatry relies on self-report measures collected during face-to-face interviews. Taking into account both neural and experiential dimensions thus appears as one of the key challenges to the integration between neuroscience and psychiatry. One aspect in which neuroscience and psychiatry do see eye to eye is in their restricted account of interpersonal dynamics. In psychiatry, the focus is primarily put on the mental state examination of the patient, although most mental disorders severely affect and are affected by social dynamics. Similarly, in neuroscience, the “social brain” has been paradoxically studied in isolated contexts, inferring that mere passive social perception and active social interaction are encoded in the same way at the brain level. Yet, research has widely shown that the development of children’s social abilities requires subtle social interactions with their parents, involving an active and reciprocal co-regulation of the exchanges. Recent advancements in social neuroscience suggest that the relationship between brains and social dynamics might offer a unique opportunity for the neuroscience-psychiatry integration while acknowledging the inherent socialness of mental disorders. In 2002, a groundbreaking functional magnetic resonance imaging (fMRI) study introduced a technique called hyperscanning1, where the authors simultaneously scanned the brains of several participants while they were interacting through an economic game. This study paved the way for the design of realistic experimental protocols capable of capturing the crucial features of sociality, i.e. dynamicity and reciprocity, to investigate the neural mechanisms supporting social cognition and behavior. The idea quickly spread to other brain recording techniques, such as electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), which are cheaper and more flexible for social tasks requiring direct face-to-face interaction. This led to the discovery of specific neural circuits that support social interaction and that differ from those enabling the sole perception of social stimuli. For instance, both mirror and mentalizing networks are simultaneously engaged, with a subtle modulation of shared representations and the maintenance of a distinction between self and other. Beyond this better understanding at the intra-brain level, the development of hyperscanning has also inspired several teams of researchers to look at the inter-brain level, i.e. between-participants brain activity. The underlying hypothesis was that communication of information across brains might follow the same principles that govern communication of information inside brains. Thus, it was expected to find coherent activity between one region and another, but extended to two or more individuals. This novel inter-personal and dynamic perspective on social cognition was strongly associated with the development of 4E cognition, arguing that the mind is not solely in the head, but is also embodied, embedded, enacted, and extended. Thanks to hyperscanning recordings, a new type of neural correlate was identified: inter-brain connectivity (IBC)2. This can be defined as the synchronized brain activity of two or more people involved in a social scenario that can be attributed to their interaction rather than a shared external environment. All common neuroimaging techniques can be used to reveal IBC, from fMRI and fNIRS, which allow measuring amplitude correlation (i.e., when the brains activate regions at the same time), to EEG and magnetoencephalography, that provide sufficient temporal resolution to observe phase synchronization (i.e., when the brains present coherent oscillatory activity in time). In the last two decades, the observation of IBC has grown from a few isolated studies to a whole new field now covering non-verbal and verbal exchanges, in dyadic and group contexts, with interaction between mother-infants, romantic couples, friends, but also complete strangers. Those experiments have identified many correlates of IBC, from behavioral synchronization and imitation of movement to language familiarity, empathic connection, and even human attachment. This massive growth has recently allowed the first meta-analyses and triggered the development of standardized IBC tools, consolidating both scientific progress and replicability in the nascent multi-brain neuroscience research. But, how can psychiatry use this new form of multi-brain measurements? What can IBC bring to the understanding of psychiatric conditions, and how can it ultimately help in the daily practice of clinicians? First, IBC can provide a neural correlate for core clinical features of mental disorders. For instance, the alteration of interactive social cognition may be more specific than that of perceptual social cognition3. In autism spectrum disorder, as an example, patients rarely mention misunderstanding of complex social plots in movies; they rather complain about their difficulties with improvising in real-time social interaction during daily life. Hyperscanning recordings can thus help in further exploring the mechanisms and manifestations of psychiatric conditions with a strong social dimension4. Second, IBC can provide an objective measurement of the empathic connection or other social phenomena that are fundamental to the psychotherapeutic process but remain hard to capture at the biological level. For instance, hyperscanning studies have started to uncover the biological correlates of complex inter-personal phenomena such as the analgesic effect of affective touch5 or the therapeutic alliance6. In both cases, the alignment at affective and cognitive levels is reflected in the alignment at the neurobehavioral level. So, IBC promises to better capture the underlying biological factors impacting psychiatric manifestations and treatment, without necessarily reducing them to only intra-personal processes. Beyond these recent developments, we can also wonder what are the next steps for multi-brain neuroscience, and especially what potential avenues it can open for psychiatric research and clinical practice. First, while early work was done in humans, the recent increased interest in IBC comes from multiple papers published with animal models7. Not only have these studies replicated the early observation of inter-brain correlates in humans, but they have also uncovered for the first time cellular mechanisms. This move from mesoscopic to microscopic levels opens possibilities to decipher which biological mechanisms can be targeted pharmacologically to potentially enhance IBC and with them neurobehavioral inter-personal dynamics. Second, another recent trend is the move from multi-brain recording to multi-brain stimulations. The burgeoning field of hyper-stimulation8 may thus represent the next technological step to go from inter-brain correlational measurement to direct causal manipulation. Preliminary results already demonstrate that induction of inter-brain synchronization of neural processes shapes social interaction within groups of mice, and facilitates motor coordination in humans. If multi-brain electromagnetic stimulation provides insights about the causal factors modulating IBC and eventually sheds light onto biological mechanisms, a long-term challenge will be to move even beyond the traditional “correlation vs. causation” debate and provide an integrative explanation of the IBC phenomenon9. Ultimately, inter-personal neuromodulation through pharmacological compounds, electromagnetic stimulations, and even both, could open the way to new forms of therapeutics in psychiatry. We have seen how the nascent multi-brain neuroscience may lead to transformative applications in psychiatry, from inter-brain measures for clinical characterization to inter-brain neuromodulation for treatments. Interestingly, this inter-personal psychiatry will also help take seriously our biological grounding as much as our social embedding.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».