Concurrent Changes of Brain Functional Connectivity and Motor Variability When Adapting to Task Constraints

In behavioral neuroscience, the adaptability of humans facing different constraints has been addressed on one side at the brain level, where a variety of functional networks dynamically support the same performance, and on the other side at the behavioral level, where fractal properties in sensorimotor variables have been considered as a hallmark of adaptability. To bridge the gap between the two levels of observation, we have jointly investigated the changes of network connectivity in the sensorimotor cortex assessed by modularity analysis and the properties of motor variability assessed by multifractal analysis during a prolonged tapping task. Four groups of participants had to produce the same tapping performance while being deprived from 0, 1, 2, or 3 sensory feedbacks simultaneously (auditory and/or visual and/or tactile). Whereas tapping performance was not statistically different across groups, the number of brain networks involved and the degree of multifractality of the inter-tap interval series were significantly correlated, increasing as a function of feedback deprivation. Our findings provide first evidence that concomitant changes in brain modularity and multifractal properties characterize adaptations underlying unchanged performance. We discuss implications of our findings with respect to the degeneracy properties of complex systems, and the entanglement of adaptability and effective adaptation

Effects of visuo-spatial working memory load on auditory attention: behavioural and cortical evidence

Working memory (WM) plays an important role in pilots since they have to continuously integrate and dynamically update information within a rapidly changing environment. WM is essential for overcoming response conflict and for optimal selective attention performance. Yet, WM is a capacity-limited system and increasing the demands on WM reduces the ability to ignore irrelevant stimuli and can led decreased performance in dual –tasking. In the present study we used an experimental approach aiming at providing evidence for the sensitivity of the functional near infrared spectroscopy (fNIRS) in providing measures of brain activity within the prefrontal cortex (PFC), with regard to WM-specific task demands combined to an additional different secondary task

AI can fool us humans, but not at the psycho-physiological level: a hyperscanning and physiological synchrony study

This study aims at investigating the neural and physiological correlates of human-human and human-AI interactions under ecological settings. We designed a scenario in which a ground controller had to guide his/her pilot to reach a location. We also implemented a Controller-Bot and a Pilot-Bot using AI techniques to behave like real human operators. The cooperation between controllers and pilots were either genuine (‘Coop scenarios’ – four missions), explicitly notified as pilot-Bot and controller-Bot interactions (‘No coop scenarios’ – two missions), or with no notification that they were actually collaborating with their AI counterparts (‘fake coop scenarios’ – two missions). Sixteen participants (8 dyads) equipped with EEG and ECG took part in this experiment. Our findings disclosed that Human-Human dyads exhibited similar performance to Human-Bots dyads whether the human participants were aware that they were playing with a bot or not. Our participants declared that they did not realize they were playing with an AI in the fake cooperation condition. These findings indicate that 1) humans can be fooled by AI, and that 2) humans can behave in a natural way with AI. Interestingly enough, our analyses revealed that the cardiac activity of controllers and pilots was more synchronized when they were collaborating together than when they were playing with AI (being aware or not). Similarly, EEG analyses disclosed a higher cerebral efficiency and connectivity between the two brains when teammates were interacting together than when cooperating with AI

Hyperscan Project: investigate the physiological and neural markers of teammates cooperation

Servicemen are now by far engaged in complex operations involving cooperation with multiple actors and specialists under time pressure in uncertain and highly dynamic hostile environments. Moreover, military operators will be more likely to interact with advanced artificial intelligence (AI) based technology. There is a need to implement monitoring solutions to objectively assess the efficiency of human-human and human-AI teaming on the battlefield. The Hyperscan research project forms part of this perspective and aims to investigate the physiological and neural markers of cooperation between human teammates and as well as between humans and artificial agents

Adaptabilité et adaptation dans une tâche sensorimotrice : de la signification fonctionnelle des propriétés fractales à la dynamique des réseaux cérébraux

The study of fractal properties in biological time series is of increasing interest. Nevertheless, the literature highlights an ambiguity on the causal explanation of the presence of these time series which does not make it possible to distinguish between the effective adaptation made by a subject or his overall adaptability capacities. The aim of this dissertation is to decorrelate these two notions, notably by linking the behavioral level to the cerebral level. Our first study allowed to highlight that the mono-fractal properties could reflect the adaptability of the subjects whereas the multifractal properties would be related to the effective adaptation carried out during the task. The second study showed a correlation between the multifractal properties and the number of brain networks implemented during the task, reflecting the effective adaptation to the experimental constraints imposed. The results of this work have allowed us to better understand the functional meaning of fractal analyzes in terms of effective adaptation and adaptability.L’étude des propriétés fractales des séries biologiques fait l’objet d’un intérêt croissant. Néanmoins la littérature met en évidence une ambiguïté quand à l’explication causale de la présence de ces séries temporelles ne permettant pas de distinguer entre l’adaptation effective réalisée par un sujet ou ses capacités d’adaptabilité globales. La présente thèse a pour objectif de décorréler ces deux notions, notamment en liant le niveau comportemental au niveau cérébral. Notre première étude a permise de mettre en évidence que les propriétés mono-fractales pourraient refléter l’adaptabilité des sujets tandis que les propriétés multifractales seraient liées à l’adaptation effective réalisée au cours de la tâche. La seconde étude à mise en évidence une corrélation entre les propriétés multifractales et le nombre de réseaux cérébraux mis en œuvre au cours de la tâche, reflétant l’adaptation effective aux contraintes expérimentales imposées. Les résultats de ces travaux de thèse nous ont permis de mieux comprendre la signification fonctionnelle des analyses fractales en terme d’adaptation effective et d’adaptabilité

Adaptabilité et adaptation dans une tâche sensorimotrice : de la signification fonctionnelle des propriétés fractales à la dynamique des réseaux cérébraux

The study of fractal properties in biological time series is of increasing interest. Nevertheless, the literature highlights an ambiguity on the causal explanation of the presence of these time series which does not make it possible to distinguish between the effective adaptation made by a subject or his overall adaptability capacities. The aim of this dissertation is to decorrelate these two notions, notably by linking the behavioral level to the cerebral level. Our first study allowed to highlight that the mono-fractal properties could reflect the adaptability of the subjects whereas the multifractal properties would be related to the effective adaptation carried out during the task. The second study showed a correlation between the multifractal properties and the number of brain networks implemented during the task, reflecting the effective adaptation to the experimental constraints imposed. The results of this work have allowed us to better understand the functional meaning of fractal analyzes in terms of effective adaptation and adaptability.L’étude des propriétés fractales des séries biologiques fait l’objet d’un intérêt croissant. Néanmoins la littérature met en évidence une ambiguïté quand à l’explication causale de la présence de ces séries temporelles ne permettant pas de distinguer entre l’adaptation effective réalisée par un sujet ou ses capacités d’adaptabilité globales. La présente thèse a pour objectif de décorréler ces deux notions, notamment en liant le niveau comportemental au niveau cérébral. Notre première étude a permise de mettre en évidence que les propriétés mono-fractales pourraient refléter l’adaptabilité des sujets tandis que les propriétés multifractales seraient liées à l’adaptation effective réalisée au cours de la tâche. La seconde étude à mise en évidence une corrélation entre les propriétés multifractales et le nombre de réseaux cérébraux mis en oeuvre au cours de la tâche, reflétant l’adaptation effective aux contraintes expérimentales imposées. Les résultats de ces travaux de thèse nous ont permis de mieux comprendre la signification fonctionnelle des analyses fractales en terme d’adaptation effective et d’adaptabilité

Adaptabilité ou adaptation ? De la variabilité sensorimotrice aux patterns d'activation corticales

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Distinction between the potential of adaptability and effective adaptation in a motor task

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Hemodynamic response alterations in primary motor area as a function ofmuscle action: An fNIRS study

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Test-retest reliability of transcranial direct current stimulation-induced modulation of resting-state sensorimotor cortex oxygenation time course

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