Nicolas Deperrois

ORCID: 0000-0001-7178-1818
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About
Contact & Profiles
Research Areas
  • Sleep and Wakefulness Research
  • Neural dynamics and brain function
  • Memory and Neural Mechanisms
  • Neuroscience and Music Perception
  • Neuroscience and Neuropharmacology Research
  • Nicotinic Acetylcholine Receptors Study
  • Advanced Memory and Neural Computing
  • Neurotransmitter Receptor Influence on Behavior
  • Receptor Mechanisms and Signaling
  • Sleep and related disorders
  • Topic Modeling
  • Neuroscience, Education and Cognitive Function
  • Natural Language Processing Techniques
  • Mind wandering and attention
  • Functional Brain Connectivity Studies
  • Photoreceptor and optogenetics research
  • Radiology practices and education

University of Bern
2021-2024

Kirchhoff (Germany)
2023

Heidelberg University
2023

University of Cambridge
2021

SPPIN - Saints-Pères Paris Institute for Neurosciences
2019-2020

Université Paris Cité
2019-2020

Institut de Psychiatrie et Neurosciences de Paris
2019-2020

Centre National de la Recherche Scientifique
2019-2020

Institut de Biologie de l'École Normale Supérieure
2019

Inserm
2018-2019

The widespread use of chest X-rays (CXRs), coupled with a shortage radiologists, has driven growing interest in automated CXR analysis and AI-assisted reporting. While existing vision-language models (VLMs) show promise specific tasks such as report generation or abnormality detection, they often lack support for interactive diagnostic capabilities. In this work we present RadVLM, compact, multitask conversational foundation model designed interpretation. To end, curate large-scale...

10.48550/arxiv.2502.03333 preprint EN arXiv (Cornell University) 2025-02-05

Humans and other animals learn to extract general concepts from sensory experience without extensive teaching. This ability is thought be facilitated by offline states like sleep where previous experiences are systemically replayed. However, the characteristic creative nature of dreams suggests that learning semantic representations may go beyond merely replaying experiences. We support this hypothesis implementing a cortical architecture inspired generative adversarial networks (GANs)....

10.7554/elife.76384 article EN cc-by eLife 2022-04-06

Semantic representations in higher sensory cortices form the basis for robust, yet flexible behavior. These are acquired over course of development an unsupervised fashion and continuously maintained organism's lifespan. Predictive processing theories propose that these emerge from predicting or reconstructing inputs. However, brains known to generate virtual experiences, such as during imagination dreaming, go beyond previously experienced Here, we suggest experiences may be just relevant...

10.1016/j.neubiorev.2023.105508 article EN cc-by Neuroscience & Biobehavioral Reviews 2023-12-12

Synaptic efficacy is subjected to activity-dependent changes on short- and long time scales. While short-term decay over minutes, long-term modifications last from hours up a lifetime are thought constitute the basis of learning memory. Both plasticity mechanisms have been studied extensively but how their interaction shapes synaptic dynamics little known. To investigate both together control induction depression potentiation, we used numerical simulations mathematical analysis calcium-based...

10.1371/journal.pcbi.1008265 article EN cc-by PLoS Computational Biology 2020-09-25

The importance of sleep for healthy brain function is widely acknowledged. However, it remains unclear how the internal generation dreams might facilitate cognitive processes. In this perspective we review a computational approach inspired by artificial intelligence that proposes framework occurring during rapid-eye-movement (REM) can contribute to learning and creativity. framework, REM are characterized an adversarial process that, against dream reality, tell discriminator network classify...

10.20944/preprints202403.0684.v2 preprint EN 2024-05-10

The importance of sleep for healthy brain function is widely acknowledged. However, it remains unclear how the internal generation dreams might facilitate cognitive processes. In this perspective, we review a computational approach inspired by artificial intelligence that proposes framework occurring during rapid-eye-movement (REM) can contribute to learning and creativity. framework, REM are characterized an adversarial process that, against dream reality, tells discriminator network...

10.3390/ctn8020021 article EN cc-by Clinical and Translational Neuroscience 2024-05-31

The importance of sleep for healthy brain function is widely acknowledged. However, it re- mains mysterious how the sleeping brain, disconnected from outside world and plunged into fantastic experiences dreams, actively learning. In this perspective article, we review a computational approach inspired by modern artificial intelligence that suggests role dreams occurring during rapid-eye-movement (REM) sleep. REM are characterized an adver- sarial process between feedforward feedback pathways...

10.20944/preprints202403.0684.v1 preprint EN 2024-03-12

Dopamine (DA) neurons in the ventral tegmental area (VTA) are thought to encode reward prediction errors (RPE) by comparing actual and expected rewards. In recent years, much work has been done identify how brain uses computes this signal. While several lines of evidence suggest interplay DA inhibitory interneurons VTA implements RPE computation, it still remains unclear learn key quantities, for example amplitude timing primary rewards during conditioning tasks. Furthermore, endogenous...

10.3389/fncir.2018.00116 article EN cc-by Frontiers in Neural Circuits 2019-01-08

Abstract Dopamine (DA) neurons in the ventral tegmental area (VTA) are thought to encode reward prediction errors (RPE) by comparing actual and expected rewards. In recent years, much work has been done identify how brain uses computes this signal.While several lines of evidence suggest interplay he DA inhibitory interneurons VTA implements RPE computaiton, it still remains unclear learn key quantities, for example amplitude timing primary rewards during conditioning tasks. Furthermore,...

10.1101/423806 preprint EN cc-by-nc-nd bioRxiv (Cold Spring Harbor Laboratory) 2018-09-25

Abstract Synaptic efficacy is subjected to activity-dependent changes on short- and long time scales. While short-term decay over minutes, long-term modifications last from hours up a lifetime are thought constitute the basis of learning memory. Both plasticity mechanisms have been studied extensively but how their interaction shapes synaptic dynamics little known. To investigate both together control induction depression potentiation, we used numerical simulations mathematical analysis...

10.1101/565291 preprint EN bioRxiv (Cold Spring Harbor Laboratory) 2019-03-01

Semantic representations in higher sensory cortices form the basis for robust, yet flexible behavior. These are acquired over course of development an unsupervised fashion and continuously maintained organism's lifespan. Predictive learning theories propose that these emerge from predicting or reconstructing inputs. However, brains known to generate virtual experiences, such as during imagination dreaming, go beyond previously experienced Here, we suggest experiences may be just relevant...

10.48550/arxiv.2308.01830 preprint EN cc-by arXiv (Cornell University) 2023-01-01

Humans and other animals learn to extract general concepts from sensory experience without extensive teaching. This ability is thought be facilitated by offline states like sleep where previous experiences are systemically replayed. However, the characteristic creative nature of dreams suggests that learning semantic representations may go beyond merely replaying experiences. We support this hypothesis implementing a cortical architecture inspired generative adversarial networks (GANs)....

10.48550/arxiv.2109.04261 preprint EN cc-by arXiv (Cornell University) 2021-01-01
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