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Artikel: Editorial: Neurorobotics explores the human senses.

Khamassi, Mehdi / Mirolli, Marco / Wallraven, Christian

2023 Band 17, Seite(n) 1214871

Sprache	Englisch
Erscheinungsdatum	2023-05-22
Erscheinungsland	Switzerland
Dokumenttyp	Editorial
ZDB-ID	2453002-5
ISSN	1662-5218
ISSN	1662-5218
DOI	10.3389/fnbot.2023.1214871
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Zero-shot model-free learning of periodic movements for a bio-inspired soft-robotic arm.

Oikonomou, Paris / Dometios, Athanasios / Khamassi, Mehdi / Tzafestas, Costas S

Frontiers in robotics and AI

2023 Band 10, Seite(n) 1256763

Abstract: In recent years, soft robots gain increasing attention as a result of their compliance when operating in unstructured environments, and their flexibility that ensures safety when interacting with humans. However, challenges lie on the difficulty to ... ...

Abstract	In recent years, soft robots gain increasing attention as a result of their compliance when operating in unstructured environments, and their flexibility that ensures safety when interacting with humans. However, challenges lie on the difficulty to develop control algorithms due to various limitations induced by their soft structure. In this paper, we introduce a novel technique that aims to perform motion control of a modular bio-inspired soft-robotic arm, with the main focus lying on facilitating the qualitative reproduction of well-specified periodic trajectories. The introduced method combines the notion behind two previously developed methodologies both based on the Movement Primitive (MP) theory, by exploiting their capabilities while coping with their main drawbacks. Concretely, the requested actuation is initially computed using a Probabilistic MP (ProMP)-based method that considers the trajectory as a combination of simple movements previously learned and stored as a MP library. Subsequently, the key components of the resulting actuation are extracted and filtered in the frequency domain. These are eventually used as input to a Central Pattern Generator (CPG)-based model that takes over the generation of rhythmic patterns at the motor level. The proposed methodology is evaluated on a two-module soft arm. Results show that the first algorithmic component (ProMP) provides an immediate estimation of the requested actuation by avoiding time-consuming training, while the latter (CPG) further simplifies the execution by allowing its control through a low-dimensional parameterization. Altogether, these results open new avenues for the rapid acquisition of periodic movements in soft robots, and their compression into CPG parameters for long-term storage and execution.
Sprache	Englisch
Erscheinungsdatum	2023-10-19
Erscheinungsland	Switzerland
Dokumenttyp	Journal Article
ZDB-ID	2781824-X
ISSN	2296-9144 ; 2296-9144
ISSN (online)	2296-9144
ISSN	2296-9144
DOI	10.3389/frobt.2023.1256763
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel: Editorial: Computational models of affordance for robotics.

Renaudo, Erwan / Zech, Philipp / Chatila, Raja / Khamassi, Mehdi

Frontiers in neurorobotics

2022 Band 16, Seite(n) 1045355

Sprache	Englisch
Erscheinungsdatum	2022-10-06
Erscheinungsland	Switzerland
Dokumenttyp	Editorial
ZDB-ID	2453002-5
ISSN	1662-5218
ISSN	1662-5218
DOI	10.3389/fnbot.2022.1045355
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Modeling awake hippocampal reactivations with model-based bidirectional search.

Khamassi, Mehdi / Girard, Benoît

Biological cybernetics

2020 Band 114, Heft 2, Seite(n) 231–248

Abstract: Hippocampal offline reactivations during reward-based learning, usually categorized as replay events, have been found to be important for performance improvement over time and for memory consolidation. Recent computational work has linked these phenomena ...

Abstract	Hippocampal offline reactivations during reward-based learning, usually categorized as replay events, have been found to be important for performance improvement over time and for memory consolidation. Recent computational work has linked these phenomena to the need to transform reward information into state-action values for decision making and to propagate it to all relevant states of the environment. Nevertheless, it is still unclear whether an integrated reinforcement learning mechanism could account for the variety of awake hippocampal reactivations, including variety in order (forward and reverse reactivated trajectories) and variety in the location where they occur (reward site or decision-point). Here, we present a model-based bidirectional search model which accounts for a variety of hippocampal reactivations. The model combines forward trajectory sampling from current position and backward sampling through prioritized sweeping from states associated with large reward prediction errors until the two trajectories connect. This is repeated until stabilization of state-action values (convergence), which could explain why hippocampal reactivations drastically diminish when the animal's performance stabilizes. Simulations in a multiple T-maze task show that forward reactivations are prominently found at decision-points while backward reactivations are exclusively generated at reward sites. Finally, the model can generate imaginary trajectories that are not allowed to the agent during task performance. We raise some experimental predictions and implications for future studies of the role of the hippocampo-prefronto-striatal network in learning.
Mesh-Begriff(e)	Algorithms ; Animals ; Computer Simulation ; Hippocampus/physiology ; Learning ; Maze Learning ; Models, Neurological ; Place Cells/physiology ; Reinforcement, Psychology ; Reward ; Rodentia ; Wakefulness
Sprache	Englisch
Erscheinungsdatum	2020-02-17
Erscheinungsland	Germany
Dokumenttyp	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	220699-7
ISSN	1432-0770 ; 0340-1200
ISSN (online)	1432-0770
ISSN	0340-1200
DOI	10.1007/s00422-020-00817-x
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Illusion of knowledge in statistics among clinicians: evaluating the alignment between objective accuracy and subjective confidence, an online survey.

Lakhlifi, Camille / Lejeune, François-Xavier / Rouault, Marion / Khamassi, Mehdi / Rohaut, Benjamin

Cognitive research: principles and implications

2023 Band 8, Heft 1, Seite(n) 23

Abstract: Healthcare professionals' statistical illiteracy can impair medical decision quality and compromise patient safety. Previous studies have documented clinicians' insufficient proficiency in statistics and a tendency in overconfidence. However, an ... ...

Abstract	Healthcare professionals' statistical illiteracy can impair medical decision quality and compromise patient safety. Previous studies have documented clinicians' insufficient proficiency in statistics and a tendency in overconfidence. However, an underexplored aspect is clinicians' awareness of their lack of statistical knowledge that precludes any corrective intervention attempt. Here, we investigated physicians', residents' and medical students' alignment between subjective confidence judgments and objective accuracy in basic medical statistics. We also examined how gender, profile of experience and practice of research activity affect this alignment, and the influence of problem framing (conditional probabilities, CP vs. natural frequencies, NF). Eight hundred ninety-eight clinicians completed an online survey assessing skill and confidence on three topics: vaccine efficacy, p value and diagnostic test results interpretation. Results evidenced an overall consistent poor proficiency in statistics often combined with high confidence, even in incorrect answers. We also demonstrate that despite overconfidence bias, clinicians show a degree of metacognitive sensitivity, as their confidence judgments discriminate between their correct and incorrect answers. Finally, we confirm the positive impact of the more intuitive NF framing on accuracy. Together, our results pave the way for the development of teaching recommendations and pedagogical interventions such as promoting metacognition on basic knowledge and statistical reasoning as well as the use of NF to tackle statistical illiteracy in the medical context.
Mesh-Begriff(e)	Humans ; Illusions ; Judgment ; Health Personnel ; Physicians/psychology ; Metacognition
Sprache	Englisch
Erscheinungsdatum	2023-04-20
Erscheinungsland	England
Dokumenttyp	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	2365-7464
ISSN (online)	2365-7464
DOI	10.1186/s41235-023-00474-1
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: The rodent lateral orbitofrontal cortex as an arbitrator selecting between model-based and model-free learning systems.

Panayi, Marios C / Khamassi, Mehdi / Killcross, Simon

Behavioral neuroscience

2021 Band 135, Heft 2, Seite(n) 226–244

Abstract: Our understanding of orbitofrontal cortex (OFC) function has progressed remarkably over the past decades in part due to theoretical advances in associative and reinforcement learning theories. These theoretical accounts of OFC function have implicated ... ...

Abstract	Our understanding of orbitofrontal cortex (OFC) function has progressed remarkably over the past decades in part due to theoretical advances in associative and reinforcement learning theories. These theoretical accounts of OFC function have implicated the region in progressively more psychologically refined processes from the value and sensory-specific properties of expected outcomes to the representation and inference over latent state representations in cognitive maps of task space. While these accounts have been successful at modeling many of the effects of causal manipulation of OFC function in both rodents and primates, recent findings suggest that further refinement of our current models are still required. Here, we briefly review how our understanding of OFC function has developed to understand two cardinal deficits following OFC dysfunction: Reversal learning and outcome devaluation. We then consider recent findings that OFC dysfunction also significantly affects initial acquisition learning, often assumed to be intact. To account for these findings, we consider a possible role for the OFC in the arbitration and exploration between model-free (MF) and model-based (MB) learning systems, offline updating of MB representations. While the function of the OFC as a whole is still likely to be integral to the formation and use of a cognitive map of task space, these refinements suggest a way in which distinct orbital subregions, such as the rodent lateral OFC, might contribute to this overall function. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
Sprache	Englisch
Erscheinungsdatum	2021-05-31
Erscheinungsland	United States
Dokumenttyp	Journal Article
ZDB-ID	230159-3
ISSN	1939-0084 ; 0735-7044
ISSN (online)	1939-0084
ISSN	0735-7044
DOI	10.1037/bne0000454
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: The magical orbitofrontal cortex.

Schoenbaum, Geoffrey / Khamassi, Mehdi / Pessiglione, Mathias / Gottfried, Jay A / Murray, Elisabeth A

Behavioral neuroscience

2021 Band 135, Heft 2, Seite(n) 108

Abstract: This special issue, commissioned after the 4th Quadrennial Meeting on Orbitofrontal Cortex Function held in Paris in November of 2019 (https://ofc2019.sciencesconf.org/), is intended to provide a snapshot of this ongoing transformation; we hope that the ... ...

Abstract	This special issue, commissioned after the 4th Quadrennial Meeting on Orbitofrontal Cortex Function held in Paris in November of 2019 (https://ofc2019.sciencesconf.org/), is intended to provide a snapshot of this ongoing transformation; we hope that the ideas presented herein will provide a foundation for the next stage in the evolution of our understanding of this magical brain region. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
Mesh-Begriff(e)	Prefrontal Cortex
Sprache	Englisch
Erscheinungsdatum	2021-05-31
Erscheinungsland	United States
Dokumenttyp	Journal Article
ZDB-ID	230159-3
ISSN	1939-0084 ; 0735-7044
ISSN (online)	1939-0084
ISSN	0735-7044
DOI	10.1037/bne0000470
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Hippocampal replays under the scrutiny of reinforcement learning models.

Cazé, Romain / Khamassi, Mehdi / Aubin, Lise / Girard, Benoît

Journal of neurophysiology

2018 Band 120, Heft 6, Seite(n) 2877–2896

Abstract: Multiple in vivo studies have shown that place cells from the hippocampus replay previously experienced trajectories. These replays are commonly considered to mainly reflect memory consolidation processes. Some data, however, have highlighted a ... ...

Abstract	Multiple in vivo studies have shown that place cells from the hippocampus replay previously experienced trajectories. These replays are commonly considered to mainly reflect memory consolidation processes. Some data, however, have highlighted a functional link between replays and reinforcement learning (RL). This theory, extensively used in machine learning, has introduced efficient algorithms and can explain various behavioral and physiological measures from different brain regions. RL algorithms could constitute a mechanistic description of replays and explain how replays can reduce the number of iterations required to explore the environment during learning. We review the main findings concerning the different hippocampal replay types and the possible associated RL models (either model-based, model-free, or hybrid model types). We conclude by tying these frameworks together. We illustrate the link between data and RL through a series of model simulations. This review, at the frontier between informatics and biology, paves the way for future work on replays.
Mesh-Begriff(e)	Animals ; Connectome ; Hippocampus/physiology ; Humans ; Models, Neurological ; Reinforcement (Psychology) ; Sleep
Sprache	Englisch
Erscheinungsdatum	2018-10-10
Erscheinungsland	United States
Dokumenttyp	Journal Article ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	80161-6
ISSN	1522-1598 ; 0022-3077
ISSN (online)	1522-1598
ISSN	0022-3077
DOI	10.1152/jn.00145.2018
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Interactions of spatial strategies producing generalization gradient and blocking: A computational approach.

Dollé, Laurent / Chavarriaga, Ricardo / Guillot, Agnès / Khamassi, Mehdi

PLoS computational biology

2018 Band 14, Heft 4, Seite(n) e1006092

Abstract: We present a computational model of spatial navigation comprising different learning mechanisms in mammals, i.e., associative, cognitive mapping and parallel systems. This model is able to reproduce a large number of experimental results in different ... ...

Abstract	We present a computational model of spatial navigation comprising different learning mechanisms in mammals, i.e., associative, cognitive mapping and parallel systems. This model is able to reproduce a large number of experimental results in different variants of the Morris water maze task, including standard associative phenomena (spatial generalization gradient and blocking), as well as navigation based on cognitive mapping. Furthermore, we show that competitive and cooperative patterns between different navigation strategies in the model allow to explain previous apparently contradictory results supporting either associative or cognitive mechanisms for spatial learning. The key computational mechanism to reconcile experimental results showing different influences of distal and proximal cues on the behavior, different learning times, and different abilities of individuals to alternatively perform spatial and response strategies, relies in the dynamic coordination of navigation strategies, whose performance is evaluated online with a common currency through a modular approach. We provide a set of concrete experimental predictions to further test the computational model. Overall, this computational work sheds new light on inter-individual differences in navigation learning, and provides a formal and mechanistic approach to test various theories of spatial cognition in mammals.
Mesh-Begriff(e)	Animals ; Behavior, Animal/physiology ; Cognition/physiology ; Computational Biology ; Computer Simulation ; Cues ; Mammals ; Maze Learning/physiology ; Memory/physiology ; Models, Psychological ; Reinforcement, Psychology ; Spatial Navigation/physiology
Sprache	Englisch
Erscheinungsdatum	2018-04-09
Erscheinungsland	United States
Dokumenttyp	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2193340-6
ISSN	1553-7358 ; 1553-734X
ISSN (online)	1553-7358
ISSN	1553-734X
DOI	10.1371/journal.pcbi.1006092
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel: Model-Based and Model-Free Replay Mechanisms for Reinforcement Learning in Neurorobotics.

Massi, Elisa / Barthélemy, Jeanne / Mailly, Juliane / Dromnelle, Rémi / Canitrot, Julien / Poniatowski, Esther / Girard, Benoît / Khamassi, Mehdi

Frontiers in neurorobotics

2022 Band 16, Seite(n) 864380

Abstract: Experience replay is widely used in AI to bootstrap reinforcement learning (RL) by enabling an agent to remember and reuse past experiences. Classical techniques include shuffled-, reversed-ordered- and prioritized-memory buffers, which have different ... ...

Abstract	Experience replay is widely used in AI to bootstrap reinforcement learning (RL) by enabling an agent to remember and reuse past experiences. Classical techniques include shuffled-, reversed-ordered- and prioritized-memory buffers, which have different properties and advantages depending on the nature of the data and problem. Interestingly, recent computational neuroscience work has shown that these techniques are relevant to model hippocampal reactivations recorded during rodent navigation. Nevertheless, the brain mechanisms for orchestrating hippocampal replay are still unclear. In this paper, we present recent neurorobotics research aiming to endow a navigating robot with a neuro-inspired RL architecture (including different learning strategies, such as model-based (MB) and model-free (MF), and different replay techniques). We illustrate through a series of numerical simulations how the specificities of robotic experimentation (e.g., autonomous state decomposition by the robot, noisy perception, state transition uncertainty, non-stationarity) can shed new lights on which replay techniques turn out to be more efficient in different situations. Finally, we close the loop by raising new hypotheses for neuroscience from such robotic models of hippocampal replay.
Sprache	Englisch
Erscheinungsdatum	2022-06-24
Erscheinungsland	Switzerland
Dokumenttyp	Journal Article
ZDB-ID	2453002-5
ISSN	1662-5218
ISSN	1662-5218
DOI	10.3389/fnbot.2022.864380
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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