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Article ; Online: Ouvrai opens access to remote virtual reality studies of human behavioural neuroscience.

Cesanek, Evan / Shivkumar, Sabyasachi / Ingram, James N / Wolpert, Daniel M

Nature human behaviour

2024

Abstract: Modern virtual reality (VR) devices record six-degree-of-freedom kinematic data with high spatial and temporal resolution and display high-resolution stereoscopic three-dimensional graphics. These capabilities make VR a powerful tool for many types of ... ...

Abstract	Modern virtual reality (VR) devices record six-degree-of-freedom kinematic data with high spatial and temporal resolution and display high-resolution stereoscopic three-dimensional graphics. These capabilities make VR a powerful tool for many types of behavioural research, including studies of sensorimotor, perceptual and cognitive functions. Here we introduce Ouvrai, an open-source solution that facilitates the design and execution of remote VR studies, capitalizing on the surge in VR headset ownership. This tool allows researchers to develop sophisticated experiments using cutting-edge web technologies such as WebXR to enable browser-based VR, without compromising on experimental design. Ouvrai's features include easy installation, intuitive JavaScript templates, a component library managing front- and backend processes and a streamlined workflow. It integrates with Firebase, Prolific and Amazon Mechanical Turk and provides data processing utilities for analysis. Unlike other tools, Ouvrai remains free, with researchers managing their web hosting and cloud database via personal Firebase accounts. Ouvrai is not limited to VR studies; researchers can also develop and run desktop or touchscreen studies using the same streamlined workflow. Through three distinct motor learning experiments, we confirm Ouvrai's efficiency and viability for conducting remote VR studies.
Language	English
Publishing date	2024-04-26
Publishing country	England
Document type	Journal Article
ISSN	2397-3374
ISSN (online)	2397-3374
DOI	10.1038/s41562-024-01834-7
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Spatial uncertainty and environmental geometry in navigation.

Kang, Yul Hr / Wolpert, Daniel M / Lengyel, Máté

bioRxiv : the preprint server for biology

2023

Abstract: Variations in the geometry of the environment, such as the shape and size of an enclosure, have profound effects on navigational behavior and its neural underpinning. Here, we show that these effects arise as a consequence of a single, unifying principle: ...

Abstract	Variations in the geometry of the environment, such as the shape and size of an enclosure, have profound effects on navigational behavior and its neural underpinning. Here, we show that these effects arise as a consequence of a single, unifying principle: to navigate efficiently, the brain must maintain and update the uncertainty about one's location. We developed an image-computable Bayesian ideal observer model of navigation, continually combining noisy visual and self-motion inputs, and a neural encoding model optimized to represent the location uncertainty computed by the ideal observer. Through mathematical analysis and numerical simulations, we show that the ideal observer accounts for a diverse range of sometimes paradoxical distortions of human homing behavior in anisotropic and deformed environments, including 'boundary tethering', and its neural encoding accounts for distortions of rodent grid cell responses under identical environmental manipulations. Our results demonstrate that spatial uncertainty plays a key role in navigation.
Language	English
Publishing date	2023-02-01
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.01.30.526278
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: The Computational and Neural Bases of Context-Dependent Learning.

Heald, James B / Wolpert, Daniel M / Lengyel, Máté

Annual review of neuroscience

2023 Volume 46, Page(s) 233–258

Abstract: Flexible behavior requires the creation, updating, and expression of memories to depend on context. While the neural underpinnings of each of these processes have been intensively studied, recent advances in computational modeling revealed a key ... ...

Abstract	Flexible behavior requires the creation, updating, and expression of memories to depend on context. While the neural underpinnings of each of these processes have been intensively studied, recent advances in computational modeling revealed a key challenge in context-dependent learning that had been largely ignored previously: Under naturalistic conditions, context is typically uncertain, necessitating contextual inference. We review a theoretical approach to formalizing context-dependent learning in the face of contextual uncertainty and the core computations it requires. We show how this approach begins to organize a large body of disparate experimental observations, from multiple levels of brain organization (including circuits, systems, and behavior) and multiple brain regions (most prominently the prefrontal cortex, the hippocampus, and motor cortices), into a coherent framework. We argue that contextual inference may also be key to understanding continual learning in the brain. This theory-driven perspective places contextual inference as a core component of learning.
MeSH term(s)	Learning ; Brain ; Hippocampus ; Prefrontal Cortex ; Computer Simulation
Language	English
Publishing date	2023-03-27
Publishing country	United States
Document type	Journal Article ; Review ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, Non-U.S. Gov't
ZDB-ID	282459-0
ISSN	1545-4126 ; 0147-006X
ISSN (online)	1545-4126
ISSN	0147-006X
DOI	10.1146/annurev-neuro-092322-100402
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Memory, perceptual, and motor costs affect the strength of categorical encoding during motor learning of object properties.

Cesanek, Evan / Flanagan, J Randall / Wolpert, Daniel M

Scientific reports

2023 Volume 13, Issue 1, Page(s) 8619

Abstract: Nearly all tasks of daily life involve skilled object manipulation, and successful manipulation requires knowledge of object dynamics. We recently developed a motor learning paradigm that reveals the categorical organization of motor memories of object ... ...

Abstract	Nearly all tasks of daily life involve skilled object manipulation, and successful manipulation requires knowledge of object dynamics. We recently developed a motor learning paradigm that reveals the categorical organization of motor memories of object dynamics. When participants repeatedly lift a constant-density "family" of cylindrical objects that vary in size, and then an outlier object with a greater density is interleaved into the sequence of lifts, they often fail to learn the weight of the outlier, persistently treating it as a family member despite repeated errors. Here we examine eight factors (Similarity, Cardinality, Frequency, History, Structure, Stochasticity, Persistence, and Time Pressure) that could influence the formation and retrieval of category representations in the outlier paradigm. In our web-based task, participants (N = 240) anticipated object weights by stretching a virtual spring attached to the top of each object. Using Bayesian t-tests, we analyze the relative impact of each manipulated factor on categorical encoding (strengthen, weaken, or no effect). Our results suggest that category representations of object weight are automatic, rigid, and linear and, as a consequence, the key determinant of whether an outlier is encoded as a member of the family is its discriminability from the family members.
MeSH term(s)	Humans ; Memory ; Bayes Theorem ; Hand Strength ; Learning
Language	English
Publishing date	2023-05-27
Publishing country	England
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, N.I.H., Extramural
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-023-33515-2
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Judging the difficulty of perceptual decisions.

Löffler, Anne / Zylberberg, Ariel / Shadlen, Michael N / Wolpert, Daniel M

bioRxiv : the preprint server for biology

2023

Abstract: Deciding how difficult it is going to be to perform a task allows us to choose between tasks, allocate appropriate resources, and predict future performance. To be useful for planning, difficulty judgments should not require completion of the task. Here ... ...

Abstract	Deciding how difficult it is going to be to perform a task allows us to choose between tasks, allocate appropriate resources, and predict future performance. To be useful for planning, difficulty judgments should not require completion of the task. Here we examine the processes underlying difficulty judgments in a perceptual decision making task. Participants viewed two patches of dynamic random dots, which were colored blue or yellow stochastically on each appearance. Stimulus coherence (the probability,
Language	English
Publishing date	2023-06-05
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.02.13.528254
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Judging the difficulty of perceptual decisions.

Löffler, Anne / Zylberberg, Ariel / Shadlen, Michael N / Wolpert, Daniel M

eLife

2023 Volume 12

Abstract	Deciding how difficult it is going to be to perform a task allows us to choose between tasks, allocate appropriate resources, and predict future performance. To be useful for planning, difficulty judgments should not require completion of the task. Here, we examine the processes underlying difficulty judgments in a perceptual decision-making task. Participants viewed two patches of dynamic random dots, which were colored blue or yellow stochastically on each appearance. Stimulus coherence (the probability,
MeSH term(s)	Humans ; Decision Making ; Prospective Studies ; Reaction Time ; Judgment
Language	English
Publishing date	2023-11-17
Publishing country	England
Document type	Journal Article
ZDB-ID	2687154-3
ISSN	2050-084X ; 2050-084X
ISSN (online)	2050-084X
ISSN	2050-084X
DOI	10.7554/eLife.86892
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Contextual inference in learning and memory.

Heald, James B / Lengyel, Máté / Wolpert, Daniel M

Trends in cognitive sciences

2022 Volume 27, Issue 1, Page(s) 43–64

Abstract: Context is widely regarded as a major determinant of learning and memory across numerous domains, including classical and instrumental conditioning, episodic memory, economic decision-making, and motor learning. However, studies across these domains ... ...

Abstract	Context is widely regarded as a major determinant of learning and memory across numerous domains, including classical and instrumental conditioning, episodic memory, economic decision-making, and motor learning. However, studies across these domains remain disconnected due to the lack of a unifying framework formalizing the concept of context and its role in learning. Here, we develop a unified vernacular allowing direct comparisons between different domains of contextual learning. This leads to a Bayesian model positing that context is unobserved and needs to be inferred. Contextual inference then controls the creation, expression, and updating of memories. This theoretical approach reveals two distinct components that underlie adaptation, proper and apparent learning, respectively referring to the creation and updating of memories versus time-varying adjustments in their expression. We review a number of extensions of the basic Bayesian model that allow it to account for increasingly complex forms of contextual learning.
MeSH term(s)	Humans ; Memory ; Bayes Theorem ; Learning ; Hippocampus
Language	English
Publishing date	2022-11-24
Publishing country	England
Document type	Journal Article ; Review ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2010989-1
ISSN	1879-307X ; 1364-6613
ISSN (online)	1879-307X
ISSN	1364-6613
DOI	10.1016/j.tics.2022.10.004
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Interaction between decision-making and motor learning when selecting reach targets in the presence of bias and noise.

Zhu, Tianyao / Gallivan, Jason P / Wolpert, Daniel M / Flanagan, J Randall

PLoS computational biology

2023 Volume 19, Issue 11, Page(s) e1011596

Abstract: Motor errors can have both bias and noise components. Bias can be compensated for by adaptation and, in tasks in which the magnitude of noise varies across the environment, noise can be reduced by identifying and then acting in less noisy regions of the ... ...

Abstract	Motor errors can have both bias and noise components. Bias can be compensated for by adaptation and, in tasks in which the magnitude of noise varies across the environment, noise can be reduced by identifying and then acting in less noisy regions of the environment. Here we examine how these two processes interact when participants reach under a combination of an externally imposed visuomotor bias and noise. In a center-out reaching task, participants experienced noise (zero-mean random visuomotor rotations) that was target-direction dependent with a standard deviation that increased linearly from a least-noisy direction. They also experienced a constant bias, a visuomotor rotation that varied (across groups) from 0 to 40 degrees. Critically, on each trial, participants could select one of three targets to reach to, thereby allowing them to potentially select targets close to the least-noisy direction. The group who experienced no bias (0 degrees) quickly learned to select targets close to the least-noisy direction. However, groups who experienced a bias often failed to identify the least-noisy direction, even though they did partially adapt to the bias. When noise was introduced after participants experienced and adapted to a 40 degrees bias (without noise) in all directions, they exhibited an improved ability to find the least-noisy direction. We developed two models-one for reach adaptation and one for target selection-that could explain participants' adaptation and target-selection behavior. Our data and simulations indicate that there is a trade-off between adaptation and selection. Specifically, because bias learning is local, participants can improve performance, through adaptation, by always selecting targets that are closest to a chosen direction. However, this comes at the expense of improving performance, through selection, by reaching toward targets in different directions to find the least-noisy direction.
MeSH term(s)	Humans ; Psychomotor Performance ; Visual Perception ; Learning ; Noise ; Bias ; Adaptation, Physiological ; Movement
Language	English
Publishing date	2023-11-02
Publishing country	United States
Document type	Journal Article
ZDB-ID	2193340-6
ISSN	1553-7358 ; 1553-734X
ISSN (online)	1553-7358
ISSN	1553-734X
DOI	10.1371/journal.pcbi.1011596
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Memory, perceptual, and motor costs affect the strength of categorical encoding during motor learning of object properties

Evan Cesanek / J. Randall Flanagan / Daniel M. Wolpert

Scientific Reports, Vol 13, Iss 1, Pp 1-

2023 Volume 14

Abstract: Abstract Nearly all tasks of daily life involve skilled object manipulation, and successful manipulation requires knowledge of object dynamics. We recently developed a motor learning paradigm that reveals the categorical organization of motor memories of ...

Abstract	Abstract Nearly all tasks of daily life involve skilled object manipulation, and successful manipulation requires knowledge of object dynamics. We recently developed a motor learning paradigm that reveals the categorical organization of motor memories of object dynamics. When participants repeatedly lift a constant-density “family” of cylindrical objects that vary in size, and then an outlier object with a greater density is interleaved into the sequence of lifts, they often fail to learn the weight of the outlier, persistently treating it as a family member despite repeated errors. Here we examine eight factors (Similarity, Cardinality, Frequency, History, Structure, Stochasticity, Persistence, and Time Pressure) that could influence the formation and retrieval of category representations in the outlier paradigm. In our web-based task, participants (N = 240) anticipated object weights by stretching a virtual spring attached to the top of each object. Using Bayesian t-tests, we analyze the relative impact of each manipulated factor on categorical encoding (strengthen, weaken, or no effect). Our results suggest that category representations of object weight are automatic, rigid, and linear and, as a consequence, the key determinant of whether an outlier is encoded as a member of the family is its discriminability from the family members.
Keywords	Medicine ; R ; Science ; Q
Language	English
Publishing date	2023-05-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Reach adaption to a visuomotor gain with terminal error feedback involves reinforcement learning.

Ikegami, Tsuyoshi / Flanagan, J Randall / Wolpert, Daniel M

PloS one

2022 Volume 17, Issue 6, Page(s) e0269297

Abstract: Motor adaptation can be achieved through error-based learning, driven by sensory prediction errors, or reinforcement learning, driven by reward prediction errors. Recent work on visuomotor adaptation has shown that reinforcement learning leads to more ... ...

Abstract	Motor adaptation can be achieved through error-based learning, driven by sensory prediction errors, or reinforcement learning, driven by reward prediction errors. Recent work on visuomotor adaptation has shown that reinforcement learning leads to more persistent adaptation when visual feedback is removed, compared to error-based learning in which continuous visual feedback of the movement is provided. However, there is evidence that error-based learning with terminal visual feedback of the movement (provided at the end of movement) may be driven by both sensory and reward prediction errors. Here we examined the influence of feedback on learning using a visuomotor adaptation task in which participants moved a cursor to a single target while the gain between hand and cursor movement displacement was gradually altered. Different groups received either continuous error feedback (EC), terminal error feedback (ET), or binary reinforcement feedback (success/fail) at the end of the movement (R). Following adaptation we tested generalization to targets located in different directions and found that generalization in the ET group was intermediate between the EC and R groups. We then examined the persistence of adaptation in the EC and ET groups when the cursor was extinguished and only binary reward feedback was provided. Whereas performance was maintained in the ET group, it quickly deteriorated in the EC group. These results suggest that terminal error feedback leads to a more robust form of learning than continuous error feedback. In addition our findings are consistent with the view that error-based learning with terminal feedback involves both error-based and reinforcement learning.
MeSH term(s)	Feedback ; Feedback, Sensory ; Humans ; Learning ; Psychomotor Performance ; Reinforcement, Psychology
Language	English
Publishing date	2022-06-01
Publishing country	United States
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0269297
Database	MEDical Literature Analysis and Retrieval System OnLINE

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