Fields of Gain in the Brain

Blohm, Gunnar; Crawford, J. Douglas

doi:10.1016/j.neuron.2009.11.022

Cited by 29 publications

(25 citation statements)

References 15 publications

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“…For example, decreased neural activity between the standard and plane dissociation conditions in the current study might be explained by the shift in gaze between conditions (Crawford et al, 2011;Blohm & Crawford, 2009). To account for this, we tested the potential contribution of eye movements alone to the difference in neural discharge observed between the standard and plane dissociation conditions and found no significance (see Results).…”

Section: Study Limitationsmentioning

confidence: 53%

Neural Activity in Superior Parietal Cortex during Rule-based Visual-motor Transformations

Hawkins

Sayegh²,

Yan³

et al. 2013

Journal of Cognitive Neuroscience

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Cognition allows for the use of different rule-based sensorimotor strategies, but the neural underpinnings of such strategies are poorly understood. The purpose of this study was to compare neural activity in the superior parietal lobule during a standard (direct interaction) reaching task, with two nonstandard (gaze and reach spatially incongruent) reaching tasks requiring the integration of rule-based information. Specifically, these nonstandard tasks involved dissociating the planes of reach and vision or rotating visual feedback by 180°. Single unit activity, gaze, and reach trajectories were recorded from two female Macaca mulattas. In all three conditions, we observed a temporal discharge pattern at the population level reflecting early reach planning and on-line reach monitoring. In the plane-dissociated task, we found a significant overall attenuation in the discharge rate of cells from deep recording sites, relative to standard reaching. We also found that cells modulated by reach direction tended to be significantly tuned either during the standard or the plane-dissociated task but rarely during both. In the standard versus feedback reversal comparison, we observed some cells that shifted their preferred direction by 180° between conditions, reflecting maintenance of directional tuning with respect to the reach goal. Our findings suggest that the superior parietal lobule plays an important role in processing information about the nonstandard nature of a task, which, through reciprocal connections with precentral motor areas, contributes to the accurate transformation of incongruent sensory inputs into an appropriate motor output. Such processing is crucial for the integration of rule-based information into a motor act.

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Section: Study Limitationsmentioning

confidence: 53%

Neural Activity in Superior Parietal Cortex during Rule-based Visual-motor Transformations

Hawkins

Sayegh²,

Yan³

et al. 2013

Journal of Cognitive Neuroscience

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“…This mechanism describes how the activity level of gain-field neurons can be modulated by the amplitude-level of several neurons sensitive to different variables, which is therefore interesting for neural control [91] and context switch [11]. Gain-modulation is found important for the neural processing in the parieto-motor cortices [92] and may provide a hint on how generative causal chains are formed in a neural population for planning in PFC as proposed by [1]. …”

Section: Discussionmentioning

confidence: 99%

Iterative free-energy optimization for recurrent neural networks (INFERNO)

Pitti¹,

Gaussier²,

Quoy³

2017

PLoS ONE

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The intra-parietal lobe coupled with the Basal Ganglia forms a working memory that demonstrates strong planning capabilities for generating robust yet flexible neuronal sequences. Neurocomputational models however, often fails to control long range neural synchrony in recurrent spiking networks due to spontaneous activity. As a novel framework based on the free-energy principle, we propose to see the problem of spikes’ synchrony as an optimization problem of the neurons sub-threshold activity for the generation of long neuronal chains. Using a stochastic gradient descent, a reinforcement signal (presumably dopaminergic) evaluates the quality of one input vector to move the recurrent neural network to a desired activity; depending on the error made, this input vector is strengthened to hill-climb the gradient or elicited to search for another solution. This vector can be learned then by one associative memory as a model of the basal-ganglia to control the recurrent neural network. Experiments on habit learning and on sequence retrieving demonstrate the capabilities of the dual system to generate very long and precise spatio-temporal sequences, above two hundred iterations. Its features are applied then to the sequential planning of arm movements. In line with neurobiological theories, we discuss its relevance for modeling the cortico-basal working memory to initiate flexible goal-directed neuronal chains of causation and its relation to novel architectures such as Deep Networks, Neural Turing Machines and the Free-Energy Principle.

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“…We will see examples of this approach throughout the robotic part of the paper, in particular in Section III-C. However, in a novel view, coordinate transformations can be computed implicitly and in parallel [55]. The above mentioned neurons which encode for the difference between the hand and the target are a good example of such a view.…”

Section: Coordinate Transformationsmentioning

confidence: 99%

Body Schema in Robotics: A Review

Hoffmann

Marques

Arieta

et al. 2010

IEEE Trans. Auton. Mental Dev.

208

104

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Abstract-How is our body imprinted in our brain? This seemingly simple question is a subject of investigations of diverse disciplines, psychology, and philosophy originally complemented by neurosciences more recently. Despite substantial efforts, the mysteries of body representations are far from uncovered. The most widely used notions-body image and body schema-are still waiting to be clearly defined. The mechanisms that underlie body representations are coresponsible for the admiring capabilities that humans or many mammals can display: combining information from multiple sensory modalities, controlling their complex bodies, adapting to growth, failures, or using tools. These features are also desirable in robots. This paper surveys the body representations in biology from a functional or computational perspective to set ground for a review of the concept of body schema in robotics. First, we examine application-oriented research: how a robot can improve its capabilities by being able to automatically synthesize, extend, or adapt a model of its body. Second, we summarize the research area in which robots are used as tools to verify hypotheses on the mechanisms underlying biological body representations. We identify trends in these research areas and propose future research directions.

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Fields of Gain in the Brain

Cited by 29 publications

References 15 publications

Neural Activity in Superior Parietal Cortex during Rule-based Visual-motor Transformations

Neural Activity in Superior Parietal Cortex during Rule-based Visual-motor Transformations

Iterative free-energy optimization for recurrent neural networks (INFERNO)

Body Schema in Robotics: A Review

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