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Visual Perception

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Causal importance of low-level feature selectivity for generalization in image recognition.

Neural networks : the official journal of the International Neural Network Society
Although our brain and deep neural networks (DNNs) can perform high-level sensory-perception tasks, such as image or speech recognition, the inner mechanism of these hierarchical information-processing systems is poorly understood in both neuroscienc...

A systematic evaluation of the evidence for perceptual control theory in tracking studies.

Neuroscience and biobehavioral reviews
Perceptual control theory (PCT) proposes that perceptual inputs are controlled to intentional 'reference' states by hierarchical negative feedback control, evidence for which comes from manual tracking experiments in humans. We reviewed these experim...

Numerosity discrimination in deep neural networks: Initial competence, developmental refinement and experience statistics.

Developmental science
Both humans and non-human animals exhibit sensitivity to the approximate number of items in a visual array, as indexed by their performance in numerosity discrimination tasks, and even neonates can detect changes in numerosity. These findings are oft...

A neural circuit model for a contextual association task inspired by recommender systems.

Hippocampus
Behavioral data shows that humans and animals have the capacity to learn rules of associations applied to specific examples, and generalize these rules to a broad variety of contexts. This article focuses on neural circuit mechanisms to perform a con...

Learning Mobile Manipulation through Deep Reinforcement Learning.

Sensors (Basel, Switzerland)
Mobile manipulation has a broad range of applications in robotics. However, it is usually more challenging than fixed-base manipulation due to the complex coordination of a mobile base and a manipulator. Although recent works have demonstrated that d...

Reconstruction of natural visual scenes from neural spikes with deep neural networks.

Neural networks : the official journal of the International Neural Network Society
Neural coding is one of the central questions in systems neuroscience for understanding how the brain processes stimulus from the environment, moreover, it is also a cornerstone for designing algorithms of brain-machine interface, where decoding inco...

Decoding dynamic affective responses to naturalistic videos with shared neural patterns.

NeuroImage
This study explored the feasibility of using shared neural patterns from brief affective episodes (viewing affective pictures) to decode extended, dynamic affective sequences in a naturalistic experience (watching movie-trailers). Twenty-eight partic...

Separability and geometry of object manifolds in deep neural networks.

Nature communications
Stimuli are represented in the brain by the collective population responses of sensory neurons, and an object presented under varying conditions gives rise to a collection of neural population responses called an 'object manifold'. Changes in the obj...

Semantic and structural image segmentation for prosthetic vision.

PloS one
Prosthetic vision is being applied to partially recover the retinal stimulation of visually impaired people. However, the phosphenic images produced by the implants have very limited information bandwidth due to the poor resolution and lack of color ...

Evaluating the Potential Gain of Auditory and Audiovisual Speech-Predictive Coding Using Deep Learning.

Neural computation
Sensory processing is increasingly conceived in a predictive framework in which neurons would constantly process the error signal resulting from the comparison of expected and observed stimuli. Surprisingly, few data exist on the accuracy of predicti...