AIMC Topic: Visual Cortex

Clear Filters Showing 111 to 120 of 132 articles

Information-Driven Active Audio-Visual Source Localization.

PloS one
We present a system for sensorimotor audio-visual source localization on a mobile robot. We utilize a particle filter for the combination of audio-visual information and for the temporal integration of consecutive measurements. Although the system on...

Learning Slowness in a Sparse Model of Invariant Feature Detection.

Neural computation
Primary visual cortical complex cells are thought to serve as invariant feature detectors and to provide input to higher cortical areas. We propose a single model for learning the connectivity required by complex cells that integrates two factors tha...

Multimodal personalization of transcranial direct current stimulation for modulation of sensorimotor integration.

NeuroImage
Transcranial direct current stimulation (tDCS) for the modulation of smooth pursuit eye movements provides an ideal model for investigating sensorimotor integration. Within neural networks subserving smooth pursuit, visual area V5 is a core hub where...

Enabling scale and rotation invariance in convolutional neural networks with retina like transformation.

Neural networks : the official journal of the International Neural Network Society
Traditional convolutional neural networks (CNNs) struggle with scale and rotation transformations, resulting in reduced performance on transformed images. Previous research focused on designing specific CNN modules to extract transformation-invariant...

Representation of locomotive action affordances in human behavior, brains, and deep neural networks.

Proceedings of the National Academy of Sciences of the United States of America
To decide how to move around the world, we must determine which locomotive actions (e.g., walking, swimming, or climbing) are afforded by the immediate visual environment. The neural basis of our ability to recognize locomotive affordances is unknown...

Neuronal Waveform Classification in Multielectrode Recordings Using Machine Learning Techniques and Multidimensional Analysis.

International journal of neural systems
Extracellular recordings of neuronal spikes are crucial for studying brain activity. These signals are typically classified based on firing patterns and waveform shape, particularly trough-to-peak duration. While useful, this method oversimplifies th...

Beyond binding: from modular to natural vision.

Trends in cognitive sciences
The classical view of visual cortex organization as a collection of specialized modules processing distinct features like color and motion has profoundly influenced neuroscience for decades. This framework, rooted in historical philosophical distinct...

Human Visual Pathways for Action Recognition versus Deep Convolutional Neural Networks: Representation Correspondence in Late but Not Early Layers.

Journal of cognitive neuroscience
Deep convolutional neural networks (DCNNs) have attained human-level performance for object categorization and exhibited representation alignment between network layers and brain regions. Does such representation alignment naturally extend to other v...

Convolutional neural network models applied to neuronal responses in macaque V1 reveal limited nonlinear processing.

Journal of vision
Computational models of the primary visual cortex (V1) have suggested that V1 neurons behave like Gabor filters followed by simple nonlinearities. However, recent work employing convolutional neural network (CNN) models has suggested that V1 relies o...

Probing the Structure and Functional Properties of the Dropout-Induced Correlated Variability in Convolutional Neural Networks.

Neural computation
Computational neuroscience studies have shown that the structure of neural variability to an unchanged stimulus affects the amount of information encoded. Some artificial deep neural networks, such as those with Monte Carlo dropout layers, also have ...