ReviewFrontiers in computational neuroscience2021
Learning Invariant Object and Spatial View Representations in the Brain Using Slow Unsupervised Learning.
Review in Frontiers in computational neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed, 35 citations in OpenAlex.
- Mental Scene and Memory Construction and the Hippocampus.Hippocampus · 2026Article
- Visual Cortical Lateralization in Activations and Functional Connectivity to the Sight of Faces, Scenes, Body Parts, and Tools.Human brain mapping · 2026Article
- Invariant visual object and face learning in the ventral cortical visual pathway: A biologically plausible model.PLoS computational biology · 2026Article
- Article
- Hippocampal Discoveries: Spatial View Cells, Connectivity, and Computations for Memory and Navigation, in Primates Including Humans.Hippocampus · 2025Review
- Neuroscientific insights about computer vision models: a concise review.Biological cybernetics · 2024Review
- An inductive bias for slowly changing features in human reinforcement learning.PLoS computational biology · 2024Article
- A ventromedial visual cortical 'Where' stream to the human hippocampus for spatial scenes revealed with magnetoencephalography.Communications biology · 2024Article
- Selective activations and functional connectivities to the sight of faces, scenes, body parts and tools in visual and non-visual cortical regions leading to the human hippocampus.Brain structure & function · 2024Article
- Review
- Emotion, motivation, decision-making, the orbitofrontal cortex, anterior cingulate cortex, and the amygdala.Brain structure & function · 2023Review
- Hippocampal spatial view cells for memory and navigation, and their underlying connectivity in humans.Hippocampus · 2023Review
- Lifestyle risks associated with brain functional connectivity and structure.Human brain mapping · 2023Article
- The human posterior parietal cortex: effective connectome, and its relation to function.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- The human posterior cingulate, retrosplenial, and medial parietal cortex effective connectome, and implications for memory and navigation.Human brain mapping · 2023Article
- The connections of neocortical pyramidal cells can implement the learning of new categories, attractor memory, and top-down recall and attention.Brain structure & function · 2021Article
Corrections and comments
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Authors and funding
1 author at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
First, neurophysiological evidence for the learning of invariant representations in the inferior temporal visual cortex is described. This includes object and face representations with invariance for position, size, lighting, view and morphological transforms in the temporal lobe visual cortex; global object motion in the cortex in the superior temporal sulcus; and spatial view representations in the hippocampus that are invariant with respect to eye position, head direction, and place. Second, computational mechanisms that enable the brain to learn these invariant representations are proposed. For the ventral visual system, one key adaptation is the use of information available in the statistics of the environment in slow unsupervised learning to learn transform-invariant representations of objects. This contrasts with deep supervised learning in artificial neural networks, which uses training with thousands of exemplars forced into different categories by neuronal teachers. Similar slow learning principles apply to the learning of global object motion in the dorsal visual system leading to the cortex in the superior temporal sulcus. The learning rule that has been explored in VisNet is an associative rule with a short-term memory trace. The feed-forward architecture has four stages, with convergence from stage to stage. This type of slow learning is implemented in the brain in hierarchically organized competitive neuronal networks with convergence from stage to stage, with only 4-5 stages in the hierarchy. Slow learning is also shown to help the learning of coordinate transforms using gain modulation in the dorsal visual system extending into the parietal cortex and retrosplenial cortex. Representations are learned that are in allocentric spatial view coordinates of locations in the world and that are independent of eye position, head direction, and the place where the individual is located. This enables hippocampal spatial view cells to use idiothetic, self-motion, signals for navigation when the view details are obscured for short periods.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.