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Cortical Learning via Prediction

Christos H. Papadimitriou, Santosh S. Vempala
2015 Annual Conference Computational Learning Theory  
Prediction and feedback are well-known features of neural cognition and, as far as we know, this is the first theoretical prediction of their essential role in learning.  ...  We show that PJOIN can be implemented naturally in Valiant's conservative, formal model of cortical computation.  ...  Unsupervised Learning Cortical activity acquires meaning only when it interacts with the world via appropriate sensors and actuators.  ... 
dblp:conf/colt/PapadimitriouV15 fatcat:gqpgwi2ksngotdbzp7roo6b4q4

Predictive models in the brain

Keith L. Downing
2009 Connection science  
This paper reviews a host of neural models believed to underlie the learning and deployment of predictive knowledge in a variety of brain regions: neocortex, hippocampus, thalamus, basal ganglia and cerebellum  ...  Many neuroscientists view prediction as one of the core brain functions.  ...  As sketched in Figure 21 , two stimuli are linked via thalamic and cortical activation, monitoring and learning.  ... 
doi:10.1080/09540090802610666 fatcat:ehrnvzrczrbizn4b7eydv4sp3y

Consciousness CLEARS the mind

Stephen Grossberg
2007 Neural Networks  
This prediction clarifies why it is easier to quickly learn about information to which one pays attention.  ...  oscillations, rather than the higher-frequency gamma oscillations that occur more frequently in superficial cortical layers.  ...  stabilize learning without supporting conscious experiences, which seems to be what happens in the perceptual learning experiments of Watanabe et al. (2001) .  ... 
doi:10.1016/j.neunet.2007.09.014 pmid:17964756 fatcat:7ao5vziuerbvdhnw4nhdegnxsq

Linking Visual Development and Learning to Information Processing: Preattentive and Attentive Brain Dynamics [chapter]

Stephen Grossberg
2006 Plasticity in the Visual System  
This emerging model of visual cortical dynamics, called the LAMINART model suggests how the layered circuits of visual cortex interact to control cortical development and learning, notably how bottom-up  ...  A rapidly developing cortical model links processes of development in the infant to processes of perception and learning in the adult.  ...  This is the feedback circuit that embodies the prediction that "The pre-attentive grouping is its own attentional prime", and thus the circuit that is predicted to stabilize cortical development and learning  ... 
doi:10.1007/0-387-28190-8_15 fatcat:adk3axkmtnaqzogfqyzqmhypwa

Supervision of motor cortex by basal ganglia

Bryan Tripp, Chris Eliasmith
2007 BMC Neuroscience  
patterns are gradually transferred to the cortex via supervised learning.  ...  On the basis of this model, we predict that patients should have difficulty learning novel, complex movement patterns following ablation of basal ganglia output nuclei.  ...  patterns are gradually transferred to the cortex via supervised learning.  ... 
doi:10.1186/1471-2202-8-s2-s17 fatcat:dfc5cw2335gydmwuqz53cy7kny

Homeostasis causes hallucinations in a hierarchical generative model of the visual cortex: the Charles Bonnet Syndrome

David P Reichert, Peggy Series, Amos J Storkey
2011 BMC Neuroscience  
Hierarchical predictive models of the cortex [1, 2] pose that the prediction of sensory input is a crucial aspect of cortical processing.  ...  Evaluating the internally generated predictions against actual input could be a powerful means of learning about causes in the world.  ...  Hierarchical predictive models of the cortex [1, 2] pose that the prediction of sensory input is a crucial aspect of cortical processing.  ... 
doi:10.1186/1471-2202-12-s1-p319 pmcid:PMC3240433 fatcat:577iocyjprgvrgf44z45wzdwny

Linking Attention to Learning, Expectation, Competition, and Consciousness [chapter]

Stephen Grossberg
2005 Neurobiology of Attention  
Attention is part of a unified design of bottom-up, horizontal, and top-down interactions among identified cells in laminar cortical circuits.  ...  The present article summarizes neural models and supportive data about how attention is linked to processes of learning, expectation, competition, and consciousness.  ...  Attention, Competition, and Matching Both ART and LAMINAR 'I' predict that attention from higher cortical areas, such as area V2, acts on cells in area V1 via a top-clown modulatory on-center off-surround  ... 
doi:10.1016/b978-012375731-9/50111-7 fatcat:fmvqvxyij5grtpcow2kyay6zzy

Deep Modeling of Growth Trajectories for Longitudinal Prediction of Missing Infant Cortical Surfaces [article]

Peirong Liu, Zhengwang Wu, Gang Li, Pew-Thian Yap, Dinggang Shen
2020 arXiv   pre-print
The proposed method is designed to model the cortical growth trajectories and jointly predict inner and outer cortical surfaces at multiple time points.  ...  Predicting the surfaces directly allows cortical attributes such as cortical thickness, curvature, and convexity to be computed for subsequent analysis.  ...  Our method is able to learn intrinsic, non-linear growth features via spatial convolution directly applied on the cortical surfaces.  ... 
arXiv:2009.02797v2 fatcat:xmjy3czkffelzf5ky3rt6anm5a

Neural inhibition for continual learning and memory

Helen C Barron
2021 Current Opinion in Neurobiology  
I present recent findings from studies in humans that suggest inhibition regulates the stability of neural networks to gate cortical plasticity and memory retrieval.  ...  Yet, this new learning does not necessarily occur at the expense of old memories.  ...  During multi-trial learning, measures of cortical inhibition acquired using MRS reveal a rapid, reversible decrease in neocortical GABA, where a larger drop in GABA predicts superior learning.  ... 
doi:10.1016/j.conb.2020.09.007 pmid:33129012 pmcid:PMC7116367 fatcat:7dwjyrkgovf6nidbkh27uvz47i

Neuroscientific implications for situated and embodied artificial intelligence

Keith L. Downing
2007 Connection science  
systems still struggle to properly incorporate commonsense knowledge, Situated and Embodied Artificial Intelligence (SEAI) aims to build animats that acquire a commonsense understanding of the world via  ...  Neuroscientists believe that much of this common sense involves predictive models for physical activities, but the transfer of sensorimotor skill knowledge to cognition is non-trivial, indicating that  ...  Basically, the cortical predictive mechanisms would learn to complete C by assumption, rather than by additional sensory input.  ... 
doi:10.1080/09540090701192584 fatcat:whffzwwttffmzbnpimfaz3od5m

Reinforcement-guided learning in frontal neocortex: emerging computational concepts

Abhishek Banerjee, Rajeev V Rikhye, Adam Marblestone
2021 Current Opinion in Behavioral Sciences  
The classical concepts of reinforcement learning in the mammalian brain focus on dopamine release in the basal ganglia as the neural substrate of reward prediction errors, which drive plasticity in striatal  ...  In this framework, reward drives plasticity in various neocortical regions, implementing multiple distinct reinforcement learning algorithms.  ...  using RL, and potentially by learning to implement entire RL algorithms cortically.  ... 
doi:10.1016/j.cobeha.2021.02.019 fatcat:e23xwqtibzgidcuozvfdm47dzy

Prediction and memory: a predictive coding account

Helen C. Barron, Ryszard Auksztulewicz, Karl Friston
2020 Progress in Neurobiology  
This contrasts with empirical and theoretical work on predictive processing, where descending predictions suppress prediction errors to 'explain away' ascending inputs via cortical inhibition.  ...  Namely, during episodic recall, the hippocampus is thought to exert an excitatory influence on the neocortex, to reinstate activity patterns across cortical circuits.  ...  via inhibition and another that amplifies cortical activity patterns via disinhibition.  ... 
doi:10.1016/j.pneurobio.2020.101821 pmid:32446883 pmcid:PMC7305946 fatcat:3qdbjbshnfgrtcxzw6q2hmahhu

Bootstrapping your brain [chapter]

Earl K. Miller, Timothy J. Buschman
2007 Neurobiology of Learning and Memory  
Channels within the BG return outputs, via the thalamus, to the same cortical areas that gave rise to their initial cortical input, forming BG-cortex loops.  ...  via PFC activity patterns.  ... 
doi:10.1016/b978-012372540-0/50011-x fatcat:mzkzcpwsirhwzkfpp7avv3ehx4

Reconciling Predictive Coding and Biased Competition Models of Cortical Function

Michael W. Spratling
2008 Frontiers in Computational Neuroscience  
A simple variation of the standard biased competition model is shown, via some trivial mathematical manipulations, to be identical to predictive coding.  ...  Specifically, it is shown that a particular implementation of the biased competition model, in which nodes compete via inhibition that targets the inputs to a cortical region, is mathematically equivalent  ...  Attention operates via cortical feedback pathways (Desimone and Duncan, 1995; Mehta et al., 2000; Treue, 2001) .  ... 
doi:10.3389/neuro.10.004.2008 pmid:18978957 pmcid:PMC2576514 fatcat:umompdscxnd7xonea4aph5k7wy

Relating Cortical Wave Dynamics to Learning and Remembering

Eduardo Mercado III
2014 AIMS Neuroscience  
Here, an alternative theoretical framework is suggested that integrates Pavlovian hypotheses about learning and cortical function with concepts from contemporary proceduralist theories of memory.  ...  performances, may provide new insights into the nature of learning and memory.  ...  Acknowledgments This research was supported in part by NSF grant #SBE-0542013 to the Temporal Dynamics of Learning Center, an NSF Science of Learning Center.  ... 
doi:10.3934/neuroscience.2014.3.185 fatcat:cv5nswjcgvg6fjmdxhof6gtkvu
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