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Behavioral flexibility is learning from previous experiences and planning appropriate actions in a changing or novel environment. Successful behavioral adaptation depends on internal models the brain builds to represent the relational…

Neurons and Cognition · Quantitative Biology 2021-07-01 Linda Q. Yu , Seongmin A. Park , Sarah C. Sweigart , Erie D. Boorman , Matthew R. Nassar

Value guides behavior. With knowledge of stimulus values and action consequences, behaviors that maximize expected reward can be selected. Prior work has identified several brain structures critical for representing both stimuli and their…

Neurons and Cognition · Quantitative Biology 2016-07-15 Marcelo G Mattar , Sharon L Thompson-Schill , Danielle S Bassett

The human cognitive system is a remarkable exemplar of a general intelligent system whose competence is not confined to a specific problem domain. Evidently, general cognitive competences are a product of a prolonged and complex process of…

Neurons and Cognition · Quantitative Biology 2014-12-16 David Weinbaum , Viktoras Veitas

This is a follow-up tutorial article of [17] and [16], in this paper, we will introduce several important cognitive functions of the brain. Brain cognitive functions are the mental processes that allow us to receive, select, store,…

Neurons and Cognition · Quantitative Biology 2019-07-08 Jiawei Zhang

As we discussed in Part I of this topic, there is a clear desire to model and comprehend human behavior. Given the popular presupposition of human reasoning as the standard for learning and decision-making, there have been significant…

Artificial Intelligence · Computer Science 2022-05-16 Andrew Fuchs , Andrea Passarella , Marco Conti

I think that the main reason why we do not understand the general principles of how knowledge works (and probably also the reason why we have not yet designed and built efficient machines capable of artificial intelligence), is not the…

Artificial Intelligence · Computer Science 2014-04-21 Devis Pantano

Human navigation has been a topic of interest in spatial cognition from the past few decades. It has been experimentally observed that humans accomplish the task of way-finding a destination in an unknown environment by recognizing…

Social and Information Networks · Computer Science 2011-11-22 Vijesh M. , Sudarshan Iyengar , Vijay Mahantesh , Amitash Ramesh , Veni Madhavan

We introduce a novel approach to endowing neural networks with emergent, long-term, large-scale memory. Distinct from strategies that connect neural networks to external memory banks via intricately crafted controllers and hand-designed…

Machine Learning · Computer Science 2020-08-18 Tri Huynh , Michael Maire , Matthew R. Walter

Recent progress in artificial intelligence (AI) has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as object recognition, video…

Artificial Intelligence · Computer Science 2016-11-03 Brenden M. Lake , Tomer D. Ullman , Joshua B. Tenenbaum , Samuel J. Gershman

Human cognition emerges from coordinated spiking dynamics in distributed neural circuits, where information is encoded via both firing rates and precise spike timing determined by brain rhythms. Inspired by this notion, we propose a…

Neurons and Cognition · Quantitative Biology 2026-05-05 Tingting Dan , Guorong Wu

One fascinating aspect of the brain is its ability to process information in a fast and reliable manner. The functional architecture is thought to play a central role in this task, by encoding efficiently complex stimuli and facilitating…

Neurons and Cognition · Quantitative Biology 2016-02-17 Alberto Romagnoni , Jérôme Ribot , Daniel Bennequin , Jonathan D. Touboul

This article presents an artificial intelligence (AI) architecture intended to simulate the iterative updating of the human working memory system. It features several interconnected neural networks designed to emulate the specialized…

Neurons and Cognition · Quantitative Biology 2026-02-11 Jared Edward Reser

This article provides an analytical framework for how to simulate human-like thought processes within a computer. It describes how attention and memory should be structured, updated, and utilized to search for associative additions to the…

Neurons and Cognition · Quantitative Biology 2024-11-15 Jared Edward Reser

The human brain achieves its remarkable computational prowess not despite its inherent non-ideal factors noise, heterogeneity, structural irregularities, decentralized plasticity, systematic errors, and chaotic dynamics but precisely…

Neurons and Cognition · Quantitative Biology 2026-03-24 Da-Zheng Feng , Hao-Xuan Du

Self-organization is ubiquitous in nature and mind. However, machine learning and theories of cognition still barely touch the subject. The hurdle is that general patterns are difficult to define in terms of dynamical equations and…

Artificial Intelligence · Computer Science 2023-02-07 Danilo Vasconcellos Vargas , Tham Yik Foong , Heng Zhang

Humans are remarkably flexible when understanding new sentences that include combinations of concepts they have never encountered before. Recent work has shown that while deep networks can mimic some human language abilities when presented…

Computation and Language · Computer Science 2021-10-20 Yen-Ling Kuo , Boris Katz , Andrei Barbu

We study functional activity in the human brain using functional Magnetic Resonance Imaging and recently developed tools from network science. The data arise from the performance of a simple behavioural motor learning task. Unsupervised…

Human intelligence is characterized not only by the capacity to learn complex skills, but the ability to rapidly adapt and acquire new skills within an ever-changing environment. In this work we study how the learning of modular solutions…

Machine Learning · Computer Science 2020-10-26 Jianan Wang , Eren Sezener , David Budden , Marcus Hutter , Joel Veness

Individual-intelligence research, from a neurological perspective, discusses the hierarchical layers of the cortex as a structure that performs conceptual abstraction and specification. This theory has been used to explain how motor-cortex…

Computers and Society · Computer Science 2007-05-23 Marko A. Rodriguez

Chaos is generic in strongly-coupled recurrent networks of model neurons, and thought to be an easily accessible dynamical regime in the brain. While neural chaos is typically seen as an impediment to robust computation, we show how such…

Neurons and Cognition · Quantitative Biology 2024-09-30 Rishidev Chaudhuri , Vivek Handebagh
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