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The human brain is the substrate for human intelligence. By simulating the human brain, artificial intelligence builds computational models that have learning capabilities and perform intelligent tasks approaching the human level. Deep…

神经元与认知 · 定量生物学 2024-02-20 Barco Jie You

In this paper, we will provide an introduction to the brain structure and function. Brain is an astonishing living organ inside our heads, weighing about 1.5kg, consisting of billions of tiny cells. The brain enables us to sense the world…

神经元与认知 · 定量生物学 2019-06-11 Jiawei Zhang

Despite the rapid pace at which deep networks are improving on standardized vision benchmarks, they are still outperformed by humans on real-world vision tasks. One solution to this problem is to make deep networks more brain-like. Although…

计算机视觉与模式识别 · 计算机科学 2025-12-12 Niranjan Rajesh , Georgin Jacob , SP Arun

The mammalian brain could contain dense and sparse network connectivity structures, including both excitatory and inhibitory neurons, but is without any clearly defined output layer. The neurons have time constants, which mean that the…

神经元与认知 · 定量生物学 2021-06-04 Udaya B. Rongala , Henrik Jörntell

The brain is an intricately structured organ responsible for the rich emergent dynamics that support the complex cognitive functions we enjoy as humans. With around $10^{11}$ neurons and $10^{15}$ synapses, understanding how the human brain…

神经元与认知 · 定量生物学 2019-02-12 Jason Z. Kim , Danielle S. Bassett

Degeneration and adaptation are two competing sides of the same coin called resilience in the progressive processes of brain aging or diseases. Degeneration accumulates during brain aging and other cerebral activities, causing structural…

A fundamental feature of human intelligence is that we accumulate and transfer knowledge as a society and across generations. We describe here a network architecture for the human brain that may support this feature and suggest that two key…

神经元与认知 · 定量生物学 2022-07-19 Eric C. Wong

In this review, we describe the singular success of attractor neural network models in describing how the brain maintains persistent activity states for working memory, error-corrects, and integrates noisy cues. We consider the mechanisms…

神经元与认知 · 定量生物学 2022-03-03 Mikail Khona , Ila R. Fiete

A given neural network in the brain is involved in many different tasks. This implies that, when considering a specific task, the network's connectivity contains a component which is related to the task and another component which can be…

神经元与认知 · 定量生物学 2021-03-17 Friedrich Schuessler , Alexis Dubreuil , Francesca Mastrogiuseppe , Srdjan Ostojic , Omri Barak

A hallmark of human intelligence is the ability to adapt to new situations, by applying learned rules to new content (systematicity) and thereby enabling an open-ended number of inferences and actions (generativity). Here, we propose that…

神经元与认知 · 定量生物学 2021-08-10 Randall C. O'Reilly , Charan Ranganath , Jacob L. Russin

Nowadays, we have witnessed the great success of AI in various applications, including image classification, game playing, protein structure analysis, language translation, and content generation. Despite these powerful applications, there…

Several approaches to cognition and intelligence research rely on statistics-based models testing, namely factor analysis. In the present work we exploit the emerging dynamical systems perspective putting the focus on the role of the…

物理与社会 · 物理学 2018-03-15 Gemma Rosell-Tarragó , Emanuele Cozzo , Albert Díaz-Guilera

Functional networks provide a topological description of activity patterns in the brain, as they stem from the propagation of neural activity on the underlying anatomical or structural network of synaptic connections. This latter is well…

无序系统与神经网络 · 物理学 2021-02-11 Ali Safari , Paolo Moretti , Ibai Diez , Jesus M. Cortes , Miguel Ángel Muñoz

Self-sustained activity in the brain is observed in the absence of external stimuli and contributes to signal propagation, neural coding, and dynamic stability. It also plays an important role in cognitive processes. In this work, by means…

The continuous integration of experimental data into coherent models of the brain is an increasing challenge of modern neuroscience. Such models provide a bridge between structure and activity, and identify the mechanisms giving rise to…

神经元与认知 · 定量生物学 2017-03-03 Jannis Schuecker , Maximilian Schmidt , Sacha J. van Albada , Markus Diesmann , Moritz Helias

A growing body of research indicates that structural plasticity mechanisms are crucial for learning and memory consolidation. Starting from a simple phenomenological model, we exploit a mean-field approach to develop a theoretical framework…

神经元与认知 · 定量生物学 2024-06-19 Gianmarco Tiddia , Luca Sergi , Bruno Golosio

Humans excel at continually acquiring, consolidating, and retaining information from an ever-changing environment, whereas artificial neural networks (ANNs) exhibit catastrophic forgetting. There are considerable differences in the…

神经与进化计算 · 计算机科学 2023-04-17 Fahad Sarfraz , Elahe Arani , Bahram Zonooz

A neuron is a basic physiological and computational unit of the brain. While much is known about the physiological properties of a neuron, its computational role is poorly understood. Here we propose to view a neuron as a signal processing…

神经元与认知 · 定量生物学 2014-05-14 Tao Hu , Zaid J. Towfic , Cengiz Pehlevan , Alex Genkin , Dmitri B. Chklovskii

Large-scale white matter pathways crisscrossing the cortex create a complex pattern of connectivity that underlies human cognitive function. Generative mechanisms for this architecture have been difficult to identify in part because little…

神经元与认知 · 定量生物学 2015-06-16 Florian Klimm , Danielle S. Bassett , Jean M. Carlson , Peter J. Mucha

A fundamental question in the conjunction of information theory, biophysics, bioinformatics and thermodynamics relates to the principles and processes that guide the development of natural intelligence in natural environments where…

神经与进化计算 · 计算机科学 2024-12-31 Serge Dolgikh