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Black Holes as Brains: Neural Networks with Area Law Entropy

Black Holes As Brains: Neural Networks With Area Law Entropy

Motivated by the potential similarities between the underlying mechanisms of the enhanced memory storage capacity in black holes and in brain networks, we construct an artificial quantum neural network based on gravity-like synaptic connections and a symmetry structure that allows to describe the network in terms of geometry of a d-dimensional space. We show that the network possesses a critical state in which the gapless neurons emerge that appear to inhabit a (d-1)-dimensional surface, with their number given by the surface area. In the excitations of these neurons, the network can store and retrieve an exponentially large number of patterns within an arbitrarily narrow energy gap. The corresponding micro-state entropy of the brain network exhibits an area law. The neural network can be described in terms of a quantum field, via identifying the different neurons with the different momentum modes of the field, while identifying the synaptic connections among the neurons with the interactions among the corres Jan 11, 2018 ... ... and in brain networks, we construct an artificial quantum neural network ... The corresponding micro-state entropy of the brain network ... [ReadMore..]

Deep Neural Networks: A New Framework for Modeling Biological ...

Deep Neural Networks: A New Framework For Modeling Biological ...

Recent advances in neural network modeling have enabled major strides in computer vision and other artificial intelligence applications. Human-level visual recognition abilities are coming within reach of artificial systems. Artificial neural networks are inspired by the brain, and their computations could be implemented in biological neurons. Convolutional feedforward networks, which now dominate computer vision, take further inspiration from the architecture of the primate visual hierarchy. However, the current models are designed with engineering goals, not to model brain computations. Nevertheless, initial studies comparing internal representations between these models and primate brains find surprisingly similar representational spaces. With human-level performance no longer out of reach, we are entering an exciting new era, in which we will be able to build biologically faithful feedforward and recurrent computational models of how biological brains perform high-level feats of intelligence, including vi The brain is a deep and complex recurrent neural network. The ... [ReadMore..]

Modeling human brain function with artificial neural networks

Modeling Human Brain Function With Artificial Neural Networks

Artificial neural networks. An artificial neural network (ANN) is a computational model that is loosely inspired by the human brain consisting of an ... [ReadMore..]

Human Cortical Organoids Model Neuronal Networks | The Scientist ...

Human Cortical Organoids Model Neuronal Networks | The Scientist ...

After growing in culture for a few months, the mini-brains produced rhythmic neural activity that strengthened over time. Aug 29, 2019 ... After growing in culture for a few months, the mini-brains produced rhythmic neural activity that strengthened over time. [ReadMore..]

neural network | computing | Britannica

Neural Network | Computing | Britannica

neural network, a computer program that operates in a manner inspired by the natural neural network in the brain. The objective of such artificial neural networks is to perform such cognitive functions as problem solving and machine learning. The theoretical basis of neural networks was developed in 1943 by the neurophysiologist Warren McCulloch of the University of Illinois and the mathematician Walter Pitts of the University of Chicago. In 1954 Belmont Farley and Wesley Clark of the Massachusetts Institute of Technology succeeded in running the first simple neural network. The primary appeal of neural networks is their ability to emulate neural network, a computer program that operates in a manner inspired by the natural neural network in the brain. The objective of such artificial neural ... [ReadMore..]

A Brief Introduction to the Brain:Neural Nets

A Brief Introduction To The Brain:Neural Nets

In the brain, a typical neuron collect signals from others through a host of fine structures called dendrites. The neuron sends out spikes of electrical ... [ReadMore..]

Ultramicroscopy: three-dimensional visualization of neuronal ...

Ultramicroscopy: Three-dimensional Visualization Of Neuronal ...

Mar 25, 2007 ... Visualizing entire neuronal networks for analysis in the intact brain has been impossible up to now. Techniques like computer tomography or ... [ReadMore..]

What are Neural Networks? | IBM

What Are Neural Networks? | IBM

Learn about neural networks that allow programs to recognize patterns and solve common problems in artificial intelligence, machine learning and deep learning. Aug 17, 2020 ... Their name and structure are inspired by the human brain, mimicking the way that biological neurons signal to one another. Artificial neural ... [ReadMore..]

Human Brain's Neuronal Network Has Similarities to Cosmic Web ...

Human Brain's Neuronal Network Has Similarities To Cosmic Web ...

In a paper published this week in the journal Frontiers of Physics, a duo of researchers from Italy investigated the similarities between the network of neurons in the human brain and the cosmic network of galaxies. Nov 18, 2020 ... The human brain is a complex temporally and spatially multiscale structure in which cellular, molecular and neuronal phenomena coexist. It can ... [ReadMore..]

Neuronal network disintegration: common pathways linking ...

Neuronal Network Disintegration: Common Pathways Linking ...

Neurodegeneration refers to a heterogeneous group of brain disorders that progressively evolve. It has been increasingly appreciated that many neurodegenerative ... [ReadMore..]

NSF Award Search: Award # 1940162 - Collaborative Research ...

NSF Award Search: Award # 1940162 - Collaborative Research ...

Collaborative Research: MEMONET: Understanding memory in neuronal networks through a brain-inspired spin-based artificial intelligence ... [ReadMore..]