Advantages of dilution in the connectivity of attractor networks in the brain
نویسنده
چکیده
r a 201 ica.2012 olls@oxc g Abstract A fundamental question about brain function is why the connectivity in the cortex is diluted, in that neurons in a local region of the neocortex and in the CA3 part of the hippocampal cortex typically have a probability of having a synaptic connection between them that is less than 0.1. In both these types of cortex, there is evidence that the excitatory interconnections between neurons are associatively modifiable, and that the system supports attractor dynamics that enable memories to be stored, which are used in for example short-term memory and in episodic memory. The hypothesis proposed is that the diluted connectivity allows biological processes that set up synaptic connections between neurons to arrange for there to be only very rarely more than one synaptic connection between any pair of neurons. If probabilistically there were more than one connection between any two neurons, it is shown by simulation of an autoassociation attractor network that such connections would dominate the attractor states into which the network could enter and be stable, thus strongly reducing the memory capacity of the network (the number of memories that can be stored and correctly retrieved), below the normal large capacity for diluted connectivity. Diluted connectivity between neurons in the cortex thus has an important role in allowing high capacity of memory networks in the cortex, and helping to ensuring that the critical capacity is not reached at which overloading occurs leading to an impairment in the ability to retrieve any memories from the network. This intra-area diluted connectivity complements the diluted connectivity in the feedforward connections between cortical areas that helps the representations built by competitive learning to be stable. a 2012 Elsevier B.V. All rights reserved.
منابع مشابه
Evaluation of Model-Based Methods in Estimating Dynamic Functional Connectivity of Brain Regions
Today, neuroscientists are interested in discovering human brain functions through brain networks. In this regard, the evaluation of dynamic changes in functional connectivity of the brain regions by using functional magnetic resonance imaging data has attracted their attention. In this paper, we focus on two model-based approaches, called the exponential weighted moving average model and the d...
متن کاملDetection of schizophrenia patients using convolutional neural networks from brain effective connectivity maps of electroencephalogram signals
Background: Schizophrenia is a mental disorder that severely affects the perception and relations of individuals. Nowadays, this disease is diagnosed by psychiatrists based on psychiatric tests, which is highly dependent on their experience and knowledge. This study aimed to design a fully automated framework for the diagnosis of schizophrenia from electroencephalogram signals using advanced de...
متن کاملComputer-Aided Tinnitus Detection based on Brain Network Analysis of EEG Functional Connectivity
Background: Tinnitus known as a central nervous system disorder is correlated with specific oscillatory activities within auditory and non-auditory brain areas. Several studies in the past few years have revealed that in the most tinnitus cases, the response pattern of neurons in auditory system is changed due to auditory deafferentation, which leads to variation and disruption of the brain net...
متن کاملChanges in Effective Connectivity Network Patterns in Drug Abusers, Treated With Different Methods
Introduction: Various treatment methods for drug abusers will result in different success rates. This is partly due to different neural assumptions and partly due to various rate of relapse in abusers because of different circumstances. Investigating the brain activation networks of treated subjects can reveal the hidden mechanisms of the therapeutic methods. Methods: We studied three groups o...
متن کاملENERGY AWARE DISTRIBUTED PARTITIONING DETECTION AND CONNECTIVITY RESTORATION ALGORITHM IN WIRELESS SENSOR NETWORKS
Mobile sensor networks rely heavily on inter-sensor connectivity for collection of data. Nodes in these networks monitor different regions of an area of interest and collectively present a global overview of some monitored activities or phenomena. A failure of a sensor leads to loss of connectivity and may cause partitioning of the network into disjoint segments. A number of approaches have be...
متن کاملA new conforming mesh generator for three-dimensional discrete fracture networks
Nowadays, numerical modelings play a key role in analyzing hydraulic problems in fractured rock media. The discrete fracture network model is one of the most used numerical models to simulate the geometrical structure of a rock-mass. In such media, discontinuities are considered as discrete paths for fluid flow through the rock-mass while its matrix is assumed impermeable. There are two main pa...
متن کامل