The Role Of Synaptic Tagging And Capture For Memory Dynamics In Spiking Neural Networks

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The Role of Synaptic Tagging and Capture for Memory Dynamics in Spiking Neural Networks

Author : Jannik Luboeinski
Publisher :
ISBN 13 :
Total Pages : 201 pages
Book Rating : 4./5 ( download)

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Book Synopsis The Role of Synaptic Tagging and Capture for Memory Dynamics in Spiking Neural Networks by : Jannik Luboeinski

Download or read book The Role of Synaptic Tagging and Capture for Memory Dynamics in Spiking Neural Networks written by Jannik Luboeinski and published by . This book was released on 2021-09-02 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: Memory serves to process and store information about experiences such that this information can be used in future situations. The transfer from transient storage into long-term memory, which retains information for hours, days, and even years, is called consolidation. In brains, information is primarily stored via alteration of synapses, so-called synaptic plasticity. While these changes are at first in a transient early phase, they can be transferred to a late phase, meaning that they become stabilized over the course of several hours. This stabilization has been explained by so-called synaptic tagging and capture (STC) mechanisms. To store and recall memory representations, emergent dynamics arise from the synaptic structure of recurrent networks of neurons. This happens through so-called cell assemblies, which feature particularly strong synapses. It has been proposed that the stabilization of such cell assemblies by STC corresponds to so-called synaptic consolidation, which is observed in humans and other animals in the first hours after acquiring a new memory. The exact connection between the physiological mechanisms of STC and memory consolidation remains, however, unclear. It is equally unknown which influence STC mechanisms exert on further cognitive functions that guide behavior. On timescales of minutes to hours (that means, the timescales of STC) such functions include memory improvement, modification of memories, interference and enhancement of similar memories, and transient priming of certain memories. Thus, diverse memory dynamics may be linked to STC, which can be investigated by employing theoretical methods based on experimental data from the neuronal and the behavioral level. In this thesis, we present a theoretical model of STC-based memory consolidation in recurrent networks of spiking neurons, which are particularly suited to reproduce biologically realistic dynamics. Furthermore, we combine the STC mechanisms with calcium dynamics, which have been found to guide the major processes of early-phase synaptic plasticity in vivo. In three included research articles as well as additional sections, we develop this model and investigate how it can account for a variety of behavioral effects. We find that the model enables the robust implementation of the cognitive memory functions mentioned above. The main steps to this are: 1. demonstrating the formation, consolidation, and improvement of memories represented by cell assemblies, 2. showing that neuromodulator-dependent STC can retroactively control whether information is stored in a temporal or rate-based neural code, and 3. examining interaction of multiple cell assemblies with transient and attractor dynamics in different organizational paradigms. In summary, we demonstrate several ways by which STC controls the late-phase synaptic structure of cell assemblies. Linking these structures to functional dynamics, we show that our STC-based model implements functionality that can be related to long-term memory. Thereby, we provide a basis for the mechanistic explanation of various neuropsychological effects. Keywords: synaptic plasticity; synaptic tagging and capture; spiking recurrent neural networks; memory consolidation; long-term memory

The Role of Synaptic Tagging and Capture for Memory Dynamics in Spiking Neural Networks

Author : Jannik Luboeinski
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (126 download)

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Book Synopsis The Role of Synaptic Tagging and Capture for Memory Dynamics in Spiking Neural Networks by : Jannik Luboeinski

Synaptic Tagging and Capture

Author : Sreedharan Sajikumar
Publisher : Springer Nature
ISBN 13 : 3031548647
Total Pages : 507 pages
Book Rating : 4.0/5 (315 download)

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Book Synopsis Synaptic Tagging and Capture by : Sreedharan Sajikumar

Download or read book Synaptic Tagging and Capture written by Sreedharan Sajikumar and published by Springer Nature. This book was released on with total page 507 pages. Available in PDF, EPUB and Kindle. Book excerpt:

The Role of Short-term Synaptic Plasticity in Neural Network Spiking Dynamics and in the Learning of Multiple Distal Rewards

Author : Michael John O'Brien
Publisher :
ISBN 13 :
Total Pages : 135 pages
Book Rating : 4.:/5 (853 download)

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Book Synopsis The Role of Short-term Synaptic Plasticity in Neural Network Spiking Dynamics and in the Learning of Multiple Distal Rewards by : Michael John O'Brien

Download or read book The Role of Short-term Synaptic Plasticity in Neural Network Spiking Dynamics and in the Learning of Multiple Distal Rewards written by Michael John O'Brien and published by . This book was released on 2013 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, we assess the role of short-term synaptic plasticity in an artificial neural network constructed to emulate two important brain functions: self-sustained activity and signal propagation. We employ a widely used short-term synaptic plasticity model (STP) in a symbiotic network, in which two subnetworks with differently tuned STP behaviors are weakly coupled. This enables both self-sustained global network activity, generated by one of the subnetworks, as well as faithful signal propagation within subcircuits of the other subnetwork. Finding the parameters for a properly tuned STP network is difficult. We provide a theoretical argument for a method which boosts the probability of finding the elusive STP parameters by two orders of magnitude, as demonstrated in tests. We then combine STP with a novel critic-like synaptic learning algorithm, which we call ARG-STDP for attenuated-reward-gating of STDP. STDP refers to a commonly used long term synaptic plasticity model called spike-timing dependent plasticity. With ARG-STDP, we are able to learn multiple distal rewards simultaneously, improving on the previous reward modulated STDP (R-STDP) that could learn only a single distal reward. However, we also provide a theoretical upperbound on the number of distal reward that can be learned using ARG-STDP. We also consider the problem of simulating large spiking neural networks. We describe an architecture for efficiently simulating such networks. The architecture is suitable for implementation on a cluster of General Purpose Graphical Processing Units (GPGPU). Novel aspects of the architecture are described and an analysis of its performance is benchmarked on a GPGPU cluster. With the advent of inexpensive GPGPU cards and compute power, the described architecture offers an affordable and scalable tool for the design, real-time simulation, and analysis of large scale spiking neural networks. DP.

Improving Associative Memory in a Network of Spiking Neurons

Author : Russell I. Hunter
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (16 download)

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Book Synopsis Improving Associative Memory in a Network of Spiking Neurons by : Russell I. Hunter

Download or read book Improving Associative Memory in a Network of Spiking Neurons written by Russell I. Hunter and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis we use computational neural network models to examine the dynamics and functionality of the CA3 region of the mammalian hippocampus. The emphasis of the project is to investigate how the dynamic control structures provided by inhibitory circuitry and cellular modification may effect the CA3 region during the recall of previously stored information. The CA3 region is commonly thought to work as a recurrent auto-associative neural network due to the neurophysiological characteristics found, such as, recurrent collaterals, strong and sparse synapses from external inputs and plasticity between coactive cells. Associative memory models have been developed using various configurations of mathematical artificial neural networks which were first developed over 40 years ago. Within these models we can store information via changes in the strength of connections between simplified model neurons (two-state). These memories can be recalled when a cue (noisy or partial) is instantiated upon the net. The type of information they can store is quite limited due to restrictions caused by the simplicity of the hard-limiting nodes which are commonly associated with a binary activation threshold. We build a much more biologically plausible model with complex spiking cell models and with realistic synaptic properties between cells. This model is based upon some of the many details we now know of the neuronal circuitry of the CA3 region. We implemented the model in computer software using Neuron and Matlab and tested it by running simulations of storage and recall in the network. By building this model we gain new insights into how different types of neurons, and the complex circuits they form, actually work. The mammalian brain consists of complex resistive-capacative electrical circuitry which is formed by the interconnection of large numbers of neurons. A principal cell type is the pyramidal cell within the cortex, which is the main information processor in our neural networks. Pyramidal cells are surrounded by diverse populations of interneurons which have proportionally smaller numbers compared to the pyramidal cells and these form connections with pyramidal cells and other inhibitory cells. By building detailed computational models of recurrent neural circuitry we explore how these microcircuits of interneurons control the flow of information through pyramidal cells and regulate the efficacy of the network. We also explore the effect of cellular modification due to neuronal activity and the effect of incorporating spatially dependent connectivity on the network during recall of previously stored information. In particular we implement a spiking neural network proposed by Sommer and Wennekers (2001). We consider methods for improving associative memory recall using methods inspired by the work by Graham and Willshaw (1995) where they apply mathematical transforms to an artificial neural network to improve the recall quality within the network. The networks tested contain either 100 or 1000 pyramidal cells with 10% connectivity applied and a partial cue instantiated, and with a global pseudo-inhibition. We investigate three methods. Firstly, applying localised disynaptic inhibition which will proportionalise the excitatory post synaptic potentials and provide a fast acting reversal potential which should help to reduce the variability in signal propagation between cells and provide further inhibition to help synchronise the network activity. Secondly, implementing a persistent sodium channel to the cell body which will act to non-linearise the activation threshold where after a given membrane potential the amplitude of the excitatory postsynaptic potential (EPSP) is boosted to push cells which receive slightly more excitation (most likely high units) over the firing threshold. Finally, implementing spatial characteristics of the dendritic tree will allow a greater probability of a modified synapse existing after 10% random connectivity has been applied throughout the network. We apply spatial characteristics by scaling the conductance weights of excitatory synapses which simulate the loss in potential in synapses found in the outer dendritic regions due to increased resistance. To further increase the biological plausibility of the network we remove the pseudo-inhibition and apply realistic basket cell models with differing configurations for a global inhibitory circuit. The networks are configured with; 1 single basket cell providing feedback inhibition, 10% basket cells providing feedback inhibition where 10 pyramidal cells connect to each basket cell and finally, 100% basket cells providing feedback inhibition. These networks are compared and contrasted for efficacy on recall quality and the effect on the network behaviour. We have found promising results from applying biologically plausible recall strategies and network configurations which suggests the role of inhibition and cellular dynamics are pivotal in learning and memory.

Synaptic Tagging and Capture Mechanisms During the Formation of Memory

Author : Bruno Miguel Ferreira Teixeira da Silva
Publisher :
ISBN 13 :
Total Pages : 196 pages
Book Rating : 4.:/5 (78 download)

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Book Synopsis Synaptic Tagging and Capture Mechanisms During the Formation of Memory by : Bruno Miguel Ferreira Teixeira da Silva

Download or read book Synaptic Tagging and Capture Mechanisms During the Formation of Memory written by Bruno Miguel Ferreira Teixeira da Silva and published by . This book was released on 2009 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: In everybody's lives, there are strong emotional or surprising events that, for being special, are vividly remembered for a lifetime. Sometimes, these memories include one-shot images or details of associated daily life events that, for being ordinary, should have been rapidly forgotten. Why and how does the brain form and retain detailed memories of trivial events? The synaptic tagging and capture (STC) hypothesis of memory formation (Frey & Morris, Nature 1997) provides a theoretical framework that might explain the formation of these flashbulb memories at a cellular level. The hypothesis suggests that strong events, producing long-lasting memories, might stabilise memory for weak events by up-regulating the synthesis of late-phase plasticity-related proteins in neurons encoding memory traces for both events. This thesis tests this prediction of the STC hypothesis during the formation of long-term place memory in rodents. First, two new behavioural tasks are developed which provide sensitive measures of rapidly acquired place memory persistence - a new one-trial place memory task in the "event arena" and a modified delayed matching-to-place (DMP) protocol in the watermaze. Persistence of place memory is assessed and compared in these tasks. Given the important role of NMDA receptor activation during STC mechanisms, the contribution of NMDA and AMPA receptor activation in the hippocampus for the encoding and retrieval of place memory, respectively, is also established. Finally, weak and strong encoding events, leading to the formation of either shortor long-lasting place memory in the watermaze DMP task, are characterized. A second series of experiments investigates the possibility of synergistic interactions between different encoding events that occur in two different watermazes. First, weak and strong encoding events are arranged to occur within a short time-window to test behavioural analogues of the "strong-before-weak" and "weak-before-strong" STC paradigms characterised in electrophysiological experiments in rat hippocampal slices (Frey and Morris, 1997, 1998b). Then, after establishing i) the time course and local specificity of protein synthesis inhibition by intra-hippocampal infusion of anisomycin in vivo, ii) the dependence of long-term memory for strong encoding events on protein synthesis in the hippocampus, and iii) the induction of transcriptional and translational mechanisms in the hippocampus by strong encoding events, a behavioural analogue of the "strong-before-strong" STC paradigm (Frey and Morris, 1997) is also investigated. The results of these experiments are supportive of i) a role for hippocampal NMDA receptor-mediated synaptic plasticity in the encoding of rapidly acquired place memory; ii) a role for hippocampal AMPA receptor-mediated synaptic transmission in both encoding and retrieval of memory; and iii) a role for transcriptional and translational mechanisms in the hippocampus in the stabilisation of place memory. However, no evidence could be found supporting the involvement of synaptic tagging and capture mechanisms during the formation of long-lasting place memory.

Neural Computation in Embodied Closed-Loop Systems for the Generation of Complex Behavior: From Biology to Technology

Author : Poramate Manoonpong
Publisher : Frontiers Media SA
ISBN 13 : 2889456056
Total Pages : 278 pages
Book Rating : 4.8/5 (894 download)

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Book Synopsis Neural Computation in Embodied Closed-Loop Systems for the Generation of Complex Behavior: From Biology to Technology by : Poramate Manoonpong

Download or read book Neural Computation in Embodied Closed-Loop Systems for the Generation of Complex Behavior: From Biology to Technology written by Poramate Manoonpong and published by Frontiers Media SA. This book was released on 2018-10-11 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: How can neural and morphological computations be effectively combined and realized in embodied closed-loop systems (e.g., robots) such that they can become more like living creatures in their level of performance? Understanding this will lead to new technologies and a variety of applications. To tackle this research question, here, we bring together experts from different fields (including Biology, Computational Neuroscience, Robotics, and Artificial Intelligence) to share their recent findings and ideas and to update our research community. This eBook collects 17 cutting edge research articles, covering neural and morphological computations as well as the transfer of results to real world applications, like prosthesis and orthosis control and neuromorphic hardware implementation.

Value and Reward Based Learning in Neurobots

Author : Jeffrey L Krichmar
Publisher : Frontiers Media SA
ISBN 13 : 2889194310
Total Pages : 159 pages
Book Rating : 4.8/5 (891 download)

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Book Synopsis Value and Reward Based Learning in Neurobots by : Jeffrey L Krichmar

Download or read book Value and Reward Based Learning in Neurobots written by Jeffrey L Krichmar and published by Frontiers Media SA. This book was released on 2015-03-05 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: Organisms are equipped with value systems that signal the salience of environmental cues to their nervous system, causing a change in the nervous system that results in modification of their behavior. These systems are necessary for an organism to adapt its behavior when an important environmental event occurs. A value system constitutes a basic assumption of what is good and bad for an agent. These value systems have been effectively used in robotic systems to shape behavior. For example, many robots have used models of the dopaminergic system to reinforce behavior that leads to rewards. Other modulatory systems that shape behavior are acetylcholine’s effect on attention, norepinephrine’s effect on vigilance, and serotonin’s effect on impulsiveness, mood, and risk. Moreover, hormonal systems such as oxytocin and its effect on trust constitute as a value system. This book presents current research involving neurobiologically inspired robots whose behavior is: 1) Shaped by value and reward learning, 2) adapted through interaction with the environment, and 3) shaped by extracting value from the environment.

Spike-timing dependent plasticity

Author : Henry Markram
Publisher : Frontiers E-books
ISBN 13 : 2889190439
Total Pages : 575 pages
Book Rating : 4.8/5 (891 download)

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Book Synopsis Spike-timing dependent plasticity by : Henry Markram

Download or read book Spike-timing dependent plasticity written by Henry Markram and published by Frontiers E-books. This book was released on with total page 575 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hebb's postulate provided a crucial framework to understand synaptic alterations underlying learning and memory. Hebb's theory proposed that neurons that fire together, also wire together, which provided the logical framework for the strengthening of synapses. Weakening of synapses was however addressed by "not being strengthened", and it was only later that the active decrease of synaptic strength was introduced through the discovery of long-term depression caused by low frequency stimulation of the presynaptic neuron. In 1994, it was found that the precise relative timing of pre and postynaptic spikes determined not only the magnitude, but also the direction of synaptic alterations when two neurons are active together. Neurons that fire together may therefore not necessarily wire together if the precise timing of the spikes involved are not tighly correlated. In the subsequent 15 years, Spike Timing Dependent Plasticity (STDP) has been found in multiple brain brain regions and in many different species. The size and shape of the time windows in which positive and negative changes can be made vary for different brain regions, but the core principle of spike timing dependent changes remain. A large number of theoretical studies have also been conducted during this period that explore the computational function of this driving principle and STDP algorithms have become the main learning algorithm when modeling neural networks. This Research Topic will bring together all the key experimental and theoretical research on STDP.

Inhibitory Synaptic Plasticity

Author : Melanie A. Woodin
Publisher : Springer Science & Business Media
ISBN 13 : 1441969780
Total Pages : 191 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Inhibitory Synaptic Plasticity by : Melanie A. Woodin

Download or read book Inhibitory Synaptic Plasticity written by Melanie A. Woodin and published by Springer Science & Business Media. This book was released on 2010-11-02 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume will explore the most recent findings on cellular mechanisms of inhibitory plasticity and its functional role in shaping neuronal circuits, their rewiring in response to experience, drug addiction and in neuropathology. Inhibitory Synaptic Plasticity will be of particular interest to neuroscientists and neurophysiologists.

From Neuron to Cognition via Computational Neuroscience

Author : Michael A. Arbib
Publisher : MIT Press
ISBN 13 : 0262335271
Total Pages : 810 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis From Neuron to Cognition via Computational Neuroscience by : Michael A. Arbib

Download or read book From Neuron to Cognition via Computational Neuroscience written by Michael A. Arbib and published by MIT Press. This book was released on 2016-11-04 with total page 810 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive, integrated, and accessible textbook presenting core neuroscientific topics from a computational perspective, tracing a path from cells and circuits to behavior and cognition. This textbook presents a wide range of subjects in neuroscience from a computational perspective. It offers a comprehensive, integrated introduction to core topics, using computational tools to trace a path from neurons and circuits to behavior and cognition. Moreover, the chapters show how computational neuroscience—methods for modeling the causal interactions underlying neural systems—complements empirical research in advancing the understanding of brain and behavior. The chapters—all by leaders in the field, and carefully integrated by the editors—cover such subjects as action and motor control; neuroplasticity, neuromodulation, and reinforcement learning; vision; and language—the core of human cognition. The book can be used for advanced undergraduate or graduate level courses. It presents all necessary background in neuroscience beyond basic facts about neurons and synapses and general ideas about the structure and function of the human brain. Students should be familiar with differential equations and probability theory, and be able to pick up the basics of programming in MATLAB and/or Python. Slides, exercises, and other ancillary materials are freely available online, and many of the models described in the chapters are documented in the brain operation database, BODB (which is also described in a book chapter). Contributors Michael A. Arbib, Joseph Ayers, James Bednar, Andrej Bicanski, James J. Bonaiuto, Nicolas Brunel, Jean-Marie Cabelguen, Carmen Canavier, Angelo Cangelosi, Richard P. Cooper, Carlos R. Cortes, Nathaniel Daw, Paul Dean, Peter Ford Dominey, Pierre Enel, Jean-Marc Fellous, Stefano Fusi, Wulfram Gerstner, Frank Grasso, Jacqueline A. Griego, Ziad M. Hafed, Michael E. Hasselmo, Auke Ijspeert, Stephanie Jones, Daniel Kersten, Jeremie Knuesel, Owen Lewis, William W. Lytton, Tomaso Poggio, John Porrill, Tony J. Prescott, John Rinzel, Edmund Rolls, Jonathan Rubin, Nicolas Schweighofer, Mohamed A. Sherif, Malle A. Tagamets, Paul F. M. J. Verschure, Nathan Vierling-Claasen, Xiao-Jing Wang, Christopher Williams, Ransom Winder, Alan L. Yuille

Local Cortical Circuits

Author : Moshe Abeles
Publisher : Springer Science & Business Media
ISBN 13 : 3642817084
Total Pages : 105 pages
Book Rating : 4.6/5 (428 download)

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Book Synopsis Local Cortical Circuits by : Moshe Abeles

Download or read book Local Cortical Circuits written by Moshe Abeles and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 105 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neurophysiologists are often accused by colleagues in the physical sci ences of designing experiments without any underlying hypothesis. This impression is attributable to the ease of getting lost in the ever-increasing sea of professional publications which do not state explicitly the ultimate goal of the research. On the other hand, many of the explicit models for brain function in the past were so far removed from experimental reality that they had very little impact on further research. It seems that one needs much intimate experience with the real nerv-. ous system before a reasonable model can be suggested. It would have been impossible for Copernicus to suggest his model of the solar system without the detailed observations and tabulations of star and planet motion accu mulated by the preceeding generations. This need for intimate experience with the nervous system before daring to put forward some hypothesis about its mechanism of action is especially apparent when theorizing about cerebral cortex function. There is widespread agreement that processing of information in the cor tex is associated with complex spatio-temporal patterns of activity. Yet the vast majority of experimental work is based on single neuron recordings or on recordings made with gross electrodes to which tens of thousands of neurons contribute in an unknown fashion. Although these experiments have taught us a great deal about the organization and function of the cor tex, they have not enabled us to examine the spatio-temporal organization of neuronal activity in any detail.

Synaptic Plasticity in the Hippocampus

Author : Helmut L. Haas
Publisher : Springer Science & Business Media
ISBN 13 : 364273202X
Total Pages : 219 pages
Book Rating : 4.6/5 (427 download)

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Book Synopsis Synaptic Plasticity in the Hippocampus by : Helmut L. Haas

Download or read book Synaptic Plasticity in the Hippocampus written by Helmut L. Haas and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the second time that I have had the honor of opening an interna tional symposium dedicated to the functions of the hippocampus here in Pecs. It was a pleasure to greet the participants in the hope that their valuable contributions will make this meeting a tradition in this town. As one of the hosts of the symposium, I had the sorrowful duty to remind you of the absence of a dear colleague, Professor Graham God dard. His tragic and untimely death represents the irreparable loss of both a friend and an excellent researcher. This symposium is dedicated to his memory. If I compare the topics of the lectures of this symposium with those of the previous one, a striking difference becomes apparent. A dominating tendency of the previous symposium was to attempt to define hippocam pal function or to offer data relevant to supporting or rejecting existing theoretical positions. No such tendency is reflected in the titles of the present symposium, in which most of the contributions deal with hip pocampal phenomena at the most elementary level. Electrical, biochemi cal, biophysical, and pharmacological events at the synaptic, membrane, or intracellular level are analyzed without raising the question of what kind of integral functions these elementary phenomena are a part of.

Spiking Neuron Models

Author : Wulfram Gerstner
Publisher : Cambridge University Press
ISBN 13 : 9780521890793
Total Pages : 498 pages
Book Rating : 4.8/5 (97 download)

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Book Synopsis Spiking Neuron Models by : Wulfram Gerstner

Download or read book Spiking Neuron Models written by Wulfram Gerstner and published by Cambridge University Press. This book was released on 2002-08-15 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neurons in the brain communicate by short electrical pulses, the so-called action potentials or spikes. How can we understand the process of spike generation? How can we understand information transmission by neurons? What happens if thousands of neurons are coupled together in a seemingly random network? How does the network connectivity determine the activity patterns? And, vice versa, how does the spike activity influence the connectivity pattern? These questions are addressed in this 2002 introduction to spiking neurons aimed at those taking courses in computational neuroscience, theoretical biology, biophysics, or neural networks. The approach will suit students of physics, mathematics, or computer science; it will also be useful for biologists who are interested in mathematical modelling. The text is enhanced by many worked examples and illustrations. There are no mathematical prerequisites beyond what the audience would meet as undergraduates: more advanced techniques are introduced in an elementary, concrete fashion when needed.

Synaptic Tagging and Capture

Author : Sreedharan Sajikumar
Publisher : Springer
ISBN 13 : 1493917617
Total Pages : 278 pages
Book Rating : 4.4/5 (939 download)

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Book Synopsis Synaptic Tagging and Capture by : Sreedharan Sajikumar

Download or read book Synaptic Tagging and Capture written by Sreedharan Sajikumar and published by Springer. This book was released on 2014-10-15 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Serves as a comprehensive introduction and overview of synaptic tagging and capture (STC) and covers the topic from molecular and cellular aspects to behavior. Circa 15 years ago the STC model was proposed to provide a conceptual basis for how short-term memories are transformed into long-term memories. Though the hypothesis remains unconfirmed due to technological limitations, the model is well consolidated and generally accepted in the field. Various researchers have investigated the cellular mechanisms for the formation of long-term memory using the STC model, but this is the first book-length treatments of STC. This volume features an introduction by Prof. Richard Morris and Prof. Cliff Abraham.

Foundations of Human Memory

Author : Michael Jacob Kahana
Publisher : Oxford University Press
ISBN 13 : 0199715521
Total Pages : 364 pages
Book Rating : 4.1/5 (997 download)

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Book Synopsis Foundations of Human Memory by : Michael Jacob Kahana

Download or read book Foundations of Human Memory written by Michael Jacob Kahana and published by Oxford University Press. This book was released on 2014-05-01 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foundations of Human Memory provides an introduction to the scientific study of human memory with an emphasis on both the major theories of memory and the laboratory studies that have been used to test those theories and inspire their further development. Written with the undergraduate student in mind, the text assumes no specific background in the subject, but a general familiarity with scientific method and quantitative approaches to the treatment of data. Foundations of human memory is organized around the major empirical paradigms used to study memory in the laboratory and the theories used to explain data obtained using those paradigms. The text begins with a focus on memory for individual items, building up to memory for associations between items, and finally to memory for entire sequences of items and the problem of memory search. Several major theories of memory are considered in detail, including strength theory, summed-similarity theory, neural network based theories, retrieved-context theory, and theories based on the division of memory into separate short-term and long-term storage systems. The text emphasizes basic research over applied problems, but brings in real-world examples and neuroscientific evidence as appropriate.

Working Memory Capacity

Author : Nelson Cowan
Publisher : Psychology Press
ISBN 13 : 1317232380
Total Pages : 238 pages
Book Rating : 4.3/5 (172 download)

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Book Synopsis Working Memory Capacity by : Nelson Cowan

Download or read book Working Memory Capacity written by Nelson Cowan and published by Psychology Press. This book was released on 2016-04-14 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: The idea of one's memory "filling up" is a humorous misconception of how memory in general is thought to work; it actually has no capacity limit. However, the idea of a "full brain" makes more sense with reference to working memory, which is the limited amount of information a person can hold temporarily in an especially accessible form for use in the completion of almost any challenging cognitive task. This groundbreaking book explains the evidence supporting Cowan's theoretical proposal about working memory capacity, and compares it to competing perspectives. Cognitive psychologists profoundly disagree on how working memory is limited: whether by the number of units that can be retained (and, if so, what kind of units and how many), the types of interfering material, the time that has elapsed, some combination of these mechanisms, or none of them. The book assesses these hypotheses and examines explanations of why capacity limits occur, including vivid biological, cognitive, and evolutionary accounts. The book concludes with a discussion of the practical importance of capacity limits in daily life. This 10th anniversary Classic Edition will continue to be accessible to a wide range of readers and serve as an invaluable reference for all memory researchers.