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
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Author : Jannik Luboeinski
language : en
Publisher:
Release Date : 2021-09-02
The Role Of Synaptic Tagging And Capture For Memory Dynamics In Spiking Neural Networks written by Jannik Luboeinski and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-02 with Science categories.
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
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Author : Jannik Luboeinski
language : en
Publisher:
Release Date : 2021
The Role Of Synaptic Tagging And Capture For Memory Dynamics In Spiking Neural Networks written by Jannik Luboeinski and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
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 syn...
Synaptic Tagging And Capture
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Author : Sreedharan Sajikumar
language : en
Publisher: Springer Nature
Release Date :
Synaptic Tagging And Capture written by Sreedharan Sajikumar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Spike Timing Dependent Plasticity
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Author : Henry Markram
language : en
Publisher: Frontiers E-books
Release Date :
Spike Timing Dependent Plasticity written by Henry Markram and has been published by Frontiers E-books this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
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.
Value And Reward Based Learning In Neurobots
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Author : Jeffrey L Krichmar
language : en
Publisher: Frontiers Media SA
Release Date : 2015-03-05
Value And Reward Based Learning In Neurobots written by Jeffrey L Krichmar and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-05 with Neurosciences. Biological psychiatry. Neuropsychiatry categories.
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.
Inhibitory Synaptic Plasticity
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Author : Melanie A. Woodin
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-11-02
Inhibitory Synaptic Plasticity written by Melanie A. Woodin and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-02 with Medical categories.
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
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Author : Michael A. Arbib
language : en
Publisher: MIT Press
Release Date : 2016-11-04
From Neuron To Cognition Via Computational Neuroscience written by Michael A. Arbib and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-04 with Science categories.
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
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Author : Moshe Abeles
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Local Cortical Circuits written by Moshe Abeles and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Medical categories.
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.
Spiking Neuron Models
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Author : Wulfram Gerstner
language : en
Publisher: Cambridge University Press
Release Date : 2002-08-15
Spiking Neuron Models written by Wulfram Gerstner and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-08-15 with Computers categories.
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.
Neuromorphic Cognitive Systems
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Author : Qiang Yu
language : en
Publisher: Springer
Release Date : 2017-05-03
Neuromorphic Cognitive Systems written by Qiang Yu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-03 with Technology & Engineering categories.
This book presents neuromorphic cognitive systems from a learning and memory-centered perspective. It illustrates how to build a system network of neurons to perform spike-based information processing, computing, and high-level cognitive tasks. It is beneficial to a wide spectrum of readers, including undergraduate and postgraduate students and researchers who are interested in neuromorphic computing and neuromorphic engineering, as well as engineers and professionals in industry who are involved in the design and applications of neuromorphic cognitive systems, neuromorphic sensors and processors, and cognitive robotics. The book formulates a systematic framework, from the basic mathematical and computational methods in spike-based neural encoding, learning in both single and multi-layered networks, to a near cognitive level composed of memory and cognition. Since the mechanisms for integrating spiking neurons integrate to formulate cognitive functions as in the brain are little understood, studies of neuromorphic cognitive systems are urgently needed. The topics covered in this book range from the neuronal level to the system level. In the neuronal level, synaptic adaptation plays an important role in learning patterns. In order to perform higher-level cognitive functions such as recognition and memory, spiking neurons with learning abilities are consistently integrated, building a system with encoding, learning and memory functionalities. The book describes these aspects in detail.