Literature DB >> 20700470

The Neurobiological Basis of Cognition: Identification by Multi-Input, Multioutput Nonlinear Dynamic Modeling: A method is proposed for measuring and modeling human long-term memory formation by mathematical analysis and computer simulation of nerve-cell dynamics.

Theodore W Berger1, Dong Song, Rosa H M Chan, Vasilis Z Marmarelis.   

Abstract

The successful development of neural prostheses requires an understanding of the neurobiological bases of cognitive processes, i.e., how the collective activity of populations of neurons results in a higher level process not predictable based on knowledge of the individual neurons and/or synapses alone. We have been studying and applying novel methods for representing nonlinear transformations of multiple spike train inputs (multiple time series of pulse train inputs) produced by synaptic and field interactions among multiple subclasses of neurons arrayed in multiple layers of incompletely connected units. We have been applying our methods to study of the hippocampus, a cortical brain structure that has been demonstrated, in humans and in animals, to perform the cognitive function of encoding new long-term (declarative) memories. Without their hippocampi, animals and humans retain a short-term memory (memory lasting approximately 1 min), and long-term memory for information learned prior to loss of hippocampal function. Results of more than 20 years of studies have demonstrated that both individual hippocampal neurons, and populations of hippocampal cells, e.g., the neurons comprising one of the three principal subsystems of the hippocampus, induce strong, higher order, nonlinear transformations of hippocampal inputs into hippocampal outputs. For one synaptic input or for a population of synchronously active synaptic inputs, such a transformation is represented by a sequence of action potential inputs being changed into a different sequence of action potential outputs. In other words, an incoming temporal pattern is transformed into a different, outgoing temporal pattern. For multiple, asynchronous synaptic inputs, such a transformation is represented by a spatiotemporal pattern of action potential inputs being changed into a different spatiotemporal pattern of action potential outputs. Our primary thesis is that the encoding of short-term memories into new, long-term memories represents the collective set of nonlinearities induced by the three or four principal subsystems of the hippocampus, i.e., entorhinal cortex-to-dentate gyrus, dentate gyrus-to-CA3 pyramidal cell region, CA3-to-CA1 pyramidal cell region, and CA1-to-subicular cortex. This hypothesis will be supported by studies using in vivo hippocampal multineuron recordings from animals performing memory tasks that require hippocampal function. The implications for this hypothesis will be discussed in the context of "cognitive prostheses"-neural prostheses for cortical brain regions believed to support cognitive functions, and that often are subject to damage due to stroke, epilepsy, dementia, and closed head trauma.

Entities:  

Year:  2010        PMID: 20700470      PMCID: PMC2917774          DOI: 10.1109/JPROC.2009.2038804

Source DB:  PubMed          Journal:  Proc IEEE Inst Electr Electron Eng        ISSN: 0018-9219            Impact factor:   10.961


  42 in total

1.  The time-rescaling theorem and its application to neural spike train data analysis.

Authors:  Emery N Brown; Riccardo Barbieri; Valérie Ventura; Robert E Kass; Loren M Frank
Journal:  Neural Comput       Date:  2002-02       Impact factor: 2.026

2.  Spike-timing-dependent synaptic modification induced by natural spike trains.

Authors:  Robert C Froemke; Yang Dan
Journal:  Nature       Date:  2002-03-28       Impact factor: 49.962

Review 3.  Brain-machine interfaces to restore motor function and probe neural circuits.

Authors:  Miguel A L Nicolelis
Journal:  Nat Rev Neurosci       Date:  2003-05       Impact factor: 34.870

Review 4.  Hierarchical model of the population dynamics of hippocampal dentate granule cells.

Authors:  G A Chauvet; T W Berger
Journal:  Hippocampus       Date:  2002       Impact factor: 3.899

Review 5.  Multiple neural spike train data analysis: state-of-the-art and future challenges.

Authors:  Emery N Brown; Robert E Kass; Partha P Mitra
Journal:  Nat Neurosci       Date:  2004-05       Impact factor: 24.884

6.  Predicting EMG with generalized Volterra kernel model.

Authors:  Dong Song; Phillip Hendrickson; Vasilis Z Marmarelis; Jose Aguayo; Jiping He; Gerald E Loeb; Theodore W Berger
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2008

7.  Vector reconstruction from firing rates.

Authors:  E Salinas; L F Abbott
Journal:  J Comput Neurosci       Date:  1994-06       Impact factor: 1.621

Review 8.  Short-term synaptic plasticity.

Authors:  Robert S Zucker; Wade G Regehr
Journal:  Annu Rev Physiol       Date:  2002       Impact factor: 19.318

9.  Nonlinear systems analysis of the hippocampal perforant path-dentate projection. III. Comparison of random train and paired impulse stimulation.

Authors:  T W Berger; J L Eriksson; D A Ciarolla; R J Sclabassi
Journal:  J Neurophysiol       Date:  1988-09       Impact factor: 2.714

10.  Nonlinear systems analysis of the hippocampal perforant path-dentate projection. II. Effects of random impulse train stimulation.

Authors:  T W Berger; J L Eriksson; D A Ciarolla; R J Sclabassi
Journal:  J Neurophysiol       Date:  1988-09       Impact factor: 2.714

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  22 in total

1.  A nonlinear autoregressive Volterra model of the Hodgkin-Huxley equations.

Authors:  Steffen E Eikenberry; Vasilis Z Marmarelis
Journal:  J Comput Neurosci       Date:  2012-08-10       Impact factor: 1.621

2.  A cortical neural prosthesis for restoring and enhancing memory.

Authors:  Theodore W Berger; Robert E Hampson; Dong Song; Anushka Goonawardena; Vasilis Z Marmarelis; Sam A Deadwyler
Journal:  J Neural Eng       Date:  2011-06-15       Impact factor: 5.379

3.  Multi-Input, Multi-Output Neuronal Mode Network Approach to Modeling the Encoding Dynamics and Functional Connectivity of Neural Systems.

Authors:  Kunling Geng; Dae C Shin; Dong Song; Robert E Hampson; Samuel A Deadwyler; Theodore W Berger; Vasilis Z Marmarelis
Journal:  Neural Comput       Date:  2019-05-21       Impact factor: 2.026

4.  A hippocampal cognitive prosthesis: multi-input, multi-output nonlinear modeling and VLSI implementation.

Authors:  Theodore W Berger; Dong Song; Rosa H M Chan; Vasilis Z Marmarelis; Jeff LaCoss; Jack Wills; Robert E Hampson; Sam A Deadwyler; John J Granacki
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2012-03       Impact factor: 3.802

5.  Nonlinear dynamic modeling of synaptically driven single hippocampal neuron intracellular activity.

Authors:  Ude Lu; Dong Song; Theodore W Berger
Journal:  IEEE Trans Biomed Eng       Date:  2011-01-13       Impact factor: 4.538

6.  Modeling Nonlinear Synaptic Dynamics: A Laguerre-Volterra Network Framework for Improved Computational Efficiency in Large Scale Simulations.

Authors:  Eric Y Hu; Gene Yu; Dong Song; C Jean-Marie Bouteiller; W Theodore Berger
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2018-07

7.  Nonlinear dynamic modeling of neuron action potential threshold during synaptically driven broadband intracellular activity.

Authors:  Ude Lu; Shane M Roach; Dong Song; Theodore W Berger
Journal:  IEEE Trans Biomed Eng       Date:  2011-12-06       Impact factor: 4.538

8.  Design of optimal stimulation patterns for neuronal ensembles based on Volterra-type hierarchical modeling.

Authors:  V Z Marmarelis; D C Shin; R E Hampson; S A Deadwyler; D Song; T W Berger
Journal:  J Neural Eng       Date:  2012-10-17       Impact factor: 5.379

9.  Identification of sparse neural functional connectivity using penalized likelihood estimation and basis functions.

Authors:  Dong Song; Haonan Wang; Catherine Y Tu; Vasilis Z Marmarelis; Robert E Hampson; Sam A Deadwyler; Theodore W Berger
Journal:  J Comput Neurosci       Date:  2013-05-15       Impact factor: 1.621

10.  The volterra functional series is a viable alternative to kinetic models for synaptic modeling--calibration and benchmarking.

Authors:  Eric Y Hu; Jean-Marie C Bouteiller; Dong Song; Theodore W Berger
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2015
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