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Sparse Large-Scale Nonlinear Dynamical Modeling of Human Hippocampus for Memory Prostheses

Dong Song, Brian S. Robinson, Robert E. Hampson, Vasilis Z. Marmarelis, Sam A. Deadwyler, Theodore W. Berger
2018 IEEE transactions on neural systems and rehabilitation engineering  
In order to build hippocampal prostheses for restoring memory functions, we build sparse multiinput, multi-output (MIMO) nonlinear dynamical models of the human hippocampus.  ...  Using CA3 and CA1 spike trains as inputs and outputs respectively, sparse generalized Laguerre-Volterra models are estimated with group lasso and local coordinate descent methods to capture the nonlinear  ...  In our previous studies, we have shown that, using a closed-loop system based on nonlinear dynamical input-output models, we can restore the hippocampal signal transmissions and transformations in (a)  ... 
doi:10.1109/tnsre.2016.2604423 pmid:28113595 pmcid:PMC5623111 fatcat:nht7wb4bbfb5zk33sjuuuxyjy4

Nonlinear Dynamic Modeling of Synaptically Driven Single Hippocampal Neuron Intracellular Activity

Ude Lu, Dong Song, T W Berger
2011 IEEE Transactions on Biomedical Engineering  
A high-order nonlinear dynamic model of the input-output properties of single hippocampal CA1 pyramidal neurons was developed based on synaptically driven intracellular activity.  ...  The purpose of this study is to construct a model that: 1) can capture the nonlinear dynamics of both subthreshold activities [postsynaptic potentials (PSPs)] and suprathreshold activities (action potentials  ...  neural network models to real-world signal processing problems, very large-scale integration (VLSI)-based implementations of biologically realistic models of higher brain function, neuron-silicon interfaces  ... 
doi:10.1109/tbme.2011.2105870 pmid:21233041 pmcid:PMC3125057 fatcat:zwczlm4rzje7nmgbbi4f7emx2a

A Hippocampal Cognitive Prosthesis: Multi-Input, Multi-Output Nonlinear Modeling and VLSI Implementation

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
2012 IEEE transactions on neural systems and rehabilitation engineering  
The animal model used is delayed nonmatch-to-sample (DNMS) behavior in the rat, and the "core" of the prosthesis is a biomimetic multi-input/multi-output (MIMO) nonlinear model that provides the capability  ...  Index Terms Hippocampus; multi-input/multi-output (MIMO) nonlinear model; neural prosthesis; spatiotemporal coding  ...  With respect to the multi-input, multi-output (MIMO) nonlinear dynamic modeling used to predict hippocampal spatiotemporal activity, we will introduce major advances in the procedures for estimating parameters  ... 
doi:10.1109/tnsre.2012.2189133 pmid:22438335 pmcid:PMC3395724 fatcat:4v7euidbtbenffuuquw4w6gc2u

Nonlinear System Identification of Neural Systems from Neurophysiological Signals [article]

Fei He, Yuan Yang
2020 bioRxiv   pre-print
We argue that nonlinear modelling and analysis are necessary to study neuronal processing and signal transfer in neural systems quantitatively.  ...  These approaches can hopefully provide new insights to advance our understanding of neurophysiological mechanisms underlying neural functions.  ...  All of those black-box modelling approaches are usually flexible and accurate in quantifying complex and long-range nonlinear interactions.  ... 
doi:10.1101/2020.08.09.243253 fatcat:uu3xscbombh7dfwrn5wlsbugn4

Boolean Modeling of Neural Systems with Point-Process Inputs and Outputs. Part II: Application to the Rat Hippocampus

Theodoros P. Zanos, Robert E. Hampson, Samuel E. Deadwyler, Theodore W. Berger, Vasilis Z. Marmarelis
2009 Annals of Biomedical Engineering  
The modeling objective is to identify and quantify the causal links among the neurons generating the recorded activity, using Boolean-Volterra models estimated directly from the data according to the methodological  ...  rhythmic characteristics in the neuronal dynamics of these ensembles), making the proposed methodology an attractive tool for the analysis and modeling of multi-unit recordings from neuronal systems in  ...  METHODS This application is motivated by the desire to quantify the multi-unit transformations of neuronal activity between different regions of the hippocampus.  ... 
doi:10.1007/s10439-009-9716-z pmid:19499341 pmcid:PMC2917724 fatcat:myypr5idy5gwhenuutwttonyde

Modeling the Nonlinear Properties of the in vitro Hippocampal Perforant Path-Dentate System Using Multielectrode Array Technology

A. Dimoka, S.H. Courellis, G.I. Gholmieh, V.Z. Marmarelis, T.W. Berger
2008 IEEE Transactions on Biomedical Engineering  
A modeling approach to characterize the nonlinear dynamic transformations of the dentate gyrus of the hippocampus is presented and experimentally validated.  ...  The proposed approach examines and captures the short-term dynamic characteristics of these two pathways using a nonparametric, third-order Poisson-Volterra model.  ...  in this study in order to fully characterize the nonlinear dynamics of the LPP and the MPP neuronal transformations.  ... 
doi:10.1109/tbme.2007.908075 pmid:18270006 pmcid:PMC2749727 fatcat:bqa24al5knfndecy2sqg7ihgii

Modeling the Nonlinear Dynamic Interactions of Afferent Pathways in the Dentate Gyrus of the Hippocampus

Angelika Dimoka, Spiros H. Courellis, Vasilis Z. Marmarelis, Theodore W. Berger
2008 Annals of Biomedical Engineering  
We employ non-parametric Poisson-Volterra models that serve as canonical quantitative descriptors of the nonlinear dynamic transformations of the neuronal signals propagating through these two neuronal  ...  The data are acquired through a custom-made multi-electrode-array system, which stimulated simultaneously the two pathways with random impulse trains and recorded the neuronal postsynaptic activity at  ...  Following this approach, future research can expand the mathematical model to include three or more inputs of the dentate gyrus and to incorporate other hippocampal regions.  ... 
doi:10.1007/s10439-008-9463-6 pmid:18299993 pmcid:PMC2749714 fatcat:hunme2nelracvbpznzghkiimda

System identification of point-process neural systems using Probability Based Volterra kernels

Roman A. Sandler, Samuel A. Deadwyler, Robert E. Hampson, Dong Song, Theodore W. Berger, Vasilis Z. Marmarelis
2015 Journal of Neuroscience Methods  
Background-Neural information processing involves a series of nonlinear dynamical input/ output transformations between the spike trains of neurons/neuronal ensembles.  ...  Conclusions- The PBV kernels provide a novel and intuitive method of characterizing pointprocess input-output nonlinear systems.  ...  Acknowledgements This work was supported by NIH grant P41-EB001978 to the Biomedical Simulations Resource at the University of Southern California and DARPA contract N66601-09-C-2081.  ... 
doi:10.1016/j.jneumeth.2014.11.013 pmid:25479231 pmcid:PMC4286344 fatcat:lrctxglcyjfwdov5ciy37arvpa

Model-based asessment of an in-vivo predictive relationship from CA1 to CA3 in the rodent hippocampus

Roman A. Sandler, Dong Song, Robert E. Hampson, Sam A. Deadwyler, Theodore W. Berger, Vasilis Z. Marmarelis
2014 Journal of Computational Neuroscience  
This relationship is thought to be caused by a combination of truly causal connections such as the CA1→EC→CA3 pathway and common inputs such as those from the Septum.  ...  Here, single spike activity was recorded using a multi-electrode array from the CA3 and CA1 areas of the rodent hippocampus (N=7) during a behavioral task.  ...  Acknowledgments This work was supported by NIH grant P41-EB001978 to the Biomedical Simulations Resource at the University of Southern California and DARPA contract N66601-09-C-2081.  ... 
doi:10.1007/s10827-014-0530-8 pmid:25260381 pmcid:PMC4297547 fatcat:vsg64uatrnbwvpvzhaz2sqio2a

Nonlinear Dynamic Modeling of Neuron Action Potential Threshold During Synaptically Driven Broadband Intracellular Activity

Ude Lu, S. M. Roach, Dong Song, T. W. Berger
2012 IEEE Transactions on Biomedical Engineering  
Third, a nonlinear dynamical third-order Volterra model was built to describe the relations between the threshold dynamics and the AP activities.  ...  Finally, the dynamic threshold model was integrated into a previously developed single neuron model and resulted in a 33% improvement in spike prediction.  ...  This report describes the development of a nonlinear model that is used to quantify and study the nonlinear dynamics of neuronal threshold as a function of AP firing history.  ... 
doi:10.1109/tbme.2011.2178241 pmid:22156947 pmcid:PMC3399271 fatcat:i47wjyc3mbehtcaeicbhe4rkxe

Cannabinoids disrupt memory encoding by functionally isolating hippocampal CA1 from CA3

Roman A. Sandler, Dustin Fetterhoff, Robert E. Hampson, Sam A. Deadwyler, Vasilis Z. Marmarelis, Daniel Bush
2017 PLoS Computational Biology  
Multivariate autoregressive models, estimated from spontaneous spiking activity, were then used to describe the dynamical transformation from CA3 to CA1.  ...  This study aims to disentangle the effects of CBs on the functional dynamics of the hippocampal Schaffer collateral synapse by using data-driven nonparametric modeling.  ...  effects of THC on hippocampal nonlinear dynamics [51, 65] .  ... 
doi:10.1371/journal.pcbi.1005624 pmid:28686594 pmcid:PMC5521875 fatcat:oiay75jt5ze3pfrajxoxkdttdy

Multi-level Models [chapter]

Péter Érdi, Tamás Kiss, Balázs Ujfalussy
2010 Hippocampal Microcircuits  
Examples from membrane channel transport kinetics to integration of receptor kinetics to network models, an integrated hippocampal model for navigation in real and memory spaces, dynamical methods towards  ...  The brain is a prototype of hierarchical dynamic systems. Multiple time-and spatial scales phenomena and multi-level organization of the brain are analyzed.  ...  Neurons are reliable transformers of synaptic inputs to spiking patterns.  ... 
doi:10.1007/978-1-4419-0996-1_18 fatcat:mvjphgquczfe3cgmpyqduqo57i

Parametric and non-parametric modeling of short-term synaptic plasticity. Part I: computational study

Dong Song, Vasilis Z. Marmarelis, Theodore W. Berger
2008 Journal of Computational Neuroscience  
In order to synergistically use the two approaches, we estimate the Volterra kernels of the parametric models of STP for four types of synapses using synthetic broadband input-output data.  ...  The nonlinear dynamics of STP are modeled by means: (1) previously proposed parametric models based on mechanistic hypotheses and/or specific dynamical processes, and (2) non-parametric models (in the  ...  The PV kernels estimated in this study correspond to the cascade of K 2 and F in the sense that they describe the nonlinear dynamic transformation of a pointprocess input (presynaptic spike train) to varying-amplitude  ... 
doi:10.1007/s10827-008-0097-3 pmid:18506609 pmcid:PMC2770349 fatcat:iufmfllpujchbadsllkyc5c7ne

Active Dendrites Regulate Spectral Selectivity in Location-Dependent Spike Initiation Dynamics of Hippocampal Model Neurons

A. Das, R. Narayanan
2014 Journal of Neuroscience  
Our results identify explicit roles for plastic active dendrites in neural coding and strongly recommend a dynamically reconfigurable multi-STA model to characterize location-dependent input feature selectivity  ...  We transformed the STA computed from these models to the spectral and the spectrotemporal domains and found that the spike initiation dynamics exhibited temporally localized selectivity to a characteristic  ...  We propose a dynamically reconfigurable multi-STA model as an alternative to the traditional single-STA model for characterizing the input-output relationship of a neuron with plastic active dendrites.  ... 
doi:10.1523/jneurosci.3203-13.2014 pmid:24453312 pmcid:PMC6705308 fatcat:glnlnmefx5dotarucfua4xbwwu

BigBrainWarp: Toolbox for integration of BigBrain 3D histology with multimodal neuroimaging [article]

Casey Paquola, Jessica Royer, Lindsay B. Lewis, Claude Lepage, Tristan Glatard, Konrad Wagstyl, Jordan DeKraker, Paule-J Toussaint, Sofie L Valk, Louis Collins, Ali R. Khan, Katrin Amunts (+3 others)
2021 bioRxiv   pre-print
To simplify workflows and support adoption of best practices, we developed BigBrainWarp, a toolbox for integration of BigBrain with multimodal neuroimaging.  ...  Together, this work paves the way for multi-scale investigations of brain organisation.  ...  Approach: (i) Transform functionally-defined regions from a standard neuroimaging surface template to the BigBrain surface.  ... 
doi:10.1101/2021.05.04.442563 fatcat:6fxfjt6cajbnfpbt2vrk6iv5t4
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