Hippocampal Microcircuits, Functional Connectivity, and Prostheses

Hippocampus is a brain region critical for the formation of new long-term declarative memories. It transmits and processes memory information with its distinct feedforward trisynaptic pathway. Identifying functional properties of the hippocampal circuits is important for understanding the mechanisms of memory formation and building hippocampal prostheses for restoring memory functions lost in diseases or injuries. In hippocampal slices, trisynaptic responses can be elicited and recorded using conformal multi-electrode arrays. A proof-of-principle hippocampal prosthetic system has been successfully developed based on a computational model that accurately describes the input-output properties of the hippocampal circuit. In behaving animals, hippocampal functional connectivities are analyzed with a nonlinear dynamical multi-input, multi-output (MIMO) model using behaviorally-driven spiking data. Results show that the hippocampal CA3-CA1 functional connection is diffusive along the septo-temporal axis, as opposed to strictly laminar. There are strong causal relations between the CA3 and CA1 spiking activities. The MIMO model can accurately predict the spatio-temporal patterns of the CA1 output spikes based on the ongoing spatio-temporal patterns of the CA3 input spikes. MIMO model-based electrical stimulation to the CA1 region effectively restores the hippocampal memory function by reinstating the CA1 activities. The recording component, the nonlinear dynamical MIMO model, and the stimulation component essentially constitute a closed-loop prosthetic system that bypasses the impaired hippocampal region.

[1]  Robert E. Hampson,et al.  A Hippocampal Cognitive Prosthesis: Multi-Input, Multi-Output Nonlinear Modeling and VLSI Implementation , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[2]  Masao Ito Error detection and representation in the olivo-cerebellar system , 2013, Front. Neural Circuits.

[3]  Robert E. Hampson,et al.  Nonlinear Dynamic Modeling of Spike Train Transformations for Hippocampal-Cortical Prostheses , 2007, IEEE Transactions on Biomedical Engineering.

[4]  B. Milner MEMORY AND THE MEDIAL TEMPORAL REGIONS OF THE BRAIN , 1970 .

[5]  R E Hampson,et al.  Hippocampal ensemble activity during spatial delayed-nonmatch-to-sample performance in rats , 1996, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[6]  Theodore W Berger,et al.  A cortical neural prosthesis for restoring and enhancing memory , 2011, Journal of neural engineering.

[7]  Robert E. Hampson,et al.  Extraction and restoration of hippocampal spatial memories with non-linear dynamical modeling , 2014, Front. Syst. Neurosci..

[8]  Theodore W. Berger,et al.  Identification of Nonlinear Dynamics in Neural Population Activity , 2010 .

[9]  Theodore W. Berger,et al.  Parametric and non-parametric modeling of short-term synaptic plasticity. Part I: computational study , 2009, Journal of Computational Neuroscience.

[10]  Robert E. Hampson,et al.  Identification of sparse neural functional connectivity using penalized likelihood estimation and basis functions , 2013, Journal of Computational Neuroscience.

[11]  Theodore W. Berger,et al.  The Neurobiological Basis of Cognition: Identification by Multi-Input, Multioutput Nonlinear Dynamic Modeling , 2010, Proceedings of the IEEE.

[12]  T. Bliss,et al.  Lamellar organization of hippocampal excitatory pathways , 1971, Experimental Brain Research.

[13]  Ben Goertzel,et al.  A world survey of artificial brain projects, Part II: Biologically inspired cognitive architectures , 2010, Neurocomputing.

[14]  H. Eichenbaum The hippocampus and mechanisms of declarative memory , 1999, Behavioural Brain Research.

[15]  L. Squire,et al.  The medial temporal lobe memory system , 1991, Science.

[16]  D. Amaral,et al.  Neurons, numbers and the hippocampal network. , 1990, Progress in brain research.

[17]  Theodore W. Berger,et al.  Nonlinear dynamical model based control of in vitro hippocampal output , 2012, Front. Neural Circuits.

[18]  M. Yeckel,et al.  Monosynaptic excitation of hippocampal CA1 pyramidal cells by afferents from the entorhinal cortex , 1995, Hippocampus.

[19]  Rosa H. M. Chan,et al.  A Nonlinear Model for Hippocampal Cognitive Prosthesis: Memory Facilitation by Hippocampal Ensemble Stimulation , 2012, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[20]  G. Buzsáki,et al.  Interneurons of the hippocampus , 1998, Hippocampus.

[21]  James C. Munch,et al.  Nobel Lectures Physiology or Medicine 1901–1921 , 1968 .

[22]  Robert E. Hampson,et al.  Distribution of spatial and nonspatial information in dorsal hippocampus , 1999, Nature.

[23]  Lucas M. Santos,et al.  Facilitation and restoration of cognitive function in primate prefrontal cortex by a neuroprosthesis that utilizes minicolumn-specific neural firing , 2012, Journal of neural engineering.

[24]  Robert E. Hampson,et al.  Sparse generalized Laguerre-Volterra model of neural population dynamics , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[25]  M. Yeckel,et al.  Feedforward excitation of the hippocampus by afferents from the entorhinal cortex: redefinition of the role of the trisynaptic pathway. , 1990, Proceedings of the National Academy of Sciences of the United States of America.

[26]  Robert E. Hampson,et al.  Nonlinear modeling of neural population dynamics for hippocampal prostheses , 2009, Neural Networks.

[27]  Dae C. Shin,et al.  Facilitation of memory encoding in primate hippocampus by a neuroprosthesis that promotes task-specific neural firing , 2013, Journal of neural engineering.