Incorporating anatomically realistic cellular-level connectivity in neural network models of the rat hippocampus.

The specific connectivity patterns among neuronal classes can play an important role in the regulation of firing dynamics in many brain regions. Yet most neural network models are built based on vastly simplified connectivity schemes that do not accurately reflect the biological complexity. Taking the rat hippocampus as an example, we show here that enough quantitative information is available in the neuroanatomical literature to construct neural networks derived from accurate models of cellular connectivity. Computational simulations based on this approach lend themselves to a direct investigation of the potential relationship between cellular connectivity and network activity. We define a set of fundamental parameters to characterize cellular connectivity, and are collecting the related values for the rat hippocampus from published reports. Preliminary simulations based on these data uncovered a novel putative role for feedforward inhibitory neurons. In particular, "mopp" cells in the dentate gyrus are suitable to help maintain the firing rate of granule cells within physiological levels in response to a plausibly noisy input from the entorhinal cortex. The stabilizing effect of feedforward inhibition is further shown to depend on the particular ratio between the relative threshold values of the principal cells and the interneurons. We are freely distributing the connectivity data on which this study is based through a publicly accessible web archive (http://www.krasnow.gmu.edu/L-Neuron).

[1]  G. Ascoli.  Computational Neuroanatomy , 2002, Humana Press.

[2]  Giorgio A. Ascoli,et al.  Reconstruction of Brain Networks by Algorithmic Amplification of Morphometry Data , 1999, IWANN.

[3]  G. Paxinos.  The Rat nervous system , 1985 .

[4]  G Buzsáki,et al.  GABAergic Cells Are the Major Postsynaptic Targets of Mossy Fibers in the Rat Hippocampus , 1998, The Journal of Neuroscience.

[5]  R. Cannon,et al.  Model of spatio‐temporal propagation of action potentials in the Schaffer collateral pathway of the CA1 area of the rat hippocampus , 1997, Hippocampus.

[6]  César A. Hidalgo,et al.  Scale-free networks , 2008, Scholarpedia.

[7]  Yi-Bing Lin.  Performance modeling for mobile telephone networks , 1997 .

[8]  Marcus Kaiser,et al.  Clustered organization of cortical connectivity , 2007, Neuroinformatics.

[9]  Giorgio A. Ascoli,et al.  Passive dendritic integration heavily affects spiking dynamics of recurrent networks , 2003, Neural Networks.

[10]  W. Levy,et al.  Controlling activity fluctuations in large, sparsely connected random networks , 2000, Network.

[11]  C. Bernard,et al.  Model of local connectivity patterns in CA3 and CA1 areas of the hippocampus , 1994, Hippocampus.

[12]  D. Henze,et al.  Revisiting the role of the hippocampal mossy fiber synapse , 2001, Hippocampus.

[13]  Olaf Sporns,et al.  Computational Methods for the Analysis of Brain Connectivity , 2002 .

[14]  William H. Press,et al.  Numerical Recipes in FORTRAN - The Art of Scientific Computing, 2nd Edition , 1987 .

[15]  S. Shen-Orr,et al.  Network motifs: simple building blocks of complex networks. , 2002, Science.

[16]  Paul E. Patton,et al.  Connection matrix of the hippocampal formation: I. The dentate gyrus , 1995, Hippocampus.

[17]  Eugene M. Izhikevich,et al.  Neural excitability, Spiking and bursting , 2000, Int. J. Bifurc. Chaos.

[18]  G. Buzsáki,et al.  Hippocampal network patterns of activity in the mouse , 2003, Neuroscience.

[19]  W. Pitts,et al.  A Logical Calculus of the Ideas Immanent in Nervous Activity (1943) , 2021, Ideas That Created the Future.

[20]  M P Young,et al.  Analysis of the connectional organization of neural systems associated with the hippocampus in rats. , 2000, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[21]  L. F Abbott,et al.  Lapicque’s introduction of the integrate-and-fire model neuron (1907) , 1999, Brain Research Bulletin.

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

[23]  Olaf Sporns,et al.  The small world of the cerebral cortex , 2007, Neuroinformatics.