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Toward Networks from Spikes

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Validating Neuro-Computational Models of Neurological and Psychiatric Disorders

Part of the book series: Springer Series in Computational Neuroscience ((NEUROSCI,volume 14))

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Abstract

Computational models of brain tissue provide important insights for understanding pathological behavior within neuronal networks. Validating these models poses difficult challenges due to the number of neurons and synaptic connections in even the most modest samples. An important step toward validation is determining connectivity within the biological network so that simulations can be configured to match and then compared directly to the observed behaviors. Cultures of dissociated neurons on multi-electrode arrays provide a flexible experimental platform for the study of fundamental network behaviors. Extracting connectivity from this in vitro setup is challenging because we are able to measure only a relatively small number of neurons. Today, cultures are routinely grown on arrays of microelectrodes, each reporting the activity of several neurons. With these techniques we can distinguish at most hundreds of spiking neurons while cultures comprise thousands of neurons. Even as the number of electrodes increases with gains in technology, it is important to understand how much information about the network connectivity can be discovered with sparse spatial sampling. We describe an approach to searching for repeating patterns in parallel spike train data, the presence of which can inform inferences of causality and connectivity in the network.

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Acknowledgments

This work was supported in part by the Ralph and Marian Falk Medical Research Trust, the National Institutes of Health under award number R01NS084142, and the U.S. Department of Energy under contract DE-AC02–06CH11357. The content is solely the responsibility of the authors and does not necessarily represent the official views of the granting agencies.

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Authors and Affiliations

  1. Argonne National Laboratory, The University of Chicago, BLDG 240, RM 4139, 9700 S. Cass Ave., 60439, Argonne, IL, USA

    Mark Hereld

  2. The University of Chicago, Chicago, IL, USA

    Jyothsna Suresh, Mihailo Radojicic, Lorenzo L. Pesce, Janice Wang, Jeremy Marks & Wim van Drongelen

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  1. Mark Hereld
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  2. Jyothsna Suresh
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  3. Mihailo Radojicic
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  4. Lorenzo L. Pesce
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  7. Wim van Drongelen
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Correspondence to Mark Hereld .

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Editors and Affiliations

  1. School of Engineering, University of Lincoln, Lincoln, United Kingdom

    Basabdatta Sen Bhattacharya

  2. Office of Multidisciplinary Activities, National Science Foundation, Arlington, Virginia, USA

    Fahmida N. Chowdhury

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Hereld, M. et al. (2015). Toward Networks from Spikes. In: Bhattacharya, B., Chowdhury, F. (eds) Validating Neuro-Computational Models of Neurological and Psychiatric Disorders. Springer Series in Computational Neuroscience, vol 14. Springer, Cham. https://doi.org/10.1007/978-3-319-20037-8_10

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