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Improving data quality in neuronal population recordings

Nature Neuroscience volume 19, pages 1165–1174 (2016)Cite this article

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Abstract

Understanding how the brain operates requires understanding how large sets of neurons function together. Modern recording technology makes it possible to simultaneously record the activity of hundreds of neurons, and technological developments will soon allow recording of thousands or tens of thousands. As with all experimental techniques, these methods are subject to confounds that complicate the interpretation of such recordings, and could lead to erroneous scientific conclusions. Here we discuss methods for assessing and improving the quality of data from these techniques and outline likely future directions in this field.

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Figure 1: Spike sorting is required to draw valid conclusions in extracellular electrophysiology.
Figure 2: Quantitative measures of unit isolation in extracellular electrophysiology.
Figure 3: Subtracting neuropil contamination from raw fluorescence time courses.
Figure 4: Probabilistic estimation of spike times from calcium signals.

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Acknowledgements

We thank N. Steinmetz and M. Pachitariu for comments on the manuscript. K.D.H. is supported by the Wellcome Trust (95668, 95669, 100154), EPSRC (K015141, I005102), MRC and Simons foundation (SCGB 325512). S.L.S. is supported by the Human Frontier Science Program (CDA00063/2012, RGP0027/2016), National Science Foundation (1450824), Whitehall Foundation, Klingenstein Foundation, McKnight Foundation, Simons Foundation (SCGB 325407SS) and the National Institutes of Health (R01NS091335, R01EY024294). R.Q.Q. is supported by the Human Frontiers Science Program (RGP0015/2013).

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Authors and Affiliations

  1. UCL Institute of Neurology, University College London, London, UK

    Kenneth D Harris

  2. UCL Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK

    Kenneth D Harris

  3. Centre for Systems Neuroscience, University of Leicester, Leicester, UK

    Rodrigo Quian Quiroga

  4. Howard Hughes Medical Institute, Janelia Farm Research Campus, Ashburn, Virginia, USA

    Jeremy Freeman

  5. Department of Cell Biology and Physiology, UNC School of Medicine, Chapel Hill, North Carolina, USA

    Spencer L Smith

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  1. Kenneth D Harris
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Correspondence to Kenneth D Harris or Spencer L Smith.

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Harris, K., Quiroga, R., Freeman, J. et al. Improving data quality in neuronal population recordings. Nat Neurosci 19, 1165–1174 (2016). https://doi.org/10.1038/nn.4365

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