title: Improving data quality in neuronal population recordings.
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.
authors: UCL Institute of Neurology, University College London, London, UK.|UCL Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK.
authors: Kenneth D
authors: 0000-0002-5930-6456
authors: KD
authors: Harris
authors: Centre for Systems Neuroscience, University of Leicester, Leicester, UK.
authors: Rodrigo Quian
authors: RQ
authors: Quiroga
authors: Howard Hughes Medical Institute, Janelia Farm Research Campus, Ashburn, Virginia, USA.
authors: Jeremy
authors: J
authors: Freeman
authors: Department of Cell Biology and Physiology, UNC School of Medicine, Chapel Hill, North Carolina, USA.
authors: Spencer L
authors: SL
authors: Smith
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D001921:Brain / Q000166:cytology / Q000502:physiology; D000068598:Data Accuracy; D055724:Electrophysiological Phenomena / Q000502:physiology; D006801:Humans; D009415:Nerve Net / Q000166:cytology / Q000502:physiology; D009474:Neurons / Q000502:physiology*; D061848:Optical Imaging / Q000379:methods / Q000592:standards*