Extended LATER model can account for trial-by-trial variability of both pre- and post-processes

  • Authors:

  • Hiroyuki Nakahara;Kae Nakamura;Okihide Hikosaka

  • Affiliations:

  • Laboratory for Integrated Theoretical Neuroscience, RIKEN Brain Science Institute, Wako, Saitama, Japan and Laboratory for Mathematical Neuroscience, RIKEN Brain Science Institute, Wako, Saitama, ...;Laboratory of Sensorimotor Research, National Eye Institute, National Institute of Health, Bethesda, MD;Laboratory of Sensorimotor Research, National Eye Institute, National Institute of Health, Bethesda, MD

  • Venue:
  • Neural Networks - 2006 Special issue: Neurobiology of decision making
  • Year:
  • 2006

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Abstract

We present a new decision-making model that can account for trial-by-trial variability induced by a process ("pre-process") that occurs before an explicit sensory signal specifying a later motor response. A process after explicit sensory signals, referred to herein as the "post-process", has been investigated by a variety of so-called rise-to-threshold models including the LATER model. The LATER model formulates postprocess variability but treats the pre-process as fixed within a block of an experiment. We propose an extension of the LATER model, which we call the extended LATER (ELATER) model, to account for trial-by-trial variability of both pre- and post-processes together. We present the mathematical formulation of the ELATER model and analyze its characteristics, including numerical examples and an example of saccade latency data in reward-manipulated conditions with caudate activity. The ELATER model is useful for investigating decision making by taking account of trial-by-trial variability of both pre- and post-processes.