Neural correlates of dynamic sensory cue re-weighting in macaque area MSTd
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1
Washington University School of Medicine, United States
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2
University of Rochester , United States
Psychophysical studies have demonstrated that human observers integrate sensory information across modalities to improve perceptual sensitivity. These studies often frame multisensory cue integration as a problem in probabilistic (i.e., Bayesian) inference. In this framework, a working hypothesis is that the brain represents and combines probability distributions over stimuli, and thereby takes into account the inherent uncertainty in sensory information when making perceptual decisions. One key prediction from such optimal cue integration models is that subjects will re-weight cues according to their relative reliability (uncertainty) on a trial-by-trial basis, and indeed this has been shown in several paradigms. However, direct neurophysiological evidence for probabilistic computations during multisensory integration is scarce, and it remains unclear exactly how neuronal populations accomplish rapid re-weighting of cues based on their reliability. To address this question, we trained rhesus monkeys to perform a 2AFC fine discrimination of self-motion (heading) direction. Monkeys were seated on a motion platform facing a rear-projection screen, and on each trial were presented with a heading trajectory defined either by physical motion (’vestibular’ condition), optic flow simulating observer motion (’visual’ condition), or a combination of both cues (’combined’ condition). Cue reliability was varied randomly across trials by changing the motion coherence of the optic flow pattern. As in previous studies, we generated optimal predictions for the cue weights by measuring performance in the single-cue conditions, then tested those predictions in the combined condition by placing the cues in conflict on a subset of trials. Our behavioral results suggest that monkeys, like humans, can dynamically re-weight cues according to their reliability. During the task, we recorded the activity of single neurons in area MSTd, a region thought to contribute to multisensory integration for heading perception. Using ROC analysis, we quantified the behavior of an ideal observer performing the same task as the animal but using only the firing rate of an individual neuron. The majority of MSTd neurons in our sample showed near-optimal cue re-weighting with changes in reliability, similar to the monkey’s behavior. We also constructed a decoding model in which a simulated observer performed the discrimination task based on MSTd population activity. On a given simulated trial, the population response (R) was generated by drawing from the individual neuron responses to a particular stimulus (s). From this response and the known tuning curves of the neurons in the sample, the model computed the likelihood P(R|s) for each possible value of the stimulus, then took the maximum likelihood estimate as its choice on each trial. Even on the basis of relatively few neurons (N = 28), the simulated observer showed cue re-weighting that was remarkably similar to the behavior of the animal. Together with the single-neuron results, this suggests that MSTd activity implicitly encodes cue reliability on a trial-by-trial basis, and thus could contribute to the re-weighting observed behaviorally. More broadly, our results support the hypothesis that sensory populations encode the distributions used to mediate probabilistic inference, and that an explicit reliability signal is not required for optimal cue integration.
Conference:
Computational and Systems Neuroscience 2010, Salt Lake City, UT, United States, 25 Feb - 2 Mar, 2010.
Presentation Type:
Poster Presentation
Topic:
Poster session II
Citation:
Fetsch
CR,
DeAngelis
GC and
Angelaki
DE
(2010). Neural correlates of dynamic sensory cue re-weighting in macaque area MSTd.
Front. Neurosci.
Conference Abstract:
Computational and Systems Neuroscience 2010.
doi: 10.3389/conf.fnins.2010.03.00299
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Received:
07 Mar 2010;
Published Online:
07 Mar 2010.
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Correspondence:
Christopher R Fetsch, Washington University School of Medicine, Saint Louis, United States, crfetsch@gmail.com