Research topics
- Artificial Intelligence
- Computer Science
- Neuroscience
- Cognitive psychology
- Psychology
- Communication
- Medicine
- Genetics
- Cognitive science
- Biology
- Telecommunications
Selected publications
Coordinated multiplexing of information about separate objects in visual cortex
eLife · 2022 · 32 citations
Senior authorCorresponding- Computer Science
- Artificial Intelligence
- Neuroscience
of the stimuli that may be present at a given moment? We recently showed that when more than one stimulus is present, single neurons can fluctuate between coding one vs. the other(s) across some time period, suggesting a form of neural multiplexing of different stimuli (Caruso et al., 2018). Here, we investigate (a) whether such coding fluctuations occur in early visual cortical areas; (b) how coding fluctuations are coordinated across the neural population; and (c) how coordinated coding fluctuations depend on the parsing of stimuli into separate vs. fused objects. We found coding fluctuations do occur in macaque V1 but only when the two stimuli form separate objects. Such separate objects evoked a novel pattern of V1 spike count ('noise') correlations involving distinct distributions of positive and negative values. This bimodal correlation pattern was most pronounced among pairs of neurons showing the strongest evidence for coding fluctuations or multiplexing. Whether a given pair of neurons exhibited positive or negative correlations depended on whether the two neurons both responded better to the same object or had different object preferences. Distinct distributions of spike count correlations based on stimulus preferences were also seen in V4 for separate objects but not when two stimuli fused to form one object. These findings suggest multiple objects evoke different response dynamics than those evoked by single stimuli, lending support to the multiplexing hypothesis and suggesting a means by which information about multiple objects can be preserved despite the apparent coarseness of sensory coding.
Journal of Neurophysiology · 2021 · 28 citations
Senior authorCorresponding- Neuroscience
- Psychology
- Communication
Models for visual-auditory integration posit that visual signals are eye-centered throughout the brain, whereas auditory signals are converted from head-centered to eye-centered coordinates. We show instead that both modalities largely employ hybrid reference frames: neither fully head- nor eye-centered. Across three hubs of the oculomotor network (intraparietal cortex, frontal eye field, and superior colliculus) visual and auditory signals evolve from hybrid to a common eye-centered format via different dynamics across brain areas and time.
Monkeys and humans implement causal inference to simultaneously localize auditory and visual stimuli
Journal of Neurophysiology · 2020 · 31 citations
Senior authorCorresponding- Computer Science
- Artificial Intelligence
- Psychology
We developed a novel behavioral paradigm for the study of multisensory causal inference in both humans and monkeys and found that both species make causal judgments in the same Bayes-optimal fashion. To our knowledge, this is the first demonstration of behavioral causal inference in animals, and this cross-species comparison lays the groundwork for future experiments using neuronal recording techniques that are impractical or impossible in human subjects.
Recent grants
NIH · $2.6M · 2015
NIH · $1.8M · 2011
Eye Position and the Neural Basis of Sound Localization
NSF · $436k · 2005–2007
NIH · $1.6M · 2017–2023
Eye Position and the Neural Basis of Sound Localization
NSF · $439k · 2006–2010
Frequent coauthors
- 22 shared
David LK Murphy
Duke University
- 20 shared
Christopher A. Shera
University of Southern California
- 19 shared
Valeria C. Caruso
University of Michigan–Ann Arbor
- 17 shared
Surya T. Tokdar
Duke University
- 17 shared
Cynthia King
Duke University
- 16 shared
Stephanie N Lovich
Duke University
- 14 shared
Rachel Landrum
Duke University
- 13 shared
Shawn M. Willett
Center for the Neural Basis of Cognition
Labs
Groh LabPI
Education
- 1997
postdoctoral, Neurobiology
Stanford University
- 1993
PhD, Neuroscience
University of Pennsylvania
- 1989
M. S., Neuroscience
University of Michigan
- 1988
A.B., Biology
Princeton University
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