Michael Wehr

Associate Professor, Department of Psychology
Member, ION

Ph.D. California Institute of Technology
Sc.B. Brown University

Office:
LISB 213
541-346-5866
Lab:
LISB 203-206
541-346-6302

 

Research Interests: How local circuits in the auditory cortex encode and transform sensory information

Overview: We study how local circuits in the cerebral cortex encode and transform sensory information. We use the rodent auditory cortex as a model system to investigate how cellular and network properties shape cortical responses to a continuous and temporally complex stream of sensory data. Research in my laboratory combines aspects of both cellular, systems, and computational neuroscience, by using the tools of molecular biology and cellular physiology to address systems-level questions. By using a variety of electrophysiological approaches, in particular in vivo whole cell recording methods in combination with molecular manipulations, we are trying to identify the cellular and synaptic mechanisms with which cortical circuits process auditory information, leading ultimately to our perceptual experiences of acoustic streams, such as music and speech.

RECENT PUBLICATIONS

Related Articles

Mice can learn phonetic categories.

J Acoust Soc Am. 2019 Mar;145(3):1168

Authors: Saunders JL, Wehr M

Abstract
Speech is perceived as a series of relatively invariant phonemes despite extreme variability in the acoustic signal. To be perceived as nearly-identical phonemes, speech sounds that vary continuously over a range of acoustic parameters must be perceptually discretized by the auditory system. Such many-to-one mappings of undifferentiated sensory information to a finite number of discrete categories are ubiquitous in perception. Although many mechanistic models of phonetic perception have been proposed, they remain largely unconstrained by neurobiological data. Current human neurophysiological methods lack the necessary spatiotemporal resolution to provide it: speech is too fast, and the neural circuitry involved is too small. This study demonstrates that mice are capable of learning generalizable phonetic categories, and can thus serve as a model for phonetic perception. Mice learned to discriminate consonants and generalized consonant identity across novel vowel contexts and speakers, consistent with true category learning. A mouse model, given the powerful genetic and electrophysiological tools for probing neural circuits available for them, has the potential to powerfully augment a mechanistic understanding of phonetic perception.

PMID: 31067917 [PubMed - in process]