Professor of Neurobiology*
*and Helen Wills Neuroscience Institute
My laboratory studies the function and plasticity of the cerebral cortex at the synapse, cellular, and neural systems levels. We focus on the rodent primary somatosensory (S1) cortex, which is a major model system for studying how neural circuits process information, develop, and learn. S1 contains an orderly map of sensory input from the facial whiskers, which are active tactile detectors analogous to human fingertips. The lab's first major focus is to determine how the whisker system extracts tactile information from the world, and how this information is dynamically encoded and processed by S1 circuits. The goal is to discover basic principles of cortical processing, and to understand how these principles are implemented by specific circuit and synapse properties. The second major focus is on cortical plasticity. The whisker map, like other sensory maps in the brain, is not fixed, but varies strongly in response to recent sensory experience. This phenomenon, called experience-dependent map plasticity, acts during development to transform immature circuits into appropriately organized connections that mediate adult sensory perception. In adults, map plasticity allows the brain to dynamically allocate processing capacity in response to changing behavioral needs, and is a model for simple forms of learning. We are working to identify the synaptic and circuit mechanisms that drive map plasticity, and to understand how they drive information storage and learning in the cortex. Experiments combine synapse, circuit, and systems-level analysis, with a strong emphasis on neurophysiology, to understand how S1 cells and circuits process and store information under natural conditions. Experiments are designed to provide much needed basic knowledge about learning and brain development, which will promote improved therapies for plasticity-related brain disorders including autism, learning disability, and mental retardation.
Synaptic Mechanisms for Cortical Map Plasticity. Cortical map plasticity is widely hypothesized to reflect use-dependent changes at cortical synapses, including long-term potentiation (LTP) and long-term depression (LTD). We have provided some of the strongest evidence that LTD at specific cortical synapses contributes to weakening of underused sensory inputs within cortical maps. But many questions remain. Most studies of cortical plasticity focus on experience-driven changes in excitatory circuits. But cerebral cortex contains diverse and powerful inhibitory circuits as well. Recent findings indicate that inhibitory circuits are a major site of compensatory (homeostatic) plasticity that stabilizes, rather than changes, cortical sensory representations. We are currently testing how specific inhibitory subcircuits are regulated by experience, and how plasticity in inhibitory and excitatory circuits interact to alter sensory representations. This work is done using advanced whole-cell recording techniques in brain slices, extracellular and whole-cell recording in vivo, and optogenetics and 2-photon calcium imaging.
Active sensory coding in the whisker system. A major feature of sensory systems is that sensory detectors are actively moved to sample the environment (e.g., whiskers, fingertips, eyes, sniffing in the olfactory system). How the brain processes active sensory inputs is not understood. Rodents actively sweep their whiskers at 5-12 Hz to detect objects and determine object location, surface features, and shape. We are currently performing several types of experiments to determine how tactile information is extracted by moving whiskers and processed and encoded in somatosensory areas of the cortex. These include multi-site tetrode recordings during whisker detection and discrimination tasks, and single-unit and whole-cell patch clamp recordings to determine how S1 neurons encode complex, natural whisker inputs.
Time and timing in sensory processing and learning. Precise timing is critical for sensory processing, from speech production and recognition to processing of visual motion, and disruption of rapid temporal processing may be the basic deficit in dyslexia and other language impairment. Recent work from our laboratory indicates that whisker inputs are also encoded with high temporal precision, and that this precision is critical for sensory representation and for plasticity in the cortex. We are currently testing how this temporal precision arises, and its perceptual importance, with the goal of understanding the neurobiological basis for temporal processing deficits, and how they may be remedied. This work is done as part of the NSF-funded Temporal Dynamics of Learning Center.
Miyashita T, Feldman DE (2012) Behavioral detection of passive whisker stimuli requires somatosensory cortex. Cerebral Cortex, in press.
Feldman DE (2012). The spike-timing dependence of plasticity. Neuron 75: 556-71.
House DRC, Elstrott J, Koh E, Chung J, Feldman DE (2011) Parallel regulation of feedforward inhibition and excitation during whisker map plasticity. Neuron, 72: 819-31.
Morita T, Kang H, Wolfe J, Jadhav SP, Feldman DE (2011) Psychometric curve and behavioral strategies for whisker-based texture discrimination in rats. PLoS ONE 6(6): e20437.
Li L, Bender KJ, Drew PJ, Jadhav SP, Sylwestrak E, Feldman DE (2009). Endocannabinoid signaling is required for development and critical period plasticity of the whisker map in somatosensory cortex. Neuron 64: 537-49.
Jadhav SP, Wolfe J, Feldman DE (2009). Sparse temporal coding of elementary tactile features during active whisker sensation. Nat. Neurosci. doi:10.1038/nn.2328.
Wolfe J, Hill DN, Pahlavan S, Drew PJ, Kleinfeld D, Feldman DE (2008). Slip-stick events versus differential resonance in texture coding in the whisker system. PLoS Biology, 6(8): e215.
Jacob V, Brasier DJ, Erchova I, Feldman D, Shulz DE (2007). Spike timing-dependent synaptic depression in the in vivo barrel cortex of the rat. J. Neuroscience, 27: 1271-84.
Bender V, Bender K, Brasier DJ, Feldman DE (2006). Two coincidence detectors for spike timing-dependent plasticity in somatosensory cortex. Journal of Neuroscience, 26: 4166-77.
Bender K, Allen CB, Feldman DE (2006). Synaptic basis for deprivation-induced synaptic weakening in rat somatosensory cortex. Journal of Neuroscience, 26: 4155-65.
Gabernet L, Jadhav SP, Feldman DE, Carandini M, Scanziani M (2005). Somatosensory integration controlled by dynamic thalamocortical feed-forward inhibition. Neuron, 48: 1-13.
Feldman DE, Brecht M (2005). Map plasticity in somatosensory cortex. Science, 310: 810-5.
Photo credit: Mark Hanson at Mark Joseph Studios.
Last Updated 2013-05-31