Daniel Feldman

Professor of Neurobiology*
*and Coates Family Endowed Chair

Lab Homepage: http://mcb.berkeley.edu/labs/feldman/

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Research Interests

How do neural circuits in the brain’s cerebral cortex mediate sensation, memory and information processing, and how does this break down in neurological disease? Our lab seeks to answer these questions by studying cortical function at the synaptic, circuit, and systems neuroscience levels. We study how cortical circuits process sensory information, adapt to experience, and store information during learning. We investigate the cellular and circuit mechanisms for brain plasticity, and the homeostatic mechanisms that maintain proper cortical function across age and experience. We study the micro-organization of sensory maps in the cortex to reveal principles of information processing and circuit design. Beyond this basic science discovery, we apply our understanding of cortical function to develop new insights into how cortical circuit function goes awry in autism spectrum disorders.

Approaches include synaptic physiology, 2-photon calcium imaging, in vivo circuit physiology and optogenetics, and quantitative sensory behavior. The model system is the rodent’s primary somatosensory (S1) cortex, which is a leading system for studying sensory information processing, learning, and plasticity.  S1 processes tactile (touch) information from the rodent’s facial whiskers, which are active tactile detectors analogous to human fingertips.  Cell types and circuits in rodent S1 are similar to primates.  Thus, studying rodent S1 can reveal the underlying principles of cortical function across mammals, including humans.

Current Projects

Our goal is to identify major principles of cortical information processing, information storage and learning, from synapse to circuit to neural systems levels.  We study how synapse function impacts circuit-level processing; how recent sensory experience alters S1 neurons and circuits to store sensory information and optimize cortical processing;  and how homeostatic plasticity acts to maintain normal circuit function despite changing sensory input.  We study how sensory information is organized within precise micro-scale maps, and how whisker information is transformed across cortical layers.  We study how real-world tactile information is encoded by population activity in S1, to guide perception and behavior.   

Our research will provide much-needed basic knowledge about brain function, and will enable better understanding of common disorders of cortical function and plasticity, including autism and epilepsy.  We are actively investigating the neural circuit basis for autism, using transgenic mouse models of this disorder.

Neural coding and information processing in whisker somatosensory cortex.  How do cortical circuits extract and represent sensory information?  What is the role of the different cortical layers in this process?  What computations are implemented by sensory cortex?  To address these questions, we study how tactile information is sensed by moving whiskers and processed and encoded in S1 cortex.  Methods include multi-site neural recordings during quantitative sensory behavior, 2-photon calcium imaging of neural activity in S1, optogenetics, and computational analysis of population coding.  We also study the precise structure of sensory maps, how they vary across layers, and how learning is implemented by changes in maps.

Synaptic mechanisms for cortical map plasticity and stability.  Information is stored in neural networks by Hebbian synaptic plasticity, as well as by anatomical rewiring of cortical microcircuits and other mechanisms.  We work to identify specific sites and mechanisms of plasticity, and to understand how multiple plasticity mechanisms interact to drive overall changes in receptive fields and maps.  Methods include slice physiology, whole-cell patch clamp recording, optogenetics, and calcium imaging.  Many of our current studies focus on plasticity in inhibitory microcircuits, and how it contributes to plasticity and stability in cortical maps.

Neural circuit basis for autism spectrum disorders.  Autism is a family of neurodevelopmental disorders with a complex genetic basis, and is often associated with tactile sensory phenotypes.  Using transgenic mouse models of monogenic forms of autism, we study how synapse- and circuit-level function is disrupted in cerebral cortex in autism. We study how this affects neural coding and information processing, and test whether different genetic forms of autism share common physiological phenotypes in cortex. If so, it may be possible to develop therapeutic interventions that are broadly effective across multiple genetic types of autism.

Selected Publications

Selected recent publications

Isett BR, Feldman DE.  Cortical coding of whisking phase during surface whisking (2020). Current Biology Jun 5:S0960-9822(20)30751-X.

LeMessurier AM, Laboy-Juárez KJ, McClain K, Chen S, Nguyen TM, Feldman DE (2019). Enrichment drives emergence of functional columns and improves sensory coding in the whisker map in L2/3 of mouse S1.  eLife, 8. pii: e46321. doi: 10.7554/eLife.46321.

Laboy-Juarez KJ, Ahn S, Feldman DE. (2019) A normalized template matching method for improving spike detection in extracellular voltage recordings. Scientific Reports, 9, 12087 (2019)

Laboy-Juárez KJ, Langberg T, Ahn S, Feldman DE (2019).  Elementary motion sequence detectors in whisker somatosensory cortex.  Nature Neuroscience, 22(9):1438-1449.

Antoine MW*, Langberg T*, Schnepel P*, Feldman DE. (2019) Increased excitation-inhibition ratio stabilizes synapse and circuit excitability in four autism mouse models. Neuron, 101(4) 648-661

Isett BR, Feasal SH, Lane MA, Feldman DE. (2018) Slip-based coding of local shape and texture in mouse S1. Neuron 97: 1-16.

Gainey MA, Aman JW, Feldman DE. (2018) Rapid disinhibition by adjustment of PV intrinsic excitability during whisker map plasticity in mouse S1. Journal of Neuroscience, 38(20) 4829-4839.

Gainey MA, Feldman DE (2017).  Multiple shared mechanisms for homeostatic plasticity in rodent somatosensory and visual cortex.  Phil. Trans. Royal Soc. B.  372(1715): 20160157. 

McGuire LM*, Telian G*, Laboy-Juárez KJ*, Miyashita T, Lee DJ, Smith KA, Feldman DE. (2016) Short time-scale sensory coding in S1 during discrimination of whisker vibrotactile sequences. PLoS Biology, 14(8):e1002549.

Clancy KB, Schnepel P, Rao AT, Feldman DE (2015) Structure of a single whisker representation in layer 2 of mouse somatosensory cortex. Journal of Neuroscience, 35: 3946-58.

Clancy KB*, Koralek AC*, Costa RM†, Feldman DE†, Carmena JM† (2014). Volitional modulation of optically recorded calcium signals during neuroprosthetic learning. Nature Neuroscience, 17: 807-9.

Li L, Gainey MA, Goldbeck JE, Feldman DE (2014). Rapid homeostasis by disinhibition during whisker map plasticity. Proc. Natl. Acad Sci. USA, 111: 1616-21.

Shao YR, Isett BR, Miyashita T, Chung J, Pourzia O, Gasperini RJ, Feldman DE (2013) Plasticity of recurrent L2/3 inhibition and gamma oscillations by whisker experience. Neuron, 80: 210-22.

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.

Feldman DE (2012).  The spike-timing dependence of plasticity. Neuron 75: 556-71.

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.  Nature Neuroscience 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.

Photo credit: Mark Hanson at Mark Joseph Studios.

Last Updated 2020-09-10