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Kate Hong - Carnegie Mellon University. Pittsburgh, PA, US

Kate Hong

Associate Professor | Carnegie Mellon University


Kate Hong's research is in understanding the organization and function of neural circuits that underlie sensory-guided behaviors.


Kate Hong's research interests include systems neuroscience, characterization of neural circuits, diseases & disorders, sensation & perception, behavioral methods, computational, mathematical & statistical methods and physiological & anatomical methods. Her work combines animal behavior, high-speed imaging, motion tracking, in vivo electrophysiology and optogenetic methods to determine how cortical and subcortical activity cooperate to mediate (tactile) sensory-motor transformations in parallel, providing a foundation for understanding behavioral deficits and recovery mechanisms associated with cortical injury.

Areas of Expertise (7)

Behavioral Methods

Characterization of Neural Circuits

Computational, Mathematical & Statistical Methods

Diseases & Disorders

Physiological & Anatomical Methods

Sensation & Perception

Systems Neuroscience

Media Appearances (2)

Biology Professor Receives Grant for Autism Research

Mellon College of Science  online


Kate Hong, an assistant professor of biological sciences and a member of Carnegie Mellon University's Neuroscience Institute, has received a Simons Foundation Autism Research Initiative (SFARI) grant for research into the interaction between sensory processing and decision-making in individuals with autism spectrum disorder (ASD).

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CMNI Welcomes Two New Faculty: Kate Hong and Matt Smith

Carnegie Mellon Neuroscience Institute  online


The Carnegie Mellon Neuroscience Institute is excited to welcome two new faculty members on board: Kate Hong, who will join in January 2020 as an Assistant Professor jointly in CMNI and Biological Sciences; and Matt Smith, who will also join in January 2020 as an Associate Professor with tenure in CMNI and Biomedical Engineering.

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Accomplishments (1)

Molecular Basis of Cognition Team Award (professional)


Education (2)

Harvard University: Ph.D., Neurobiology

Brown University: Sc.B., Biochemistry

Articles (5)

Effects of arousal and movement on secondary somatosensory and visual thalamus


2021 Sensory information reaches the neocortex through multiple anatomical pathways in the thalamus. Prior work has disagreed on whether these encode parallel components of the same sensory signals or differ in how they mix sensory signals with information about behavioral state. Studying the somatosensory system in awake mice, the authors provide evidence supporting the second view. The authors find similar state dependent activity in a higher order visual thalamic nucleus. This is a timely study in that many have observed state-dependent activity throughout the cortex and thalamus, but the mechanisms of this activity are incompletely understood. This study brings us closer to revealing the source of this signal by ruling out major excitatory inputs including afferents carrying movement information, feedback from the cortex and inputs from the colliculus in the midbrain.

Sensorimotor strategies and neuronal representations for shape discrimination


2021 Humans and other animals can identify objects by active touch, requiring the coordination of exploratory motion and tactile sensation. Both the motor strategies and neural representations employed could depend on the subject's goals. We developed a shape discrimination task that challenged head-fixed mice to discriminate concave from convex shapes. Behavioral decoding revealed that mice did this by comparing contacts across whiskers. In contrast, a separate group of mice performing a shape detection task simply summed up contacts over whiskers. We recorded populations of neurons in the barrel cortex, which processes whisker input, and found that individual neurons across the cortical layers encoded touch, whisker motion, and task-related signals.

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A rapid whisker-based decision underlying skilled locomotion in mice


2021 Skilled motor behavior requires rapidly integrating external sensory input with information about internal state to decide which movements to make next. Using machine learning approaches for high-resolution kinematic analysis, we uncover the logic of a rapid decision underlying sensory-guided locomotion in mice. After detecting obstacles with their whiskers mice select distinct kinematic strategies depending on a whisker-derived estimate of obstacle location together with the position and velocity of their body. Although mice rely on whiskers for obstacle avoidance, lesions of primary whisker sensory cortex had minimal impact. While motor cortex manipulations affected the execution of the chosen strategy, the decision-making process remained largely intact.

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Deep and superficial layers of the primary somatosensory cortex are critical for whisker-based texture discrimination in mice


2020 The neocortex, comprised of multiple distinct layers, processes sensory input from the periphery, makes decisions, and executes actions. Despite extensive investigation of cortical anatomy and physiology, the contributions of different cortical layers to sensory guided behaviors remain unknown. Here, we developed a two-alternative forced choice (2AFC) paradigm in which head-fixed mice use a single whisker to either discriminate textures of parametrically varied roughness or detect the same textured surfaces. Lesioning the barrel cortex revealed that 2AFC texture discrimination, but not detection, was cortex-dependent. Paralyzing the whisker pad had little effect on performance, demonstrating that passive can rival active perception and cortical dependence is not movement-related.

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Primary somatosensory cortex is essential for texture discrimination but not object detection in mice

IBRO Reports

2019 The sense of touch is a fundamental part of our sensory experience, yet our understanding of the underlying neural circuitry is limited. For example, the primary somatosensory cortex (S1) has long been assumed to play a crucial role in tactile processing. Yet, surprising results from our lab has recently shown that S1 is completely dispensable for a whisker-based go/no-go object detection task in mice. We therefore asked whether finer discrimination of tactile stimuli require the greater computational power of the cortex. In order to test this, we developed a two-alternative forced choice (2AFC) paradigm in which head-fixed mice are trained to either (1) detect objects or (2) discriminate between two textures using only their whiskers.

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