Christopher Fetsch PhD

Assistant Professor of Neuroscience

cfetsch@jhu.edu
Telephone Number: 410-516-8640
Fax Number: 410-516-8648

The Zanvyl Krieger Mind/Brain Institute
Johns Hopkins University
3400 N. Charles Street
338 Krieger Hall
Baltimore, MD 21218
Room: Krieger Hall 353
Areas of Research
Systems, Cognitive + Computational Neuroscience
Neural Circuits, Ensembles + Connectomes

Graduate Program Affiliations

Neuroscience Training Program

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    AAV-mediated expression of the light-driven chloride pump Jaws in superficial and deep layers of macaque parietal cortex.

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    Depiction of bounded accumulation model for decision making. Left panel: Noisy momentary evidence is drawn from a Gaussian distribution and accumulated over time, as shown for three example trials (colored traces). Decision formation terminates when the stimulus is turned off (green and blue trials) or when the accumulated evidence reaches an upper or lower decision bound (red trial). Right panel: To explain confidence in a decision, the model assumes the brain has implicit knowledge of the probability of being correct (formalized as the logarithm of the posterior odds) as a function of accumulated evidence and decision time. Black contours indicate a criterion on log-odds that partitions the space into low- and high-confidence regions.


Neural Basis of Multisensory Perception and Decision Making

The neuroscience of decision making offers a path to understanding higher brain function at a mechanistic level, the level of neural populations and circuits. Indeed, even relatively simple decisions about sensory stimuli contain the rudiments of more complex processes necessary for human cognition. These include evaluating sources of evidence, predicting and planning for the near future, and reasoning about one’s own mental operations (i.e., metacognition).

The goal of my research is to reverse-engineer these building blocks of mental function by combining the quantitative measurement and modeling of behavior with modern tools for recording and manipulating neural activity in nonhuman primates. Beyond its intrinsic value, the level of understanding we achieve with this approach could eventually open new avenues for treating neurological and psychiatric disorders, such as schizophrenia and Alzheimer’s disease.

In the natural world, the brain faces the challenge of how to interpret a multitude of signals — often ambiguous and corrupted by noise — arriving at the sensory periphery at all times. In my lab we study the problem of perceiving one’s own self-motion, as well as motion of objects in the environment, based on visual and non-visual (e.g., vestibular) cues. Using state-of-the-art flight simulator technology, we can deliver arbitrary three-dimensional movement trajectories and/or simulated movement through virtual environments, while simultaneously recording neural population activity in multisensory and decision-related brain areas. Advances in causal methods, including optogenetics, enable temporally and spatially precise manipulations of such activity to dissect the behavioral role of specific populations and circuit components.

 

 

 

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