Dr. Christopher Fetsch is an assistant professor of neuroscience at the John Hopkins University School of Medicine and a researcher in the Zanvyl Krieger Mind/Brain Institute. His work focuses on the neurobiology of multisensory decisions, decision confidence, and the perception of self-motion.
Dr. Fetsch received his PhD in 2009 from Washington University in St. Louis under the joint supervision of Gregory DeAngelis and Dora Angelaki. His graduate work explored how neurons in extrastriate visual cortex combine visual and vestibular signals to enable precise judgements of self-motion direction, or heading. In 2010 he joined the laboratory of Michael Shadlen at the University of Washington (later Columbia University) as a postdoctoral fellow. There, he used both conventional and emerging causal methods to study how cortical activity gives rise to a perceptual choice, as well as the animal’s confidence in that choice.
Dr. Fetsch joined the Johns Hopkins faculty in 2017, and plans to combine the approaches used in his previous work to study how the brain makes decisions based on multiple noisy and ambiguous sources of information.
Neural basis of perceptual decision making and multisensory integration
Our senses do not reflect the external world with perfect fidelity; on the contrary, sensory information is inherently noisy and often ambiguous. How do humans and animals make adaptive perceptual decisions in the face of such uncertainty?
My research addresses this question on two fronts: (a) how the brain combines information from multiple sensory modalities, and (b) how it establishes a level of confidence in a decision. Confidence—the degree of belief that a pending decision will turn out to be correct—is crucial for guiding behavior in complex environments, yet it only recently has become amenable to neuroscientific investigation. We use behavioral assays to ask animal subjects how confident they are in decisions about visual stimuli while recording and manipulating neural activity in sensory and decision-related brain areas. To complement traditional causal methods such as electrical microstimulation and pharmacological inactivation, we have developed and refined optogenetic approaches for activating and inactivating neuronal populations with greater spatial and temporal specificity. The results to date support the idea that confidence arises from the same neural mechanism—bounded evidence accumulation—that explains the choice itself and the time needed to decide.
My future work will bring the experimental and theoretical toolkit of decision making to bear on the more natural case of multiple, time-varying sensory inputs. For example, as an animal moves through its environment, it can use both visual and vestibular cues to judge its speed and direction of self-motion (and confidence therein). Exploring how neural circuits perform this feat, despite the inherent uncertainty of the incoming signals, will shed light on general principles of higher brain function.
Zylberberg A, Fetsch CR, and Shadlen MN. (2016) The influence of evidence volatility on choice, reaction time and confidence in a perceptual decision. eLife 2016;5:e17688. full text
Fetsch CR. (2016) The importance of task design and behavioral control for understanding the neural basis of cognitive functions. Current Opinion in Neurobiology 37: 16-22. journalfull text
Fetsch CR, Kiani R, and Shadlen MN. (2015) Predicting the accuracy of a decision: A neural mechanism of confidence. Cold Spring Harbor Symposia on Quantitative Biology 79: 185-97. journalfull text
Fetsch CR, Kiani R, Newsome WT, and Shadlen MN. (2014) Effects of cortical microstimulation on confidence in a perceptual decision. Neuron 83(4): 797-804. journalfull text
Fetsch CR, DeAngelis GC, and Angelaki DE. (2013) Bridging the gap between theories of sensory cue integration and the physiology of multisensory neurons. Nature Reviews Neuroscience 14(1): 429-42. journalfull text
Webb AB, Fetsch CR, Israel E, Roman CM, Encarnación CH, Zacks JM, Thoroughman KA, Herzog ED. (2012) Training scientists in a science center improves science communication to the public. Advances in Physiology Education 36(1): 72-76. journal
Fetsch CR, Pouget A, DeAngelis GC, and Angelaki DE. (2011) Neural correlates of reliability-based cue weighting during multisensory integration. Nature Neuroscience 15(1): 146-54. journalfull text
Gu Y, Liu S, Fetsch CR, Yang Y, Fok S, Sunkara A, DeAngelis GC, Angelaki DE. (2011) Perceptual learning reduces interneuronal correlations in macaque visual cortex. Neuron 71(4): 750-61. journalfull text
Fetsch CR, Rajguru SM, Karunaratne A, Gu Y, DeAngelis GC, and Angelaki DE. (2010) Spatiotemporal properties of vestibular responses in area MSTd. Journal of Neurophysiology 104(3): 1506-22. journalfull text
Fetsch CR, DeAngelis GC, and Angelaki DE. (2010) Visual-vestibular cue integration for heading perception: applications of optimal cue integration theory. European Journal of Neuroscience 31(10): 1721-9. journalfull text
Gu Y, Fetsch CR, Gu Y, Adeyemo B, Angelaki DE, and DeAngelis GC. (2010) Decoding of MSTd population activity accounts for variations in the precision of heading perception. Neuron 66(4): 596-609. journalfull text
Fetsch CR, Turner AH, DeAngelis GC, and Angelaki DE. (2009) Dynamic re-weighting of visual and vestibular cues during self-motion perception. Journal of Neuroscience 29: 15601-12. journalfull text
Fetsch CR, Wang S, Gu Y, DeAngelis GC, and Angelaki DE. (2007) Spatial reference frames of visual, vestibular, and multimodal heading signals in the dorsal subdivision of the medial superior temporal area. Journal of Neuroscience 27(3): 700-12. journalfull text
Fetsch CR, Heideman PD, and Griffin JD. (2006) Effects of melatonin on thermally classified anterior hypothalamic neurons in the white-footed mouse (Peromyscus leucopus). Journal of Thermal Biology 31: 40-49. journal
Kossler WJ, Fetsch C, and Baranowski K. (2003) Magnetic field distributions from longitudinally disordered pancake vortices. Physica B: Condensed Matter 326: 300-304. journal
Angelaki DE, Gu Y, Fetsch CR, and DeAngelis GC. (2012) Mechanisms of multisensory perception: probabilistic integration of visual and vestibular signals. In: The New Handbook of Multisensory Processing, Stein BE ed. MIT Press, Cambridge, MA; pp. 483-494.
Fetsch CR, Gu Y, DeAngelis GC, and Angelaki DE. (2011) Self-motion perception: multisensory integration in extrastriate visual cortex. In Sensory Cue Integration, Trommershäuser J, Körding K, and Landy MS, eds. Oxford University Press, pp. 295-316.