- Assistant Professor, Brain and Cognitive Sciences
PhD, University of California at San Diego, 2002
307 Meliora Hall
Office Hours: By appointment
An understanding of information processing at the level of cortical circuits remains a key challenge for understanding the brain and how the dysfunction of its circuits contributes to human mental disease. It has long been appreciated that internal brain states, such as selective attention, can profoundly modulate our perception. For example, when an observer focuses their attention toward a single object, such as a friend at a crowded party, it can lead to an almost complete filtering of the background. My research focuses on the role that internal brain states, such as selective attention, play in modulating sensory processing. In particular, I am interested in the distinct roles that different neuronal classes play in this process.
I have forged a new direction in research developing the smaller New World primate, the marmoset (Callithrix Jacchus), to study active visual perception and attention. The marmoset provides several advantages as a model organism for these studies. First, the marmoset’s visual and oculomotor system is highly similar to that of larger primates and humans. Second, the recent development of transgenic lines in this species has opened many new opportunities for biomedical research. At present, multiple international projects are developing genetic models of human mental disease as well as the methodologies to study their brain physiology. Last, due to their smooth lissencephalic brain, all of the visual and oculomotor areas lie accessible at the cortical surface of the marmoset, much facilitating the use of modern recording methods with planar and laminar arrays. In recent work I have established the necessary techniques for visual behavior and neurophysiology in this species. This opens new opportunities to study visual perception and attention in cortical circuits at a much deeper level.
- How spatial attention alters statistics of neuronal spiking
- Extracellular classification of neuronal types in awake animals
- Systems identification models of sensory processing and attention
- Network models of spiking neurons and correlations in firing
- Human psychophysics in object-based attention, recognition, and perceptual learning
- Mitchell, J. F., & Leopold, D. A. (2015). The marmoset monkey as a model for visual neuroscience. Neuroscience research, 93, 20-46.
- Kwon S, Huxlin KR, & Mitchell JF (2021). Perceptual restoration fails to recover unconscious processing for smooth eye movements after occipital stroke. bioRxiv.
- Kwon S, Rolfs M, Mitchell JF (2019). Presaccadic motion integration drives a predictive postsaccadic following response. Journal of vision, 19(11), 12-12.
- Cloherty SL, Yates JL, Graf D, DeAngelis GC, Mitchell JF (2019). Motion Perception in the Common Marmoset. Cereb Cortex. doi: 10.1093/cercor/bhz267
- Nummela SU, Coop S, Cloherty SL, Boisvert CJ, Leblanc M, Mitchell JF (2016). ‘Psychophysical measurement of marmoset acuity and myopia’ Devel Neurobio. Accepted Author Manuscript. Doi:10.1002/denu.22467.
- MacDougall M, Nummela SU, Coop S, Disney A, Mitchell JF, Miller CT (2016). Optogenetic manipulation of neural circuits in awake marmosets. J Neurophysiol, 116(3), 1286-94.
- Miller CT, Friewald W, Leopold DA, Mitchell JF, Silva AC, Wang XJ (2016). ‘Marmosets: A Neuroscientific Model of Human Social Behavior.’ Neuron, 90(2), 219-233.
- Mitchell, JF, Priebe, NJ, & Miller, CT (2015). Motion dependence of smooth pursuit eye movements in the marmoset. Journal of Neurophysiology, 113(10), 3954-3960.
- The marmoset monkey as a model for visual neuroscience. Mitchell, J. F., & Leopold, D. A. Neuroscience research, 93, 20-46 (2015).
- Active Vision in Marmosets: A Model System for Visual Neuroscience. JF Mitchell, JH Reynolds, CT Miller. The Journal of Neuroscience, 2014, 34(4):1183–1194.
- The fine structure of shape tuning in area V4. AS Nandy, TO Sharpee, JH Reynolds, JF Mitchell. Neuron, 2013, 78:1102-15.
- Attention-dependent reductions in burstiness and action-potential height in macaque area V4. EB Anderson, JF Mitchell, JH Reynolds. Nature Neuroscience 16, 1125-1131 (2013).
- Attention influences single unit and local field potential response latencies in visual cortical area V4. KA Sundberg, JF Mitchell, TJ Gawne, JH Reynolds. J Neurosci, 2012, 32(45):16040-50.
- Attentional modulation of firing rate varies with burstiness across putative pyramidal neurons in macaque visual area V4. EB Anderson, JF Mitchell, JH Reynolds. J Neurosci, 2011, 31(30):10983-92.
- Spatial attention decorrelates intrinsic activity fluctuations in macaque area V4. JF Mitchell, KA Sundberg, JH Reynolds. Neuron, 2009, 63. 879-888. .... and Supplemental
- Spatial attention modulates center-surround interactions in macaque visual area V4. KA Sundberg, JF Mitchell, JH Reynolds. Neuron, 2009, 61. 1-12.
- Differential attention-dependent response modulation across cell classes in macaque visual area V4. JF Mitchell, KA Sundberg, JH Reynolds. Neuron, 2007, 55. 131-141. ... and Supplemental
- ERP evidence that surface-based attention biases interocular competition during rivalry. W Khoe, JF Mitchell, JH Reynolds, SA Hillyard. J. Vision, 2008, 8(3):18, p1-11.
- Exogenous attentional selection of transparent superimposed surfaces modulates early event-related potentials. W Khoe, JF Mitchell, JH Reynolds, SA Hillyard. Vision Research, 2005, 45. 3004-3014.
- Object-based attention determines dominance in binocular rivalry. JF Mitchell, GR Stoner, JH Reynolds. Nature, 2004, 429. 410-413.
- Sequential memory-guided saccades and target selection: A neural model of the frontal eye fields. JF Mitchell and D Zipser. Vision Research, 2003, 43. 2669-2695.
- Attentional selection of superimposed surfaces cannot be explained by modulation of the gain of color channels. JF Mitchell, GR Stoner, M Fallah, and JH Reynolds. Vision Research, 2003, 43(12). 1323-8.
- A model of visual-spatial memory across saccades. JF Mitchell and D Zipser. Vision Research 41(2001): 1575-1592.
- Age-independent stability, prevision, and near-24-hour period of the human circadian pacemaker. Czeisler CA, Duffy JF, Shanahan TL, Brown EN, Mitchell JF, Rimmer DW, Ronda JM, Silva EJ, Allan JS, Emens JS, Dijk DJ, Kronauer RE. Science, 1999, June, 284: 1-5.
Cory Miller, Dept of Psychology and Neuroscience Graduate Program, UCSD
Ed Callaway, Systems Neurobiology, The Salk Institute, La Jolla, CA
John Reynolds, Systems Neurobiology, The Salk Institute, La Jolla, CA