Dr. Ed Connor is a professor of neuroscience at the Johns Hopkins University School of Medicine. He serves as director of the Zanvyl Krieger Mind/Brain Institute. His research examines object synthesis in the higher-level visual cortex.
Dr. Connor obtained his PhD in neuroscience from Johns Hopkins in 1989. After postdoctoral studies at the California Institute of Technology and Washington University, he joined the Hopkins Neuroscience Department in 1996. He has served as Director of the Zanvyl Krieger Mind/Brain Institute since 2007.
His work has shown how object structure is represented by populations of neurons in higher-level visual regions of the brain. In new studies funded by the Hopkins Brain Science Institute, his laboratory has begun to investigate the neural basis of shape aesthetics.
Object Synthesis in Higher Level Visual Cortex
The brain’s most computationally remarkable ability is visual object perception. Computers can beat us at math and chess, but machine vision has never come remotely close to the human capacity for identifying, categorizing, evaluating, and interacting with objects. The difficulty lies in the enormous complexity and high dimensionality of object information. Our research aims at understanding the neural algorithms that make object vision possible. We hope that our findings will not only explain the neural basis of visual experience but will someday contribute to designs for more powerful machine vision systems and brain-machine interfaces.
Ongoing Lines of Research
How is complex 3D object structure represented?
How is large-scale 3D structure (buildings, landscapes) represented?
How is 4D object structure (shape-in-motion through time) represented?
How are these representations generated from retinal input signals?
How is object information stored, recalled, and used in decision-making?
How do neural representations determine visual aesthetics—what is special about the neural activity patterns evoked by beautiful sculptures or paintings?
Action potential responses (electrical spikes) were recorded from an individual neuron in a high-level object-sensitive visual region of the brain (anterior inferotemporal cortex). Background color (see scale bar) indicates spikes per second evoked by each 3D shape stimulus. Neural responses were used to guide the evolution of stimuli that morphed through multiple generations (rows at top). This genetic algorithm produces sufficiently dense, focused sampling to constrain a quantitative model of 3D shape sensitivity (equations and plots showing tuning regions in surface curvature/orientation/position space). Both lineages produced models that identify sharp convex (cyan) and broad saddle-shaped (magenta) surface fragments that characterize the beak-like formation at the top right of high-response stimuli. Both models successfully cross-predict responses in the opposite, independent stimulus lineage (bottom). For more details, see Yamane, Y., Carlson, E.T., Bowman, K.C., Wang, Z. & Connor, C.E. (2008) Nature Neuroscience 11: 1352-1360.
Vaziri, S, & Connor, C.E. Representation of Gravity-Aligned Scene Structure in Ventral Pathway Visual Cortex. Current Biology (2016) 26: 766-77
Vaziri, S., Carlson, E. T., Wang, Z., & Connor, C. E. (2014). A channel for 3D environmental shape in anterior inferotemporal cortex. Neuron84: 55–62. PMCID: PMC4247160.
Yau, J.M., Pasupathy, A., Brincat, S.L., Connor C.E. (2013) Curvature processing dynamics in macaque area V4. Cerebral Cortex 23: 198–209. PMCID: PMC3513958.
Pasupathy, A. & Connor, C.E. (2002) Population coding of shape in area V4. Nature Neuroscience 5: 1332-1338.
Hinkle, D.A. & Connor, C.E. (2002) Three-dimensional orientation tuning in macaque area V4 Nature Neuroscience 5: 665-670.
Pasupathy, A. & Connor, C.E. (2001) Shape representation in area V4: Position-specific tuning for boundary conformation. Journal of Neurophysiology 86: 2505-2519.
Hinkle, D.A. & Connor, C.E. (2001) Disparity tuning in macaque area V4. NeuroReport 12: 365-369.
Pasupathy, A. & Connor, C.E. (1999) Responses to contour features in macaque area V4. Journal of Neurophysiology 82: 2490-2502.
Gallant, J.L., Connor, C.E. & Van Essen, D.C. (1998) Neural activity in areas V1, V2 and V4 during free viewing of natural scenes compared to controlled viewing. NeuroReport 9: 2153-2158.
Connor, C.E., Preddie, D.C., Gallant, J.L. & Van Essen, D.C. (1997) Spatial attention effects in macaque area V4. Journal of Neuroscience 17: 3201-3214.
Connor, C.E., Gallant, J.L., Preddie, D.C. & Van Essen, D.C. (1996) Responses in area V4 depend on the spatial relationship between stimulus and attention. Journal of Neurophysiology 75: 1306-1308.
Gallant, J.L., Connor, C.E., Rakshit, S., Lewis, J. & Van Essen, D.C. (1996) Neural responses to polar, hyperbolic, and Cartesian gratings in area V4 of the macaque monkey. Journal of Neurophysiology 76: 2718-2739.
Steinmetz, M.A., Connor, C.E., Constantinidis, C. & McLaughlin, J.R. (1994) Covert attention suppresses neuronal responses in area 7a of the posterior parietal cortex. Journal of Neurophysiology 72: 1020-1023.
Connor, C.E. & Johnson, K.O. (1992) Neural coding of tactile texture: comparison of spatial and temporal mechanisms for roughness perception. Journal of Neuroscience 12: 3414-3426.
Connor, C.E., Hsiao, S.S., Phillips, J.R. & Johnson, K.O. (1990) Tactile roughness: neural codes that account for psychophysical magnitude estimates. Journal of Neuroscience 10: 3823-3836.
Connor, C.E. & Kuczenski, R. (1986) Evidence that amphetamine and Na+ gradient reversal increase striatal synaptosomal dopamine synthesis through carrier-mediated efflux of dopamine. Biochemical Pharmacology 35: 3123-3130.
Reviews, Comments, and Chapters
Connor, C.E. Stuphorn, V. The Decision Path Not Taken. Neuron (2015) 87: 1128–1130.
Connor, C. E. (2014). Cortical geography is destiny. Nature Neuroscience17: 1631–1632.
Roe, A.W., Chelazzi, L., Connor, C.E., Conway, B.R., Fujita, I., Gallant, J.L., Lu, H., Vanduffel, W. (2012) Toward a unified theory of visual area V4. Neuron74: 12–29.
Kourtzi, Z. & Connor, C.E. (2011) Neural representations for object perception: structure, category, and adaptive coding. In: Annual Review of Neuroscience34: 45–67.
Connor, C.E. (2010) A new viewpoint on faces. Science330: 764–765.
Connor CE, Pasupathy A, Brincat S,Yamane Y. Neural transformation of object information by ventral pathway visual cortex. In: The Cognitive Neurosciences IV: Fourth Edition, Gazzaniga MS, ed, MIT Press, Cambridge MA (2009).
Vaziri SL, Pasupathy A, Brincat SL, Connor CE. Structural representation of object shape in the brain. In: Object Categorization: Computer and Human Vision Perspectives, Cambridge University Press (2009).
Connor CE, Brincat SL, Pasupathy A. Shape representation in the ventral visual pathway. Current Opinion in Neurobiology (2007) 17: 140-147.
Connor CE. Neural construction of objects from parts. In: Computational vision in neural and machine systems, Harris LR, Jenkin MRM, eds, Cambridge University Press (2007).