Professor of the Graduate School
School of Optometry
Member of groups in Neuroscience, Bioengineering, and Biophysics; and the Helen Wills Neuroscience Institute
Central Visual Pathways: Systems and Computational Neuroscience
Our laboratory is concerned with the neural organization of central visual pathways in the brain. We are interested in how visual information is encoded, transmitted and detected. We seek to determine the neural basis of specific aspects of visual performance. In addition to the consideration of normal visual organization, we are interested in development and plasticity of vision. What is genetically determined and what is shaped by the visual environment?
Our approach is to try to formulate physiologically plausible hypotheses or models whose predictions are subject to experimental verification. We then design and perform experiments that are specifically intended to test the predictions of the hypotheses or models.
Our experimental approaches are neurophysiological and involve extracellular microelectrode recordings from single or multiple neurons. Most of our work concerns striate or extra-striate visual cortex but we also address questions that require recording in the lateral geniculate nucleus. We are now able to record from small groups of cells simultaneously by use of several adjacent electrodes. This allows cross-correlation analysis to be used between different combinations of cell pairs, which provides insights about functional connections between neurons. Conventional and elaborate visual stimulation techniques are used. In this way, a variety of visual parameters can be studied simultaneously. Most of our work is of a quantitative nature and extensive use is made of computers.
Recently, we have developed an interest in the relationship between neural and metabolic activity in the brain. This topic is fundamentally important for the field of functional magnetic resonance imaging (fMRI). fMRI is an exciting and relatively new method for monitoring neural activity non-invasively. It has both basic and clinical applications. The technique infers changes in neural activity through signals dependent on blood flow and oxidative metabolism. To explore this relationship, we have made simultaneous measurements of neural activity and associated levels of tissue oxygenation in co-localized regions of the visual pathway (Thompson, J.K., Peterson, M., Freeman, R.D. (2003) Single Neuron Activity and Tissue Oxygenation in the Cerebral Cortex. Science 299: 1070-1072). We are pursuing this work in current investigations.
B. Li and R.D. Freeman (2011). Neurometabolic coupling differs for suppression within and beyond the classical receptive field in visual cortex. J. Physiology, 589.13: 3175-3190.
T. Duong, B.D. Moore IV, and R.D. Freeman (2011). Adaptation changes stereoscopic depth selectivity in visual cortex. J. Neuroscience, 31(34)12198-12207.
B. Li and R.D. Freeman (2010). Neurometabolic coupling in the lateral geniculate nucleus changes with extended age. J. Neurophysiol, 104: 414-423.
R.D. Freeman (2009). Visual Deprivation (Section in New Encyclopedia of Neuroscience, Larry R. Squire, ed., Elsevier Press.
N. Qian and R.D. Freeman (2009) Pulfrich phenomena are coded effectively by a joint motion-disparity process Journal of Vision.9: 1-16.
B. Pasley, E. Allen, and R.D. Freeman (2009). State-Dependent Variability of Neuronal Responses to Transcranial Magnetic Stimulation of the Visual Cortex. Neuron.62: 291-303.
A. Viswanathan and R.D. Freeman (2008). BOLD and spiking activity. Nature Neuroscience.11: 523-524.
B. Pasley and R.D. Freeman (2008). Neurovascular Coupling (Scholarpedia, 3(3):5340. Online copy at Scholarpedia
T. Duong and R.D. Freeman (2008). Contrast sensitivity is enhanced by expansive nonlinear processing in the LGN. Journal of Neurophysiology. 99: 367-372.
R.D. Freeman (2008). Binocular Vision. (Section in Encyclopedia of Neuroscience, Andreas K. Engel, ed., Springer-Verlag.
E. Allen*, B. Pasley*, T. Duong, and R.D. Freeman (2007). Transcranial magnetic stimulation elicits coupled neural and hemodynamic consequence. (Science. 317: 1918-1921. (*equal contributions)
A. Viswanathan and R.D. Freeman (2007). Neurometabolic coupling in cerebral cortex reflects synaptic more than spiking activit. (Nature Neuroscience. 10: 1308-12.
B. Li and R.D. Freeman (2007). High-resolution neuro-metabolic coupling in the lateral geniculate nucleus. Journal of Neuroscience. 27: 10223-9.
T. Duong and R.D. Freeman (2007). Spatial Frequency Specific Contrast Adaptation Originates in the Primary Visual Cortex. Journal of Neurophysiology. 98: 187-195.
B. Pasley, B.A. Inglis, and R.D. Freeman (2007). Analysis of oxygen metabolism implies a neural origin for the negative BOLD response in human visual cortex. NeuroImage. 36: 269-276.
E. Allen and R.D. Freeman (2006). Dynamic spatial processing originates in early visual pathways. Journal of Neuroscience. 26: 11763-11774.
B. Li, J.K. Thompson, T. Duong, M.R. Peterson, and R.D. Freeman (2006). Origins of Cross-Orientation Suppression in the Visual Cortex. Journal of Neurophysiology. 96: 1755-1764.
Peterson, Li, Freeman. (2006). Direction selectivity of neurons in the striate cortex increases as stimulus contrast is decrease. (Journal of Neurophysiology. 95: 2705-2712.
Thompson, Peterson, Freeman. (2005). Separate spatial scales determine neural activity-dependent changes in tissue oxygen within central visual pathways. Journal of Neuroscience. 25: 9046-9058.
Li, Peterson, Thompson, Duong, and Freeman. (2005). Cross-orientation suppression: monoptic and dichoptic mechanisms are different. Journal of Neurophysiology 94: 1645-1650.
Thompson, J.K., Peterson, M., and Freeman, R.D. (2004). High resolution neurometabolic coupling revealed by focal activation of visual neurons. Nature Neuroscience 7: 919-920.
Peterson, Li, and Freeman. (2004). The Derivation of Direction Selectivity in the Striate Cortex. Journal of Neuroscience 24: 3583-3591.
Menz, Freeman. (2004). Temporal dynamics of binocular disparity processing in the central visual pathway. Journal of Neurophysiology. 91: 1782-1793.
Menz, Freeman. (2004). Functional connectivity of disparity tuned neurons in the visual cortex. Journal of Neurophysiology. 91: 1794-1807.
Freeman. (2004). Binocular interaction in the visual cortex. Chapter for “The Visual Neurosciences”, Chalupa, Werner, ed., M.I.T. Press.
Freeman. (2003). Cortical Columns: A multi-parameter examination. Cerebral Cortex 13: 70-72.
Menz, Freeman. (2003). Stereoscopic Depth Processing in the Visual Cortex: a Coarse-to-Fine Mechanism. Nature Neuroscience. 6:59-65
Thompson, Peterson, Freeman. (2003). Single neuron activity and tissue oxygenation in the cerebral cortex. Science 299: 1070-1072.
Li, Peterson, Freeman. (2003). The Oblique Effect: a neural basis in the visual cortex. Journal of Neurophysiology, 90: 204-217.
Walker, Ohzawa, Freeman. (2002). Disinhibition outside receptive fields in the visual cortex. Journal of Neuroscience. 22: 5659-5668.
Freeman, Ohzawa, Walker. (2001). Beyond the classical receptive field in the visual cortex. Progress in Brain Research. 134: 157-170.
Peterson, Ohzawa, Freeman. (2001). Neural and perceptual adjustments to dim light. Visual Neuroscience. 18: 203-208.
Anzai, Ohzawa, Freeman. (2001). Joint-encoding of motion and depth by visual cortical neurons: Neural basis of the Pulfrich effect. Nature Neuroscience. 4: 513-518.
Walker, Ohzawa, Freeman. (2000). Suppression outside the classical cortical receptive field. Visual Neuroscience. 17: 1-11.
Truchard, Ohzawa, Freeman. (2000). Contrast gain control in the visual cortex: monocular versus binocular mechanisms. Journal of Neuroscience 20: 3017-3032.