David Freedman

Professor

Department of Neurobiology

The University of Chicago
947 E. 58th St., MC0928
Chicago, IL 60637

Email: dfreedman@uchicago.edu
Phone: (773) 834-5186/(773) 834-5186
Fax: (773) 702-3774

Freedman Lab website

 

Research Summary

Neurophysiology of Visual Learning, Memory and Recognition.

 

Research Statement

We have a remarkable ability to learn from our experiences. Through experience, we learn to interpret the meaning of the sights and sounds around us and to behave in ways that move us closer to achieving our goals. This capacity to learn from and adapt to our ever changing environment is a foundation of complex behavior, as it allows us to make sense of incoming sensory stimuli and to plan successful behavioral responses. While decades of research have revealed a great deal about the neural processing of simple visual features such as color, orientation and direction of motion, much less is known about how the brain learns, stores, recognizes and recalls the behavioral significance, or meaning, of our sensory experiences.

The central goal of the Freedman laboratory is to understand how the brain transforms visual feature encoding in sensory brain areas into more abstract and experience-dependent representations that reflect the behavioral significance of visual stimuli. To study this process, we use advanced multielectrode neurophysiological techniques to record the activity of groups of cortical neurons from multiple brain areas during performance of behavioral tasks that require visual learning, memory and recognition. Visual categorization tasks have proven to be an excellent tool for investigating how visual representations are transformed through experience. In previous work, we compared the roles of neurons in the frontal, temporal and parietal lobes during visual categorization, and found that the activity of neurons in the parietal and frontal lobes reflects the learned significance, or category membership, of visual stimuli as a result of experience. This contrasted sharply with the response patterns in brain areas considered to be more involved in sensory processing (such as the middle temporal and inferior temporal cortices) which seemed more involved in visual feature encoding and did not reflect more abstract, or meaningful, information about stimuli. Understanding how feature-based sensory encoding in visual cortex is transformed into more abstract and meaningful representations in subsequent neuronal processing stages is the central goal of our research.

Our hope is that a greater understanding of the brain mechanisms of visual learning, memory and recognition in healthy subjects will provide a step toward addressing a number of neurological diseases and conditions (such as Alzheimer’s disease, schizophrenia, stroke, and attention deficit disorder) that can leave patients impaired in tasks that require visual learning, recognition and/or evaluating and responding appropriately to sensory information.

 

Select Publications

Sarma A., Masse N.Y., Wang X.J., and Freedman D.J. Task Specific versus Generalized Mnemonic Representations in Parietal and Prefrontal Cortices. Nature Neuroscience, 19: 143-149, 2016.

Ibos G. and Freedman D.J. Dynamic integration of task-relevant visual features in posterior parietal cortex. Neuron, 83: 1-13, 2014.

Swaminathan S.K.*, Masse N.Y.*, and Freedman D.J. A comparison of lateral and medial intraparietal areas during a visual categorization task. Journal of Neuroscience, 33: 13157-13170, 2013.

Rishel C.A., Huang G., and Freedman D.J. Independent category and spatial encoding in parietal cortex. Neuron, 77: 969-979, 2013.

Fitzgerald J.K., Freedman D.J., Fanini A., Bennur S., Gold J.I., and Assad J.A. Biased associative representations in parietal cortex. Neuron, 77: 180-191, 2013.

Swaminathan S.K. and Freedman D.J. Preferential encoding of visual categories in parietal cortex compared to prefrontal cortex. Nature Neuroscience, 15: 315-320, 2012.

Fitzgerald J.K, Freedman D.J., and Assad J.A. Generalized Associative Representations in Parietal Cortex. Nature Neuroscience,14: 1075-1079, 2011.

Freedman D.J. and Assad J.A. Distinct Encoding of Spatial and Non-Spatial Factors in Parietal Cortex. Journal of Neuroscience, 29: 5671-5680, 2009.

Meyers E.M., Freedman D.J., Krieman G., Poggio T., and Miller E.K. Using Neuron Population Readout to Decode the Temporal Dynamics of Category Information. Journal of Neurophysiology 100: 1407-1419, 2008.

Freedman D.J. and Assad J.A. Experience-Dependent Representation of Visual Categories in Parietal Cortex. Nature 443: 85-88, 2006.

Freedman D.J., Riesenhuber M., Poggio T., and Miller E.K. A Comparison of Primate Prefrontal and Inferior Temporal Cortices During Visual Categorization. Journal of Neuroscience 23: 5235-5246, 2003.

Nieder A., Freedman D.J., and Miller E.K. Representation of the Quantity of Visual Items in the Primate Prefrontal Cortex. Science 297: 1708-1711, 2002.

Freedman D.J., Riesenhuber M., Poggio T., Miller E.K. Categorical Representation of Visual Stimuli in the Primate Prefronal Cortex. Science 291: 312-316, 2001.

Assad J.A. and Freedman D.J. Neuronal Mechanisms of Visual Categorization: An Abstract View on Decision Making. Annual Review of Neuroscience, 39:129-147, 2016.

 

Recent Reviews

Fitzgerald J.K, Swaminathan S.K., and Freedman D.J. Visual categorization and the Parietal Cortex. Frontiers in Integrative Neuroscience, 6: 18, 2012.

Freedman D.J.and Assad J.A. A Proposed Common Neural Mechanisms for Categorization and Perceptual Decisions. Nature Neuroscience, 14:143-146, 2011.

Freedman D.J. Neuronal Mechanisms of Visual Categorization and Category Learning. In: The Neuroscience of Rule-Guided Behavior. Wallis J.D. and Bunge S. (eds.). Oxford University Press, pp 391-418, 2007.