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.

Recent publications

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. Experience-Dependent Sharpening of Visual Shape Selectivity in Inferior Temporal Cortex. Cerebral Cortex, 16: 1631-1644, 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., and Miller E.K. Visual Categorization and the Primate Prefrontal Cortex: Neurophysiology and Behavior. Journal of Neurophysiology 88: 914-928, 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.

Recent reviews

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.

Miller E.K., Nieder A., Freedman D.J., and Wallis J.D. Neural Correlates of Categories and Concepts. Current Opinion in Neurobiology, 13:2:198-203, 2003.

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