Preston, Alison

Alison R Preston

Associate Professor, Associate Professor of Psychiatry
Department of Psychology, Department of Neuroscience



apreston@utexas.edu

Phone: 512-475-7255

Office Location
NHB 3.352

Postal Address
The University of Texas at Austin
Department of Psychology, College of Liberal Arts
1 University Station A8000
Austin, TX 78712

Our memories are the essence of who we are. The skills we have acquired, the knowledge we have amassed, and the personal experiences we have had define us as individuals.  The overarching goal of work in the Preston Lab is to understand and manipulate the neural mechanisms that support learning and memory in the human brain. Our research focuses primarily on how interactions between the hippocampus and prefrontal cortex promote formation of new knowledge. In addition to exploring how hippocampal—prefrontal networks function in adulthood, we are interested in how development of these structures through childhood and adolescence supports not only gains in memory, but also underlies improvements in problem solving, creativity, reasoning, and planning abilities during development. To address the core questions of our research program, the lab employs a number of techniques on the leading edge of human neuroscience, including high-resolution functional magnetic resonance imaging (fMRI), neurostimulation, intracranial recordings in human patients, and computational modeling. These techniques provide unprecedented leverage to determine not only where particular cognitive processes are instantiated in the brain, but also the precise nature of the representations and computations that give rise to them.

Representative publications

Morton, N.W., Sherrill, K.R., & Preston, A.R. (2017). Memory integration constructs maps of space, time, and concepts. Current Opinion in Behavioral Sciences, 17, 161-168.

Schlichting, M.L., Guarino, K.F., Schapiro, A.C., Turk-Browne, N.B., & Preston, A.R.(2017). Hippocampal structure predicts statistical learning and associative inference abilities during development. Journal of Cognitive Neuroscience, 29(1): 37-51.

Mack, M.L., Love, B.C., & Preston, A.R. (2016). Dynamic updating of hippocampal conceptual representations through interactions with prefrontal cortex. Proceedings of the National Academy of Sciences USA113(46), 13203-13208.

Mack, M.L., & Preston, A.R. (2016). Decisions about the past are guided by reinstatement of specific memories in the hippocampus and perirhinal cortex. Neuroimage, 127, 144-157.

Schlichting, M.L., & Preston, A.R. (2016). Hippocampal-medial prefrontal circuit supports memory updating during learning and post-encoding rest. Neurobiology of Learning and Memory, 134, 91-106.

Schlichting, M.L., Mumford, J.A., & Preston, A.R. (2015). Learning-related representational changes reveal dissociable integration and separation signatures in hippocampus and prefrontal cortex. Nature Communications6, 8151.

Schlichting, M.L., & Preston, A.R. (2015). Memory integration: Neural mechanisms and implications for behavior. Current Opinion in Behavioral Sciences, 1, 1-8.

Schlichting, M.L., & Preston, A.R. (2014). Memory reactivation during rest supports upcoming learning of related content. Proceedings of the National Academy of Sciences USA, 111(44), 15845-50.

Mack, M.L., Preston, A.R., & Love, B.C. (2013). Decoding the brain’s algorithm for categorization from its neural implementation. Current Biology23(20), 2023-7.

Preston, A.R., & Eichenbaum, H. (2013). Interplay of the hippocampus and prefrontal cortex in memory. Current Biology, 23(17), R764-R773.

Liang, J.C., Wagner, A.D., & Preston, A.R. (2013). Content representation in the human medial temporal lobe. Cerebral Cortex23(1), 80-96.

Wolosin, S.M., Zeithamova, D., & Preston, A.R. (2012). Reward modulation of hippocampal subfield activation during successful associative encoding and retrieval. Journal of Cognitive Neuroscience, 24(7), 1532-47.

Zeithamova, D., Dominick, A.L., & Preston, A.R. (2012). Hippocampal and ventral medial prefrontal activation during retrieval-mediated learning supports novel inference. Neuron, 75(1), 168-179.