Marc Howard, PhD
Boston University College of Arts and Sciences
Dept of Psychological and Brain Sciences

PhD, Brandeis University

Marc Howard, PhD, is a Professor in the Department of Psychological and Brain Sciences and member of the Center for Memory and Brain. He received his PhD from Brandeis University in Neuroscience. His research interests include: cognitive and neural representation of time and space; mathematical psychology; computational neuroscience; episodic and semantic memory; and reward learning and prediction.

About the Theoretical Cognitive Neuroscience Lab:
We develop mathematical models of cognition and evaluate them against both behavioral and neurophysiological data, providing a bridge between cognition and systems-level neuroscience. We use a combination of mathematical, computational and behavioral tools to evaluate our hypotheses. The topics we investigate are centered on episodic memory, the ability we have to remember specific events situated in a particular spatiotemporal context. At present, our efforts are focused on developing and evaluating a unified mathematical framework to describe how the brain constructs the spatial and temporal context believed to underlie episodic memory. This model appears to have far-ranging implications, leading to research interests in statistical learning, semantic memory, time perception, and reward systems.

2004 Society for Mathematical Psychology: New Investigator Award

Temporal Organization of Memory in the Hippocampus
07/19/2016 - 04/30/2021 (PI)
NIH/National Institute of Mental Health

NCS-FO: Learning Efficient Visual Representations From Realistic Environments Across Time Scales
09/01/2016 - 08/31/2020 (PI)
National Science Foundation

Toward a Theory for Macroscopic Neural Computation Based on Laplace Transform
09/27/2016 - 08/31/2019 (PI)
NIH/National Institute of Biomedical Imaging & Bioengineering

Navigation Through a Memory Space in the Rodent Hippocampus
07/15/2016 - 04/30/2019 (PI)
NIH/National Institute of Mental Health

Memory Enhancement with Modeling, Electrophysiology, and Stimulation (MEMES)
07/16/2014 - 06/03/2016 (PI)
Trustees of the University of Pennsylvania DOD DARPA

Sequential Learning From a Scale-Invariant Representation of Remembered Time
01/15/2012 - 12/31/2015 (PI)
National Science Foundation

A Distributed Representation of Remembered Time
07/01/2012 - 06/30/2015 (PI)
Department of Defense/AFOSR

A Distributed Representation of Remembered Time
09/01/2011 - 04/30/2012 (PI)
Syracuse University DOD AFOSR

Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.

  1. Folkerts S, Rutishauser U, Howard MW. Human episodic memory retrieval is accompanied by a neural contiguity effect. J Neurosci. 2018 Apr 03. PMID: 29615486.
  2. Redish AD, Howard MW. The legacy of Adam Johnson. Hippocampus. 2018 Mar 30. PMID: 29601117.
  3. Howard MW. Memory as Perception of the Past: Compressed Time inMind and Brain. Trends Cogn Sci. 2018 Feb; 22(2):124-136. PMID: 29389352.
  4. Tiganj Z, Jung MW, Kim J, Howard MW. Sequential Firing Codes for Time in Rodent Medial Prefrontal Cortex. Cereb Cortex. 2017 Dec 01; 27(12):5663-5671. PMID: 29145670.
  5. Howard MW, Shankar KH. Neural scaling laws for an uncertain world. Psychol Rev. 2018 Jan; 125(1):47-58. PMID: 29035080.
  6. Howard MW. Temporal and spatial context in the mind and brain. Curr Opin Behav Sci. 2017 Oct; 17:14-19. PMID: 28845441.
  7. Shankar KH, Singh I, Howard MW. Neural Mechanism to Simulate a Scale-Invariant Future. Neural Comput. 2016 Dec; 28(12):2594-2627. PMID: 27626961.
  8. Salz DM, Tiganj Z, Khasnabish S, Kohley A, Sheehan D, Howard MW, Eichenbaum H. Time Cells in Hippocampal Area CA3. J Neurosci. 2016 Jul 13; 36(28):7476-84. PMID: 27413157; PMCID: PMC4945667; DOI: 10.1523/JNEUROSCI.0087-16.2016;.
  9. Criss AH, Howard MW. Episodic memory. In Oxford Handbook of Computational and Mathematical Psychology, J. R. Busemeyer, J. T. Townsend, Z. J. Wang, and A. Eidels (Eds.). University Press. Oxford. 2015.
  10. Howard MW, Shankar KH, Tiganj Z. Efficient neural computation in the Laplace domain. In Tarek R. Besold, Artur d’Avila Garcez, Gary F. Marcus, Risto Miikulainen (eds.): Proceedings of the NIPS 2015 workshop on Cognitive Computation: Integrating Neural and Symbolic Approaches. Montreal, Canada. 2015.
Showing 10 of 56 results. Show More

This graph shows the total number of publications by year, by first, middle/unknown, or last author.

Bar chart showing 56 publications over 18 distinct years, with a maximum of 6 publications in 2008

Contact for Mentoring:

2 Cummington St
Boston MA 02215
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