Computational Cognitive Neuroscience
Research Interests
How do we navigate familiar cities to reach goals? How do we remember the events of our lives? Why are these abilities impaired in memory-related disorders such as Alzheimer’s disease? Can we improve these cognitive processes by further understanding how they work in healthy younger and older adults?
We are a team of computational cognitive neuroscientists that are fascinated by studying the ways in which we learn and remember information about the world around us. Specifically, we are interested in environmental cognition, with an emphasis on studying navigation and spatial memory for large-scale environments such as cities. In addition to studying spatial cognition, we are interested in studying how we remember the events of our lives (i.e., episodic memory). Decades of research have revealed that spatial context (i.e., the location in which an event takes place) exerts a fundamental influence on our ability to form and retrieve episodic memories; therefore, we are also interested in understanding the connection between spatial cognition and episodic memory. Finally, we are also interested, more generally, in how people perceive, remember, and think about the environment (e.g., with respect to issues surrounding the environment, such as climate change).
We study spatial cognition and episodic memory by having participants engage in highly immersive experiences, such as virtual reality and real-world tasks, because these methods better approximate our everyday experiences. We aim to find converging evidence across a variety of approaches, including behavior, EEG, and fMRI. We also leverage computational techniques (e.g., machine learning, multivariate analysis, modeling) to analyze the human brain and behavior.
Team
Principal Investigator
Derek J. Huffman (Assistant Professor of Psychology)
Honors Thesis Students
Ainsley Bonin ’24 (major: Computational Psychology)
Research Assistants
Chandrachud Gowda ’25 (major: Computer Science)
Paisley Annes ’26 (major: Computational Psychology)
Olivia Doherty ’26 (major: Computational Psychology)
Maddie Gibbs ’27 (major: Psychology: Neuroscience)
Linh Dang ’27 (major: Computational Psychology)
Lab Alumni
Ainsley Bonin ’24 (major: Computational Psychology, with honors)
Ainsley is now pursuing her Ph.D. in psychology (cognitive neuroscience) at Penn!
Lola Villafranco ’26 (major: Biology: Neuroscience)
Shuran Yang ’23 (majors: Psychology, with honors; Biology: Neuroscience)
Shuran completed her Master’s of Education at Harvard and is now working at Colby at an Instructional Technologist!
Sinan Yumurtaci ’23 (majors: Computer Science, Economics)
Hannah Guan ’24 (majors: Psychology, Computer Science)
Katia Koelliker ’22 (collaboration with Professor Glenn; major: Psychology: Neuroscience)
Lior Colina ’22 (major: Psychology: Neuroscience)
Lior is currently completing his Doctor of Dental Surgery degree at University of Southern California!
Sophia Merriweather ’23 (major: Psychology: Neuroscience)
Ruby Nunez ’24 (majors: Computer Science, Psychology: Neuroscience)
Chioma Ezuma-Ngwu ’22 (major: Computational Psychology)
Publications
* Denotes co-first author; + Denotes Colby College student collaborator
Huffman, DJ and +Guan, R (in press). Computational models suggest that human memory judgments exhibit interference due to the use of overlapping representations. Psychological Review.
Huffman, DJ (2024). An in-depth exploration of the interplay between fMRI methods and theory in cognitive neuroscience. Journal of Undergraduate Neuroscience Education.
*Rollins, L, *Huffman, DJ, Walters, LA, and Bennett, K (2023). Prolonged development of forced-choice recognition when targets are paired with non-corresponding lures. Journal of Experimental Child Psychology, 236:105742.
Crivelli-Decker, J, Clarke, A, Park, SA, Huffman, DJ, Boorman, E, and Ranganath, C (2023). Goal-oriented representations in the human hippocampus during planning and navigation. Nature Communications, 14:2496.
Starrett, MJ, Huffman, DJ, and Ekstrom, AD (2023). Combining egoformative and alloformative cues in a novel tabletop navigation task. Psychological Research, 87:1644-1664.
Huffman, DJ and Ekstrom, AD (2021). An important step toward understanding the role of body-based cues on human spatial memory for large-scale environments. Journal of Cognitive Neuroscience, 33(2):167-179.
Starrett, MJ, McAvan, AS, Huffman, DJ, Stokes, JD, Kyle, CT, Smuda, DN, Kolarik, BS, Laczko, J, and Ekstrom, AD (2021). Landmarks: A solution for spatial navigation and memory experiments in virtual reality. Behavior Research Methods, 53:1046-1059.
Ekstrom, AD, Harootonian, S, and Huffman, DJ (2020). Grid coding, spatial representation, and behavior: Should we assume an isomorphism? Hippocampus, 30(4):422-432.
Huffman, DJ and Ekstrom, AD (2019). A modality-independent network underlies the retrieval of large-scale spatial environments in the human brain. Neuron, 104(3):611-622.e7.
Huffman, DJ and Ekstrom, AD (2019). Which way is the bookstore? A closer look at the judgments of relative directions task. Spatial Cognition and Computation, 19(2):93-129.
Starrett, MJ, Stokes, JD, Huffman, DJ, Ferrer, E, and Ekstrom, AD (2019). Learning-dependent evolution of spatial representations for large-scale virtual environments. Journal of Experimental Psychology: Learning, Memory, and Cognition, 45(3):497-514.
White, AO, Javier, LK, Goldberg, NR, Boucquey, V, Overman, J, Ochaba, J, Marsh, S, Huffman, D, and Nicholas, A (2017). Front and back flipping for neurobiology! Developing a hybrid upper-division lab course. Journal of Undergraduate Neuroscience Education, 16(1):A95-A101.
Ekstrom, A, Huffman, DJ, and Starrett, M (2017). Interacting networks of brain regions underlie human spatial navigation: A review and novel synthesis of the literature. Journal of Neurophysiology, 118(6):3328-3344.
Huffman, DJ and Stark, CEL (2017). The influence of low-level stimulus features on the representation of contexts, items, and their mnemonic associations. NeuroImage, 155:513-529.
Huffman, DJ and Stark, CEL (2017). Age-related impairment on a forced-choice version of the Mnemonic Similarity Task. Behavioral Neuroscience, 131(1):55-67.
Bennett, IJ, Huffman, DJ, and Stark, CEL (2015). Limbic tract integrity contributes to pattern separation performance across the lifespan. Cerebral Cortex, 25(9):2988-2999.
Huffman, DJ and Stark, CEL (2014). Multivariate pattern analysis of the human medial temporal lobe revealed representationally categorical cortex and representationally agnostic hippocampus. Hippocampus, 24(11):1394-1403.
Nashiro, K, Sakaki, M, Huffman, D, and Mather, M (2013). Both younger and older adults have diffculty updating emotional memories. The Journal of Gerontology, Series B: Psychological Sciences and Social Sciences, 68(2):224-227.