Publications

  • Cao, R., Bright, I.M., and Howard, M.W. (2024). Ramping cells in rodent mPFC encode time to past and future events via real Laplace transform. (bioRxiv).
  • Affan, R.O., Bright, I.M., Pemberton, L.N., Cruzado, N.A., Scott, B.B., and Howard, M.W. (2024). Ramping dynamics in the frontal cortex unfold over multiple timescales during motor planning. (bioRxiv).
  • Lohnas, L. J. and Howard, M. W. (submitted). The influence of emotion on temporal context models. (PsyArXiv)
  • Mikkelsen, C., Charczynski, S.J., Warden, M.R., Miller, E.K., and Howard, M.W. (2023). Coding of time with non-linear mixed selectivity in prefrontal cortex ensembles. (bioRxiv) (pdf).
  • Maini, S.S., Mojizuki-Freeman, J., Indi, C.S., Jacques, B., Sederberg, P.B., Howard, M.W., and Tiganj, T. (2023). Representing latent dimensions using compressed number lines. 2023 International Joint Conference on Neural Networks (IJCNN). (pdf) (doi).
  • Howard, M.W., Esfahani, Z.G., Le, B., and Sederberg, P.B. (2023). Foundations of a temporal RL. (pdf) (arXiv)
  • Cao, R.*, Bladon, J.H.*, Charczynski, S.J., Hasselmo, M.E., and Howard, M.W. (2022). Internally generated time in the rodent hippocampus is logarithmically compressed. eLife,11, e75353. (pdf) (bioRxiv) (doi)
  • Bright, I.M., Singh, I., Didomenica, R., Oliva, A., and Howard, M.W. (2022).  The time to initiate retrieval of a memory depends on recency. (pdf) (bioRxiv)
  • Howard, M.W. (In press). Formal models of memory based on temporally-varying representations. In F. G. Ashby, H. Colonius, & E. Dzhafarov (Eds.), The New Handbook of Mathematical Psychology, Volume 3. Cambridge University Press. (pdf) (arXiv)
  • Jacques, B.G, Tiganj, Z., Sarkar, A., Howard, M.W., and Sederberg, P.B. (2022). A deep convolutional neural network that is invariant to time rescaling. Proceedings of the 39th International Conference on Machine Learning, 162, 9729-9738. (arXiv) (pdf) (github)
  • Maini, S.S., Mochizuki-Freeman, J., Indi, C.S., Jacques, B.G., Sederberg, P.B., Howard, M.W., and Tiganj, Z. (2022). Constructing compressed number lines of latent variables using a cognitive model of memory and deep neural networks. NeurIPS MemARI workshop. (pdf) (Video)
  • Tiganj, Z.*, Singh, I.*, Esfahani, Z.G., and Howard, M.W. (2022). Scanning a compressed ordered representation of the future. Journal of Experimental Psychology: General. 151, 3082–3096. (pdf) (bioRxiv) (doi)
  • Liu, Y., Levy, S.J., Mau, W., Geva, N., Rubin, A., Ziv, Y., Hasselmo, M.E., and Howard, M.W. (2022). Consistent population activity on the scale of minutes in the mouse hippocampus. Hippocampus, 32, 359-372. (bioRxiv) (doi)
  • Goh, W.Z., Ursekar, V., and Howard, M.W. (2022). Predicting the future with a scale-invariant temporal memory for the past. Neural Computation, 34, 642-685. (arXiv) (doi)
  • Tiganj, Z., Tang, W., and Howard, M.W. (2021). A computational model for simulating the future using a memory timeline. Proceedings of the Annual Meeting of the Cognitive Science Society, 43, 1173-1179. (pdf)
  • Jacques, B., Tiganj, Z., Howard, M.W., and Sederberg, P.B. (2021). DeepSITH: Efficient learning via decomposition of what and when across time scales. 35th Conference on Neural Information Processing, M. Ranzato, A. Beygelzimer, P.S. Liang, J.W. Vaughan and Y. Dauphin Eds. (pdf) (arXiv) (github)
  • Sheehan, D.J., Charczynski, S., Fordyce, B.A., Hasselmo, M.E., and Howard, M.W. (2021). A compressed representation of spatial distance in the rodent hippocampus. (bioRxiv)
  • Howard, M.W. (In press). Memory for time. Oxford Handbook of Human Memory. (pdf) (PsyArXiv)
  • Sarkar, A., and Howard, M.W. (2021). Scale-dependent relationships in natural language. Computational Brain & Behavior. 4, 164-177. (arXiv) (doi)
  • Howard, M.W. and Hasselmo, M.E. (2020). Cognitive computation using neural representations of time and space in the Laplace domain. (pdf) (arXiv)
  • Cruzado, N.A., Tiganj, Z., Brincat, S.L., Miller, E.K., and Howard, M.W. (2020). Conjunctive representation of what and when in monkey hippocampus and lateral prefrontal cortex during an associative memory task. Hippocampus, 30, 1332-1346. (bioRxiv) (doi)
  • Bright, I.M.*, Meister, M.L.R.*, Cruzado, N.A., Tiganj, Z., Buffalo, E.A.*, and Howard, M.W.* (2020). A temporal record of the past with a spectrum of time constants in the monkey entorhinal cortex. Proceedings of the National Academy of Science, 117, 20274-20283. (bioRxiv) (doi)
  • Liu, Y., and Howard M.W. (2020). Generation of scale-invariant sequential activity in linear recurrent networks. Neural Computation, 32, 1379-1407. (doi) (pdf) (bioRxiv)
  • Babcock, S., Howard, M., and McGuire, J. (2020). Time-conjunctive representations of future events. Memory & Cognition, 48, 672-682. (PsyArXiv) (doi)
  • Bladon, J.H, Sheehan, D.J., De Freitas, C.S., and Howard, M.W. (2019). In a temporally segmented experience hippocampal neurons represent temporally drifting context but not discrete segments. Journal of Neuroscience 39, 6936-6952. (doi) (bioRxiv)
  • Tiganj, Z., Cruzado, N. and Howard, M.W. (2019). Towards a neural-level cognitive architecture: modeling behavior in working memory tasks with neurons. Proceedings of the 41st Annual Meeting of the Cognitive Science Society. (pdf)
  • Toro-Serey, C., Bright, I.M., Wyble, B.P., and Howard, M.W. (2019). Rapid presentation rate negatively impacts the contiguity effect in free recall. Proceedings of the 41st Annual Meeting of the Cognitive Science Society. (pdf) (arXiv)
  • Tiganj, Z., Gershman, S.J., Sederberg, P.B. and Howard, M.W. (2019). Estimating scale-invariant future in continuous time. Neural Computation, 31, 681-709. (arXiv) (pdf) (doi)
  • Palombo, D.J.*, DiLascio, J.M.*, Howard, M.W., and Verfaellie, M. (2019). Medial temporal lobe amnesia is associated with a deficit in recovering temporal context. Journal of Cognitive Neuroscience, 31, 236-248. (doi) (PsyArXiv)
  • Liu, Y., Tiganj, Z., Hasselmo, M.E., and Howard, M.W. (2019). A neural microcircuit model for a scalable scale-invariant representation of time. Hippocampus 29, 260-274. (doi) (bioRxiv)
  • Momennejad, I., and Howard M.W. (2018). Predicting the future with multi-scale successor representations. (bioRxiv)
  • Howard, M.W., Luzardo, A., and Tiganj, Z. (2018). Evidence accumulation in a Laplace domain decision space. Computational Brain & Behavior. 1, 237-251. (doi) (pdf) (arXiv)
  • Singh, I.*, Tiganj, Z.*, and Howard, M.W. (2018). Is working memory stored along a logarithmic timeline? Converging evidence from neuroscience, behavior and models. Neurobiology of Learning and Memory. 153, 104-110. (doi) (pdf)
  • Folkerts, S., Rutishauser, U., and Howard, M.W. (2018). Human episodic memory retrieval is accompanied by a neural contiguity effect. Journal of Neuroscience 38, 4200-4211. (doi) (pdf) (bioRxiv)
  • Tiganj, Z., Cromer, J.A., Roy, J.E., Miller, E.K., and Howard, M.W. (2018). Compressed timeline of recent experience in monkey lPFC. Journal of Cognitive Neuroscience. 30, 935-950. (doi) (bioRxiv)
  • Mau, W., Sullivan, D.W., Kinsky, N.R., Hasselmo, M.E., Howard, M.W., and Eichenbaum, H. (2018). The same hippocampal CA1 population simultaneously codes temporal information over multiple timescales. Current Biology, 18, 1-10. (doi) (commentary) (pdf)
  • Howard, M.W. (2018). Memory as perception of the past: Compressed time in mind and brain. Trends in Cognitive Sciences. 22, 124-126. (doi)
  • Howard, M. W. and Shankar, K. H. (2018). Neural scaling laws for an uncertain world. Psychological Review. 125, 47-58. (doi) (pdf) (arXiv)
  • Howard, M. W. (2017). Temporal and spatial context in the mind and brain. Current Opinion in Behavioral Sciences, 17, 14-19. (pdf) (doi)
  • Spears, T.A., Jacques, B.G., Howard, M.W., and Sederberg, P.B. (2017). Scale-invariant temporal history (SITH): optimal slicing of the past in an uncertain world. (arXiv)
  • Singh, I., Oliva, A., and Howard, M.W. (2017). Visual memories are stored along a compressed timeline. (pdf) (bioRxiv)
  • Tiganj, Z., Shankar, K. H., and Howard M. W. (2017). Scale invariant value computation for reinforcement learning in continuous time. AAAI Spring Symposium Series – Science of Intelligence: Computational Principles of Natural and Artificial Intelligence. (pdf)
  • Tiganj, Z., Kim, J., Jung, M. W., and Howard M. W. (2016). Sequential firing codes for time in rodent mPFC. Cerebral Cortex., 27, 5663-5671. (pdf)
  • Shankar, K. H., Singh, I., and Howard M. W. (2016). Neural mechanism to simulate a scale-invariant future. Neural Computation, 28, 2594–2627. (pdf) (doi)
  • Salz, D. M., Tiganj, Z., Khasnabish, S., Kohley, A., Sheehan, D., Howard,  M. W., and Eichenbaum, H. (2016). Time cells in hippocampal area CA3.  Journal of Neuroscience36, 7476-7484. (pdf)
  • Howard, M. W., Shankar, K. H., and Tiganj, Z. (2015). 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. (pdf)
  • Howard, M.W. and Eichenbaum, H. (2015). Time and space in the hippocampus. Brain Research. 1621, 345-354. (pdf) (doi)
  • Criss, A.H. and Howard, M.W. (2015). Episodic memory. In Oxford Handbook of Computational and Mathematical Psychology J.R. Busemeyer, J.T. Townsend, Z.J. Wang, and A. Eidels (Eds.). Oxford University Press.
  • Howard, M.W., Shankar, K.H., Aue, W.R., and Criss, A.H. (2015). A distributed representation of internal time, Psychological Review, 122, 24-53. (pdf) (doi)
  • Shankar, K.H. (2015). Generic construction of scale-invariantly coarse grained memory. Australasian Conference on Artificial Life and Computational Intelligence 2015, S.K. Chalup et al. (Eds.), 8955, 175-184. (pdf)
  • Tiganj, Z., Hasselmo, M.E., and Howard, M.W. (2015). A simple biophysically plausible model for long time constants in single neurons, Hippocampus, 25, 27-37. (pdf(doi)
  • Howard, M.W., MacDonald, C.J., Tiganj, Z., Shankar, K.H., Du, Q., Hasselmo, M.E., and Eichenbaum, H. (2014). A unified mathematical framework for coding time, space, and sequences in the hippocampal region. Journal of Neuroscience, 34, 4692-4707. (pdf)
  • Howard, M.W. (2014). Mathematical learning theory through time. Journal of Mathematical Psychology, 59, 18-29. (pdf(doi)
  • Shankar, K.H. and Howard, M.W. (2013). Optimally fuzzy scale-free memory, Journal of Machine Learning Research, 14, 3753-3780. (pdf)
  • Howard, M.W. and Eichenbaum, H. (2013). The hippocampus, time, and memory across scales. Journal of Experimental Psychology: General, 142, 1211-1230. (pdf(doi)
  • Shankar, K.H. (2013). Quantum random walks and decision making. Topics in Cognitive Science, 6, 108-113. (pdf)
  • Komorowski, R.W., Garcia, C.G., Wilson, A., Hattori, S., Howard, M.W., and Eichenbaum, H. (2013). Ventral hippocampal neurons are shaped by experience to represent behaviorally relevant contexts. Journal of Neuroscience, 33, 8079-8087. (pdf)
  • Kilic, A., Hoyer, W.J., and Howard, M.W. (2013). Effects of Spacing of Item Repetitions in Continuous Recognition Memory: Does Item Retrieval Difficulty Promote Item Retention in Older Adults? Experimental Aging Research, 39, 322-341.
  • Kilic, A., Criss, A.H., and Howard, M.W. (2013). A causal contiguity effect that persists across time scales. Journal of Experimental Psychology: Learning, Memory and Cognition, 39, 297-303. (pdf)
  • Howard, M.W., Viskontas, I.V., Shankar, K.H., and Fried, I. (2012). Ensembles of human MTL neurons “jump back in time” in response to a repeated stimulus. Hippocampus, 22, 1833-1847. (pdf)
  • Shankar, K.H., and Howard, M.W. (2012). A scale-invariant internal representation of time. Neural Computation, 24, 134-193. (pdf)
  • Howard, M.W., Shankar, K.H., and Jagadisan, U.K.K. (2011). Constructing semantic representations from a gradually-changing representation of temporal context. Topics in Cognitive Science, 3, 48-73. (pdf(doi)
  • Shankar, K.H., and Howard, M.W. (2010). Timing using temporal context. Brain Research, 1365, 3-17. (doi)
  • Sederberg, P.B., Miller, J.F., Howard, M.W., and Kahana, M.J. (2010). The temporal contiguity effect predicts episodic memory performance. Memory & Cognition, 38, 689-699.(doi)
  • Onyper, S.V., Zhang, Y., and Howard, M.W. (2010). Some-or-none recollection: Evidence from item and source memory. Journal of Experimental Psychology: General, 139, 341-364. (pdf(PMC)
  • Shankar, K.H., Jagadisan, U.K.K., and Howard, M.W. (2009). Sequential learning using temporal context. Journal of Mathematical Psychology, 53, 474-485. (pdf)
  • Howard, M.W., Sederberg, P.B., and Kahana, M. J.(2009). Reply to Farrell & Lewandowsky: Recency-contiguity interactions predicted by the temporal context model. Psychonomic Bulletin & Review, 16, 973-984. (doi)
  • Howard, M.W., Jing, B., Rao, V.A., Provyn, J.P., & Datey, A.V. (2009). Bridging the gap: Transitive associations between items presented in similar temporal contexts. Journal of Experimental Psychology: Learning, Memory & Cognition, 35, 391-407. (pdf)
  • Howard, M.W. (2009). Memory: Computational models. in L. R. Squire (Ed), New Encyclopedia of Neuroscience, volume 5, pp. 771-777. Oxford: Academic Press.
  • Howard, M.W., Kahana, M.J., and Sederberg, P.B., (2008). Postscript: Distinguishing between temporal context and short-term store. Psychological Review, 115, 1125-6.
  • Kahana, M.J., Sederberg, P.B., and Howard, M.W. (2008). Putting short-term memory into context: Reply to Usher, Davelaar, Haarman and Goshen-Gottstein (2008). Psychological Review, 115, 1119-1126.
  • Sederberg, P.B., Howard, M.W., and Kahana, M.J. (2008). A context-based theory of recency and contiguity in free recall. Psychological Review, 115, 893-912. (pdf)
  • Rao, V. A. and Howard, M. W. (2008). Retrieved context and the discovery of semantic structure. Advances in Neural Information Processing Systems 20, J.C. Platt, D. Koller, Y. Singer and S. Roweis, Eds. MIT Press: Cambridge, MA. (pdf)
  • Kahana, M.J., Howard, M.W., & Polyn, S.M. (2008). Associative retrieval processes in episodic memory. In, H. L. Roediger, (Ed), Learning and Memory-A Comprehensive Reference, Academic Press, Oxford, pp. 467-490. (pdf)
  • Howard, M.W., Youker, T.E., and Venkatadass, V. (2008). The persistence of memory: Contiguity effects across several hundred seconds. Psychonomic Bulletin & Review, 15, 58-63.(pdf)
  • Provyn, J.P., Sliwinski, M.J. & Howard, M.W. (2007). Effects of age on contextually mediated associations in paired associate learning. Psychology and Aging, 22, 846-857.
  • Manns, J.R., Howard, M.W., & Eichenbaum, H.B. (2007). Gradual changes in hippocampal activity support remembering the order of events, Neuron, 56, 530-540. (doi)
  • Howard, M.W., Venkatadass, V., Norman, K.A., and Kahana, M.J. (2007). Associative processes in immediate recency. Memory & Cognition, 35, 1700-1711. (pdf)
  • Howard, M.W., Addis, K.A., Jing, B., and Kahana, M.J. (2007), Semantic structure and episodic recall, in Landauer, McNamara, Dennis, & Kintsch (Eds) Handbook of Latent Semantic Analysis, Laurence Erlbaum Associates: Mahwah, NJ, pp. 121-141.
  • Siekmeier, P.J., Hasselmo, M.E., Howard, M.W., and Coyle, J.T. (2007). Modeling of context dependent retrieval in hippocampal region CA1: Implications for cognitive function in schizophrenia. Schizophrenia Research, 89, 177-190. (pdf)
  • Zaromb, F.M., Howard, M.W., Dolan, E.D., Sirotin, Y.B., Tully, M., Wingfield, A.and Kahana, M.J. (2006). Temporally-based false memories in free recall. Journal of Experimental Psychology: Learning, Memory and Cognition, 32, 792-804.
  • Howard, M.W., Wingfield, A.and Kahana, M.J. (2006). Aging and contextual binding: Modeling recency and lag-recency effects with the temporal context model, Psychonomic Bulletin & Review, 13, 439-445.
  • Howard, M.W., Bessette-Symons, B.A., Zhang, Y., and Hoyer, W.J. (2006). Aging selectively impairs recollection in recognition memory for pictures: Evidence from modeling and ROC curves, Psychology and Aging, 21, 96-106. (pdf)
  • Howard, M.W.,  and Natu, V.S. (2005). Position from time: Spatial precision in the temporal context model, Neural Networks, 18, 1150-1162. (pdf)
  • Schwartz, G., Howard, M.W., Jing, B., and Kahana, M.J. (2005). Shadows of the past: Temporal retrieval effects in recognition memory, Psychological Science, 16, 898-904. (pdf)
  • Kahana, M.J. and Howard, M.W. (2005). The spacing and lag effect in free recall, Psychonomic Bulletin & Review, 12, 159-164.
  • Howard, M.W., Fotedar, M.S., Datey, A.V. and Hasselmo, M.E. (2005). The temporal context model in spatial navigation and relational learning: Toward a common explanation of medial temporal lobe function across domains, Psychological Review, 112, 75-116. (pdf)
  • Howard, M.W. (2004). Scaling behavior in the temporal context model, Journal of Mathematical Psychology, 48, 230-238. (pdf)
  • Sederberg, P.B., Kahana, M.J., Howard, M.W., Donner, E., and Madsen, J.R. (2003). Theta and gamma oscillations during encoding predict subsequent recall, Journal of Neuroscience, 23, 10809-14. (pdf)
  • Howard, M.W., Rizzuto, D.S., Madsen, J.R., Lisman, J.E., Aschenbrenner-Scheibe, R., Schulze-Bonhage, A., and Kahana, M.J. (2003). Gamma oscillations correlate with working memory load in humans, Cerebral Cortex, 13, 1369-1374. (pdf)
  • Sherman, S.J., Atri, A., Hasselmo, M.E., Stern, C.E., and Howard, M.W. (2003). Scopolamine impairs human recognition memory: Data and modeling. Behavioral Neuroscience, 117, 526-539. (pdf)
  • Kahana, M.J., Howard, M.W., Zaromb, F.M., and Wingfield, A. (2002). Age dissociates recency and lag-recency effects in free recall. Journal of Experimental Psychology: Learning, Memory and Cognition, 28, 530-540.
  • Howard, M.W. and Kahana, M.J. (2002). A distributed representation of temporal context. Journal of Mathematical Psychology, 46, 269-299. (pdf(doi)
  • Howard, M.W.  and Kahana, M.J. (2002). When does semantic similarity help episodic retrieval? Journal of Memory and Language, 46, 85-98.
  • Howard, M.W. and Kahana, M.J. (1999). Contextual variability and serial position effects in free recall. Journal of Experimental Psychology: Learning, Memory and Cognition, 25, 923-941.