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Michael E. Hasselmo
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2020 – today
- 2024
- [j41]Vittorio Giammarino
, Matthew F. Dunne, Kylie N. Moore, Michael E. Hasselmo, Chantal E. Stern, Ioannis Ch. Paschalidis:
Combining imitation and deep reinforcement learning to human-level performance on a virtual foraging task. Adapt. Behav. 32(3): 251-263 (2024) - [c11]G. William Chapman, Andrew S. Alexander, Frances S. Chance, Michael E. Hasselmo:
Self-Supervised Mapping and Localization by Predictive Learning. ICONS 2024: 193-200 - [i3]Quan Do, Thomas M. Morin, Chantal E. Stern, Michael E. Hasselmo:
A Feature-based Generalizable Prediction Model for Both Perceptual and Abstract Reasoning. CoRR abs/2403.05641 (2024) - 2023
- [j40]Mahir Patel
Animal Pose Tracking: 3D Multimodal Dataset and Token-based Pose Optimization. Int. J. Comput. Vis. 131(2): 514-530 (2023) - [i2]Mahir Patel, Lucas C. Carstensen, Yiwen Gu, Michael E. Hasselmo, Margrit Betke:
BU-CVKit: Extendable Computer Vision Framework for Species Independent Tracking and Analysis. CoRR abs/2306.04736 (2023) - 2022
- [i1]Vittorio Giammarino, Matthew F. Dunne, Kylie N. Moore, Michael E. Hasselmo, Chantal E. Stern, Ioannis Ch. Paschalidis:
Learning from humans: combining imitation and deep reinforcement learning to accomplish human-level performance on a virtual foraging task. CoRR abs/2203.06250 (2022) - 2020
- [j39]Stephen Hausler, Zetao Chen, Michael E. Hasselmo, Michael Milford
Bio-inspired multi-scale fusion. Biol. Cybern. 114(2): 209-229 (2020) - [j38]Yue Liu, Scott L. Brincat, Earl K. Miller, Michael E. Hasselmo:
A Geometric Characterization of Population Coding in the Prefrontal Cortex and Hippocampus during a Paired-Associate Learning Task. J. Cogn. Neurosci. 32(8): 1455-1465 (2020)
2010 – 2019
- 2019
- [j37]Holger Dannenberg, Andrew S. Alexander, Jennifer C. Robinson, Michael E. Hasselmo:
The Role of Hierarchical Dynamical Functions in Coding for Episodic Memory and Cognition. J. Cogn. Neurosci. 31(9): 1271-1289 (2019) - [c10]Henghui Zhu, Ioannis Ch. Paschalidis, Michael E. Hasselmo:
A Hebbian learning algorithm for training a neural circuit to perform context-dependent associations of stimuli. ACC 2019: 848-853 - 2018
- [j36]Henghui Zhu, Ioannis Ch. Paschalidis
Neural circuits for learning context-dependent associations of stimuli. Neural Networks 107: 48-60 (2018) - [j35]Jason S. Sherfey
Flexible resonance in prefrontal networks with strong feedback inhibition. PLoS Comput. Biol. 14(8) (2018) - 2017
- [c9]Henghui Zhu, Ioannis Ch. Paschalidis, Michael E. Hasselmo:
Feature extraction in Q-learning using neural networks. CDC 2017: 3330-3335 - 2015
- [j34]Katherine R. Sherrill
Functional connections between optic flow areas and navigationally responsive brain regions during goal-directed navigation. NeuroImage 118: 386-396 (2015) - [j33]Zetao Chen
Bio-inspired homogeneous multi-scale place recognition. Neural Networks 72: 48-61 (2015) - [j32]Florian Raudies, Michael E. Hasselmo
Differences in Visual-Spatial Input May Underlie Different Compression Properties of Firing Fields for Grid Cell Modules in Medial Entorhinal Cortex. PLoS Comput. Biol. 11(11) (2015) - 2014
- [j31]Michael E. Hasselmo
Theta rhythm and the encoding and retrieval of space and time. NeuroImage 85: 656-666 (2014) - [c8]Zetao Chen, Adam Jacobson
Multi-scale bio-inspired place recognition. ICRA 2014: 1895-1901 - 2013
- [j30]Jan R. Engelbrecht, Kristen Loncich, Renato Mirollo, Michael E. Hasselmo
Rhythm-induced spike-timing patterns characterized by 1D firing maps. J. Comput. Neurosci. 34(1): 59-71 (2013) - 2012
- [j29]Florian Raudies, Ennio Mingolla
Modeling the influence of optic flow on grid cell firing in the absence of other cues1. J. Comput. Neurosci. 33(3): 475-493 (2012) - [j28]Florian Raudies, Michael E. Hasselmo
Modeling Boundary Vector Cell Firing Given Optic Flow as a Cue. PLoS Comput. Biol. 8(6) (2012) - 2011
- [j27]Vassilis Cutsuridis
Spatial Memory Sequence Encoding and Replay During Modeled Theta and Ripple Oscillations. Cogn. Comput. 3(4): 554-574 (2011) - [j26]Michael E. Hasselmo:
A Handbook for Modeling Hippocampal Circuits. Frontiers Comput. Neurosci. 5: 2 (2011) - [j25]Michael E. Hasselmo:
Models of hippocampus. Scholarpedia 6(5): 1371 (2011) - [c7]Vassilis Cutsuridis
Bio-inspired models of memory capacity, recall performance and theta phase precession in the hippocampus. IJCNN 2011: 3141-3148 - 2010
- [c6]Vassilis Cutsuridis, Michael E. Hasselmo
Dynamics and Function of a CA1 Model of the Hippocampus during Theta and Ripples. ICANN (1) 2010: 230-240
2000 – 2009
- 2009
- [j24]Yifei Huang, Mark P. Brandon, Amy L. Griffin
Decoding Movement Trajectories Through a T-Maze Using Point Process Filters Applied to Place Field Data from Rat Hippocampal Region CA1. Neural Comput. 21(12): 3305-3334 (2009) - [j23]Michael E. Hasselmo
A phase code for memory could arise from circuit mechanisms in entorhinal cortex. Neural Networks 22(8): 1129-1138 (2009) - [j22]Eric A. Zilli, Motoharu Yoshida, Babak Tahvildari, Lisa M. Giocomo
Evaluation of the Oscillatory Interference Model of Grid Cell Firing through Analysis and Measured Period Variance of Some Biological Oscillators. PLoS Comput. Biol. 5(11) (2009) - 2008
- [j21]Eric A. Zilli, Michael E. Hasselmo
Analyses of Markov decision process structure regarding the possible strategic use of interacting memory systems. Frontiers Comput. Neurosci. 2: 6 (2008) - [j20]Randal A. Koene, Michael E. Hasselmo
Reversed and forward buffering of behavioral spike sequences enables retrospective and prospective retrieval in hippocampal regions CA3 and CA1. Neural Networks 21(2-3): 276-288 (2008) - 2007
- [j19]Yael Katz, William L. Kath
Coincidence Detection of Place and Temporal Context in a Network Model of Spiking Hippocampal Neurons. PLoS Comput. Biol. 3(12) (2007) - [c5]Randal A. Koene, Michael E. Hasselmo
A reversing buffer mechanism that enables instances of retrospective activity in hippocampal regions CA3 and CA1. IJCNN 2007: 1401-1406 - [c4]Michael E. Hasselmo, Lisa M. Giocomo, Mark P. Brandon, Motoharu Yoshida:
Mechanisms for Memory-Guided Behavior Involving Persistent Firing and Theta Rhythm Oscillations in the Entorhinal Cortex. Summer School on Neural Networks 2007: 28-37 - 2005
- [j18]Anatoli Gorchetchnikov, Michael E. Hasselmo
A biophysical implementation of a bidirectional graph search algorithm to solve multiple goal navigation tasks. Connect. Sci. 17(1-2): 145-164 (2005) - [j17]Anatoli Gorchetchnikov, Michael E. Hasselmo
A simple rule for spike-timing-dependent plasticity: local influence of AHP current. Neurocomputing 65-66: 885-890 (2005) - [j16]Michael E. Hasselmo
A Model of Prefrontal Cortical Mechanisms for Goal-directed Behavior. J. Cogn. Neurosci. 17(7): 1115-1129 (2005) - [j15]Anatoli Gorchetchnikov, Massimiliano Versace, Michael E. Hasselmo
A model of STDP based on spatially and temporally local information: Derivation and combination with gated decay. Neural Networks 18(5-6): 458-466 (2005) - [j14]Michael E. Hasselmo
Hippocampal mechanisms for the context-dependent retrieval of episodes. Neural Networks 18(9): 1172-1190 (2005) - 2003
- [j13]Robert C. Cannon, Michael E. Hasselmo, Randal A. Koene:
From biophysics to behavior - Catacomb2 and the design of biologically-plausible models for spatial navigation. Neuroinformatics 1(1): 3-42 (2003) - [j12]Donald C. Wunsch II, Michael E. Hasselmo
Welcome to the special issue: the best of the best. Neural Networks 16(5-6): 519 (2003) - [j11]Randal A. Koene, Anatoli Gorchetchnikov, Robert C. Cannon, Michael E. Hasselmo
Modeling goal-directed spatial navigation in the rat based on physiological data from the hippocampal formation. Neural Networks 16(5-6): 577-584 (2003) - 2002
- [j10]Anatoli Gorchetchnikov, Michael E. Hasselmo
A model of hippocampal circuitry mediating goal-driven navigation in a familiar environment. Neurocomputing 44-46: 423-427 (2002) - [j9]Michael E. Hasselmo
A Proposed Function for Hippocampal Theta Rhythm: Separate Phases of Encoding and Retrieval Enhance Reversal of Prior Learning. Neural Comput. 14(4): 793-817 (2002) - [j8]Kenji Doya
Introduction for 2002 Special Issue: Computational Models of Neuromodulation. Neural Networks 15(4-6): 475-477 (2002) - [j7]Michael E. Hasselmo
Neuromodulation, theta rhythm and rat spatial navigation. Neural Networks 15(4-6): 689-707 (2002) - 2001
- [j6]Erik Fransén, Angel A. Alonso, Michael E. Hasselmo
Entorhinal neuronal activity during delayed matching tasks may depend upon muscarinic-induced non-specific cation current I(CANM). Neurocomputing 38-40: 601-606 (2001) - [j5]Michael E. Hasselmo
Theta rhythm oscillations and sequence encoding in the hippocampus. Neurocomputing 38-40: 633-640 (2001)
1990 – 1999
- 1999
- [j4]Erik Fransén, Gene V. Wallenstein, Angel A. Alonso, Clayton T. Dickson
A biophysical simulation of intrinsic and network properties of entorhinal cortex. Neurocomputing 26-27: 375-380 (1999) - 1998
- [j3]Vikaas S. Sohal
Changes in GABAB Modulation During a Theta Cycle May Be Analogous to the Fall of Temperature During Annealing. Neural Comput. 10(4): 869-882 (1998) - 1996
- [e1]David S. Touretzky, Michael Mozer, Michael E. Hasselmo:
Advances in Neural Information Processing Systems 8, NIPS, Denver, CO, USA, November 27-30, 1995. MIT Press 1996, ISBN 0-262-20107-0 [contents] - 1995
- [c3]Michael E. Hasselmo, Milos Cekic:
Cholinergic suppression of transmission may allow combined associative memory function and self-organization in the neocortex. NIPS 1995: 131-137 - 1994
- [j2]Michael E. Hasselmo
Runaway synaptic modification in models of cortex: Implications for Alzheimer's disease. Neural Networks 7(1): 13-40 (1994) - [c2]Michael E. Hasselmo, Eric Schnell, Joshua Berke, Edi Barkai:
A model of the hippocampus combibing self-organization and associative memory function. NIPS 1994: 77-84 - 1993
- [j1]Michael E. Hasselmo:
Acetylcholine and Learning in a Cortical Associative Memory. Neural Comput. 5(1): 32-44 (1993) - 1990
- [c1]Michael E. Hasselmo, Brooke P. Anderson, James M. Bower:
Cholinergic Modulation May Enhance Cortical Associative Memory Function. NIPS 1990: 46-52
Coauthor Index
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