Cholinergic Modulation May Enhance Cortical Associative Memory Function. - Michael E. Hasselmo; Brooke P. Anderson; James M. Bower (NIPS, 1990)

Acetylcholine and Learning in a Cortical Associative Memory. - Michael E. Hasselmo (Neural Comput., 1993)

A model of the hippocampus combibing self-organization and associative memory function. - Michael E. Hasselmo; Eric Schnell; Joshua Berke; Edi Barkai (NIPS, 1994)

Runaway synaptic modification in models of cortex: Implications for Alzheimer's disease. - Michael E. Hasselmo (Neural Networks, 1994)

Cholinergic suppression of transmission may allow combined associative memory function and self-organization in the neocortex. - Michael E. Hasselmo; Milos Cekic (NIPS, 1995)

Changes in GABAB Modulation During a Theta Cycle May Be Analogous to the Fall of Temperature During Annealing. - Vikaas S. Sohal; Michael E. Hasselmo (Neural Comput., 1998)

A biophysical simulation of intrinsic and network properties of entorhinal cortex. - Erik Fransén; Gene V. Wallenstein; Angel A. Alonso; Clayton T. Dickson; Michael E. Hasselmo (Neurocomputing, 1999)

Entorhinal neuronal activity during delayed matching tasks may depend upon muscarinic-induced non-specific cation current I(CANM). - Erik Fransén; Angel A. Alonso; Michael E. Hasselmo (Neurocomputing, 2001)

Theta rhythm oscillations and sequence encoding in the hippocampus. - Michael E. Hasselmo; Ajay Kapur; Bradley P. Wyble (Neurocomputing, 2001)

A model of hippocampal circuitry mediating goal-driven navigation in a familiar environment. - Anatoli Gorchetchnikov; Michael E. Hasselmo (Neurocomputing, 2002)

A Proposed Function for Hippocampal Theta Rhythm: Separate Phases of Encoding and Retrieval Enhance Reversal of Prior Learning. - Michael E. Hasselmo; Clara Bodelón; Bradley P. Wyble (Neural Comput., 2002)

Introduction for 2002 Special Issue: Computational Models of Neuromodulation. - Kenji Doya; Peter Dayan; Michael E. Hasselmo (Neural Networks, 2002)

Neuromodulation, theta rhythm and rat spatial navigation. - Michael E. Hasselmo; Jonathan Hay; Maxim Ilyn; Anatoli Gorchetchnikov (Neural Networks, 2002)

Timing of consecutive traveling pulses in a model of entorhinal cortex. - Anatoli Gorchetchnikov; Michael E. Hasselmo (IJCNN, 2003)

Theta theory: Requirements for encoding events and task rules explain theta phase relationships in hippocampus and neocortex. - Michael E. Hasselmo (IJCNN, 2003)

Goal-directed spatial navigation of the rat depends on phases of theta oscillation in hippocampal circuitry. - Randal A. Koene; Robert C. Cannon; Michael E. Hasselmo (IJCNN, 2003)

From biophysics to behavior - Catacomb2 and the design of biologically-plausible models for spatial navigation. - Robert C. Cannon; Michael E. Hasselmo; Randal A. Koene (Neuroinformatics, 2003)

Modeling goal-directed spatial navigation in the rat based on physiological data from the hippocampal formation. - Randal A. Koene; Anatoli Gorchetchnikov; Robert C. Cannon; Michael E. Hasselmo (Neural Networks, 2003)

Welcome to the special issue: the best of the best. - Donald C. Wunsch II; Michael E. Hasselmo; DeLiang L. Wang; Ganesh K. Venayagamoorthy (Neural Networks, 2003)

Hippocampal and prefrontal cortical mechanisms for goal-directed and memory-guided behavior. - Michael E. Hasselmo (IJCNN, 2004)

Spatially and temporally local spike-timing-dependent plasticity rule. - Anatoli Gorchetchnikov; Massimiliano Versace; Michael E. Hasselmo (IJCNN, 2005)

Hebbian synaptic modification in cortical circuits and memory-guided behavior in spatial alternation and delayed non-match to position. - Michael E. Hasselmo; Eric A. Zilli (IJCNN, 2005)

An integrate and fire model of prefrontal cortex provides a biological implementation of action selection in reinforcement learning theory that reuses known representations. - Randal A. Koene; Michael E. Hasselmo (IJCNN, 2005)

A biophysical implementation of a bidirectional graph search algorithm to solve multiple goal navigation tasks. - Anatoli Gorchetchnikov; Michael E. Hasselmo (Connect. Sci., 2005)

A simple rule for spike-timing-dependent plasticity: local influence of AHP current. - Anatoli Gorchetchnikov; Michael E. Hasselmo (Neurocomputing, 2005)

A Model of Prefrontal Cortical Mechanisms for Goal-directed Behavior. - Michael E. Hasselmo (J. Cogn. Neurosci., 2005)

A model of STDP based on spatially and temporally local information: Derivation and combination with gated decay. - Anatoli Gorchetchnikov; Massimiliano Versace; Michael E. Hasselmo (Neural Networks, 2005)

Hippocampal mechanisms for the context-dependent retrieval of episodes. - Michael E. Hasselmo; Howard Eichenbaum (Neural Networks, 2005)

A reversing buffer mechanism that enables instances of retrospective activity in hippocampal regions CA3 and CA1. - Randal A. Koene; Michael E. Hasselmo (IJCNN, 2007)

Mechanisms for Memory-Guided Behavior Involving Persistent Firing and Theta Rhythm Oscillations in the Entorhinal Cortex. - Michael E. Hasselmo; Lisa M. Giocomo; Mark P. Brandon; Motoharu Yoshida (Summer School on Neural Networks, 2007)

Coincidence Detection of Place and Temporal Context in a Network Model of Spiking Hippocampal Neurons. - Yael Katz; William L. Kath; Nelson Spruston; Michael E. Hasselmo (PLoS Comput. Biol., 2007)

Analyses of Markov decision process structure regarding the possible strategic use of interacting memory systems. - Eric A. Zilli; Michael E. Hasselmo (Frontiers Comput. Neurosci., 2008)

Reversed and forward buffering of behavioral spike sequences enables retrospective and prospective retrieval in hippocampal regions CA3 and CA1. - Randal A. Koene; Michael E. Hasselmo (Neural Networks, 2008)

Decoding Movement Trajectories Through a T-Maze Using Point Process Filters Applied to Place Field Data from Rat Hippocampal Region CA1. - Yifei Huang; Mark P. Brandon; Amy L. Griffin 002; Michael E. Hasselmo; Uri T. Eden (Neural Comput., 2009)

A phase code for memory could arise from circuit mechanisms in entorhinal cortex. - Michael E. Hasselmo; Mark P. Brandon; Motoharu Yoshida; Lisa M. Giocomo; James G. Heys; Erik Fransén; Ehren L. Newman; Eric A. Zilli (Neural Networks, 2009)

Evaluation of the Oscillatory Interference Model of Grid Cell Firing through Analysis and Measured Period Variance of Some Biological Oscillators. - Eric A. Zilli; Motoharu Yoshida; Babak Tahvildari; Lisa M. Giocomo; Michael E. Hasselmo (PLoS Comput. Biol., 2009)

Dynamics and Function of a CA1 Model of the Hippocampus during Theta and Ripples. - Vassilis Cutsuridis; Michael E. Hasselmo (ICANN (1), 2010)

Bio-inspired models of memory capacity, recall performance and theta phase precession in the hippocampus. - Vassilis Cutsuridis; Bruce P. Graham; Stuart Cobb; Michael E. Hasselmo (IJCNN, 2011)

Spatial Memory Sequence Encoding and Replay During Modeled Theta and Ripple Oscillations. - Vassilis Cutsuridis; Michael E. Hasselmo (Cogn. Comput., 2011)

A Handbook for Modeling Hippocampal Circuits. - Michael E. Hasselmo (Frontiers Comput. Neurosci., 2011)

Models of hippocampus. - Michael E. Hasselmo (Scholarpedia, 2011)

Modeling the influence of optic flow on grid cell firing in the absence of other cues1. - Florian Raudies; Ennio Mingolla; Michael E. Hasselmo (J. Comput. Neurosci., 2012)

Modeling Boundary Vector Cell Firing Given Optic Flow as a Cue. - Florian Raudies; Michael E. Hasselmo (PLoS Comput. Biol., 2012)

Rhythm-induced spike-timing patterns characterized by 1D firing maps. - Jan R. Engelbrecht; Kristen Loncich; Renato Mirollo; Michael E. Hasselmo; Motoharu Yoshida (J. Comput. Neurosci., 2013)

Multi-scale bio-inspired place recognition. - Zetao Chen; Adam Jacobson; Ugur M. Erdem; Michael E. Hasselmo; Michael Milford (ICRA, 2014)

Theta rhythm and the encoding and retrieval of space and time. - Michael E. Hasselmo; Chantal E. Stern (NeuroImage, 2014)

Functional connections between optic flow areas and navigationally responsive brain regions during goal-directed navigation. - Katherine R. Sherrill; Elizabeth R. Chrastil; Robert S. Ross; Ugur M. Erdem; Michael E. Hasselmo; Chantal E. Stern (NeuroImage, 2015)

Bio-inspired homogeneous multi-scale place recognition. - Zetao Chen; Stephanie M. Lowry; Adam Jacobson; Michael E. Hasselmo; Michael Milford (Neural Networks, 2015)

Differences in Visual-Spatial Input May Underlie Different Compression Properties of Firing Fields for Grid Cell Modules in Medial Entorhinal Cortex. - Florian Raudies; Michael E. Hasselmo (PLoS Comput. Biol., 2015)

Feature extraction in Q-learning using neural networks. - Henghui Zhu; Ioannis Ch. Paschalidis; Michael E. Hasselmo (CDC, 2017)

Neural circuits for learning context-dependent associations of stimuli. - Henghui Zhu; Ioannis Ch. Paschalidis; Michael E. Hasselmo (Neural Networks, 2018)

Flexible resonance in prefrontal networks with strong feedback inhibition. - Jason S. Sherfey; Salva Ardid; Joachim Hass; Michael E. Hasselmo; Nancy J. Kopell (PLoS Comput. Biol., 2018)

A Hebbian learning algorithm for training a neural circuit to perform context-dependent associations of stimuli. - Henghui Zhu; Ioannis Ch. Paschalidis; Michael E. Hasselmo (ACC, 2019)

The Role of Hierarchical Dynamical Functions in Coding for Episodic Memory and Cognition. - Holger Dannenberg; Andrew S. Alexander; Jennifer C. Robinson; Michael E. Hasselmo (J. Cogn. Neurosci., 2019)

Bio-inspired multi-scale fusion. - Stephen Hausler; Zetao Chen; Michael E. Hasselmo; Michael Milford (Biol. Cybern., 2020)

A Geometric Characterization of Population Coding in the Prefrontal Cortex and Hippocampus during a Paired-Associate Learning Task. - Yue Liu; Scott L. Brincat; Earl K. Miller; Michael E. Hasselmo (J. Cogn. Neurosci., 2020)

Learning from humans: combining imitation and deep reinforcement learning to accomplish human-level performance on a virtual foraging task. - Vittorio Giammarino; Matthew F. Dunne; Kylie N. Moore; Michael E. Hasselmo; Chantal E. Stern; Ioannis Ch. Paschalidis (CoRR, 2022)

BU-CVKit: Extendable Computer Vision Framework for Species Independent Tracking and Analysis. - Mahir Patel; Lucas C. Carstensen; Yiwen Gu; Michael E. Hasselmo; Margrit Betke (CoRR, 2023)

Animal Pose Tracking: 3D Multimodal Dataset and Token-based Pose Optimization. - Mahir Patel; Yiwen Gu; Lucas C. Carstensen; Michael E. Hasselmo; Margrit Betke (Int. J. Comput. Vis., 2023)

Self-Supervised Mapping and Localization by Predictive Learning. - G. William Chapman; Andrew S. Alexander; Frances S. Chance; Michael E. Hasselmo (ICONS, 2024)

Combining imitation and deep reinforcement learning to human-level performance on a virtual foraging task. - Vittorio Giammarino; Matthew F. Dunne; Kylie N. Moore; Michael E. Hasselmo; Chantal E. Stern; Ioannis Ch. Paschalidis (Adapt. Behav., 2024)

A Feature-based Generalizable Prediction Model for Both Perceptual and Abstract Reasoning. - Quan Do; Thomas M. Morin; Chantal E. Stern; Michael E. Hasselmo (CoRR, 2024)