Neuromodulation, theta rhythm and rat spatial navigation
Neural Networks - Computational models of neuromodulation
A distributed representation of temporal context
Journal of Mathematical Psychology
Neural Networks - 2003 Special issue: Advances in neural networks research IJCNN'03
A model of spatial map formation in the hippocampus of the rat
Neural Computation
Emergence of sequence sensitivity in a hippocampal CA3-CA1 model
Neural Networks
Context learning in the rodent hippocampus
Neural Computation
Phase precession through synaptic facilitation
Neural Computation
Model of Cue Extraction from Distractors by Active Recall
Neural Information Processing
Dynamic Brain - from Neural Spikes to Behaviors
Simulation of human episodic memory by using a computational model of the hippocampus
Advances in Artificial Intelligence - Special issue on artificial intelligence in neuroscience and systems biology: lessons learnt, open problems, and the road ahead
Affective, natural interaction using EEG: sensors, application and future directions
SETN'12 Proceedings of the 7th Hellenic conference on Artificial Intelligence: theories and applications
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Behaviors ranging from delivering newspapers to waiting tables depend on remembering previous episodes to avoid incorrect repetition. Physiologically, this requires mechanisms for long-term storage and selective retrieval of episodes based on the time of occurrence, despite variable intervals and similarity of events in a familiar environment. Here, this process has been modeled based on the physiological properties of the hippocampal formation, including mechanisms for sustained activity in entorhinal cortex and theta rhythm oscillations in hippocampal subregions. The model simulates the context-sensitive firing properties of hippocampal neurons including trial-specific firing during spatial alternation and trial by trial changes in theta phase precession on a linear track. This activity is used to guide behavior, and lesions of the hippocampal network impair memory-guided behavior. The model links data at the cellular level to behavior at the systems level, describing a physiologically plausible mechanism for the brain to recall a given episode which occurred at a specific place and time.