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A model of visuospatial working memory in prefrontal cortex: recurrent network and cellular bistability
1Center for Complex Systems, Brandeis University, Waltham, MA 02254, USA. camperi@lynx.cs.usfca.edu
Journal of Computational Neuroscience
|January 7, 1999
Summary
This study simulates visuospatial working memory using a computational model. Cellular bistability in neurons enhances memory reliability against noise and distractions.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Cognitive Science
Background:
- Visuospatial working memory is crucial for cognitive tasks.
- Previous models often struggle with noise and distraction.
- The role of single-neuron properties in network memory is debated.
Purpose of the Study:
- To simulate visuospatial delayed-response experiments.
- To investigate the role of cellular bistability in working memory.
- To model how neuronal properties affect memory reliability.
Main Methods:
- Developed a firing-rate computational model.
- Combined recurrent neocortical network architecture with cellular bistability.
- Simulated responses to cue stimuli and distraction stimuli.
Main Results:
- Network activity profiles store visuospatial information.
- Cellular bistability enhances robustness against noise and distraction.
- Neuronal persistent activity and memory fields are explained by network mechanisms.
Conclusions:
- Cellular bistability is key for reliable working memory.
- Intrinsic neuronal properties can be modulated to alter memory fields.
- This model provides insights into prefrontal cortex function in working memory.