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Query: UMLS:C0598853 (forgetting)
 3,232 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

The P300 is an endogenously evoked potential with amplitude and latency depending on the amount of information carried by the stimulus rather than its physical characteristics. It has been suggested that P300 is a manifestation of the context updating mechanism in the human working memory. We present a neural network-based model that mimics the learning and forgetting mechanisms of external stimuli in the human working memory that are believed to be responsible for P300 generation. A modified version of the Hebbian learning rule has been devised to govern the weight dynamics of the network. The model was validated by comparing the characteristics of simulated P300 with actual experimental findings such as the relationship between P300 amplitude and stimulus probability, and task relevance. The results show that the proposed P300 model mimics many aspects of the nervous system responsible for P300 generation.
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PMID:A computational model for generation of the P300 evoked potential component. 2297 37

The limited capacity of recent memory inevitably leads to partial memory of past stimuli. There is also evidence that behavioral and neural responses to novel or rare stimuli are dependent on one's memory of past stimuli. Thus, these responses may serve as a probe of different individuals' remembering and forgetting characteristics. Here, we utilize two lossy compression models of stimulus sequences that inherently involve forgetting, which in addition to being a necessity under many conditions, also has theoretical and behavioral advantages. One model is based on a simple stimulus counter and the other on the Information Bottleneck (IB) framework which suggests a more general, theoretically justifiable principle for biological and cognitive phenomena. These models are applied to analyze a novelty-detection event-related potential commonly known as the P300. The trial-by-trial variations of the P300 response, recorded in an auditory oddball paradigm, were subjected to each model to extract two stimulus-compression parameters for each subject: memory length and representation accuracy. These parameters were then utilized to estimate the subjects' recent memory capacity limit under the task conditions. The results, along with recently published findings on single neurons and the IB model, underscore how a lossy compression framework can be utilized to account for trial-by-trial variability of neural responses at different spatial scales and in different individuals, while at the same time providing estimates of individual memory characteristics at different levels of representation using a theoretically-based parsimonious model.
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PMID:Surprise response as a probe for compressed memory states. 3201 46