Coexistence of short and long term memory in a model network of realistic neurons
نویسندگان
چکیده
NMDA-mediated synaptic currents are believed to in#uence LTP. A recent model (Lisman et al., Nature Neurosci. (1993) 273}275) demonstrates that they can instead support short term memory based on rhythmic spike activity. We examine this e!ect in a more realistic model that uses two-compartment neurons experiencing fatigue and also includes long-term memory by synaptic LTP. We "nd that the network does support both modes of operation without any parameter changes, but depending on the input patterns. Short term memory functionality might facilitate Hebbian learning through LTP by holding a new pattern while synaptic potentiation occurs. We also "nd that susceptibility of the short term memory against new input is time-dependent and reaches a maximum around the time constant of neuronal fatigue (200}400 ms). This corresponds well to the time scale of the syllabic rhythm and various psychophysical phenomena. 2001 Elsevier Science B.V. All rights reserved.
منابع مشابه
Prediction of Covid-19 Prevalence and Fatality Rates in Iran Using Long Short-Term Memory Neural Network
Introduction: The rapid spread of COVID-19 has become a critical threat to the world. So far, millions of people worldwide have been infected with the disease. The Covid-19 pandemic has had significant effects on various aspects of human life. Currently, prediction of the virus's spread is essential in order to be safe and make necessary arrangements. It can help control the rate of its outbrea...
متن کاملPrediction of Covid-19 Prevalence and Fatality Rates in Iran Using Long Short-Term Memory Neural Network
Introduction: The rapid spread of COVID-19 has become a critical threat to the world. So far, millions of people worldwide have been infected with the disease. The Covid-19 pandemic has had significant effects on various aspects of human life. Currently, prediction of the virus's spread is essential in order to be safe and make necessary arrangements. It can help control the rate of its outbrea...
متن کاملIntegration of remote sensing and meteorological data to predict flooding time using deep learning algorithm
Accurate flood forecasting is a vital need to reduce its risks. Due to the complicated structure of flood and river flow, it is somehow difficult to solve this problem. Artificial neural networks, such as frequent neural networks, offer good performance in time series data. In recent years, the use of Long Short Term Memory networks hase attracted much attention due to the faults of frequent ne...
متن کاملEffects of exercise on spatial memory deficits induced by nucleus basalis magnocellularis lesions
Introduction: Previous studies have shown that exercise enhances cognitive and functional capacities in patients with Alzheimer's disease (AD). In this study, we investigated the effect of long-term (60 days) and short- term (10 days) exercise on the spatial memory deficits in an animal model of AD. Methods: Fifty male rats were divided into 5 groups 1) intact, 2) sham, 3) sham-Alzheimer 4) ...
متن کاملThe effect of intrahippocampal microinjection of Naloxone on short –term and long-term memory in adult male rats
Introduction:The hippocampus is one for the major centers of learning and memory. Role of the opioid system has been investigated and on the other hand receptors related to this system such as mu-opioid receptors (MOR) are extended in the hippocampus. In this study the effect of Naloxone administration as a mu opioid receptor antagonist on passive avoidance memory in adult male rats was i...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Neurocomputing
دوره 38-40 شماره
صفحات -
تاریخ انتشار 2001