- Tytuł:
- The spike-timing-dependent plasticity function based on a brain sequential learning system using a recurrent neuronal network
- Autorzy:
-
Ogata, G.
Natsume, K.
Ishizuka, S.
Hayashi, H. - Powiązania:
- https://bibliotekanauki.pl/articles/384197.pdf
- Data publikacji:
- 2010
- Wydawca:
- Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
- Tematy:
-
hippocampus
entorhinal cortex
STDP function
brain science - Opis:
- This paper examines the spike-timing-dependent plasticity (STDP) at the synapses of the medial entorhinal cortex (EC) and the dentate gyrus (DG) in the hippocampus. The medial and lateral ECs respectively convey spatial and non-spatial information to the hippocampus, and the DG of the hippocampus integrates or binds them. There is a recurrent neuronal network between the EC and the hippocampus called the EC-hippocampus loop. A computational study has shown that using this loop and STDP phenomena at the recurrent EC synapse, sequential learning can be accomplished. But the STDP functions at the synapses of the EC and DG have not yet been studied by neurophysiological experiments. Experiments on STDP phenomena were performed in rats. The STDP function was asymmetrical in the EC synapse and symmetrical in the DG. The medial EC mainly processes the time-series signals for spatial information about visual landmarks when a rat is running in an environment, the lateral EC processes their features, and the DG binds or integrates the information on the positions and features of the landmarks. Thus, the EC-hippocampus loop processes sequential learning of spatial and non-spatial information in parallel, and the DG binds or integrates the two kinds of signals. A system based on this biological phenomenon could have similar characteristics of parallel processing of object features and positions, and their binding.
- Źródło:
-
Journal of Automation Mobile Robotics and Intelligent Systems; 2010, 4, 2; 25-30
1897-8649
2080-2145 - Pojawia się w:
- Journal of Automation Mobile Robotics and Intelligent Systems
- Dostawca treści:
- Biblioteka Nauki
Artykuł