학술논문

Modification of activity pattern induced by synaptic enhancements in a semi-artificial network of living neurons
Document Type
Conference
Source
2011 International Symposium on Micro-NanoMechatronics and Human Science Micro-NanoMechatronics and Human Science (MHS), 2011 International Symposium on. :250-254 Nov, 2011
Subject
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Neurons
Biological neural networks
Synchronization
Electric potential
Extracellular
Spatiotemporal phenomena
Indexes
Language
Abstract
Higher brain function such as memory formation was not performed by activity of a single neuron but performed by functions of a complex network of neuronal cells. The simple small-scaled network of neuronal cells is fully suitable for such interactions between neurons. Dissociated neurons form a network depending on their electrical activity and spontaneous activity frequently observed within a week. We cultured a network of dissociated neurons on a culture dish with 64 planer microelectrodes. We induced synaptic enhancement in cultured neuronal networks by exposing to Mg 2+ -free condition for 20 min. Mg 2+ -free condition was achieved by exchanging of normal cell external solution to Mg 2+ -free recording solution. After the induction of synaptic enhancement, we analyzed activity pattern by an autocorrelogram-based and crosscorrelogram-based method. Autocorrelogram of the neuronal activity centralized, suggesting that the accuracy of the periodicity increased. This drastic change was induced within only 20 minutes. Crosscorrelogram shows those network activity changed to be more synchronously than one before exposure to Mg2+-free condition. These results suggest that functional connections in a semi-artificial neuronal network were changed to ones performing enhanced network activity than before. The modification of the spatiotemporal pattern of activity is thought to be a base of memory in vivo experiments. We performed similar phenomenon in this semi-artificial, autonomously reorganized network of neurons. By elucidation of these modified functional connections in neural network, we can find a cue how to control biological memory formation.