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Updated: Oct 7, 2025

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
Published on: March 2, 2015
THE ROLE OF BURSTS IN SENSORY DISCRIMINATION AND RETENTION OF FAVORED INPUTS IN THE CULTURED NEURAL NETWORKS
C Goletiani1, N Nebieridze1, O Kukhianidze1
11Free University of Tbilisi, Tbilisi, Georgia; Georgia.
Abstract:
The capacity of neural tissue to discriminiate the sensory signals determines how we recognise the world diversity. Dissociated cortical culture (DCC) homed in a multielectrode array allows mimicking neural networks of the brain and using it for investigation of neural computation processes. This in vivo-like in vitro system allows tracking and assessing structural and functional refinement, as well as the ability for information acquisition, processing, and coding in neural networks. We had an increased interest to the burst phenomenon as it represents one of the strongest tools for information coding. We were interested in whether the neural circuitry of DCC was capable of sensory discrimination and memorization of the preferred electric stimuli and to determine the role of bursts in these processes.Matured DCC from the 30th to 50th day of in vitro cultivation were used for the study. In order to simulate a variety of sensory inputs, 300 mV of single, paired-pulse (20 ms interstimulus interval), 1, 5, 10, 20 and 100 Hz stimuli for 1 sec were repeated at random time interval (>10 secs) from effective pairs of electrodes; Activity was registered from all active channels.The data revealed that during the variety of electric stimulations neurons increased activity in response to one of the stimulus types while responding less effectively to others. Single, 5Hz, and notably PP stimuli were the favored paradigms. The training phase frequently showed a progressive increase in activity level, with short burst prevalence. However, repetition of the preferred stimuli enhanced the occurrence of both tonic and burst evoked responses with prolonged duration throughout the testing phase.Data shows that neural circuits of DCC have high selectivity to physical properties and spatial position of the sensory inputs and produces early and late responses that include burst elements that may serve as the robust mechanism for reinforcement of the coding information needed for sensory discrimination and learning.
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