Spatio-temporal electrical stimuli shape behavior of an embodied cortical network in a goal-directed learning task

Abstract

We developed an adaptive training algorithm, whereby an in vitro neocortical network learned to modulate its dynamics and achieve pre-determined activity states within tens of minutes through the application of patterned training stimuli using a multi-electrode array. A priori knowledge of functional connectivity was not necessary. Instead, effective training sequences were continuously discovered and refined based on real-time feedback of performance. The short-term neural dynamics in response to training became engraved in the network, requiring progressively fewer training stimuli to achieve successful behavior in a movement task. After 2 h of training, plasticity remained significantly greater than the baseline for 80 min (p-value <0.01). Interestingly, a given sequence of effective training stimuli did not induce significant plasticity (p-value = 0.82) or desired behavior, when replayed to the network and no longer contingent on feedback. Our results encourage an in vivo investigation of how targeted multi-site artificial stimulation of the brain, contingent on the activity of the body or even of the brain itself could treat neurological disorders by gradually shaping functional connectivity.

How to Culture, Record and Stimulate Neuronal Networks on Micro-electrode Arrays (MEAs)

“…As mentioned above, ongoing work is utilizing this technology to study processes like cellular plasticity, development, excitotoxicity and neurodegeneration. [6][7][8][9][10] For example, a recent publication from our laboratory showed reproducible goal directed learning in vitro with real-time closed loop stimulation in response to current neuronal network activity 3 .…”

“…Current neuronal processes being studied with this model include network dynamics, development, learning and memory, synaptic plasticity, excitotoxicity, ischemia and neurodegeneration. [3][4][5][6][7][8][9][10] Findings from these studies could have significant implications for establishing better treatments for human diseases like congenital malformations, epilepsy, stroke and Alzheimer's disease. The purpose of this protocol is to provide the necessary information for setting up, caring for, recording from and stimulating cultures on MEAs.…”

Optimizing microstimulation using a reinforcement learning framework

“…With microelectrode arrays, there is the possibility to modify both the spatial and temporal parameters of the stimulation. An action-selection approach with binary rewards was used to select spatio-temporal stimulation patterns in [7], but in their in vitro study the goal of the stimulation was to adjust the underlying network connectivity through repeated stimulation. A study [8] using simulated neural circuits showed the ability to control firing rates treating the stimulation as MIMO control problem.…”

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

“…While the setup presented here is not the first embodied system for hybrid, closed-loop experiments 20,23,27,41,42 , the ones designed in the past were focused on a single thesis supported by data from a limited number of analogous preparations. On the other hand, the described setup has been used for a large number of experiments (more than 100 cultures have been recorded since 2012) with preparations differing for modularity and origin, while the experiments themselves addressed different issues (e.g.…”