Abstract
Distinct modules of the neural circuitry interact with each other and (through the motor-sensory loop) with the environment, forming a complex dynamic system. Neuro-prosthetic devices seeking to modulate or restore CNS function need to interact with the information flow at the level of neural modules electrically, bi-directionally and in real-time. A set of freely available generic tools is presented that allow computationally demanding multi-channel short-latency bi-directional interactions to be realized in in vivo and in vitro preparations using standard PC data acquisition and processing hardware and software (Mathworks Matlab and Simulink). A commercially available 60-channel extracellular multi-electrode recording and stimulation set-up connected to an ex vivo developing cortical neuronal culture is used as a model system to validate the method. We demonstrate how complex high-bandwidth (>10 MBit/s) neural recording data can be analyzed in real-time while simultaneously generating specific complex electrical stimulation feedback with deterministically timed responses at sub-millisecond resolution.
Highlights
The experimental method of placing a biological system within a low-latency closed loop control system is well established in the “dynamic clamping”of single nerve cells (Sharp et al.,1993; Robinson, 1994; Prinz et al, 2004)
We demonstrate how an electric stimulus can be used to interact and interfere with the ongoing activity, both as a “single-shot” and as a modulated stimulus train. These applications were chosen because they are challenging to implement in a generic fashion, and relevant for experimental paradigms aimed at characterization and modulation of complex interactions in neural systems leading to the development of neuroprosthetic devices
The spontaneous activity exhibited by a dissociated neuronal culture after 3 weeks in vitro consists of intermittent bursts of activity (“network spikes”) lasting around 100 ms each that are separated by several seconds of relatively sparse activity
Summary
The experimental method of placing a biological system within a low-latency closed loop control system is well established in the “dynamic clamping”of single nerve cells (Sharp et al.,1993; Robinson, 1994; Prinz et al, 2004). Taking a similar approach to the network level, currently requires a highly specialized software and hardware set-up to achieve a feedback system with sufficiently deterministic latencies and narrow response-time windows for realistic motor-s ensory loops (Rutten, 2002; Wolpawa et al, 2002; Ahissar and Kleinfeld, 2003; Karniel et al, 2005; Novellino et al, 2007) This constitutes both a significant investment in terms of time and cost, and limits the scope of the methods in being applicable only for the specific set of experiments they were designed for. Advanced programming is not required as the real-time stage consists of a high-level visually developed Simulink signal processing model and simple control scripts
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