Extracellular Electrical Stimulationbased in Vitro Neuroscience: A Minireview of Methods and a Paradigm Shift Proposal Biological neuronal cells communicate using neurochemistry and electrical signals. Electrical stimulation (ES) is utilized to study neuronal cells and networks. Currently, ES is applied and responses observed in an openloop fashion, which does not resemble natural network IO. We hypothesize that realtime closedloop fullduplex (simultaneous twoway) paradigms could provide deeper insight in natural neuronal networks, helping to understand our brains and to control neuronal network states to cure diseases. We present a minireview of ESbased extracellular in vitro neuroscience, our first longterm closedloop ES experiment results as the proofoffeasibility of the method, and our paradigmshifting proposal of dialogical bioICT paradigms.

DigitalSignalProcessor Realization of Izhikevich Neural Network for RealTime Interaction with Electrophysiology Experiments The paper presents a realization on a digital signal processor (DSP) of an Izhikevich Neural Network operating with biologically plausible realtime constants. The paper demonstrates the realtime realization of different neuron behavioral modes, i.e., regularspiking, chattering, bursting, and fastspiking under proper parametrization. Realtime spiketimingdependentplasticity has also been embedded in the neural network realization. The paper studies the maximum array size that can be implemented on a TMS320C6455 microprocessor to be able to reproduce correctly the realtime dynamics of the different behaviors. The TMS320C6454, from the same DSP family as TMS320C6455, is embedded in a commercial microelectrode array system for realtime interaction with biological neural cell cultures. As demonstrator, a simple classification of two binary patterns has been implemented. Upon learning activation, the system robustly unsupervisely learns to differentiate the two patterns.