Optimization of Artificial Port Reflectances for Wave Digital Filters with Topology-Related Delay-Free Loops

Kolonko, Lech; Velten, Jorg; Kummert, Anton

doi:10.1109/mwscas48704.2020.9184701

Cited by 3 publications

(1 citation statement)

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“…For instance, it provides run-time efficient algorithms well interpretable in terms of electrical circuits due to their direct correspondence with the reference circuit. Moreover, multidimensional wave digital algorithms [18][19][20][21][22] can be used, which can be very efficient for emulating larger circuit setups, cf. 19 The wave digital concept is hence well suited for this work.…”

Section: Introductionmentioning

confidence: 99%

Wave digital model of calcium‐imaging‐based neuronal activity of mice

Jenderny

Ochs

2022

Int J Numerical Modelling

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The modeling of real neuronal networks by close‐to‐biology circuits can contribute to a better understanding of these networks from a circuit theoretical point of view. This can potentially lead to novel design principles for electrical circuits. This modeling process involves the mimicking of real measured neuronal activity, which is often only available as calcium imaging recordings. In this work, we develop a wave digital model as a circuit emulator capable of mimicking the calcium‐imaging‐based neuronal activity of mouse neurons. For this purpose, we design an electrical reference circuit of a mouse neuron based on an extended Morris–Lecar model in combination with an RC circuit. The circuit parameters are determined by a parameter scaling without requiring any parameter optimization. The input signal of the resulting wave digital model is designed based on estimating spike times with the spike inference software MLspike. Wave digital emulations show the successful mimicking of calcium‐based neuronal activity for mouse neurons located in the visual, motor and somatosensory cortex as well the possibility to predict ion currents occurring during this activity. This proves the suitability of the reference circuit as a model for the considered types of mouse neurons. It also implies that the circuit can act as an observer for electrical signals of mouse neurons. This is achieved despite the lack of electrophysiological measurements in most cases. Hence, the proposed wave digital model can be seen as an important step toward being able to verify close‐to‐biology electrical circuits as a model of real neuronal networks without electrophysiology.

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