An analog vlsi model of muscular contraction

Abstract

We have developed analog VLSI circuits to model the behavior demonstrated by biological sarcomeres, the force generating components of muscle tissue. The circuits are based upon the mathematical description of crossbridge populations developed by A. F. Huxley. We have implemented the sarcomere circuit using a standard 1.2-m process, and have demonstrated the nonlinear transient behaviors exhibited by biological muscle.

Analog VLSI Biophysical Neurons and Synapses With Programmable Membrane Channel Kinetics

“…12, the variation of scales the time axis of the waveforms by a factor greater than 2. The amplitude scaling in the gating parameters reflects scaling proportional to consistent with (8)- (10). We implemented the HH model in one neuron and observed the dynamics of the membrane and gating variables as shown in Fig.…”

“…By properly setting the current bias values and sign bit for each of the seven sigmoidal functions, the summation can accommodate a wide range of functions approximating typical rate functions and (7) where the output current denotes either one of the and rates, and where is the thermal voltage. To enforce a consistent temporal scale of the dynamics across membrane and gating variables, the currents implementing the opening and closing rates as well as the membrane conductances are globally scaled with a current that drives the multiplying DACs (8) (9) (10) and, thus, uniformly controls the time base of all dynamic variables with a global temporal scale parameter .…”

“…These approaches, as described in [7], have great potential in the realization of intelligent neural prostheses when combined with embedded signal processing to process incoming neural spike data streams [8], [9] and activate prostheses [10], [12].…”

Biophysical synaptic dynamics in an analog VLSI network of hodgkin-huxley neurons

“…Furthermore, there are various analog and digital exposed probes in the circuit board allow for a real-time interface to the internal membrane channel dynamics. Previous neuron-based circuit systems have been used to either model or interface to various biological systems through the implementation of sophisticated signal processing [5], [6]. The NeuroDyn system provides greater insight into the biological basis behind the function through the biophysical origin of its models.…”