Neuromorphometric characterization with shape functionals

This work presents a procedure to extract morphological information from neuronal cells based on the variation of shape functionals as the cell geometry undergoes a dilation through a wide interval of spatial scales. The targeted shapes are alpha and beta cat retinal ganglion cells, which are characterized by different ranges of dendritic field diameter. Image functionals are expected to act as descriptors of the shape, gathering relevant geometric and topological features of the complex cell form. We present a comparative study of classification performance of additive shape descriptors, namely, Minkowski functionals, and the nonadditive multiscale fractal. We found that the proposed measures perform efficiently the task of identifying the two main classes alpha and beta based solely on scale invariant information, while also providing intraclass morphological assessment

An implantable mixed-signal CMOS die for battery-powered in vivo blowfly neural recordings

© 2018 A mixed-signal die containing two differential input amplifiers, a multiplexer and a 50 KSPS, 10-bit SAR ADC, has been designed and fabricated in a 0.35 μm CMOS process for in vivo neural recording from freely moving blowflies where power supplied voltage drops quickly due to the space/weight limited insufficient capacity of the battery. The designed neural amplifier has a 66 + dB gain, 0.13 Hz-5.3 KHz bandwidth and 0.39% THD. A 20% power supply voltage drop causes only a 3% change in amplifier gain and 0.9-bit resolution degrading for SAR ADC while the on-chip data modulation reduces the chip size, rendering the designed chip suitable for battery-powered applications. The fabricated die occupies 1.1 mm2 while consuming 238 μW, being suitable for implantable neural recordings from insects as small as a blowfly for electrophysiological studies of their sensorimotor control mechanisms. The functionality of the die has been validated by recording the signals from identified interneurons in the blowfly visual system

Adaptive encoding of motion information in the fly visual system

Kurtz R. Adaptive encoding of motion information in the fly visual system. In: Barth F, Humphrey J, Srinivasan M, eds. Frontiers in Sensing. 1st ed. Wien New York: Springer; 2012: 115-128