Abstract
We exemplify an interdisciplinary approach wherein a mesoscopic-scale functional model of a biological system is derived from time-series recordings, yielding transfer functions that can be used to design analog electronic circuits. Namely, sensory processing in the honey bee, a universal model for studying olfaction, is considered. Existing studies have focused on its antennal lobe, wherein only the responses of its functional units, known as glomeruli, have been accessible. Here, high temporal resolution calcium imaging is deployed to track the dynamics of odor-evoked activity beyond this processing stage. The responses in the somata outside of the antennal lobe are recorded, showing for the first time how the glomerular signals are transformed before entering the higher brain centers. A transfer function approach is applied to capture as a “gray box model” the remarkably heterogeneous signal transformations between odor input and glomerular response, and between glomerular signals and somata activity. The somata are tentatively mapped to the glomeruli via Granger causality, while machine learning classification and clustering allow grouping common properties regarding response amplitudes and temporal profiles. The obtained low-order transfer functions display time- and frequency-domain input-output properties closely similar to the biological system. Because transfer functions have universal applicability, once they have been determined, it is readily possible to design corresponding analog electronic circuits, with possible future applications in sensor signal conditioning. To exemplify this, examples based on resistor-capacitor (RC) networks and operational amplifiers are physically built and confirmed to generate responses highly correlated to the initial biological recordings.
Highlights
INDEX TERMS Analog filters, Calcium imaging, Circuit design, Honey bee, Neuroscience, Olfaction, Systems biology, Systems engineering, Transfer functions. This proof-of-concept work aims to introduce and exemplify an analysis and design approach based on extracting mesoscopic-scale calcium imaging time series from neurophysiological experiments and deriving transfer functions from them. These allow designing physicallyrealizable analog electronic circuits mimicking the responses of neural ensembles, focusing on the paradigmatic case of olfaction
Visual inspection of the grand-average traces for the automatically-classified responses confirmed a well-evident difference between activation, inhibition, and absence of a response, for both the glomeruli (Fig. 5b) and the somata (Fig. 5c), which was overall in line with previous observations
TRANSFER FUNCTIONS AS A "GRAY BOX" MODEL This study was predicated on the ability to simultaneously record the neural responses during olfactory stimulation in the glomeruli and somata using two-photon calcium imaging
Summary
This proof-of-concept work aims to introduce and exemplify an analysis and design approach based on extracting mesoscopic-scale calcium imaging time series from neurophysiological experiments and deriving transfer functions from them. These allow designing physicallyrealizable analog electronic circuits mimicking the responses of neural ensembles, focusing on the paradigmatic case of olfaction. Olfaction is a neurobiological process involving a complex sequence of signal transformations, starting from plumes of molecules in the environment having a spatiotemporally varying concentration These are chemically sensed and undergo multiple representations, eventually leading to odor recognition and informing an organism’s decision-making.
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