A wavelet-based neural model to optimize and read out a temporal population code - Luvizotto, Andre; Rennó-Costa, César; Verschure, Paul (Frontiers in Computational Neuroscience, 2012)
It has been proposed that the dense excitatory local connectivity of the neo-cortex plays a specific role in the transformation of spatial stimulus information into a temporal representation or a temporal population code (TPC). TPC provides for a rapid, robust and high-capacity encoding of salient stimulus features with respect to position, rotation and distortion. The TPC hypothesis gives a functional interpretation to a core feature of the cortical anatomy: its dense local and sparse long-range connectivity. Thus far, the question of how the TPC encoding can be decoded in downstream areas has not been addressed. Here, we present a neural circuit that decodes the spectral properties of the TPC using a biologically plausible implementation of a Haar transform. We perform a systematic investigation of our model in a recognition task using a standardized stimulus set. We consider alternative implementations using either regular spiking or bursting neurons and a range of spectral bands. Our results show that our wavelet readout circuit provides for robust decoding of the TPC and further compresses the code without loosing speed or quality of decoding. We show that in the TPC signal the relevant stimulus information is present in the frequencies around 100 Hz. Our results show that the TPC is constructed around a small number of coding components that can be well decoded by wavelet coefficients in a neuronal implementation. This solution to the TPC decoding problem suggests that cortical processing streams might well consist of sequential operations where spatio-temporal transformations at lower levels form a compact stimulus encoding using TPC that are are subsequently decoded back to a spatial representation using wavelet transforms. In addition, the results presented here shows that different properties of the stimulus might be transmitted to further processing stages using different frequency component that are captured by appropriately tuned wavelet based decoders.