Evaluation of auditory cortex tonotopical organization in rats Through Principal Component Analysis
Ethological communication permits the exchange of context-specific information among mammals. In recent literature, many investigations have been performed on behavioral responses but little is known about neurophysiological pattern activation. In this study we investigated neuron patterns in response to ultrasound vocalizations, mapping the auditory cortex in order to find the specific activation area which best fits with perceived vocalization in rats. Receptive fields were directly reached through implanted electrodes in order to record the ultrasound information into the auditory system, bypassing sense organs. Techniques based on Principal Component Analysis and statistical analysis were used to investigate the tonotopic organization exploiting local field-potential classifications. The results, according to the sensitivity index, identified two tonotopic fields with a gradient from high-to-low best frequency using unsupervised classification algorithm.
We address the problem of effectiveness of the high resolution techniques applied to the conditional model. The rationale is based on a definition of the probability of resolution of maximum likelihood estimators which is computable in the asymptotic region of operation (in SNR and/or in large number of snapshots). The application case is the multiple tones estimation problem (Doppler frequencies estimation in radar).