Tonotopic-column-dependent variability of neural encoding in the auditory cortex of rats.

Neural computation could benefit from the heterogeneity of neurons to achieve energy efficiency. Beyond a single neuron level, adaptation to biologically important signals should also make functional columns heterogeneous. In the present study, we test a hypothesis that variability of neural response depends on tonotopic columns in the primary auditory cortex (A1) of rats. Mutual information (MI) was estimated from multi-unit responses in A1 of anesthetized rats, to quantify how spike count (SC) and the first spike latency (FSL) carried information about frequency and intensity of test tones. Consequently, for both SC and FSL, we found best frequency (BF)-dependent MI distributions with wide variances in high BF regions. These MI distributions were caused by BF-dependence of the amount of information that neurons conveyed, i.e., total entropy, rather than the transmission efficiency. In addition, the relationship between the transmission efficiency and the total entropy differentiated SC encoding and FSL encoding, suggesting that SC encoding and FSL encoding are not redundant but each plays a different role in intensity encoding. These results provide compelling evidence that BF columns are heterogeneous. Such heterogeneity of columns may make the global computation in A1 more efficient. Thus, the efficient coding in the neural system could be achieved by multiple-scale heterogeneity.