Neural Resolution of Formant Frequencies in the Primary Auditory Cortex of Rats

Neural properties of fundamental function encoding of sound selectivity in the female avian auditory cortex

Zebra finches (Taeniopygia guttata) use their voices for communication. Song structures in the songs of individual males are important for sound recognition in females. The caudomedial mesopallium (CMM) and nidopallium (NCM) are known to be essential higher auditory regions for sound recognition. These two regions have also been discussed with respect to their fundamental functions and song selectivity. To clarify their functions and selectivity, we investigated latencies and spiking patterns and also developed a novel correlation analysis to evaluate the relationship between neural activity and the characteristics of acoustic factors. We found that the latencies and spiking patterns in response to song stimuli differed between the CMM and NCM. In addition, our correlation analysis revealed that amplitude and frequency structures were important temporal acoustic factors for both regions. Although the CMM and NCM have different fundamental functions, they share similar encoding systems for acoustic factors.

Neural representation of vowel formants in tonotopic auditory cortex

Speech sounds are encoded by distributed patterns of activity in bilateral superior temporal cortex. However, it is unclear whether speech sounds are topographically represented in cortex, or which acoustic or phonetic dimensions might be spatially mapped. Here, using functional MRI, we investigated the potential spatial representation of vowels, which are largely distinguished from one another by the frequencies of their first and second formants, i.e. peaks in their frequency spectra. This allowed us to generate clear hypotheses about the representation of specific vowels in tonotopic regions of auditory cortex. We scanned participants as they listened to multiple natural tokens of the vowels [ɑ] and [i], which we selected because their first and second formants overlap minimally. Formant-based regions of interest were defined for each vowel based on spectral analysis of the vowel stimuli and independently acquired tonotopic maps for each participant. We found that perception of [ɑ] and [i] yielded differential activation of tonotopic regions corresponding to formants of [ɑ] and [i], such that each vowel was associated with increased signal in tonotopic regions corresponding to its own formants. This pattern was observed in Heschl's gyrus and the superior temporal gyrus, in both hemispheres, and for both the first and second formants. Using linear discriminant analysis of mean signal change in formant-based regions of interest, the identity of untrained vowels was predicted with ∼73% accuracy. Our findings show that cortical encoding of vowels is scaffolded on tonotopy, a fundamental organizing principle of auditory cortex that is not language-specific.

Cluster-based analysis improves predictive validity of spike-triggered receptive field estimates

Spectrotemporal receptive field (STRF) characterization is a central goal of auditory physiology. STRFs are often approximated by the spike-triggered average (STA), which reflects the average stimulus preceding a spike. In many cases, the raw STA is subjected to a threshold defined by gain values expected by chance. However, such correction methods have not been universally adopted, and the consequences of specific gain-thresholding approaches have not been investigated systematically. Here, we evaluate two classes of statistical correction techniques, using the resulting STRF estimates to predict responses to a novel validation stimulus. The first, more traditional technique eliminated STRF pixels (time-frequency bins) with gain values expected by chance. This correction method yielded significant increases in prediction accuracy, including when the threshold setting was optimized for each unit. The second technique was a two-step thresholding procedure wherein clusters of contiguous pixels surviving an initial gain threshold were then subjected to a cluster mass threshold based on summed pixel values. This approach significantly improved upon even the best gain-thresholding techniques. Additional analyses suggested that allowing threshold settings to vary independently for excitatory and inhibitory subfields of the STRF resulted in only marginal additional gains, at best. In summary, augmenting reverse correlation techniques with principled statistical correction choices increased prediction accuracy by over 80% for multi-unit STRFs and by over 40% for single-unit STRFs, furthering the interpretational relevance of the recovered spectrotemporal filters for auditory systems analysis.

Midbrain Synchrony to Envelope Structure Supports Behavioral Sensitivity to Single-Formant Vowel-Like Sounds in Noise

Vowels make a strong contribution to speech perception under natural conditions. Vowels are encoded in the auditory nerve primarily through neural synchrony to temporal fine structure and to envelope fluctuations rather than through average discharge rate. Neural synchrony is thought to contribute less to vowel coding in central auditory nuclei, consistent with more limited synchronization to fine structure and the emergence of average-rate coding of envelope fluctuations. However, this hypothesis is largely unexplored, especially in background noise. The present study examined coding mechanisms at the level of the midbrain that support behavioral sensitivity to simple vowel-like sounds using neurophysiological recordings and matched behavioral experiments in the budgerigar. Stimuli were harmonic tone complexes with energy concentrated at one spectral peak, or formant frequency, presented in quiet and in noise. Behavioral thresholds for formant-frequency discrimination decreased with increasing amplitude of stimulus envelope fluctuations, increased in noise, and were similar between budgerigars and humans. Multiunit recordings in awake birds showed that the midbrain encodes vowel-like sounds both through response synchrony to envelope structure and through average rate. Whereas neural discrimination thresholds based on either coding scheme were sufficient to support behavioral thresholds in quiet, only synchrony-based neural thresholds could account for behavioral thresholds in background noise. These results reveal an incomplete transformation to average-rate coding of vowel-like sounds in the midbrain. Model simulations suggest that this transformation emerges due to modulation tuning, which is shared between birds and mammals. Furthermore, the results underscore the behavioral relevance of envelope synchrony in the midbrain for detection of small differences in vowel formant frequency under real-world listening conditions.