Speech-Driven Spectrotemporal Receptive Fields Beyond the Auditory Cortex

We recently developed a method to estimate speech-driven spectrotemporal receptive fields (STRFs) using fMRI. The method uses spectrotemporal modulation filtering, a form of acoustic distortion that renders speech sometimes intelligible and sometimes unintelligible. Using this method, we found significant STRF tuning only in classic auditory regions throughout the superior temporal lobes. However, our analysis was not optimized to detect small clusters of tuned STRFs as might be expected in non-auditory regions. Here, we re-analyze our data using a more sensitive multivariate procedure, and we identify STRF tuning in non-auditory regions including the left dorsal premotor cortex (left dPM), left inferior frontal gyrus (LIFG), and bilateral calcarine sulcus (calcS). All three regions responded more to intelligible than unintelligible speech, but left dPM and calcS responded significantly to vocal pitch and demonstrated strong functional connectivity with early auditory regions. However, only left dPM’s STRF predicted activation on trials rated as unintelligible by listeners, a hallmark auditory profile. LIFG, on the other hand, responded almost exclusively to intelligible speech and was functionally connected with classic speech-language regions in the superior temporal sulcus and middle temporal gyrus. LIFG’s STRF was also (weakly) able to predict activation on unintelligible trials, suggesting the presence of a partial ‘acoustic trace’ in the region. We conclude that left dPM is part of the human dorsal laryngeal motor cortex, a region previously shown to be capable of operating in an ‘auditory mode’ to encode vocal pitch. Further, given previous observations that LIFG is involved in syntactic working memory and/or processing of linear order, we conclude that LIFG is part of a higher-order speech circuit that exerts a top-down influence on processing of speech acoustics. Finally, because calcS is modulated by emotion, we speculate that changes in the quality of vocal pitch may have contributed to its response.

Tunable Fano Resonance and Enhanced Sensing in Terahertz Metamaterial

Fano resonances in metamaterial are important due to their low-loss subradiant behavior that allows excitation of high quality (Q) factor resonances extending from the microwave to the optical bands. Fano resonances have recently showed their great potential in the areas of modulation, filtering, and sensing for their extremely narrow linewidths. However, the Fano resonances in a metamaterial system arise from the interaction of all that form the structure, limiting the tunability of the resonances. Besides, sensing trace analytes using Fano resonances are still challenging. In the present work, we demonstrate the excitation of Fano resonances in metamaterial consisting of a period array of two concentric double-split-ring resonators with symmetry breaking (position asymmetry and gaps asymmetry). The tunability and sensing of Fano resonances are both studied in detail. Introducing position asymmetry in the metamaterial leads to one Fano resonance located at 0.50 THz, while introducing gaps asymmetry results in two Fano resonances located at 0.35 THz and 0.50 THz. The transmittance, position, and linewidth of the three Fano resonances can be easily tuned by varying the asymmetry deviations. The Q factor and figure of merit (FoM) of Fano resonances with different asymmetry deviations are calculated for performance optimization. The Fano resonances having the highest FoM are used for the sensing of analytes at different refractive indices, and the Fano resonance performing the best in refractive index sensing is further applied to detect the analyte thickness. The results demonstrate that the tunable Fano resonances show tremendous potential in sensing applications, offering an approach to engineering highly efficient modulators and sensors.

Mechanisms of spectrotemporal modulation detection for normal- and hearing-impaired listeners

Spectrotemporal modulations (STMs) offer a unified framework to probe suprathreshold auditory processing. Here, we introduce a novel methodological framework based on psychophysical reverse-correlation deployed in the modulation space to characterize how STMs are detected by the auditory system and how cochlear hearing loss impacts this processing. Our results show that young normal-hearing (NH) and older hearing-impaired (HI) individuals rely on a comparable non-linear processing architecture involving non-directional band-pass modulation filtering. We demonstrate that a temporal-modulation filter-bank model can capture the strategy of the NH group and that a broader tuning of cochlear filters is sufficient to explain the overall shift toward temporal modulations of the HI group. Yet, idiosyncratic behaviors exposed within each group highlight the contribution and the need to consider additional mechanisms. This integrated experimental-computational approach offers a principled way to assess supra-threshold auditory processing distortions of each individual.

Sub-Nyquist SAR via Quadrature Compressive Sampling with Independent Measurements

This paper presents an efficient sampling system for the acquisition of synthetic aperture radar (SAR) data at sub-Nyquist rate. The system adopts a quadrature compressive sampling architecture, which uses modulation, filtering, sampling and digital quadrature demodulation to produce sub-Nyquist or compressive measurements. In the sequential transmit-receive procedure of SAR, the analog echoes are modulated by random binary chipping sequences to inject randomness into the measurement projection, and the chipping sequences are independent from one observation to another. As a result, the system generates a sequence of independent structured measurement matrices, and then the resulting sensing matrix has better restricted isometry property, as proved by theoretical analysis. As a standard recovery problem in compressive sensing, image formation from the sub-Nyquist measurements has significantly improved performance, which in turn promotes low sampling/data rate. Moreover, the resulting sensing matrix has structures suitable for fast matrix-vector products, based on which we provide a first-order fast image formation algorithm. The performance of the proposed sampling system is assessed by synthetic and real data sets. Simulation results suggest that the proposed system is a valid candidate for sub-Nyquist SAR.