Spectral envelope is the shape of the power spectrum of sound. It is an important cue for the identification of sound sources such as voices or instruments, and particular classes of sounds such as vowels. In everyday life, sounds with similar spectral envelopes are perceived as similar: we recognize a voice or a vowel regardless of pitch and intensity variations, and we recognize the same vowel regardless of whether it is voiced (a spectral envelope applied to a harmonic series) or whispered (a spectral envelope applied to noise). In this functional magnetic resonance imaging (fMRI) experiment, we investigated the basis for analysis of spectral envelope by the human brain. Changing either the pitch or the spectral envelope of harmonic sounds produced similar activation within a bilateral network including Heschl's gyrus and adjacent cortical areas in the superior temporal lobe. Changing the spectral envelope of continuously alternating noise and harmonic sounds produced additional right-lateralized activation in superior temporal sulcus (STS). Our findings show that spectral shape is abstracted in superior temporal sulcus, suggesting that this region may have a generic role in the spectral analysis of sounds. These distinct levels of spectral analysis may represent early computational stages in a putative anteriorly directed stream for the categorization of sound.
Department of Interdisciplinary Courses in Engineering, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India.
Two two-element slotted patch multiple-input multiple-output (MIMO) antenna with coplanar waveguide (CPW) feed is proposed for deployment in implantable medical devices. Implantable devices are compact and demand high-gain antennae with unidirectional radiation patterns. Regarding compactness, the antenna has a size of 16 × 6×0.
Analysis of heart sound signals plays an essential role in preventing and diagnosing cardiac diseases. This study proposes a multi-level feature encoding algorithm based on frequency-balanced power spectral intensity for heart sound signal classification. Firstly, a wavelet threshold function is employed to denoise the heart sound signals.
Understanding speech in noisy settings is harder for hearing-impaired (HI) people than for normal-hearing (NH) people, even when speech is audible. This is often attributed to hearing loss altering the neural encoding of temporal and/or spectral speech cues. Here, we investigated whether this difference may also be due to an impaired ability to adapt to background noise.
Background: CT1812 is a first-in-class, sigma-2 receptor ligand, that prevents and displaces binding of amyloid beta (Aβ) oligomers. Normalization of quantitative electroencephalography (qEEG) markers suggests that CT1812 protects synapses from Aβ oligomer toxicity.
Objectives: Evaluate CT1812 impact on synaptic function using qEEG measurements.
Current tests of hearing fail to diagnose pathologies in ~10% of patients seeking help for hearing difficulties. Neural ensemble responses to perceptually relevant cues in the amplitude envelope, termed envelope following responses (EFR), hold promise as an objective diagnostic tool to probe these 'hidden' hearing difficulties. But clinical translation is impeded by current measurement approaches involving static amplitude modulated (AM) tones, which are time-consuming and lack optimal spectrotemporal resolution.
