Relationships between human auditory cortical structure and function

The human auditory cortex comprises multiple areas, largely distributed across the supratemporal plane, but the precise number and configuration of auditory areas and their functional significance have not yet been clearly established. In this paper, we discuss recent research concerning architectonic and functional organisation within the human auditory cortex, as well as architectonic and neurophysiological studies in non-human species, which can provide a broad conceptual framework for interpreting functional specialisation in humans. We review the pattern in human auditory cortex of the functional responses to various acoustic cues, such as frequency, pitch, sound level, temporal variation, motion and spatial location, and we discuss their correspondence to what is known about the organisation of the auditory cortex in other primates. There is some neuroimaging evidence of multiple tonotopically organised fields in humans and of functional specialisations of the fields in the processing of different sound features. It is thought that the primary area, on Heschl's gyrus, may have a larger involvement in processing basic sound features, such as frequency and level, and that posterior non-primary areas on the planum temporale may play a larger role in processing more spectrotemporally complex sounds. Ways in which current knowledge of auditory cortical organisation and different data analysis approaches may benefit future functional neuroimaging studies which seek to link auditory cortical structure and function are discussed

Spectral and temporal processing in human auditory cortex

Hierarchical processing suggests that spectrally and temporally complex stimuli will evoke more activation than do simple stimuli, particularly in non-primary auditory fields. This hypothesis was tested using two tones, a single frequency tone and a harmonic tone, that were either static or frequency modulated to create four stimuli. We interpret the location of differences in activation by drawing comparisons between fMRI and human cytoarchitectonic data, reported in the same brain space. Harmonic tones produced more activation than single tones in right Heschl's gyrus (HG) and bilaterally in the lateral supratemporal plane (STP). Activation was also greater to frequency-modulated tones than to static tones in these areas, plus in left HG and bilaterally in an anterolateral part of the STP and the superior temporal sulcus. An elevated response magnitude to both frequency-modulated tones was found in the lateral portion of the primary area, and putatively in three surrounding non-primary regions on the lateral STP (one anterior and two posterior to HG). A focal site on the posterolateral STP showed an especially high response to the frequency-modulated harmonic tone. Our data highlight the involvement of both primary and lateral non-primary auditory regions

On Machine-Learned Classification of Variable Stars with Sparse and Noisy Time-Series Data

With the coming data deluge from synoptic surveys, there is a growing need for frameworks that can quickly and automatically produce calibrated classification probabilities for newly-observed variables based on a small number of time-series measurements. In this paper, we introduce a methodology for variable-star classification, drawing from modern machine-learning techniques. We describe how to homogenize the information gleaned from light curves by selection and computation of real-numbered metrics ("feature"), detail methods to robustly estimate periodic light-curve features, introduce tree-ensemble methods for accurate variable star classification, and show how to rigorously evaluate the classification results using cross validation. On a 25-class data set of 1542 well-studied variable stars, we achieve a 22.8% overall classification error using the random forest classifier; this represents a 24% improvement over the best previous classifier on these data. This methodology is effective for identifying samples of specific science classes: for pulsational variables used in Milky Way tomography we obtain a discovery efficiency of 98.2% and for eclipsing systems we find an efficiency of 99.1%, both at 95% purity. We show that the random forest (RF) classifier is superior to other machine-learned methods in terms of accuracy, speed, and relative immunity to features with no useful class information; the RF classifier can also be used to estimate the importance of each feature in classification. Additionally, we present the first astronomical use of hierarchical classification methods to incorporate a known class taxonomy in the classifier, which further reduces the catastrophic error rate to 7.8%. Excluding low-amplitude sources, our overall error rate improves to 14%, with a catastrophic error rate of 3.5%.Comment: 23 pages, 9 figure

A comparative study of the physiological properties of the inner ear in Doppler shift compensating bats (Rhinolophus rouxi and Pteronotus parnellit)

Cochlear microphonic (CM) and evoked neural (N-1) potentials were studied in two species of Doppler shift compensating bats with the aid of electrodes chronically implanted in the scala tympani. Potentials were recorded from animals fully recovered from the effects of anesthesia and surgery. InPteronotus p. parnellii andRhinolophus rouxi the CM amplitude showed a narrow band, high amplitude peak at a frequency about 200 Hz above the resting frequency of each species. InPteronotus the peak was 25–35 dB higher in amplitude than the general CM level below or above the frequency of the amplitude peak. InRhinolophus the amplitude peak was only a few dB above the general CM level but it was prominent because of a sharp null in a narrow band of frequencies just below the peak. The amplitude peak and the null were markedly affected by body temperature and anesthesia. InPteronotus high amplitude CM potentials were produced by resonance, and stimulated cochlear emissions were prominent inPteronotus but they were not observed inRhinolophus. InPteronotus the resonance was indicated by a CM afterpotential that occurred after brief tone pulses. The resonance was not affected by the addition of a terminal FM to the stimulus and when the ear was stimulated with broadband noise it resulted in a continual state of resonance. Rapid, 180 degree phase shifts in the CM were observed when the stimulus frequency swept through the frequency of the CM amplitude peak inPteronotus and the frequency of the CM null inRhinolophus. These data indicate marked differences in the physiological properties of the cochlea and in the mechanisms responsible for sharp tuning in these two species of bats

Analyse des signaux AM-FM basée sur une version B-splines de l'EMD-ESA

In this paper a signal analysis framework for estimating time-varying amplitude and frequency functions of multicomponent amplitude and frequency modulated (AM–FM) signals is introduced. This framework is based on local and non-linear approaches, namely Energy Separation Algorithm (ESA) and Empirical Mode Decomposition (EMD). Conjunction of Discrete ESA (DESA) and EMD is called EMD–DESA. A new modified version of EMD where smoothing instead of an interpolation to construct the upper and lower envelopes of the signal is introduced. Since extracted IMFs are represented in terms of B-spline (BS) expansions, a closed formula of ESA robust against noise is used. Instantaneous Frequency (IF) and Instantaneous Amplitude (IA) estimates of a multi- component AM–FM signal, corrupted with additive white Gaussian noise of varying SNRs, are analyzed and results compared to ESA, DESA and Hilbert transform-based algorithms. SNR and MSE are used as figures of merit. Regularized BS version of EMD– ESA performs reasonably better in separating IA and IF components compared to the other methods from low to high SNR. Overall, obtained results illustrate the effective- ness of the proposed approach in terms of accuracy and robustness against noise to track IF and IA features of a multicomponent AM–FM signal

Disproportionate Frequency Representation in the Inferior Colliculus of Doppler-Compensating Greater Horseshoe Bats. Evidence for an Acoustic Fovea

1. The inferior colliculus of 8 Greater Horseshoe bats (Rhinolophus ferrumequinun) was systematically sampled with electrode penetrations covering the entire volume of the nucleus. The best frequencies and intensity thresholds for pure tones (Fig. 2) were determined for 591 neurons. The locations of the electrode penetrations within the inferior colliculus were histologically verified. 2. About 50% of all neurons encountered had best frequencies (BF) in the frequency range between 78 and 88 kHz (Table 1, Fig. 1A). Within this frequency range the BFs between 83.0 and 84.5 kHz were overrepresented with 16.3% of the total population of neurons (Fig. 1B). The frequencies of the constant frequency components of the echoes fall into this frequency range. 3. The representation of BFs expressed as number of neurons per octave shows a striking correspondence to the nonuniform innervation density in the afferent innervation of the basilar membrane (Bruns and Schmieszek, in press). The high innervation density of the basilar membrane in the frequency band between 83 and 84.5 kHz coincides with the maximum of the distribution of number of neurons per octave across frequency in the inferior colliculus (Fig. 1 C). 4. The disproportionate representation of frequencies in the auditory system of the greater horseshoe bat is described as an acoustical fovea functioning in analogy to the fovea in the visual system. The functional importance of the Doppler-shift compensation for such a foveal mechanism in the auditory system of horseshoe bats is related to that of tracking eye movements in the visual system

Natural ultrasonic echoes from wing beating insects are encoded by collicular neurons in the CF-FM bat, Rhinolophus f errumequinum

1. Acoustic reflections from a wing beating moth to an 80 kHz ultrasonic signal were recorded from six different incident angles and analyzed in spectral and time domains. The recorded echoes as well as independent components of amplitude and frequency modulations of the echoes were employed as acoustic stimuli during single unit studies. 2. The responses of single inferior colliculus neurons to these stimuli were recorded from four horseshoe bats,Rhinolophus ferrumequinum, a species which uses a long constant frequency (CF) sound with a final frequency modulated (FM) sweep during echolocation. All neurons responding to wing beat echoes reliably encoded the fundamental wing beat frequency as well as the more refined frequency and amplitude modulations. 3. These neurons may provide the bat a neural mechanism to detect periodically moving targets against a cluttered background and also to discriminate various insect species on the basis of their wing beat patterns

Field-Induced Magnetization Steps in Intermetallic Compounds and Manganese Oxides: The Martensitic Scenario

Field-induced magnetization jumps with similar characteristics are observed at low temperature for the intermetallic germanide Gd5Ge4and the mixed-valent manganite Pr0.6Ca0.4Mn0.96Ga0.04O3. We report that the field location -and even the existence- of these jumps depends critically on the magnetic field sweep rate used to record the data. It is proposed that, for both compounds, the martensitic character of their antiferromagnetic-to-ferromagnetic transitions is at the origin of the magnetization steps.Comment: 4 pages,4 figure