OBJECTIVE:During transcranial electrical stimulation, current passage across the scalp generates voltage across the scalp surface. The goal was to characterize these scalp voltages for the purpose of validating subject-specific finite element method (FEM) models of current flow.APPROACH:Using a recording electrode array, we mapped skin voltages resulting from low-intensity transcranial electrical stimulation. These voltage recordings were used to compare the predictions obtained from the high-resolution model based on the subject undergoing transcranial stimulation.MAIN RESULTS:Each of the four stimulation electrode configurations tested resulted in a distinct distribution of scalp voltages; these spatial maps were linear with applied current amplitude (0.1 to 1 mA) over low frequencies (1 to 10 Hz). The FEM model accurately predicted the distinct voltage distributions and correlated the induced scalp voltages with current flow through cortex.SIGNIFICANCE:Our results provide the first direct model validation for these subject-specific modeling approaches. In addition, the monitoring of scalp voltages may be used to verify electrode placement to increase transcranial electrical stimulation safety and reproducibility.

The presence of tinnitus often coincides with hearing loss. It has been argued that reduced peripheral input leads to frequency-specific increase in neuronal gains resulting in tinnitus-related hyper-activity. Following this gain-adaptation hypothesis, impaired cochlear function should be predictive of the presence and spectral characteristics of tinnitus. To assess cochlear function, perceptual thresholds and distortion product otoacoustic emissions (DPOAEs) were measured with high frequency resolution for subjects with tinnitus and non-tinnitus control subjects (N = 29 and N = 18) with and without hearing loss. Subjects with tinnitus also provided a 'tinnitus likeness spectrum' by rating the similarity of their tinnitus to tones at various frequencies. On average, subjects with tinnitus had elevated thresholds, reduced DPOAE, and increased slope of the DPOAE input-output function in the range from 4 to 10 kHz. These measures were strongly correlated and were equally predictive of the presence of tinnitus. Subjects with a pronounced edge to their hearing loss profile were very likely to have tinnitus. In the group average, the tinnitus likeness spectrum was correlated with perceptual thresholds (r = 0.98, p < 0.01), confirming previous reports. For 19 of 29 of subjects, perceptual thresholds were correlated with the tinnitus likeness ratings across frequencies and this correlation was significantly improved when low input-level DPOAE were included as an additional variable (r = 0.83 ± 0.09, N = 19). Thus, cochlear function is strongly associated with the tinnitus percept and measures of cochlear function using DPOAEs provide additional diagnostic information over perceptual thresholds alone.

Neuronal gain adaptation has been proposed as the underlying mechanism leading to the perception of phantom sounds such as Zwicker tones and tinnitus. In this gain-adaptation theory, cochlear compression plays a significant role with weaker compression leading to stronger phantom percepts. The specific aim of this study was to find a link between the strength of neuronal gain adaptation and cochlear compression. Compression was assessed using distortion product otoacoustic emissions (DPOAEs). Gain adaptation is hypothesized to manifest itself in the sensitization observed for the detection of masked tones when preceded by notched noise. Perceptual thresholds for pure tones in notched noise were measured at multiple frequencies following various priming signals. The observed sensitization was larger than expected from the combined effect of the various maskers. However, there was no link between sensitization and compression. Instead, across subjects, stronger sensitization correlated with stronger DPOAEs evoked by low-level primaries. In addition, growth of DPOAEs correlated reliably with perceptual thresholds across frequencies within subjects. Together, the data suggest that short-term dynamic adaptation leading to perceptual sensitization is the result of an active process mediated by the outer hair cells, which are thought to modulate the gain of the cochlear amplifier via efferent feedback.

Watching a speaker's facial movements can dramatically enhance our ability to comprehend words, especially in noisy environments. From a general doctrine of combining information from different sensory modalities (the principle of inverse effectiveness), one would expect that the visual signals would be most effective at the highest levels of auditory noise. In contrast, we find, in accord with a recent paper, that visual information improves performance more at intermediate levels of auditory noise than at the highest levels, and we show that a novel visual stimulus containing only temporal information does the same. We present a Bayesian model of optimal cue integration that can explain these conflicts. In this model, words are regarded as points in a multidimensional space and word recognition is a probabilistic inference process. When the dimensionality of the feature space is low, the Bayesian model predicts inverse effectiveness; when the dimensionality is high, the enhancement is maximal at intermediate auditory noise levels. When the auditory and visual stimuli differ slightly in high noise, the model makes a counterintuitive prediction: as sound quality increases, the proportion of reported words corresponding to the visual stimulus should first increase and then decrease. We confirm this prediction in a behavioral experiment. We conclude that auditory-visual speech perception obeys the same notion of optimality previously observed only for simple multisensory stimuli.

In the AV* condition, we intended to decrease the amount of information provided by the visual stimulus while preserving as much as possible the appearance of the talking face (see Figure S1). A natural appearance of the visual stimulus has been found to be important for effective AV fusion of speech (Schwartz JL et al., 2004). To this end, we used an “Active Appearance Model” (AAM) – a computer program that can generate images of faces when provided with a set of landmark points indicating locations and shape of the lips, eyes, brows, and an outline of the face (Cootes TF et al., 2001). For a

In this paper, a semifragile watermarking scheme for image authentication is proposed, which addresses the issue of protecting images from illegal manipulations and modifications. The scheme extracts a signature (watermark) from the original image and inserts this signature back into the image, avoiding additional signature files. The error correction coding (ECC) is used to encode the signatures that are extracted from the image. To increase the security of this scheme, user's private key is employed for encryption and decryption of the watermark during watermark extraction and insertion procedures. Experimental result shows that if there is no change in the obtained image, the watermark will be correctly extracted, thus will pass through the authentication system. This scheme is tolerant of lossy compression such as JPEG, but malicious changes of the image will result in the breach of the watermark detection. In addition, this scheme can detect the exact locations, which are illegal modified blocks.