Neural Modeling and Imaging of the Cortical Interactions Underlying Syllable Production

This paper describes a neural model of speech acquisition and production that accounts for a wide range of acoustic, kinematic, and neuroimaging data concerning the control of speech movements. The model is a neural network whose components correspond to regions of the cerebral cortex and cerebellum, including premotor, motor, auditory, and somatosensory cortical areas. Computer simulations of the model verify its ability to account for compensation to lip and jaw perturbations during speech. Specific anatomical locations of the model's components are estimated, and these estimates are used to simulate fMRI experiments of simple syllable production with and without jaw perturbations.National Institute on Deafness and Other Communication Disorders (R01 DC02852, RO1 DC01925

Representation of Sound Categories in Auditory Cortical Maps

We used functional magnetic resonance imaging (fMRI) to investigate the representation of sound categories in human auditory cortex. Experiment 1 investigated the representation of prototypical and non-prototypical examples of a vowel sound. Listening to prototypical examples of a vowel resulted in less auditory cortical activation than listening to nonprototypical examples. Experiments 2 and 3 investigated the effects of categorization training and discrimination training with novel non-speech sounds on auditory cortical representations. The two training tasks were shown to have opposite effects on the auditory cortical representation of sounds experienced during training: discrimination training led to an increase in the amount of activation caused by the training stimuli, whereas categorization training led to decreased activation. These results indicate that the brain efficiently shifts neural resources away from regions of acoustic space where discrimination between sounds is not behaviorally important (e.g., near the center of a sound category) and toward regions where accurate discrimination is needed. The results also provide a straightforward neural account of learned aspects of categorical perception: sounds from the center of a category are more difficult to discriminate from each other than sounds near category boundaries because they are represented by fewer cells in the auditory cortical areas.National Institute on Deafness and Other Communication Disorders (R01 DC02852

ROI-Based Analysis of Functional Imaging Data

In this technical report, we present fMRI analysis techniques that test functional hypotheses at the region of interest (ROI) level. An SPM-compatible Matlab toolbox has been developed which allows the creation of subject-specific ROI masks based on anatomical markers and the testing of functional hypotheses on the regional response using multivariate time-series analysis techniques. The combined application of subject-specific ROI definition and region-level functional analysis is shown to appropriately compensate for inter-subject anatomical variability, offering finer localization and increased sensitivity to task-related effects than standard techniques based on whole brain normalization and voxel or cluster-level functional analysis, while providing a more direct link between discrete brain region hypotheses and the statistical analyses used to test them.National Institute of Health (R29 DC02852, ROI DC02852

Improvements of Algebraic Attacks Based on Structured Gaussian Elimination

Algebraic attacks are studied as a potential cryptanalytic procedure for various types of ciphers. The XL_SGE algorithm has been recently proposed to improve the complexity of the XL attack. XL_SGE uses structured Gaussian elimination (SGE) during the expansion phase of XL. In this paper, we establish that XL_SGE suffers from some serious drawbacks that impair the effectiveness of SGE-based reduction at all multiplication stages except the first. In order to avoid this problem, we propose several improvements of XL_SGE. Our modifications are based upon partial monomial multiplication and handling of columns of weight two. Our modified algorithms have been experimentally verified to be substantially superior to XL_SGE

An Algebraic Approach to Maliciously Secure Private Set Intersection

Private set intersection is an important area of research and has been the focus of many works over the past decades. It describes the problem of finding an intersection between the input sets of at least two parties without revealing anything about the input sets apart from their intersection. In this paper, we present a new approach to compute the intersection between sets based on a primitive called Oblivious Linear Function Evaluation (OLE). On an abstract level, we use this primitive to efficiently add two polynomials in a randomized way while preserving the roots of the added polynomials. Setting the roots of the input polynomials to be the elements of the input sets, this directly yields an intersection protocol with optimal asymptotic communication complexity $O(m\kappa)$. We highlight that the protocol is information-theoretically secure assuming OLE. We also present a natural generalization of the 2-party protocol for the fully malicious multi-party case. Our protocol does away with expensive (homomorphic) threshold encryption and zero-knowledge proofs. Instead, we use simple combinatorial techniques to ensure the security. As a result we get a UC-secure protocol with asymptotically optimal communication complexity $O((n^2+nm)\kappa)$, where $n$ is the number of parties, $m$ is the set size and $\kappa$ the security parameter. Apart from yielding an asymptotic improvement over previous works, our protocols are also conceptually simple and require only simple field arithmetic. Along the way we develop tools that might be of independent interest

Toxic & Hegemonic Masculinity, Gender Stereotypes & Resonance: The Problematic Snickers’ “Get Some Nuts” Ad

This paper discusses the ethical implications of the Snickers’ ad campaign, “Get Some Nuts”. Through priming, framing, race, gender and sexuality stereotypes, researchers explore cultural resonance and hegemonic ideologies within this ad. In this study, close to 200 students examined separate international ethical standards toward this 30-second commercial starring Mr. T. Student comments collected indicated that implicit racist, sexist and homophobic lenses resonated and caused ethical concerns

Neurophysiological Vocal Source Modeling for Biomarkers of Disease

Speech is potentially a rich source of biomarkers for detecting and monitoring neuropsychological disorders. Current biomarkers typically comprise acoustic descriptors extracted from behavioral measures of source, filter, prosodic and linguistic cues. In contrast, in this paper, we extract vocal features based on a neurocomputational model of speech production, reflecting latent or internal motor control parameters that may be more sensitive to individual variation under neuropsychological disease. These features, which are constrained by neurophysiology, may be resilient to artifacts and provide an articulatory complement to acoustic features. Our features represent a mapping from a low-dimensional acoustics-based feature space to a high-dimensional space that captures the underlying neural process including articulatory commands and auditory and somatosensory feedback errors. In particular, we demonstrate a neurophysiological vocal source model that generates biomarkers of disease by modeling vocal source control. By using the fundamental frequency contour and a biophysical representation of the vocal source, we infer two neuromuscular time series whose coordination provides vocal features that are applied to depression and Parkinson’s disease as examples. These vocal source coordination features alone, on a single held vowel, outperform or are comparable to other features sets and reflect a significant compression of the feature space.United States. Air Force (Contract No. FA8721-05-C-0002)United States. Air Force (Contract No. FA8702-15- D-0001

Simulated Annealing Approach onto VLSI Circuit Partitioning

Decompositions of inter-connected components, to achieve modular independence, poses the major problem in VLSI circuit partitioning. This problem is intractable in nature, Solutions of these problems in computational science is possible through appropriate heuristics. Reduction of the cost that occurs due to interconnectivity between several VLSI components is referred to in this paper. Modification of results derived by classical iterative procedures with probabilistic methods is attempted. Verification has been done on ISCAS-85 benchmark circuits. The proposed design tool shows remarkable improvement results in comparison to the traditional one when applied to the standard benchmark circuits like ISCAS-85