Scather: programming with multi-party computation and MapReduce

We present a prototype of a distributed computational infrastructure, an associated high level programming language, and an underlying formal framework that allow multiple parties to leverage their own cloud-based computational resources (capable of supporting MapReduce [27] operations) in concert with multi-party computation (MPC) to execute statistical analysis algorithms that have privacy-preserving properties. Our architecture allows a data analyst unfamiliar with MPC to: (1) author an analysis algorithm that is agnostic with regard to data privacy policies, (2) to use an automated process to derive algorithm implementation variants that have different privacy and performance properties, and (3) to compile those implementation variants so that they can be deployed on an infrastructures that allows computations to take place locally within each participant’s MapReduce cluster as well as across all the participants’ clusters using an MPC protocol. We describe implementation details of the architecture, discuss and demonstrate how the formal framework enables the exploration of tradeoffs between the efficiency and privacy properties of an analysis algorithm, and present two example applications that illustrate how such an infrastructure can be utilized in practice.This work was supported in part by NSF Grants: #1430145, #1414119, #1347522, and #1012798

Relating alpha power modulations to competing visuospatial attention theories

Visuospatial attention theories often propose hemispheric asymmetries underlying the control of attention. In general support of these theories, previous EEG/MEG studies have shown that spatial attention is associated with hemispheric modulation of posterior alpha power (gating by inhibition). However, since measures of alpha power are typically expressed as lateralization scores, or collapsed across left and right attention shifts, the individual hemispheric contribution to the attentional control mechanism remains unclear. This is, however, the most crucial and decisive aspect in which the currently competing attention theories continue to disagree. To resolve this long-standing conflict, we derived predictions regarding alpha power modulations from Heilman's hemispatial theory and Kinsbourne's interhemispheric competition theory and tested them empirically in an EEG experiment. We used an attention paradigm capable of isolating alpha power modulation in two attentional states, namely attentional bias in a neutral cue condition and spatial orienting following directional cues. Differential alpha modulations were found for both hemispheres across conditions. When anticipating peripheral visual targets without preceding directional cues (neutral condition), posterior alpha power in the left hemisphere was generally lower and more strongly modulated than in the right hemisphere, in line with the interhemispheric competition theory. Intriguingly, however, while alpha power in the right hemisphere was modulated by both, cue-directed leftward and rightward attention shifts, the left hemisphere only showed modulations by rightward shifts of spatial attention, in line with the hemispatial theory. This suggests that the two theories may not be mutually exclusive, but rather apply to different attentional states

Guided Stereo Matching

Stereo is a prominent technique to infer dense depth maps from images, and deep learning further pushed forward the state-of-the-art, making end-to-end architectures unrivaled when enough data is available for training. However, deep networks suffer from significant drops in accuracy when dealing with new environments. Therefore, in this paper, we introduce Guided Stereo Matching, a novel paradigm leveraging a small amount of sparse, yet reliable depth measurements retrieved from an external source enabling to ameliorate this weakness. The additional sparse cues required by our method can be obtained with any strategy (e.g., a LiDAR) and used to enhance features linked to corresponding disparity hypotheses. Our formulation is general and fully differentiable, thus enabling to exploit the additional sparse inputs in pre-trained deep stereo networks as well as for training a new instance from scratch. Extensive experiments on three standard datasets and two state-of-the-art deep architectures show that even with a small set of sparse input cues, i) the proposed paradigm enables significant improvements to pre-trained networks. Moreover, ii) training from scratch notably increases accuracy and robustness to domain shifts. Finally, iii) it is suited and effective even with traditional stereo algorithms such as SGM.Comment: CVPR 201

Adjustment of interaural-time-difference analysis to sound level

To localize low-frequency sound sources in azimuth, the binaural system compares the timing of sound waves at the two ears with microsecond precision. A similarly high precision is also seen in the binaural processing of the envelopes of high-frequency complex sounds. Both for low- and high-frequency sounds, interaural time difference (ITD) acuity is to a large extent independent of sound level. The mechanisms underlying this level-invariant extraction of ITDs by the binaural system are, however, only poorly understood. We use high-frequency pip trains with asymmetric and dichotic pip envelopes in a combined psychophysical, electrophysiological, and modeling approach. Although the dichotic envelopes cannot be physically matched in terms of ITD, the match produced perceptually by humans is very reliable, and it depends systematically on the overall sound level. These data are reflected in neural responses from the gerbil lateral superior olive and lateral lemniscus. The results are predicted in an existing temporal-integration model extended with a level-dependent threshold criterion. These data provide a very sensitive quantification of how the peripheral temporal code is conditioned for binaural analysis

Determination and evaluation of clinically efficient stopping criteria for the multiple auditory steady-state response technique

Background: Although the auditory steady-state response (ASSR) technique utilizes objective statistical detection algorithms to estimate behavioural hearing thresholds, the audiologist still has to decide when to terminate ASSR recordings introducing once more a certain degree of subjectivity. Aims: The present study aimed at establishing clinically efficient stopping criteria for a multiple 80-Hz ASSR system. Methods: In Experiment 1, data of 31 normal hearing subjects were analyzed off-line to propose stopping rules. Consequently, ASSR recordings will be stopped when (1) all 8 responses reach significance and significance can be maintained for 8 consecutive sweeps; (2) the mean noise levels were ≤ 4 nV (if at this “≤ 4-nV” criterion, p-values were between 0.05 and 0.1, measurements were extended only once by 8 sweeps); and (3) a maximum amount of 48 sweeps was attained. In Experiment 2, these stopping criteria were applied on 10 normal hearing and 10 hearing-impaired adults to asses the efficiency. Results: The application of these stopping rules resulted in ASSR threshold values that were comparable to other multiple-ASSR research with normal hearing and hearing-impaired adults. Furthermore, in 80% of the cases, ASSR thresholds could be obtained within a time-frame of 1 hour. Investigating the significant response-amplitudes of the hearing-impaired adults through cumulative curves indicated that probably a higher noise-stop criterion than “≤ 4 nV” can be used. Conclusions: The proposed stopping rules can be used in adults to determine accurate ASSR thresholds within an acceptable time-frame of about 1 hour. However, additional research with infants and adults with varying degrees and configurations of hearing loss is needed to optimize these criteria

The Dialectics of Parenting: Changes in the Interplay of Maternal Behaviors during Early and Middle Childhood

Parent and child relationships continuously evolve, part of an ongoing dialectic that derives from developmental changes in both parent and child. The focus of this study is on changes in the strength of association among four types of parenting behaviors considered important for children’s development: supportive presence, respect for autonomy, stimulation, and hostility. Mother–child interaction was observed for 1229 parent–child dyads at 36 months, 54 months, 1st grade, 3rd grade, and 5th grade using similar observational paradigms. The association between respect for autonomy and supportive presence was strong at age three and continued to be strong over time. The association between respect for autonomy and stimulation was modest but also showed little change from age three to 5th grade. Respect for autonomy was negatively associated with maternal hostility, but the relation was complex. It was stronger at 54 months than 36 months but then became weaker through time. Supportive presence showed a moderate relation with stimulation at age 3 but the association became weaker over time. Supportive presence showed an expected negative association with hostility, a relation that changed little over time. The relation between hostility and stimulation also became weaker over time. In effect, there appears to be a shifting pattern of relations between maternal behaviors during early and middle childhood, one that reflects an evolving dialectic in the mother–child relationship

Connectivity reflects coding: A model of voltage-based spike-timing-dependent-plasticity with homeostasis

Electrophysiological connectivity patterns in cortex often show a few strong connections in a sea of weak connections. In some brain areas a large fraction of strong connections are bidirectional, in others they are mainly unidirectional. In order to explain these connectivity patterns, we use a model of Spike-Timing-Dependent Plasticity where synaptic changes depend on presynaptic spike arrival and the postsynaptic membrane potential. The model describes several nonlinear effects in STDP experiments, as well as the voltage dependence of plasticity under voltage clamp and classical paradigms of LTP/LTD induction. We show that in a simulated recurrent network of spiking neurons our plasticity rule leads not only to receptive field development, but also to connectivity patterns that reflect the neural code: for temporal coding paradigms strong connections are predominantly unidirectional, whereas they are bidirectional under rate coding. Thus variable connectivity patterns in the brain could reflect different coding principles across brain areas

A Novel Reinforcement-Based Paradigm for Children to Teach the Humanoid Kaspar Robot

© The Author(s) 2019. This is the final published version of an article published in Psychological Research, licensed under a Creative Commons Attri-bution 4.0 International License. Available online at: https://doi.org/10.1007/s12369-019-00607-xThis paper presents a contribution to the active field of robotics research with the aim of supporting the development of social and collaborative skills of children with Autism Spectrum Disorders (ASD). We present a novel experiment where the classical roles are reversed: in this scenario the children are the teachers providing positive or negative reinforcement to the Kaspar robot in order for the robot to learn arbitrary associations between different toy names and the locations where they are positioned. The objective of this work is to develop games which help children with ASD develop collaborative skills and also provide them tangible example to understand that sometimes learning requires several repetitions. To facilitate this game we developed a reinforcement learning algorithm enabling Kaspar to verbally convey its level of uncertainty during the learning process, so as to better inform the children interacting with Kaspar the reasons behind the successes and failures made by the robot. Overall, 30 Typically Developing (TD) children aged between 7 and 8 (19 girls, 11 boys) and 6 children with ASD performed 22 sessions (16 for TD; 6 for ASD) of the experiment in groups, and managed to teach Kaspar all associations in 2 to 7 trials. During the course of study Kaspar only made rare unexpected associations (2 perseverative errors and 1 win-shift, within a total of 272 trials), primarily due to exploratory choices, and eventually reached minimal uncertainty. Thus the robot's behavior was clear and consistent for the children, who all expressed enthusiasm in the experiment.Peer reviewe