A speech envelope landmark for syllable encoding in human superior temporal gyrus.

The most salient acoustic features in speech are the modulations in its intensity, captured by the amplitude envelope. Perceptually, the envelope is necessary for speech comprehension. Yet, the neural computations that represent the envelope and their linguistic implications are heavily debated. We used high-density intracranial recordings, while participants listened to speech, to determine how the envelope is represented in human speech cortical areas on the superior temporal gyrus (STG). We found that a well-defined zone in middle STG detects acoustic onset edges (local maxima in the envelope rate of change). Acoustic analyses demonstrated that timing of acoustic onset edges cues syllabic nucleus onsets, while their slope cues syllabic stress. Synthesized amplitude-modulated tone stimuli showed that steeper slopes elicited greater responses, confirming cortical encoding of amplitude change, not absolute amplitude. Overall, STG encoding of the timing and magnitude of acoustic onset edges underlies the perception of speech temporal structure

Multiplicative noise for masking numerical microdata with constraints

Before releasing databases which contain sensitive information about individuals, statistical agencies have to apply Statistical Disclosure Limitation (SDL) methods to such data. The goal of these methods is to minimize the risk of disclosure of the confidential information and at the same time provide legitimate data users with accurate information about the population of interest. SDL methods applicable to the microdata (i.e. collection of individual records) are often called masking methods. In this paper, several multiplicative noise masking schemes are presented. These schemes are designed to preserve positivity and inequality constraints in the data together with the vector of means and covariance matrix

A posteriori disclosure risk measure for tabular data based on conditional entropy

Statistical database protection, also known as Statistical Disclosure Control (SDC), is a part of information security which tries to prevent published statistical information (tables, individual records) from disclosing the contribution of specific respondents. This paper deals with the assessment of the disclosure risk associated to the release of tabular data. So-called sensitivity rules are currently being used to measure the disclosure risk for tables. These rules operate on an a priori basis: the data are examined and the rules are used to decide whether the data can be released as they stand or should rather be protected. In this paper, we propose to complement a priori risk assessment with a posteriori risk assessment in order to achieve a higher level of security, that is, we propose to take the protected information into account when measuring the disclosure risk. The proposed a posteriori disclosure risk measure is compatible with a broad class of disclosure protection methods and can be extended for computing disclosure risk for a set of linked tables. In the case of linked table protection via cell suppression, the proposed measure allows detection of secondary suppression patterns which offer more protection than others

Low foreign language proficiency reduces optimism about the personal future

Optimistic estimates about the personal future constitute one of the best-described and most-debated decision biases related to emotion. Nevertheless, it has been difficult to isolate manipulations that reduce optimistic estimates. Eliciting estimates in a foreign language is a promising candidate manipulation because foreign language use alters decision biases in scenarios with emotional components. Consequently, we tested whether foreign language use reduces optimistic estimates. In a laboratory experiment, participants (n = 45) estimated their probability of experiencing life events either in their native language or a foreign language, in which they were highly proficient. We found no differences in these estimates or in the updating of these estimates after receiving feedback about the population baseline probability. Importantly, three online experiments with large sample sizes (ns = 706, 530, and 473) showed that using a foreign language with low proficiency reduced comparative optimism. Participants in the online experiments had diverse proficiency levels and were matched on a variety of control metrics. Fine-grained analyses indicated that low proficiency weakens the coupling between probability estimates and rated arousal. Overall, our findings suggest that an important decision bias can be reduced when using a foreign language with low proficiency

The framing effect in a monetary gambling task is robust in minimally verbal language switching contexts

Decision-making biases, in particular the framing effect, can be altered in foreign language settings (foreign language effect) and following switching between languages (the language switching effect on framing). Recently, it has been suggested that the framing effect is only affected by foreign language use if the task is presented in a rich textual form. Here, we assess whether an elaborate verbal task is also a prerequisite for the language switching effect on framing. We employed a financial gambling task that induces a robust framing effect but is less verbal than the classical framing paradigms (e.g., the Asian disease problem). We conducted an online experiment (n = 485), where we orthogonally manipulated language use and language switching between trials. The results showed no effects of foreign language use or language switching throughout the experiment. This online result was confirmed in a laboratory experiment (n = 27). Overall, we find that language switching does not reduce the framing effect in a paradigm with little verbal content and thus that language switching effects seem contingent on the amount of verbal processing required

A Roadmap for Greater Public Use of Privacy-Sensitive Government Data: Workshop Report

Government agencies collect and manage a wide range of ever-growing datasets. While such data has the potential to support research and evidence-based policy making, there are concerns that the dissemination of such data could infringe upon the privacy of the individuals (or organizations) from whom such data was collected. To appraise the current state of data sharing, as well as learn about opportunities for stimulating such sharing at a faster pace, a virtual workshop was held on May 21st and 26th, 2021, sponsored by the National Science Foundation and National Institute of Standards and Technologies, where a multinational collection of researchers and practitioners were brought together to discuss their experiences and learn about recently developed technologies for managing privacy while sharing data. The workshop specifically focused on challenges and successes in government data sharing at various levels. The first day focused on successful examples of new technology applied to sharing of public data, including formal privacy techniques, synthetic data, and cryptographic approaches. Day two emphasized brainstorming sessions on some of the challenges and directions to address them.Comment: 23 page

Second Language Use Facilitates Implicit Emotion Regulation via Content Labeling

Previous studies reported that negative stimuli induced less affect in bilinguals when stimuli were presented in bilinguals’ second, weaker language (L2) than when they were presented in their native language (L1). This effect of L2 use was attributed to increased emotional distance as well as to increased levels of cognitive control during L2 use. Here we investigated how explicit (cognitive reappraisal, i.e., reinterpreting the meaning of the emotional stimulus to alter its emotional impact) and implicit (content labeling, i.e., categorizing the content of the image; and emotion labeling, i.e., naming the emotion induced by the emotional stimulus) emotion regulation strategies are altered in an L2 (English) context in German native speakers with medium to high proficiency in their L2. While previous studies used linguistic stimuli, such as words, to induce affect, here we used images to test whether reduced affect could also be observed for non-linguistic stimuli when presented in an L2 context. We hypothesized that the previously implicated increase in emotional distance and cognitive control in an L2 would result in an L2 advantage in emotion regulation (i.e., leading to less negative emotions compared to an L1 context), by strengthening the effect of linguistic re-evaluation on the evoked emotions. Using a classic emotion regulation paradigm, we examined changes in subjective emotional state ratings during reappraisal, emotion labeling and content labeling in a L1 and L2 context. We found that the strength of evoked affective responses did not depend on the language context in which an image was presented. Crucially, content labeling in L2 was more effective than in L1, whereas emotion labeling did not differ between languages. Overall, evoked responses were regulated most effectively through explicit emotion regulation (reappraisal) in L1 and L2 context. These results demonstrate an L2 advantage effect for emotion regulation through content labeling and suggest that L2 context alters sub- processes implicated in content labeling but not emotion labeling

A Diffusion Model Analysis

Effects of stimulus length on reaction times (RTs) in the lexical decision task are the topic of extensive research. While slower RTs are consistently found for longer pseudo-words, a finding coined the word length effect (WLE), some studies found no effects for words, and yet others reported faster RTs for longer words. Moreover, the WLE depends on the orthographic transparency of a language, with larger effects in more transparent orthographies. Here we investigate processes underlying the WLE in lexical decision in German-English bilinguals using a diffusion model (DM) analysis, which we compared to a linear regression approach. In the DM analysis, RT-accuracy distributions are characterized using parameters that reflect latent sub-processes, in particular evidence accumulation and decision-independent perceptual encoding, instead of typical parameters such as mean RT and accuracy. The regression approach showed a decrease in RTs with length for pseudo-words, but no length effect for words. However, DM analysis revealed that the null effect for words resulted from opposing effects of length on perceptual encoding and rate of evidence accumulation. Perceptual encoding times increased with length for words and pseudo-words, whereas the rate of evidence accumulation increased with length for real words but decreased for pseudo-words. A comparison between DM parameters in German and English suggested that orthographic transparency affects perceptual encoding, whereas effects of length on evidence accumulation are likely to reflect contextual information and the increase in available perceptual evidence with length. These opposing effects may account for the inconsistent findings on WLEs