We discuss event-related power differences (ERPDs) in low- and broadband-γ oscillations as the edge of embedded clauses is processed in wh-dependencies such as Which decision regarding/about him/her did Paul say that Lydie rejected without hesitation? in native and nonnative French speakers. The experimental conditions manipulated whether pronouns appeared in modifiers (Mods) or in noun complements (Comps) and whether they matched or mismatched a matrix-clause subject in gender. Across native and nonnative speakers, we found that anaphora-linked ERPDs for Mods vs. Comps in evoked power first arose in low γ and then in broadband γ. Therefore, referential elements first seem to be retrieved from working memory by narrowband processes in low-γ and then referential identification seems to be computed in broadband-γ output. Interactions between discourse- and syntax-based referential processes for the Mods vs. Comps in these ERPDs furthermore suggest that multidomain γ-range processing enables a range of elementary operations for discourse and semantic interpretation. We argue that a multidomain mechanism enabling operations conditioned by the syntactic and semantic nature of the elements processed interacts with local brain microcircuits representing features and feature sets that have been established in first- or second-language acquisition, accounting for a single language epistemology for native and nonnative language.
Spectroscopy data were collected on a BioTek Synergy H1 plate reader, then exported to and analyzed in Excel. 3D charts used in the manuscript were generated with OriginPro. Microscopy images are in proprietary .nd2 format of Nikon Elements software. .nd2 files were opened and processed with ImageJ. Gels were imaged on a BioRad Chemidoc.
Laughlin, P. M.; Young, K.; Gonzalez-Guiterrez, G.; Wang, J. C.-Y.,; Zlotnick, A. A narrow ratio of nucleic acid to SARS-CoV-2 N-protein enables phase separation. 2024.
Title:
Raw data for "A narrow ratio of nucleic acid to SARS-CoV-2 N-protein enables phase separation"
The data set consists of movement kinematic data from 92 participants that are neurotypical or have certain neurodevelopmental disorders (Autism, Attention Deficit/Hyperactivity Disorder, and their comorbidity). The data is of roughly 100 trials of a reaching paradigm per participant. The raw data consists of the linear acceleration (a), the roll (R), pitch (P), and yaw (Y), and the rate of change of the roll, pitch, and yaw.
Description of the data and file structure.
There are three primary folders: Data, Matlab Code, and the Deep Learning Code., Data:
Each folder corresponds to one participant. Inside is their motion data (sensor_data.csv) and a file describing their diagnosis and severity (diagnosis.txt). The columns of the csv are: a in x, a in y, a in z, dR/dt, dP/dt, dY/dt, R, P, Y
The diagnosis.txt file contains two lines: the first is their diagnosis (ASD, ADHD, A^2, NT), the second is their severity (HF for high functioning, MF for mid functioning, LF for low functioning, and NA for not applicable)., Matlab Code:
Information on how to analyze participants can be found in README.txt file within the folder.
The Matlab code was written and run on MATLAB_R2023b. The signal processing toolbox is required., and Deep Learning Code:
Information on how to perform the deep learning analysis can be found in README.txt file within the folder.
The deep learning code is written in Python3 and relies on PyTorch.
K. Doctor, C. McKeever, A. Phadnis, D. Wu, J. Nurnberger Jr., M. Plawecki, & J.V. Jose. Deep learning and statistical millisecond motor assessments of neurodevelopmental disorders. Science, In Submission.
Title:
Deep Learning and statistical millisecond motor assessments of neurodevelopmental disorders
The data set consists of movement kinematic data from 92 participants that are neurotypical or have certain neurodevelopmental disorders (Autism, Attention Deficit/Hyperactivity Disorder, and their comorbidity). The data is of roughly 100 trials of a reaching paradigm per participant. The raw data consists of the linear acceleration (a), the roll (R), pitch (P), and yaw (Y), and the rate of change of the roll, pitch, and yaw.
Description of the data and file structure.
There are three primary folders: Data, Matlab Code, and the Deep Learning Code., Data:
Each folder corresponds to one participant. Inside is their motion data (sensor_data.csv) and a file describing their diagnosis and severity (diagnosis.txt). The columns of the csv are: a in x, a in y, a in z, dR/dt, dP/dt, dY/dt, R, P, Y
The diagnosis.txt file contains two lines: the first is their diagnosis (ASD, ADHD, A^2, NT), the second is their severity (HF for high functioning, MF for mid functioning, LF for low functioning, and NA for not applicable)., Matlab Code:
Information on how to analyze participants can be found in README.txt file within the folder.
The Matlab code was written and run on MATLAB_R2023b. The signal processing toolbox is required., and Deep Learning Code:
Information on how to perform the deep learning analysis can be found in README.txt file within the folder.
The deep learning code is written in Python3 and relies on PyTorch.
K. Doctor, C. McKeever, A. Phadnis, D. Wu, J. Nurnberger Jr., M. Plawecki, & J.V. Jose. Deep learning and statistical millisecond motor assessments of neurodevelopmental disorders. Science, In Submission.
Title:
Deep Learning and statistical millisecond motor assessments of neurodevelopmental disorders
The purpose of this study was to examine how IMW affects the sensory and affective components of dyspnea, exercise performance, and NIRS-derived metaboreflex effects during a cycling time to exhaustion test. Additionally, to augment the ventilatory response for better elucidation of the cardiorespiratory effects of IMW, we added hypoxia as an intervention. Using both normoxic and hypoxic conditions, our hypotheses were: 1) both sensory and affective components of dyspnea would be attenuated following IMW in each condition, 2) the extent of skeletal muscle deoxygenation (i.e., a NIRS-derived surrogate for the metaboreflex) in the leg would be reduced after IMW in each condition, and 3) participants’ time to exhaustion would be prolonged following IMW in each condition.
The purpose of this study was to examine how IMW affects the sensory and affective components of dyspnea, exercise performance, and NIRS-derived metaboreflex effects during a cycling time to exhaustion test. Additionally, to augment the ventilatory response for better elucidation of the cardiorespiratory effects of IMW, we added hypoxia as an intervention. Using both normoxic and hypoxic conditions, our hypotheses were: 1) both sensory and affective components of dyspnea would be attenuated following IMW in each condition, 2) the extent of skeletal muscle deoxygenation (i.e., a NIRS-derived surrogate for the metaboreflex) in the leg would be reduced after IMW in each condition, and 3) participants’ time to exhaustion would be prolonged following IMW in each condition.
This dataset documents the outcomes of a research project where we identified, analyzed, and described a set of existing ethics-focused methods designed to support design research and practice for a range of audiences (such as technology and design researchers and practitioners, and educators). The final dataset includes 63 ethics-focused methods, describing the intended audience(s), format of guidance, interaction qualities, utilization of existing knowledge or concepts, implementation opportunities within design processes, and the "core" or "script" of the method.
The data show performance on 19 tests of auditory abilities, with 340 subjects. The data include:
1. Percent correct for each of the 19 TBAC tests used in the 2007 study
2. Arcsine transformed values of the PC scores (names ending in “AS”)
3. Percentile values for the Arcsine-transformed scores (names ending in “ASp”)
4. Latent variable scores for four independent auditory factors, plus a general auditory ability factor, as described in KWG 2007.
Sex and race data are also included.
For a subset of subjects, SAT scores, GPA, and an IQ estimate (based on SAT scores) is also provided.
Kidd, G. R., Watson, C. S., & Gygi, B. (2007). Individual differences in auditory abilities. The Journal Of The Acoustical Society Of America, 122(1), 418-435.
Title:
Individual Differences in Auditory Abilities: The Expanded TBAC dataset
The Bedrock Geologic Map of the Vincennes 30 x 60 Minute Quadrangle was created to present basic bedrock geologic information that contributes to the characterization of potential aggregate resources, characterization of bedrock aquifer systems, and analysis of the overlying predominantly glacial deposits. This map is based on data obtained from several thousand records including petroleum well drillers' logs, geophysical logs, water well drillers' logs, descriptions of cores recovered by the Indiana Geological Survey, seismic refraction records collected by the Indiana Geological Survey, natural exposures in and near the map area, and exposures in active and abandoned quarries. This database is, in large part, the result of a cooperative mapping agreement between the U.S. Geological Survey (USGS) and the Indiana Geological and Water Survey through the STATEMAP program of the USGS.
Here we present CAFE 5, a completely re-written software package with numerous performance and user-interface enhancements over previous versions. These include improved support for multithreading, the explicit modelling of rate variation among families using gamma-distributed rate categories, and command-line arguments that preclude the use of accessory scripts.
