3,492 research outputs found
Preparing Laboratory and Real-World EEG Data for Large-Scale Analysis: A Containerized Approach.
Large-scale analysis of EEG and other physiological measures promises new insights into brain processes and more accurate and robust brain-computer interface models. However, the absence of standardized vocabularies for annotating events in a machine understandable manner, the welter of collection-specific data organizations, the difficulty in moving data across processing platforms, and the unavailability of agreed-upon standards for preprocessing have prevented large-scale analyses of EEG. Here we describe a "containerized" approach and freely available tools we have developed to facilitate the process of annotating, packaging, and preprocessing EEG data collections to enable data sharing, archiving, large-scale machine learning/data mining and (meta-)analysis. The EEG Study Schema (ESS) comprises three data "Levels," each with its own XML-document schema and file/folder convention, plus a standardized (PREP) pipeline to move raw (Data Level 1) data to a basic preprocessed state (Data Level 2) suitable for application of a large class of EEG analysis methods. Researchers can ship a study as a single unit and operate on its data using a standardized interface. ESS does not require a central database and provides all the metadata data necessary to execute a wide variety of EEG processing pipelines. The primary focus of ESS is automated in-depth analysis and meta-analysis EEG studies. However, ESS can also encapsulate meta-information for the other modalities such as eye tracking, that are increasingly used in both laboratory and real-world neuroimaging. ESS schema and tools are freely available at www.eegstudy.org and a central catalog of over 850 GB of existing data in ESS format is available at studycatalog.org. These tools and resources are part of a larger effort to enable data sharing at sufficient scale for researchers to engage in truly large-scale EEG analysis and data mining (BigEEG.org)
Hierarchical Event Descriptors (HED): Semi-Structured Tagging for Real-World Events in Large-Scale EEG.
Real-world brain imaging by EEG requires accurate annotation of complex subject-environment interactions in event-rich tasks and paradigms. This paper describes the evolution of the Hierarchical Event Descriptor (HED) system for systematically describing both laboratory and real-world events. HED version 2, first described here, provides the semantic capability of describing a variety of subject and environmental states. HED descriptions can include stimulus presentation events on screen or in virtual worlds, experimental or spontaneous events occurring in the real world environment, and events experienced via one or multiple sensory modalities. Furthermore, HED 2 can distinguish between the mere presence of an object and its actual (or putative) perception by a subject. Although the HED framework has implicit ontological and linked data representations, the user-interface for HED annotation is more intuitive than traditional ontological annotation. We believe that hiding the formal representations allows for a more user-friendly interface, making consistent, detailed tagging of experimental, and real-world events possible for research users. HED is extensible while retaining the advantages of having an enforced common core vocabulary. We have developed a collection of tools to support HED tag assignment and validation; these are available at hedtags.org. A plug-in for EEGLAB (sccn.ucsd.edu/eeglab), CTAGGER, is also available to speed the process of tagging existing studies
Retrieval Failure Contributes to Gist-Based False Recognition
People often falsely recognize items that are similar to previously encountered items. This robust memory error is referred to as gist-based false recognition. A widely held view is that this error occurs because the details fade rapidly from our memory. Contrary to this view, an initial experiment revealed that, following the same encoding conditions that produce high rates of gist-based false recognition, participants overwhelmingly chose the correct target rather than its related foil when given the option to do so. A second experiment showed that this result is due to increased access to stored details provided by reinstatement of the originally encoded photograph, rather than to increased attention to the details. Collectively, these results suggest that details needed for accurate recognition are, to a large extent, still stored in memory and that a critical factor determining whether false recognition will occur is whether these details can be accessed during retrieval.Psycholog
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Interactions Between Visual Attention and Episodic Retrieval: Dissociable Contributions of Parietal Regions During Gist-Based False Recognition
The interaction between episodic retrieval and visual attention is relatively unexplored. Given that systems mediating attention and episodic memory appear to be segregated, and perhaps even in competition, it is unclear how visual attention is recruited during episodic retrieval. We investigated the recruitment of visual attention during the suppression of gist-based false recognition, the tendency to falsely recognize items that are similar to previously encountered items. Recruitment of visual attention was associated with activity in the dorsal attention network. The inferior parietal lobule, often implicated in episodic retrieval, tracked veridical retrieval of perceptual detail and showed reduced activity during the engagement of visual attention, consistent with a competitive relationship with the dorsal attention network. These findings suggest that the contribution of the parietal cortex to interactions between visual attention and episodic retrieval entails distinct systems that contribute to different components of the task while also suppressing each other.Psycholog
Latin America 2060: consolidation or crisis?
This repository item contains a single issue of the Pardee Center Task Force Reports, a publication series that began publishing in 2009 by the Boston University Frederick S. Pardee Center for the Study of the Longer-Range Future.Latin America has produced vigorous ideas throughout its history, expressed in narratives about its struggles and successes, or its weaknesses and failures. Together, these have shaped a multi-faceted vision of the region and its peoples. Some of its expositors, finding the story to be neither complete nor precise, work toward reformulations, some quite radical. Such generation of knowledge in different fields seems destined to yield a variety of distinct outcomes, at least in part because some of the emerging social and cultural movements are not yet very well structured. This Task Force Report project seeks to harness ideas about the region’s future into a coherent and policy useful discourse.
A Workshop and a Task Force meeting was held at Boston University on November 18-19, 2010. A select group of invited experts – a mix of academic scholars and practitioners – were asked to turn their ideas into short ‘Think Pieces’ essays. Each Think Piece focuses on a specific topical issue for the region as a whole, instead of looking only at particular countries. These Think Piece essays are compiled and edited by the Task Force coordinator and published by the Pardee Center as a Task Force Report
Adult Social Work and High Risk Domestic Violence Cases
Summary
This article focuses on adult social work’s response in England to high-risk domestic violence cases and the role of adult social workers in Multi-Agency Risk and Assessment Conferences. (MARACs). The research was undertaken between 2013-2014 and
focused on one city in England and involved the research team attending MARACs, Interviews with 20 adult social workers, 24 MARAC attendees, 14 adult service users at time T1 (including follow up interviews after six months, T2), focus groups with IDVAs and Women’s Aid and an interview with a Women’s Aid service user.
Findings
The findings suggest that although adult social workers accept the need to be involved in domestic violence cases they are uncertain of what their role is and are confused with the need to operate a parallel domestic violence and adult safeguarding approach, which is further, complicated by issues of mental capacity. MARACS are identified as overburdened, under-represented meetings staffed by committed managers. However, they are in danger of becoming managerial processes neglecting the service users they are meant to protect.
Applications
The article argues for a re-engagement of adult social workers with domestic violence that has increasingly become over identified with child protection. It also raises the issue whether MARACS remain fit for purpose and whether they still represent the best possible response to multi-agency coordination and practice in domestic violence
Regional Climate Trends and Scenarios for the U.S. National Climate Assessment Part 4. Climate of the U.S. Great Plains
This document is one of series of regional climate descriptions designed to provide input that can be used in the development of the National Climate Assessment (NCA). As part of a sustained assessment approach, it is intended that these documents will be updated as new and well-vetted model results are available and as new climate scenario needs become clear. It is also hoped that these documents (and associated data and resources) are of direct benefit to decision makers and communities seeking to use this information in developing adaptation plans.
There are nine reports in this series, one each for eight regions defined by the NCA, and one for the contiguous U.S. The eight NCA regions are the Northeast, Southeast, Midwest, Great Plains, Northwest, Southwest, Alaska, and Hawai‘i/Pacific Islands.
These documents include a description of the observed historical climate conditions for each region and a set of climate scenarios as plausible futures – these components are described in more detail below.
While the datasets and simulations in these regional climate documents are not, by themselves, new, (they have been previously published in various sources), these documents represent a more complete and targeted synthesis of historical and plausible future climate conditions around the specific regions of the NCA.
There are two components of these descriptions. One component is a description of the historical climate conditions in the region. The other component is a description of the climate conditions associated with two future pathways of greenhouse gas emissions
Characterization and Robust Classification of EEG Signal from Image RSVP Events with Independent Time-Frequency Features
This paper considers the problem of automatic characterization and detection of target images in a rapid serial visual presentation (RSVP) task based on EEG data. A novel method that aims to identify single-trial event-related potentials (ERPs) in time-frequency is proposed, and a robust classifier with feature clustering is developed to better utilize the correlated ERP features. The method is applied to EEG recordings of a RSVP experiment with multiple sessions and subjects.
The results show that the target image events are mainly characterized by 3 distinct patterns in the time-frequency domain, i.e., a theta band (4.3 Hz) power boosting 300–700 ms after the target image onset, an alpha band (12 Hz) power boosting 500–1000 ms after the stimulus onset, and a delta band (2 Hz) power boosting after 500 ms. The most discriminant time-frequency features are power boosting and are relatively consistent among multiple sessions and subjects.
Since the original discriminant time-frequency features are highly correlated, we constructed the uncorrelated features using hierarchical clustering for better classification of target and non-target images. With feature clustering, performance (area under ROC) improved from 0.85 to 0.89 on within-session tests, and from 0.76 to 0.84 on cross-subject tests. The constructed uncorrelated features were more robust than the original discriminant features and corresponded to a number of local regions on the time-frequency plane
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