Causal Mapping of Emotion Networks in the Human Brain: Framework and Initial Findings

Emotions involve many cortical and subcortical regions, prominently including the amygdala. It remains unknown how these multiple network components interact, and it remains unknown how they cause the behavioral, autonomic, and experiential effects of emotions. Here we describe a framework for combining a novel technique, concurrent electrical stimulation with fMRI (es-fMRI), together with a novel analysis, inferring causal structure from fMRI data (causal discovery). We outline a research program for investigating human emotion with these new tools, and provide initial findings from two large resting-state datasets as well as case studies in neurosurgical patients with electrical stimulation of the amygdala. The overarching goal is to use causal discovery methods on fMRI data to infer causal graphical models of how brain regions interact, and then to further constrain these models with direct stimulation of specific brain regions and concurrent fMRI. We conclude by discussing limitations and future extensions. The approach could yield anatomical hypotheses about brain connectivity, motivate rational strategies for treating mood disorders with deep brain stimulation, and could be extended to animal studies that use combined optogenetic fMRI

Characterizing auditory cortical receptive fields

Through this research we have a unique opportunity to explore how auditory cortices respond to naturalistic stimuli and how that response changes with different tasks. This foundational work is critical if we are to understand abnormality in auditory cortices in disorders such as autism, specific language impairment, auditory processing disorders and prolonged auditory deprivation (due to hearing loss).https://ir.lib.uwo.ca/brainscanprojectsummaries/1007/thumbnail.jp

Development, Operation, and Results From the Texas Automated Buoy System

The Texas Automated Buoy System (TABS) is a coastal network of moored buoys that report near-real-time observations about currents and winds along the Texas coast. Established in 1995, the primary mission of TABS is ocean observations in the service of oil spill preparedness and response. The state of Texas funded the system with the intent of improving the data available to oil spill trajectory modelers. In its 12 years of operation, TABS has proven its usefulness during realistic oil spill drills and actual spills. The original capabilities of TABS, i.e., measurement of surface currents and temperatures, have been extended to the marine surface layer, the entire water column, and the sea floor. In addition to observations, a modeling component has been integrated into the TABS program. The goal is to form the core of a complete ocean observing system for Texas waters. As the nation embarks on the development of an integrated ocean observing system, TABS will continue to be an active participant of the Gulf of Mexico Coastal Ocean Observing System (GCOOS) regional association and the primary source of near-surface current measurements in the northwestern Gulf of Mexico. This article describes the origin of TABS, the philosophy behind the operation and development of the system, the resulting modifications to improve the system, the expansion of the system to include new sensors, the development of TABS forecasting models and real-time analysis tools, and how TABS has met many of the societal goals envisioned for GCOOS

Copyright & Privacy - Through the Political Lens, 4 J. Marshall Rev. Intell. Prop. L. 306 (2005)

Veteran beltway players discuss the politics of P2P technology and Privacy. How far can or should Congress go? Can the United States export its values or its laws in this area? Are content owners in a losing Luddite struggle? What is the role of litigators, lobbyists and legislators in this war

Causal Mapping of Emotion Networks in the Human Brain: Framework and Initial Findings

Emotions involve many cortical and subcortical regions, prominently including the amygdala. It remains unknown how these multiple network components interact, and it remains unknown how they cause the behavioral, autonomic, and experiential effects of emotions. Here we describe a framework for combining a novel technique, concurrent electrical stimulation with fMRI (es-fMRI), together with a novel analysis, inferring causal structure from fMRI data (causal discovery). We outline a research program for investigating human emotion with these new tools, and provide initial findings from two large resting-state datasets as well as case studies in neurosurgical patients with electrical stimulation of the amygdala. The overarching goal is to use causal discovery methods on fMRI data to infer causal graphical models of how brain regions interact, and then to further constrain these models with direct stimulation of specific brain regions and concurrent fMRI. We conclude by discussing limitations and future extensions. The approach could yield anatomical hypotheses about brain connectivity, motivate rational strategies for treating mood disorders with deep brain stimulation, and could be extended to animal studies that use combined optogenetic fMRI

Analysis of single-unit responses to emotional scenes in human ventromedial prefrontal cortex

Lesion and functional imaging studies in humans have shown that the ventral and medial prefrontal cortex is critically involved in the processing of emotional stimuli, but both of these methods have limited spatiotemporal resolution. Conversely, neurophysiological studies of emotion in nonhuman primates typically rely on stimuli that do not require elaborate cognitive processing. To begin bridging this gap, we recorded from a total of 267 neurons in the left and right orbital and anterior cingulate cortices of four patients who had chronically implanted depth electrodes for monitoring epilepsy. Peristimulus activity was recorded to standardized, complex visual scenes depicting neutral, pleasant, or aversive content. Recording locations were verified with postoperative magnetic resonance imaging. Using a conservative, multistep statistical evaluation, we found significant responses in 56 neurons; 16 of these were selective for only one emotion class, most often aversive. The findings suggest sparse and widely distributed processing of emotional value in the prefrontal cortex, with a predominance of responses to aversive stimuli

A First Comparison of Kepler Planet Candidates in Single and Multiple Systems

In this letter we present an overview of the rich population of systems with multiple candidate transiting planets found in the first four months of Kepler data. The census of multiples includes 115 targets that show 2 candidate planets, 45 with 3, 8 with 4, and 1 each with 5 and 6, for a total of 170 systems with 408 candidates. When compared to the 827 systems with only one candidate, the multiples account for 17 percent of the total number of systems, and a third of all the planet candidates. We compare the characteristics of candidates found in multiples with those found in singles. False positives due to eclipsing binaries are much less common for the multiples, as expected. Singles and multiples are both dominated by planets smaller than Neptune; 69 +2/-3 percent for singles and 86 +2/-5 percent for multiples. This result, that systems with multiple transiting planets are less likely to include a transiting giant planet, suggests that close-in giant planets tend to disrupt the orbital inclinations of small planets in flat systems, or maybe even to prevent the formation of such systems in the first place.Comment: 13 pages, 13 figures, submitted to ApJ Letter

Modeling Kepler transit light curves as false positives: Rejection of blend scenarios for Kepler-9, and validation of Kepler-9d, a super-Earth-size planet in a multiple system

Light curves from the Kepler Mission contain valuable information on the nature of the phenomena producing the transit-like signals. To assist in exploring the possibility that they are due to an astrophysical false positive, we describe a procedure (BLENDER) to model the photometry in terms of a "blend" rather than a planet orbiting a star. A blend may consist of a background or foreground eclipsing binary (or star-planet pair) whose eclipses are attenuated by the light of the candidate and possibly other stars within the photometric aperture. We apply BLENDER to the case of Kepler-9, a target harboring two previously confirmed Saturn-size planets (Kepler-9b and Kepler-9c) showing transit timing variations, and an additional shallower signal with a 1.59-day period suggesting the presence of a super-Earth-size planet. Using BLENDER together with constraints from other follow-up observations we are able to rule out all blends for the two deeper signals, and provide independent validation of their planetary nature. For the shallower signal we rule out a large fraction of the false positives that might mimic the transits. The false alarm rate for remaining blends depends in part (and inversely) on the unknown frequency of small-size planets. Based on several realistic estimates of this frequency we conclude with very high confidence that this small signal is due to a super-Earth-size planet (Kepler-9d) in a multiple system, rather than a false positive. The radius is determined to be 1.64 (+0.19/-0.14) R(Earth), and current spectroscopic observations are as yet insufficient to establish its mass.Comment: 20 pages in emulateapj format, including 8 tables and 16 figures. To appear in ApJ, 1 January 2010. Accepted versio