23 research outputs found
Pattern classification based on the amygdala does not predict an individual's response to emotional stimuli
Functional magnetic resonance imaging (fMRI) studies have often recorded robust univariate group effects in the amygdala of subjects exposed to emotional stimuli. Yet it is unclear to what extent this effect also holds true when multi-voxel pattern analysis (MVPA) is applied at the level of the individual participant. Here we sought to answer this question. To this end, we combined fMRI data from two prior studies (N = 112). For each participant, a linear support vector machine was trained to decode the valence of emotional pictures (negative, neutral, positive) based on brain activity patterns in either the amygdala (primary region-of-interest analysis) or the whole-brain (secondary exploratory analysis). The accuracy score of the amygdala-based pattern classifications was statistically significant for only a handful of participants (4.5%) with a mean and standard deviation of 37% ± 5% across all subjects (range: 28–58%; chance-level: 33%). In contrast, the accuracy score of the whole-brain pattern classifications was statistically significant in roughly half of the participants (50.9%), and had an across-subjects mean and standard deviation of 49% ± 6% (range: 33–62%). The current results suggest that the information conveyed by the emotional pictures was encoded by spatially distributed parts of the brain, rather than by the amygdala alone, and may be of particular relevance to studies that seek to target the amygdala in the treatment of emotion regulation problems, for example via real-time fMRI neurofeedback training.publishedVersio
A motor association area in the depths of the central sulcus
Cells in the precentral gyrus directly send signals to the periphery to generate movement and are principally organized as a topological map of the body. We find that movement-induced electrophysiological responses from depth electrodes extend this map three-dimensionally throughout the gyrus. Unexpectedly, this organization is interrupted by a previously undescribed motor association area in the depths of the midlateral aspect of the central sulcus. This \u27Rolandic motor association\u27 (RMA) area is active during movements of different body parts from both sides of the body and may be important for coordinating complex behaviors
Virgo Detector Characterization and Data Quality during the O3 run
The Advanced Virgo detector has contributed with its data to the rapid growth
of the number of detected gravitational-wave signals in the past few years,
alongside the two LIGO instruments. First, during the last month of the
Observation Run 2 (O2) in August 2017 (with, most notably, the compact binary
mergers GW170814 and GW170817) and then during the full Observation Run 3 (O3):
an 11 months data taking period, between April 2019 and March 2020, that led to
the addition of about 80 events to the catalog of transient gravitational-wave
sources maintained by LIGO, Virgo and KAGRA. These discoveries and the manifold
exploitation of the detected waveforms require an accurate characterization of
the quality of the data, such as continuous study and monitoring of the
detector noise. These activities, collectively named {\em detector
characterization} or {\em DetChar}, span the whole workflow of the Virgo data,
from the instrument front-end to the final analysis. They are described in
details in the following article, with a focus on the associated tools, the
results achieved by the Virgo DetChar group during the O3 run and the main
prospects for future data-taking periods with an improved detector.Comment: 86 pages, 33 figures. This paper has been divided into two articles
which supercede it and have been posted to arXiv on October 2022. Please use
these new preprints as references: arXiv:2210.15634 (tools and methods) and
arXiv:2210.15633 (results from the O3 run
Virgo Detector Characterization and Data Quality: results from the O3 run
The Advanced Virgo detector has contributed with its data to the rapid growth
of the number of detected gravitational-wave (GW) signals in the past few
years, alongside the two Advanced LIGO instruments. First during the last month
of the Observation Run 2 (O2) in August 2017 (with, most notably, the compact
binary mergers GW170814 and GW170817), and then during the full Observation Run
3 (O3): an 11-months data taking period, between April 2019 and March 2020,
that led to the addition of about 80 events to the catalog of transient GW
sources maintained by LIGO, Virgo and now KAGRA. These discoveries and the
manifold exploitation of the detected waveforms require an accurate
characterization of the quality of the data, such as continuous study and
monitoring of the detector noise sources. These activities, collectively named
{\em detector characterization and data quality} or {\em DetChar}, span the
whole workflow of the Virgo data, from the instrument front-end hardware to the
final analyses. They are described in details in the following article, with a
focus on the results achieved by the Virgo DetChar group during the O3 run.
Concurrently, a companion article describes the tools that have been used by
the Virgo DetChar group to perform this work.Comment: 57 pages, 18 figures. To be submitted to Class. and Quantum Grav.
This is the "Results" part of preprint arXiv:2205.01555 [gr-qc] which has
been split into two companion articles: one about the tools and methods, the
other about the analyses of the O3 Virgo dat
Virgo Detector Characterization and Data Quality: tools
Detector characterization and data quality studies -- collectively referred
to as {\em DetChar} activities in this article -- are paramount to the
scientific exploitation of the joint dataset collected by the LIGO-Virgo-KAGRA
global network of ground-based gravitational-wave (GW) detectors. They take
place during each phase of the operation of the instruments (upgrade, tuning
and optimization, data taking), are required at all steps of the dataflow (from
data acquisition to the final list of GW events) and operate at various
latencies (from near real-time to vet the public alerts to offline analyses).
This work requires a wide set of tools which have been developed over the years
to fulfill the requirements of the various DetChar studies: data access and
bookkeeping; global monitoring of the instruments and of the different steps of
the data processing; studies of the global properties of the noise at the
detector outputs; identification and follow-up of noise peculiar features
(whether they be transient or continuously present in the data); quick
processing of the public alerts. The present article reviews all the tools used
by the Virgo DetChar group during the third LIGO-Virgo Observation Run (O3,
from April 2019 to March 2020), mainly to analyse the Virgo data acquired at
EGO. Concurrently, a companion article focuses on the results achieved by the
DetChar group during the O3 run using these tools.Comment: 44 pages, 16 figures. To be submitted to Class. and Quantum Grav.
This is the "Tools" part of preprint arXiv:2205.01555 [gr-qc] which has been
split into two companion articles: one about the tools and methods, the other
about the analyses of the O3 Virgo dat
Data from: Fully implanted brain-computer interface in a locked-in patient with ALS
Options for people with severe paralysis who have lost the ability to communicate orally are limited. We describe a method for communication in a patient with late-stage amyotrophic lateral sclerosis (ALS), involving a fully implanted brain–computer interface that consists of subdural electrodes placed over the motor cortex and a transmitter placed subcutaneously in the left side of the thorax. By attempting to move the hand on the side opposite the implanted electrodes, the patient accurately and independently controlled a computer typing program 28 weeks after electrode placement, at the equivalent of two letters per minute. The brain–computer interface offered autonomous communication that supplemented and at times supplanted the patient’s eye-tracking device. (Funded by the Government of the Netherlands and the European Union; ClinicalTrials.gov number, NCT02224469.
Fully implanted brain-computer interface in a locked-in patient with ALS
Options for people with severe paralysis who have lost the ability to communicate orally are limited. We describe a method for communication in a patient with late-stage amyotrophic lateral sclerosis (ALS), involving a fully implanted brain-computer interface that consists of subdural electrodes placed over the motor cortex and a transmitter placed subcutaneously in the left side of the thorax. By attempting to move the hand on the side opposite the implanted electrodes, the patient accurately and independently controlled a computer typing program 28 weeks after electrode placement, at the equivalent of two letters per minute. The brain-computer interface offered autonomous communication that supplemented and at times supplanted the patient's eye-tracking device