AIMC Topic: Brain Mapping
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Decoding attentional states for neurofeedback: Mindfulness vs. wandering thoughts.
NeuroImage
Oct 11, 2018
Neurofeedback requires a direct translation of neuronal brain activity to sensory input given to the user or subject. However, decoding certain states, e.g., mindfulness or wandering thoughts, from ongoing brain activity remains an unresolved problem...
The importance of recurrent top-down synaptic connections for the anticipation of dynamic emotions.
Neural networks : the official journal of the International Neural Network Society
Oct 9, 2018
Different studies have shown the efficiency of a feed-forward neural network in categorizing basic emotional facial expressions. However, recent findings in psychology and cognitive neuroscience suggest that visual recognition is not a pure bottom-up...
Scan-specific robust artificial-neural-networks for k-space interpolation (RAKI) reconstruction: Database-free deep learning for fast imaging.
Magnetic resonance in medicine
Sep 18, 2018
PURPOSE: To develop an improved k-space reconstruction method using scan-specific deep learning that is trained on autocalibration signal (ACS) data.
Neural Networks, Computer
Algorithms
Databases, Factual
Brain
Humans
Middle Aged
Deep Learning
Image Processing, Computer-Assisted
Magnetic Resonance Imaging
Brain Mapping
Female
Young Adult
Adult
Male
Phantoms, Imaging
Heart
Image Interpretation, Computer-Assisted
Image Enhancement
Radionuclide Imaging
Regularized aggregation of statistical parametric maps.
Human brain mapping
Sep 5, 2018
Combining statistical parametric maps (SPM) from individual subjects is the goal in some types of group-level analyses of functional magnetic resonance imaging data. Brain maps are usually combined using a simple average across subjects, making them ...
Creatures great and small: Real-world size of animals predicts visual cortex representations beyond taxonomic category.
NeuroImage
Aug 29, 2018
Human occipitotemporal cortex contains neural representations for a variety of perceptual and conceptual features. We report a study examining neural representations of real-world size along the visual ventral stream, while carefully accounting for t...
Image categorization from functional magnetic resonance imaging using functional connectivity.
Journal of neuroscience methods
Aug 23, 2018
BACKGROUND: Previous studies have attempted to infer the category of objects in a stimulus image from functional magnetic resonance imaging (fMRI) data recoded during image-viewing. Most studies focus on extracting activity patterns within a given re...
Using person-specific neural networks to characterize heterogeneity in eating disorders: Illustrative links between emotional eating and ovarian hormones.
The International journal of eating disorders
Aug 21, 2018
OBJECTIVE: Emotional eating has been linked to ovarian hormone functioning, but no studies to-date have considered the role of brain function. This knowledge gap may stem from methodological challenges: Data are heterogeneous, violating assumptions o...
Robot-guided pediatric stereoelectroencephalography: single-institution experience.
Journal of neurosurgery. Pediatrics
Aug 17, 2018
OBJECTIVEStereoelectroencephalography (SEEG) has increased in popularity for localization of epileptogenic zones in drug-resistant epilepsy because safety, accuracy, and efficacy have been well established in both adult and pediatric populations. Dev...
Robotic TMS mapping of motor cortex in the developing brain.
Journal of neuroscience methods
Aug 16, 2018
BACKGROUND: The human motor cortex can be mapped safely and painlessly with transcranial magnetic stimulation (TMS) to explore neurophysiology in health and disease. Human error likely contributes to heterogeneity of such TMS measures. Here, we aimed...
Improved perfusion pattern score association with type 2 diabetes severity using machine learning pipeline: Pilot study.
Journal of magnetic resonance imaging : JMRI
Aug 5, 2018
BACKGROUND: Type 2 diabetes mellitus (T2DM) is associated with alterations in the blood-brain barrier, neuronal damage, and arterial stiffness, thus affecting cerebral metabolism and perfusion. There is a need to implement machine-learning methodolog...
Perfusion
Cognition Disorders
Linear Models
Middle Aged
Severity of Illness Index
Pilot Projects
Diabetes Mellitus, Type 2
Longitudinal Studies
Magnetic Resonance Imaging
Brain Mapping
Imaging, Three-Dimensional
Insulin Resistance
Aged
Aged, 80 and over
Cross-Sectional Studies
Male
Machine Learning
Humans
Prospective Studies
Brain
Female
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