In functional magnetic resonance imaging (fMRI) studies, a cortical region in the right temporo-parietal junction (RTPJ) is recruited when participants read stories about people's thoughts ('Theory of Mind'). Both fMRI and lesion studies suggest that a region near the RTPJ is associated with attentional reorienting in response to an unexpected stimulus. Do Theory of Mind and attentional reorienting recruit a single population of neurons, or are there two neighboring but distinct neural populations in the RTPJ?
CONTEXT: Current behavioral measures poorly predict treatment outcome in social anxiety disorder (SAD). To our knowledge, this is the first study to examine neuroimaging-based treatment prediction in SAD.
OBJECTIVE: To measure brain activation in patients with SAD as a biomarker to predict subsequent response to cognitive behavioral therapy (CBT).
DESIGN: Functional magnetic resonance imaging (fMRI) data were collected prior to CBT intervention. Changes in clinical status were regressed on brain responses and tested for selectivity for social stimuli.
Neuroimaging has revealed consistent activations in medial prefrontal cortex (MPFC) and posterior cingulate cortex (PCC) extending to precuneus both during explicit self-reference tasks and during rest, a period during which some form of self-reference is assumed to occur in the default mode of brain function.
We used real-time functional magnetic resonance imaging (fMRI) to determine which regions of the human brain have a role in vigilance as measured by reaction time (RT) to variably timed stimuli. We first identified brain regions where activation before stimulus presentation predicted RT. Slower RT was preceded by greater activation in the default-mode network, including lateral parietal, precuneus, and medial prefrontal cortices; faster RT was preceded by greater activation in the supplementary motor area (SMA).
Phonological awareness, knowledge that speech is composed of syllables and phonemes, is critical for learning to read. Phonological awareness precedes and predicts successful transition from language to literacy, and weakness in phonological awareness is a leading cause of dyslexia, but the brain basis of phonological awareness for spoken language in children is unknown.
Estimating moment-to-moment changes in blood oxygenation level dependent (BOLD) activation levels from functional magnetic resonance imaging (fMRI) data has applications for learned regulation of regional activation, brain state monitoring, and brain-machine interfaces. In each of these contexts, accurate estimation of the BOLD signal in as little time as possible is desired. This is a challenging problem due to the low signal-to-noise ratio of fMRI data.
Social anxiety disorder-related alterations in basal ganglia regions, such as striatum and globus pallidus, though evident from metabolic imaging, remain to be explored using seed-based resting-state functional connectivity magnetic resonance imaging. Capitalizing on the enhanced sensitivity of a multichannel array coil, we collected high-resolution (2-mm isotropic) data from medication-naive patients and healthy control participants.
The rate of learning or memory formation varies over time for any individual, partly due to moment-to-moment fluctuation of brain state. Functional neuroimaging has revealed the neural correlates of learning and memory, but here we asked if neuroimaging can causally enhance human learning by detection of brain states that reveal when a person is prepared or not prepared to learn. The parahippocampal cortex (PHC) is essential for memory formation for scenes.
The present study examined the relationship between hand preference degree and direction, functional language lateralization in Broca's and Wernicke's areas, and structural measures of the arcuate fasciculus. Results revealed an effect of degree of hand preference on arcuate fasciculus structure, such that consistently-handed individuals, regardless of the direction of hand preference, demonstrated the most asymmetric arcuate fasciculus, with larger left versus right arcuate, as measured by DTI.
In this paper, we propose a pipeline for evaluating the performance of brain image registration methods. Our aim is to compare how well the algorithms align subtle functional/anatomical boundaries that are not easily detectable in T1- or T2-weighted magnetic resonance images (MRI). In order to achieve this, we use structural connectivity information derived from diffusion-weighted MRI data. We demonstrate the approach by looking into how two competing registration algorithms perform at aligning fine-grained parcellations of subcortical structures.
