Repetition-related reductions in neural activity support improved behavior through increases in oscillatory power.

Repeatedly processing an object leads to subsequent behavioral improvements in its identification and reductions in associated neural activity, a form of neural processing efficiency that multiple theoretical models have attempted to explain. Using simultaneous fMRI-EEG in humans during object naming, we find that stimulus-driven oscillatory power from high (gamma) to low frequencies (theta) increases and resolves earlier with repetition in task-engaged frontal and occipitotemporal brain regions identified as showing repetition suppression in fMRI. Changes in gamma oscillatory power in these regions were correlated with behavioral priming across subjects and additionally with fMRI repetition suppression in left frontal cortex, providing multimodal support for a novel mixture of the previously proposed Synchrony and Facilitation models.

Go Figure: Transparency in neuroscience images preserves context and clarifies interpretation.

Visualizations are vital for communicating scientific results. Historically, neuroimaging figures have only depicted regions that surpass a given statistical threshold. This practice substantially biases interpretation of the results and subsequent meta-analyses, particularly towards non-reproducibility.

Theta-burst TMS to the posterior superior temporal sulcus decreases resting-state fMRI connectivity across the face processing network.

Humans process faces by using a network of face-selective regions distributed across the brain. Neuropsychological patient studies demonstrate that focal damage to nodes in this network can impair face recognition, but such patients are rare. We approximated the effects of damage to the face network in neurologically normal human participants by using theta burst transcranial magnetic stimulation (TBS).

Effectiveness of navigator-based prospective motion correction in MPRAGE data acquired at 3T.

In MRI, subject motion results in image artifacts. High-resolution 3D scans, like MPRAGE, are particularly susceptible to motion because of long scan times and acquisition of data over multiple-shots. Such motion related artifacts have been shown to cause a bias in cortical measures extracted from segmentation of high-resolution MPRAGE images.

Direct modulation of aberrant brain network connectivity through real-time NeuroFeedback.

The existence of abnormal connectivity patterns between resting state networks in neuropsychiatric disorders, including Autism Spectrum Disorder (ASD), has been well established. Traditional treatment methods in ASD are limited, and do not address the aberrant network structure. Using real-time fMRI neurofeedback, we directly trained three brain nodes in participants with ASD, in which the aberrant connectivity has been shown to correlate with symptom severity.

Evaluation of multi-echo ICA denoising for task based fMRI studies: Block designs, rapid event-related designs, and cardiac-gated fMRI.

Multi-echo fMRI, particularly the multi-echo independent component analysis (ME-ICA) algorithm, has previously proven useful for increasing the sensitivity and reducing false positives for functional MRI (fMRI) based resting state connectivity studies. Less is known about its efficacy for task-based fMRI, especially at the single subject level. This work, which focuses exclusively on individual subject results, compares ME-ICA to single-echo fMRI and a voxel-wise T2(⁎) weighted combination of multi-echo data for task-based fMRI under the following scenarios: cardiac-gated block designs, constant repetition time (TR) block designs, and constant TR rapid event-related designs.

ISMRM Raw data format: A proposed standard for MRI raw datasets.

Purpose: This work proposes the ISMRM Raw Data format as a common MR raw data format, which promotes algorithm and data sharing.

Methods: A file format consisting of a flexible header and tagged frames of k-space data was designed. Application Programming Interfaces were implemented in C/C++, MATLAB, and Python.

Task Dependence, Tissue Specificity, and Spatial Distribution of Widespread Activations in Large Single-Subject Functional MRI Datasets at 7T.

It was recently shown that when large amounts of task-based blood oxygen level-dependent (BOLD) data are combined to increase contrast- and temporal signal-to-noise ratios, the majority of the brain shows significant hemodynamic responses time-locked with the experimental paradigm. Here, we investigate the biological significance of such widespread activations. First, the relationship between activation extent and task demands was investigated by varying cognitive load across participants.

Periodic changes in fMRI connectivity.

The first two decades of brain research using fMRI have been dominated by studies that measure signal changes in response to a presented task. A rapidly increasing number of studies are showing that consistent activation maps appear by assessment of signal correlations during time periods in which the subjects were not directed to perform any specific task (i.e.

Single-shot magnetic field mapping embedded in echo-planar time-course imaging.

A technique for acquiring magnetic field maps simultaneously with gradient-recalled echo-planar time-course data is described. This technique uses a trajectory in which the central part of k-space is collected twice. For a 64 x 64 image acquired with a 125-kHz bandwidth, a field map suitable for geometric correction can be collected simultaneously with the echo-planar time-course data in <70 ms.