Echo planar imaging (EPI) is the method of choice for the majority of functional magnetic resonance imaging (fMRI), yet EPI is prone to geometric distortions and thus misaligns with conventional anatomical reference data. The poor geometric correspondence between functional and anatomical data can lead to severe misplacements and corruption of detected activation patterns. However, recent advances in imaging technology have provided EPI data with increasing quality and resolution. Here we present a framework for deriving cortical surface reconstructions directly from high-resolution EPI-based reference images that provide anatomical models exactly geometric distortion-matched to the functional data. Anatomical EPI data with 1mm isotropic voxel size were acquired using a fast multiple inversion recovery time EPI sequence (MI-EPI) at 7T, from which quantitative T1 maps were calculated. Using these T1 maps, volumetric data mimicking the tissue contrast of standard anatomical data were synthesized using the Bloch equations, and these T1-weighted data were automatically processed using FreeSurfer. The spatial alignment between T2(⁎)-weighted EPI data and the synthetic T1-weighted anatomical MI-EPI-based images was improved compared to the conventional anatomical reference. In particular, the alignment near the regions vulnerable to distortion due to magnetic susceptibility differences was improved, and sampling of the adjacent tissue classes outside of the cortex was reduced when using cortical surface reconstructions derived directly from the MI-EPI reference. The MI-EPI method therefore produces high-quality anatomical data that can be automatically segmented with standard software, providing cortical surface reconstructions that are geometrically matched to the BOLD fMRI data.

The MGH-USC CONNECTOM MRI scanner housed at the Massachusetts General Hospital (MGH) is a major hardware innovation of the Human Connectome Project (HCP). The 3T CONNECTOM scanner is capable of producing a magnetic field gradient of up to 300 mT/m strength for in vivo human brain imaging, which greatly shortens the time spent on diffusion encoding, and decreases the signal loss due to T2 decay. To demonstrate the capability of the novel gradient system, data of healthy adult participants were acquired for this MGH-USC Adult Diffusion Dataset (N=35), minimally preprocessed, and shared through the Laboratory of Neuro Imaging Image Data Archive (LONI IDA) and the WU-Minn Connectome Database (ConnectomeDB). Another purpose of sharing the data is to facilitate methodological studies of diffusion MRI (dMRI) analyses utilizing high diffusion contrast, which perhaps is not easily feasible with standard MR gradient system. In addition, acquisition of the MGH-Harvard-USC Lifespan Dataset is currently underway to include 120 healthy participants ranging from 8 to 90 years old, which will also be shared through LONI IDA and ConnectomeDB. Here we describe the efforts of the MGH-USC HCP consortium in acquiring and sharing the ultra-high b-value diffusion MRI data and provide a report on data preprocessing and access. We conclude with a demonstration of the example data, along with results of standard diffusion analyses, including q-ball Orientation Distribution Function (ODF) reconstruction and tractography.

Physical activity and exercise beneficially link to brain properties and cognitive functions in older adults, but the findings concerning adolescents remain tentative. During adolescence, the brain undergoes significant changes, which are especially pronounced in white matter. Studies provide contradictory evidence regarding the influence of physical activity or aerobic-exercise on executive functions in youth. Little is also known about the link between both fitness and physical activity with the brain's white matter during puberty. We investigated the connection between aerobic fitness and physical activity with the white matter in 59 adolescents. We further determined whether white matter interacts with the connection of fitness or physical activity with core executive functions. Our results show that only the level of aerobic fitness, but not of physical activity relates to white matter. Furthermore, the white matter of the corpus callosum and the right superior corona radiata moderates the links of aerobic fitness and physical activity with working memory. Our results suggest that aerobic fitness and physical activity have an unequal contribution to the white matter properties in adolescents. We propose that the differences in white matter properties could underlie the variations in the relationship between either physical activity or aerobic fitness with working memory.

Adolescents have experienced decreased aerobic fitness levels and insufficient physical activity levels over the past decades. While both physical activity and aerobic fitness are related to physical and mental health, little is known concerning how they manifest in the brain during this stage of development, characterized by significant physical and psychosocial changes. The aim of the study is to examine the associations between both physical activity and aerobic fitness with brains' functional connectivity.

Higher levels of aerobic fitness and physical activity are linked to beneficial effects on brain health, especially in older adults. The generalizability of these earlier results to young individuals is not straightforward, because physiological responses (such as cardiovascular responses) to exercise may depend on age. Earlier studies have mostly focused on the effects of either physical activity or aerobic fitness on the brain. Yet, while physical activity indicates the amount of activity, aerobic fitness is an adaptive state or attribute that an individual has or achieves. Here, by measuring both physical activity and aerobic fitness in the same study, we aimed to differentiate the association between these two measures and grey matter volume specifically. Magnetic resonance imaging scans were used to study volumes of 30 regions of interest located in the frontal, motor and subcortical areas of 60 adolescents (12.7-16.2 years old). Moderate-to-vigorous intensity physical activity (MVPA) was measured with hip-worn accelerometers and aerobic fitness was assessed with a 20-m shuttle run. Multiple regression analyses revealed a negative association between aerobic fitness and left superior frontal cortex volume and a positive association between aerobic fitness and the left pallidum volume. No associations were found between MVPA and any brain region of interest. These results demonstrate unequal contribution of physical activity and aerobic fitness on grey matter volumes, with inherent or achieved capacity (aerobic fitness) showing clearer associations than physical activity.

Functional MRI (fMRI) benefits from both increased sensitivity and specificity with increasing magnetic field strength, making it a key application for Ultra-High Field (UHF) MRI scanners. Most UHF-fMRI studies utilize the dramatic increases in sensitivity and specificity to acquire high-resolution data reaching sub-millimeter scales, which enable new classes of experiments to probe the functional organization of the human brain. This review article surveys advanced data analysis strategies developed for high-resolution fMRI at UHF. These include strategies designed to mitigate distortion and artifacts associated with higher fields in ways that attempt to preserve spatial resolution of the fMRI data, as well as recently introduced analysis techniques that are enabled by these extremely high-resolution data. Particular focus is placed on anatomically-informed analyses, including cortical surface-based analysis, which are powerful techniques that can guide each step of the analysis from preprocessing to statistical analysis to interpretation and visualization. New intracortical analysis techniques for laminar and columnar fMRI are also reviewed and discussed. Prospects for single-subject individualized analyses are also presented and discussed. Altogether, there are both specific challenges and opportunities presented by UHF-fMRI, and the use of proper analysis strategies can help these valuable data reach their full potential.

Humans use touch to maintain their social relationships, and the emotional qualities of touch depend on who touches whom. However, it is not known how affective and social dimensions of touch are processed in the brain. We measured haemodynamic brain activity with functional magnetic resonance imaging (fMRI) from 19 subjects (10 males), while they were touched on their upper thigh by either their romantic partner, or an unfamiliar female or male confederate or saw the hand of one of these individuals near their upper thigh but were not touched. We used multi-voxel pattern analysis on pre-defined regions of interest to reveal areas that encode social touch in a relationship-specific manner. The accuracy of the machine learning classifier to identify actor for both feeling touch and seeing hand exceeded the chance level in the primary somatosensory cortex, while in the insular cortex accuracy was above chance level only for the touch condition. When classifying the relationship (partner or stranger), while keeping the toucher sex fixed, amygdala (AMYG), orbitofrontal cortex (OFC), and primary and secondary somatosensory cortices were able to discriminate toucher significantly above chance level. These results suggest that information on the social relationship of the toucher is processed consistently across several regions. More complex information about toucher identity is processed in the primary somatosensory and insular cortices, both of which can be considered early sensory areas.

Studies of brain mechanisms supporting social interaction are demanding because real interaction only occurs when persons are in contact. Instead, most brain imaging studies scan subjects individually. Here we present a proof-of-concept demonstration of two-person blood oxygenation dependent (BOLD) imaging of brain activity from two individuals interacting inside the bore of a single MRI scanner. We developed a custom 16-channel (8 + 8 channels) two-helmet coil with two separate receiver-coil pairs providing whole-brain coverage, while bringing participants into a shared physical space and realistic face-to-face contact. Ten subject pairs were scanned with the setup. During the experiment, subjects took turns in tapping each other's lip versus observing and feeling the taps timed by auditory instructions. Networks of sensorimotor brain areas were engaged alternatingly in the subjects during executing motor actions as well as observing and feeling them; these responses were clearly distinguishable from the auditory responses occurring similarly in both participants. Even though the signal-to-noise ratio of our coil system was compromised compared with standard 32-channel head coils, our results show that the two-person fMRI scanning is feasible for studying the brain basis of social interaction.