Exploring structure and function of sensory cortex with 7 T MRI

In this paper, we present an overview of 7 Tesla magnetic resonance imaging (MRI) studies of the detailed function and anatomy of sensory areas of the human brain. We discuss the motivation for the studies, with particular emphasis on increasing the spatial resolution of functional MRI (fMRI) using reduced field-of-view (FOV) data acquisitions. MRI at ultra-high-field (UHF) – defined here as 7 T and above – has several advantages over lower field strengths. The intrinsic signal-to-noise ratio (SNR) of images is higher at UHF, and coupled with the increased blood-oxygen-level-dependent (BOLD) signal change, this results in increased BOLD contrast-to-noise ratio (CNR), which can be exploited to improve spatial resolution or detect weaker signals. Additionally, the BOLD signal from the intra-vascular (IV) compartment is relatively diminished compared to lower field strengths. Together, these properties make 7 T functional MRI an attractive proposition for high spatial specificity measures. But with the advantages come some challenges. For example, increased vulnerability to susceptibility-induced geometric distortions and signal loss in EPI acquisitions tend to be much larger. Some of these technical issues can be addressed with currently available tools and will be discussed. We highlight the key methodological considerations for high resolution functional and structural imaging at 7 T. We then present recent data using the high spatial resolution available at UHF in studies of the visual and somatosensory cortex to highlight promising developments in this area

The nonhuman primate neuroimaging and neuroanatomy project

Multi-modal neuroimaging projects such as the Human Connectome Project (HCP) and UK Biobank are advancing our understanding of human brain architecture, function, connectivity, and their variability across individuals using high-quality non-invasive data from many subjects. Such efforts depend upon the accuracy of non-invasive brain imaging measures. However, ‘ground truth’ validation of connectivity using invasive tracers is not feasible in humans. Studies using nonhuman primates (NHPs) enable comparisons between invasive and non-invasive measures, including exploration of how “functional connectivity” from fMRI and “tractographic connectivity” from diffusion MRI compare with long-distance connections measured using tract tracing. Our NonHuman Primate Neuroimaging & Neuroanatomy Project (NHP_NNP) is an international effort (6 laboratories in 5 countries) to: (i) acquire and analyze high-quality multi-modal brain imaging data of macaque and marmoset monkeys using protocols and methods adapted from the HCP; (ii) acquire quantitative invasive tract-tracing data for cortical and subcortical projections to cortical areas; and (iii) map the distributions of different brain cell types with immunocytochemical stains to better define brain areal boundaries. We are acquiring high-resolution structural, functional, and diffusion MRI data together with behavioral measures from over 100 individual macaques and marmosets in order to generate non-invasive measures of brain architecture such as myelin and cortical thickness maps, as well as functional and diffusion tractography-based connectomes. We are using classical and next-generation anatomical tracers to generate quantitative connectivity maps based on brain-wide counting of labeled cortical and subcortical neurons, providing ground truth measures of connectivity. Advanced statistical modeling techniques address the consistency of both kinds of data across individuals, allowing comparison of tracer-based and non-invasive MRI-based connectivity measures. We aim to develop improved cortical and subcortical areal atlases by combining histological and imaging methods. Finally, we are collecting genetic and sociality-associated behavioral data in all animals in an effort to understand how genetic variation shapes the connectome and behavior

High-Field Functional MRI from the Perspective of Single Vessels in Rats and Humans

Functional MRI (fMRI) has been employed to map brain activity and connectivity based on the neurovascular coupled hemodynamic signal. However, in most cases of fMRI studies, the cerebral vascular hemodynamic signal has been imaged in a spatially smoothed manner due to the limit of spatial resolution. There is a need to improve the spatiotemporal resolution of fMRI to map dynamic signal from individual venule or individual arteriole directly. Here, the thesis aims to provide a vascular-specific view of hemodynamic response during active state or resting state. To better characterize the temporal features of task-related fMRI signal from different vascular compartments, we implemented a line-scanning method to acquire vessel-specific blood-oxygen-level-dependent (BOLD) / cerebral-blood-volume (CBV) fMRI signal at 100-ms temporal resolution with sensory or optogenetic stimulation. Furthermore, we extended the line-scanning method with multi-echo scheme to provide vessel-specific fMRI with the higher contrast-to-noise ratio (CNR), which allowed us to directly map the distinct evoked hemodynamic signal from arterioles and venules at different echo time (TE) from 3 ms to 30 ms. The line-scanning fMRI methods acquire single k-space line per TR under a reshuffled k space acquisition scheme which has the limitation of sampling the fMRI signal in real-time for resting-state fMRI studies. To overcome this, we implemented a balanced Steady-state free precession (SSFP) to map task-related and resting-state fMRI (rsfMRI) with high spatial resolution in anesthetized rats. We reveal venule-dominated functional connectivity for BOLD fMRI and arteriole-dominated functional connectivity for CBV fMRI. The BOLD signal from individual venules and CBV signal from individual arterioles show correlations at an ultra-slow frequency (< 0.1 Hz), which are correlated with the intracellular calcium signal measured in neighboring neurons. In complementary data from awake human subjects, the BOLD signal is spatially correlated among sulcus veins and specified intracortical veins of the visual cortex at similar ultra-slow rhythms. This work provides a high-resolution fMRI approach to resolve brain activation and functional connectivity at the level of single vessels, which opened a new avenue to investigate brian functional connectivity at the scale of vessels

Neural representations of social and non-social uncertainty in human decision making

The social landscape is filled with an intricate web of species-specific desired objects and course of actions. Humans are highly social animals and, as they navigate this landscape, they need to produce adapted decision-making behaviour. Traditionally social and non-social neural mechanisms affecting choice have been investigated using different approaches. Recently, in an effort to unite these findings, two main theories have been proposed to explain how the brain might encode social and non-social motivational decision-making: the extended common currency and the social valuation specific schema (Ruff &#38; Fehr 2014). One way to test these theories is to directly compare neural activity related to social and non-social decision outcomes within the same experimental setting. Here we address this issue by focusing on the neural substrates of social and non-social forms of uncertainty. Using functional magnetic resonance imaging (fMRI) we directly compared the neural representations of reward and risk prediction and errors (RePE and RiPE) in social and non- social situations using gambling games. We used a trust betting game to vary uncertainty along a social dimension (trustworthiness), and a card game (Preuschoff et al. 2006) to vary uncertainty along a non-social dimension (pure risk). The trust game was designed to maintain the same structure of the card game. In a first study, we exposed a divide between subcortical and cortical regions when comparing the way these regions process social and non-social forms of uncertainty during outcome anticipation. Activity in subcortical regions reflected social and non-social RePE, while activity in cortical regions correlated with social RePE and non-social RiPE. The second study focused on outcome delivery and integrated the concept of RiPE in non-social settings with that of fairness and monetary utility maximisation in social settings. In particular these results corroborate recent models of anterior insula function (Singer et al. 2009; Seth 2013), and expose a possible neural mechanism that weights fairness and uncertainty but not monetary utility. The third study focused on functionally defined regions of the early visual cortex (V1) showing how activity in these areas, traditionally considered only visual, might reflect motivational prediction errors in addition to known perceptual prediction mechanisms (den Ouden et al 2012). On the whole, while our results do not support unilaterally one or the other theory modeling the underlying neural dynamics of social and non-social forms of decision making, they provide a working framework where both general mechanisms might coexist