Understanding the amazingly complex human cerebral cortex requires a map (or parcellation) of its major subdivisions, known as cortical areas. Making an accurate areal map has been a century-old objective in neuroscience. Using multi-modal magnetic resonance images from the Human Connectome Project (HCP) and an objective semi-automated neuroanatomical approach, we delineated 180 areas per hemisphere bounded by sharp changes in cortical architecture, function, connectivity, and/or topography in a precisely aligned group average of 210 healthy young adults. We characterized 97 new areas and 83 areas previously reported using post-mortem microscopy or other specialized study-specific approaches. To enable automated delineation and identification of these areas in new HCP subjects and in future studies, we trained a machine-learning classifier to recognize the multi-modal 'fingerprint' of each cortical area. This classifier detected the presence of 96.6% of the cortical areas in new subjects, replicated the group parcellation, and could correctly locate areas in individuals with atypical parcellations. The freely available parcellation and classifier will enable substantially improved neuroanatomical precision for studies of the structural and functional organization of human cerebral cortex and its variation across individuals and in development, aging, and disease.

ConnectomeDB is a database for housing and disseminating data about human brain structure, function, and connectivity, along with associated behavioral and demographic data. It is the main archive and dissemination platform for data collected under the WU-Minn consortium Human Connectome Project. Additional connectome-style study data is and will be made available in the database under current and future projects, including the Connectome Coordination Facility. The database currently includes multiple modalities of magnetic resonance imaging (MRI) and magnetoencephalograpy (MEG) data along with associated behavioral data. MRI modalities include structural, task, resting state and diffusion. MEG modalities include resting state and task. Imaging data includes unprocessed, minimally preprocessed and analysis data. Imaging data and much of the behavioral data are publicly available, subject to acceptance of data use terms, while access to some sensitive behavioral data is restricted to qualified investigators under a more stringent set of terms. ConnectomeDB is the public side of the WU-Minn HCP database platform. As such, it is geared towards public distribution, with a web-based user interface designed to guide users to the optimal set of data for their needs and a robust backend mechanism based on the commercial Aspera fasp service to enable high speed downloads. HCP data is also available via direct shipment of hard drives and Amazon S3.

Simultaneous multi-slice (SMS) or multiband (MB) imaging has recently been attempted for arterial spin labeled (ASL) perfusion MRI in conjunction with echo-planar imaging (EPI) readout. It was found that SMS-EPI can reduce the T1 relaxation effect of the label and improve image coverage and resolution with little penalty in signal-to-noise ratio (SNR). However, EPI still suffers from geometric distortion and signal dropout from field inhomogeneity effects especially at high and ultrahigh magnetic fields. Here we present a novel scheme for achieving high fidelity distortion-free quantitative perfusion imaging by combining pseudo-continuous ASL (pCASL) with SMS Turbo-FLASH (TFL) readout at both 3 and 7 T. Bloch equation simulation was performed to characterize and optimize the TFL-based pCASL perfusion signal. Two MB factors (3 and 5) were implemented in SMS-TFL pCASL and compared with standard 2D TFL and EPI pCASL sequences. The temporal SNR of SMS-TFL pCASL relative to that of standard TFL pCASL was 0.76 ± 0.10 and 0.74 ± 0.11 at 7 T and 0.70 ± 0.05 and 0.65 ± 0.05 at 3T for MB factor of 3 and 5, respectively. By implementing background suppression in conjunction with SMS-TFL at 3T, the relative temporal SNR improved to 0.84 ± 0.09 and 0.79 ± 0.10 for MB factor of 3 and 5, respectively. Compared to EPI pCASL, significantly increased temporal SNR (p<0.001) and improved visualization of orbitofrontal cortex were achieved using SMS-TFL pCASL. By combining SMS acceleration with TFL pCASL, we demonstrated the feasibility for whole brain distortion-free quantitative mapping of cerebral blood flow at high and ultrahigh magnetic fields.

Functional magnetic resonance imaging (fMRI) allows studying human brain function non-invasively up to the spatial resolution of cortical columns and layers. Most fMRI acquisitions rely on the blood oxygenation level dependent (BOLD) contrast employing T(*) 2 weighted 2D multi-slice echo-planar imaging (EPI). At ultra-high magnetic field (i.e., 7 T and above), it has been shown experimentally and by simulation, that T2 weighted acquisitions yield a signal that is spatially more specific to the site of neuronal activity at the cost of functional sensitivity. This study compared two T2 weighted imaging sequences, inner-volume 3D Gradient-and-Spin-Echo (3D-GRASE) and 2D Spin-Echo EPI (SE-EPI), with evaluation of their imaging point-spread function (PSF), functional specificity, and functional sensitivity at sub-millimeter resolution. Simulations and measurements of the imaging PSF revealed that the strongest anisotropic blurring in 3D-GRASE (along the second phase-encoding direction) was about 60% higher than the strongest anisotropic blurring in 2D SE-EPI (along the phase-encoding direction). In a visual paradigm, the BOLD sensitivity of 3D-GRASE was found to be superior due to its higher temporal signal-to-noise ratio (tSNR). High resolution cortical depth profiles suggested that the contrast mechanisms are similar between the two sequences, however, 2D SE-EPI had a higher surface bias owing to the higher T(*) 2 contribution of the longer in-plane EPI echo-train for full field of view compared to the reduced field of view of zoomed 3D-GRASE.

Linking individual task performance to preceding, regional brain activation is an ongoing goal of neuroscientific research. Recently, it could be shown that the activation and connectivity within large-scale brain networks prior to task onset influence performance levels. More specifically, prestimulus default mode network (DMN) effects have been linked to performance levels in sensory near-threshold tasks, as well as cognitive tasks. However, it still remains uncertain how the DMN state preceding cognitive tasks affects performance levels when the period between task trials is long and flexible, allowing participants to engage in different cognitive states.

fMRI provides spatial resolution that is unmatched by non-invasive neuroimaging techniques. Its temporal dynamics however are typically neglected due to the sluggishness of the hemodynamic signal.

Functional magnetic resonance imaging neurofeedback (fMRI-NF) training of areas involved in emotion processing can reduce depressive symptoms by over 40% on the Hamilton Depression Rating Scale (HDRS). However, it remains unclear if this efficacy is specific to feedback from emotion-regulating regions. We tested in a single-blind, randomized, controlled trial if upregulation of emotion areas (NFE) yields superior efficacy compared to upregulation of a control region activated by visual scenes (NFS). Forty-three moderately to severely depressed medicated patients were randomly assigned to five sessions augmentation treatment of either NFE or NFS training. At primary outcome (week 12) no significant group mean HDRS difference was found (B = -0.415 [95% CI -4.847 to 4.016], p = 0.848) for the 32 completers (16 per group). However, across groups depressive symptoms decreased by 43%, and 38% of patients remitted. These improvements lasted until follow-up (week 18). Both groups upregulated target regions to a similar extent. Further, clinical improvement was correlated with an increase in self-efficacy scores. However, the interpretation of clinical improvements remains limited due to lack of a sham-control group. We thus surveyed effects reported for accepted augmentation therapies in depression. Data indicated that our findings exceed expected regression to the mean and placebo effects that have been reported for drug trials and other sham-controlled high-technology interventions. Taken together, we suggest that the experience of successful self-regulation during fMRI-NF training may be therapeutic. We conclude that if fMRI-NF is effective for depression, self-regulation training of higher visual areas may provide an effective alternative.

Diffusion MRI provides important information about the brain white matter structures and has opened new avenues for neuroscience and translational research. However, acquisition time needed for advanced applications can still be a challenge in clinical settings. There is consequently a need to accelerate diffusion MRI acquisitions.

The central question of the relationship between structure and function in the human brain is still not well understood. In order to investigate this fundamental relationship we create functional probabilistic maps from a large set of mapping experiments and compare the location of functionally localised regions across subjects using different whole-brain alignment schemes. To avoid the major problems associated with meta-analysis approaches, all subjects are scanned using the same paradigms, the same scanner and the same analysis pipeline. We show that an advanced, curvature driven cortex based alignment (CBA) scheme largely removes macro-anatomical variability across subjects. Remaining variability in the observed spatial location of functional regions, thus, reflects the "true" functional variability, i.e. the quantified variability is a good estimator of the underlying structural-functional correspondence. After localising 13 widely studied functional areas, we found a large variability in the degree to which functional areas respect macro-anatomical boundaries across the cortex. Some areas, such as the frontal eye fields (FEF) are strongly bound to a macro-anatomical location. Fusiform face area (FFA) on the other hand, varies in its location along the length of the fusiform gyrus even though the gyri themselves are well aligned across subjects. Language areas were found to vary greatly across subjects whilst a high degree of overlap was observed in sensory and motor areas. The observed differences in functional variability for different specialised areas suggest that a more complete estimation of the structure-function relationship across the whole cortex requires further empirical studies with an expanded test battery.

Primate inferior temporal (IT) cortex is thought to contain a high-level representation of objects at the interface between vision and semantics. This suggests that the perceived similarity of real-world objects might be predicted from the IT representation. Here we show that objects that elicit similar activity patterns in human IT (hIT) tend to be judged as similar by humans. The IT representation explained the human judgments better than early visual cortex, other ventral-stream regions, and a range of computational models. Human similarity judgments exhibited category clusters that reflected several categorical divisions that are prevalent in the IT representation of both human and monkey, including the animate/inanimate and the face/body division. Human judgments also reflected the within-category representation of IT. However, the judgments transcended the IT representation in that they introduced additional categorical divisions. In particular, human judgments emphasized human-related additional divisions between human and non-human animals and between man-made and natural objects. hIT was more similar to monkey IT than to human judgments. One interpretation is that IT has evolved visual-feature detectors that distinguish between animates and inanimates and between faces and bodies because these divisions are fundamental to survival and reproduction for all primate species, and that other brain systems serve to more flexibly introduce species-dependent and evolutionarily more recent divisions.

The accuracy of forward models for electroencephalography (EEG) partly depends on head tissues geometry and strongly affects the reliability of the source reconstruction process, but it is not yet clear which brain regions are more sensitive to the choice of different model geometry. In this paper we compare different spherical and realistic head modeling techniques in estimating EEG forward solutions from current dipole sources distributed on a standard cortical space reconstructed from Montreal Neurological Institute (MNI) MRI data. Computer simulations are presented for three different four-shell head models, two with realistic geometry, either surface-based (BEM) or volume-based (FDM), and the corresponding sensor-fitted spherical-shaped model. Point Spread Function (PSF) and Lead Field (LF) cross-correlation analyses were performed for 26 symmetric dipole sources to quantitatively assess models' accuracy in EEG source reconstruction. Realistic geometry turns out to be a relevant factor of improvement, particularly important when considering sources placed in the temporal or in the occipital cortex.

The data presented here are related to the research article: "A cross-validated cytoarchitectonic atlas of the human ventral visual stream" in which we developed a cytoarchitectonic atlas of ventral visual cortex. Here, we provide two additional quantifications of this cytoarchitectonic atlas: First, we quantify the effect of brain template on cross-validation performance. The data show a comparison between cortex-based alignment to two templates: the postmortem average brain and the FreeSurfer average brain. Second, we quantify the relationship between this cytoarchitectonic atlas and a recently published multimodal atlas of the human brain (Glasser et al., 2016).

Neurofeedback training involves presenting an individual with a representation of their brain activity and instructing them to alter the activity using the feedback. One potential application of neurofeedback is for patients to alter neural activity to improve function. For example, there is evidence that greater laterality of movement-related activity is associated with better motor outcomes after stroke; so using neurofeedback to increase laterality may provide a novel route for improving outcomes. However, we must demonstrate that individuals can control relevant neurofeedback signals. Here, we performed two proof-of-concept studies, one in younger (median age: 26years) and one in older healthy volunteers (median age: 67.5years). The purpose was to determine if participants could manipulate laterality of activity between the motor cortices using real-time fMRI neurofeedback while performing simple hand movements. The younger cohort trained using their left and right hand, the older group trained using their left hand only. In both studies participants in a neurofeedback group were able to achieve more lateralized activity than those in a sham group (younger adults: F(1,23)=4.37, p<0.05; older adults: F(1,15)=9.08, p<0.01). Moreover, the younger cohort was able to maintain the lateralized activity for right hand movements once neurofeedback was removed. The older cohort did not maintain lateralized activity upon feedback removal, with the limitation being that they did not train with their right hand. The results provide evidence that neurofeedback can be used with executed movements to promote lateralized brain activity and thus is amenable for testing as a therapeutic intervention for patients following stroke.

The advent of ultra-high field functional magnetic resonance imaging (fMRI) has greatly facilitated submillimeter resolution acquisitions (voxel volume below (1mm³)), allowing the investigation of cortical columns and cortical depth dependent (i.e. laminar) structures in the human brain. Advanced data analysis techniques are essential to exploit the information in high resolution functional measures. In this article, we use recent, exemplary 9.4T human functional and anatomical data to review the advantages and disadvantages of (1) pooling high resolution data across regions of interest for cortical depth profile analysis, (2) pooling across cortical depths for mapping patches of cortex while discarding depth-dependent (i.e. columnar) effects, and (3) isotropic sampling without pooling to assess individual voxel's responses. A set of cortical depth meshes may be a solution to sampling information tangentially while keeping correspondence across depths. For quantitative analysis of the spatial organization in fine-grained structures, a cortical grid approach is advantageous. We further extend this general framework by combining it with a previously introduced cortical layer volume-preserving (equi-volume) approach. This framework can readily accommodate the research questions which allow for spatial smoothing within or across layers. We demonstrate and discuss that equi-volume sampling yields a slight advantage over equidistant sampling given the current limitations of fMRI voxel size, participant motion, coregistration and segmentation. Our 9.4T human anatomical and functional data indicate the advantage over lower fields including 7T and demonstrate the practical applicability of T2* and T2-weighted fMRI acquisitions.

The human superior temporal plane, the site of the auditory cortex, displays high inter-individual macro-anatomical variation. This questions the validity of curvature-based alignment (CBA) methods for in vivo imaging data. Here, we have addressed this issue by developing CBA+, which is a cortical surface registration method that uses prior macro-anatomical knowledge. We validate this method by using cytoarchitectonic areas on 10 individual brains (which we make publicly available). Compared to volumetric and standard surface registration, CBA+ results in a more accurate cytoarchitectonic auditory atlas. The improved correspondence of micro-anatomy following the improved alignment of macro-anatomy validates the superiority of CBA+ compared to CBA. In addition, we use CBA+ to align in vivo and postmortem data. This allows projection of functional and anatomical information collected in vivo onto the cytoarchitectonic areas, which has the potential to contribute to the ongoing debate on the parcellation of the human auditory cortex.

Richardson's syndrome (RS) is considered the most symmetric phenotype of progressive supranuclear palsy (PSP) as opposed to PSP with predominant corticobasal syndrome (PSP-CBS) or parkinsonism (PSP-P).

The present research investigated the neural correlates of nominal inflection and aimed at disclosing their possible link with the frequency distribution of noun inflectional features: grammatical gender, inflectional suffixes and inflectional classes. The properties of the Italian nominal system were exploited since it allows to explore exhaustively fine-grained phenomena in the inflectional processing. An event-related functional magnetic resonance imaging (fMRI) experiment was carried out where Italian masculine and feminine nouns were visually presented to 50 healthy participants in an overt inflectional task: the generation of the plural from the singular and vice versa. The grammatical gender and the citation form suffix of nouns were manipulated in a factorial design. Functional data showed that inflectional operations for nouns activate an extensive cortical network involving the left inferior and right superior frontal gyri, the left and right middle temporal gyri, the posterior cingulate cortex and the cerebellum. Activations were variably modulated by the distributional features of gender-dependent properties of nouns. Particularly, cortical activity increased during inflectional operations for small and/or scarcely consistent inflectional classes. These findings demonstrate the relevance of specific morphological (inflectional suffixes) and distributional features (size and consistency) shared by groups of words (inflectional classes) in a language, particularly when implementing cognitive operations required for language processing.

Cerebral blood volume (CBV) has been shown to be a robust and important physiological parameter for quantitative interpretation of functional (f)MRI, capable of delivering highly localized mapping of neural activity. Indeed, with recent advances in ultra-high-field (≥7T) MRI hardware and associated sequence libraries, it has become possible to capture non-invasive CBV weighted fMRI signals across cortical layers. One of the most widely used approaches to achieve this (in humans) is through vascular-space-occupancy (VASO) fMRI. Unfortunately, the exact contrast mechanisms of layer-dependent VASO fMRI have not been validated for human fMRI and thus interpretation of such data is confounded. Here we validate the signal source of layer-dependent SS-SI VASO fMRI using multi-modal imaging in a rat model in response to neuronal activation (somatosensory cortex) and respiratory challenge (hypercapnia). In particular VASO derived CBV measures are directly compared to concurrent measures of total haemoglobin changes from high resolution intrinsic optical imaging spectroscopy (OIS). Quantified cortical layer profiling is demonstrated to be in agreement between VASO and contrast enhanced fMRI (using monocrystalline iron oxide nanoparticles, MION). Responses show high spatial localisation to layers of cortical processing independent of confounding large draining veins which can hamper BOLD fMRI studies, (depending on slice positioning). Thus, a cross species comparison is enabled using VASO as a common measure. We find increased VASO based CBV reactivity (3.1 ± 1.2 fold increase) in humans compared to rats. Together, our findings confirm that the VASO contrast is indeed a reliable estimate of layer-specific CBV changes. This validation study increases the neuronal interpretability of human layer-dependent VASO fMRI as an appropriate method in neuroscience application studies, in which the presence of large draining intracortical and pial veins limits neuroscientific inference with BOLD fMRI.

Prolonged mastication may induce an asymmetric modification of the local perfusion of the trigeminal principal nucleus. The aim of the present study was to evaluate the possible influence of vitamin C (vit. C) on such effect. Four groups of healthy volunteers underwent arterial spin labeling magnetic resonance imaging (ASL-MRI) to evaluate the local perfusion of the trigeminal nuclei after a vit. C-enriched lunch or a control lunch. Two ASL-MRI scans were acquired, respectively, before and after a 1 h-long masticating exercise or a 1 h long resting period. The results showed (i) an increased global perfusion of the brain in the vit. C-enriched lunch groups, (ii) an increased local perfusion of the right principal trigeminal nucleus (Vp) due to mastication, and (iii) a reduction of the rightward asymmetry of the Vp perfusion, due to mastication, after the vit C-enriched meal compared to the control meal. These results confirmed a long-lasting effect of prolonged mastication on Vp perfusion and also suggest a possible effect of vit. C on cerebral vascular tone regulation. Moreover, the data strongly draw attention on the side-to-side relation in Vp perfusion as a possible physiological parameter to be considered to understand the origin of pathological conditions like migraine.

Human brain undergoes rapid growth during the first few years of life. While previous research has employed graph theory to study early brain development, it has mostly focused on the topological attributes of the whole brain. However, examining regional graph-theory features may provide unique insights into the development of cognitive abilities. Utilizing a large and longitudinal rsfMRI dataset from the UNC/UMN Baby Connectome Project, we investigated the developmental trajectories of regional efficiency and evaluated the relationships between these changes and cognitive abilities using Mullen Scales of Early Learning during the first twenty-eight months of life. Our results revealed a complex and spatiotemporally heterogeneous development pattern of regional global and local efficiency during this age period. Furthermore, we found that the trajectories of the regional global efficiency at the left temporal occipital fusiform and bilateral occipital fusiform gyri were positively associated with cognitive abilities, including visual reception, expressive language, receptive language, and early learning composite scores (P < 0.05, FDR corrected). However, these associations were weakened with age. These findings offered new insights into the regional developmental features of brain topologies and their associations with cognition and provided evidence of ongoing optimization of brain networks at both whole-brain and regional levels.