Multilevel convergence of interoceptive impairments in hypertension: New evidence of disrupted body-brain interactions.

Interoception, the sensing of visceral body signals, involves an interplay between neural and autonomic mechanisms. Clinical studies into this domain have focused on patients with neurological and psychiatric disorders, showing that damage to relevant brain mechanisms can variously alter interoceptive functions. However, the association between peripheral cardiac-system alterations and neurocognitive markers of interoception remains poorly understood. To bridge this gap, we examined multidimensional neural markers of interoception in patients with early stage of hypertensive disease (HTD) and healthy controls. Strategically, we recruited only HTD patients without cognitive impairment (as shown by neuropsychological tests), brain atrophy (as assessed with voxel-based morphometry), or white matter abnormalities (as evidenced by diffusion tensor imaging analysis). Interoceptive domains were assessed through (a) a behavioral heartbeat detection task; (b) measures of the heart-evoked potential (HEP), an electrophysiological cortical signature of attention to cardiac signals; and (c) neuroimaging recordings (MRI and fMRI) to evaluate anatomical and functional connectivity properties of key interoceptive regions (namely, the insula and the anterior cingulate cortex). Relative to controls, patients exhibited poorer interoceptive performance and reduced HEP modulations, alongside an abnormal association between interoceptive performance and both the volume and functional connectivity of the above regions. Such results suggest that peripheral cardiac-system impairments can be associated with abnormal behavioral and neurocognitive signatures of interoception. More generally, our findings indicate that interoceptive processes entail bidirectional influences between the cardiovascular and the central nervous systems.

Tackling variability: A multicenter study to provide a gold-standard network approach for frontotemporal dementia.

Biomarkers represent a critical research area in neurodegeneration disease as they can contribute to studying potential disease-modifying agents, fostering timely therapeutic interventions, and alleviating associated financial costs. Functional connectivity (FC) analysis represents a promising approach to identify early biomarkers in specific diseases. Yet, virtually no study has tested whether potential FC biomarkers prove to be reliable and reproducible across different centers. As such, their implementation remains uncertain due to multiple sources of variability across studies: the numerous international centers capable conducting FC research vary in their scanning equipment and their samples' socio-cultural background, and, more troublingly still, no gold-standard method exists to analyze FC. In this unprecedented study, we aim to address both issues by performing the first multicenter FC research in the behavioral-variant frontotemporal dementia (bvFTD), and by assessing multiple FC approaches to propose a gold-standard method for analysis. We enrolled 52 bvFTD patients and 60 controls from three international clinics (with different fMRI recording parameters), and three additional neurological patient groups. To evaluate FC, we focused on seed analysis, inter-regional connectivity, and several graph-theory approaches. Only graph-theory analysis, based on weighted-matrices, yielded consistent differences between bvFTD and controls across centers. Also, graph metrics robustly discriminated bvFTD from the other neurological conditions. The consistency of our findings across heterogeneous contexts highlights graph-theory as a potential gold-standard approach for brain network analysis in bvFTD. Hum Brain Mapp 38:3804-3822, 2017. © 2017 Wiley Periodicals, Inc.

Processing Time Reduction: an Application in Living Human High-Resolution Diffusion Magnetic Resonance Imaging Data.

High Angular Resolution Diffusion Imaging (HARDI) is a type of brain imaging that collects a very large amount of data, and if many subjects are considered then it amounts to a big data framework (e.g., the human connectome project has 20 Terabytes of data). HARDI is also becoming increasingly relevant for clinical settings (e.g., detecting early cerebral ischemic changes in acute stroke, and in pre-clinical assessment of white matter-WM anatomy using tractography). Thus, this method is becoming a routine assessment in clinical settings. In such settings, the computation time is critical, and finding forms of reducing the processing time in high computation processes such as Diffusion Spectrum Imaging (DSI), a form of HARDI data, is very relevant to increase data-processing speed. Here we analyze a method for reducing the computation time of the dMRI-based axonal orientation distribution function h by using Monte Carlo sampling-based methods for voxel selection. Results evidenced a robust reduction in required data sampling of about 50 % without losing signal's quality. Moreover, we show that the convergence to the correct value in this type of Monte Carlo HARDI/DSI data-processing has a linear improvement in data-processing speed of the ODF determination. Although further improvements are needed, our results represent a promissory step for future processing time reduction in big data.

Early bilateral and massive compromise of the frontal lobes.

The frontal lobes are one of the most complex brain structures involved in both domain-general and specific functions. The goal of this work was to assess the anatomical and cognitive affectations from a unique case with massive bilateral frontal affectation. We report the case of GC, an eight-year old child with nearly complete affectation of bilateral frontal structures and spared temporal, parietal, occipital, and cerebellar regions. We performed behavioral, neuropsychological, and imaging (MRI, DTI, fMRI) evaluations. Neurological and neuropsychological examinations revealed a mixed pattern of affected (executive control/abstraction capacity) and considerably preserved (consciousness, language, memory, spatial orientation, and socio-emotional) functions. Both structural (DTI) and functional (fMRI) connectivity evidenced abnormal anterior connections of the amygdala and parietal networks. In addition, brain structural connectivity analysis revealed almost complete loss of frontal connections, with atypical temporo-posterior pathways. Similarly, functional connectivity showed an aberrant frontoparietal network and relative preservation of the posterior part of the default mode network and the visual network. We discuss this multilevel pattern of behavioral, structural, and functional connectivity results. With its unique pattern of compromised and preserved structures and functions, this exceptional case offers new constraints and challenges for neurocognitive theories.

Histological validation of high-resolution DTI in human post mortem tissue.

Diffusion tensor imaging (DTI) is amongst the simplest mathematical models available for diffusion magnetic resonance imaging, yet still by far the most used one. Despite the success of DTI as an imaging tool for white matter fibers, its anatomical underpinnings on a microstructural basis remain unclear. In this study, we used 65 myelin-stained sections of human premotor cortex to validate modeled fiber orientations and oft used microstructure-sensitive scalar measures of DTI on the level of individual voxels. We performed this validation on high spatial resolution diffusion MRI acquisitions investigating both white and gray matter. We found a very good agreement between DTI and myelin orientations with the majority of voxels showing angular differences less than 10°. The agreement was strongest in white matter, particularly in unidirectional fiber pathways. In gray matter, the agreement was good in the deeper layers highlighting radial fiber directions even at lower fractional anisotropy (FA) compared to white matter. This result has potentially important implications for tractography algorithms applied to high resolution diffusion MRI data if the aim is to move across the gray/white matter boundary. We found strong relationships between myelin microstructure and DTI-based microstructure-sensitive measures. High FA values were linked to high myelin density and a sharply tuned histological orientation profile. Conversely, high values of mean diffusivity (MD) were linked to bimodal or diffuse orientation distributions and low myelin density. At high spatial resolution, DTI-based measures can be highly sensitive to white and gray matter microstructure despite being relatively unspecific to concrete microarchitectural aspects.

Definition of displacement probability and diffusion time in q-space magnetic resonance measurements that use finite-duration diffusion-encoding gradients.

In q-space diffusion NMR, the probability P(r,td) of a molecule having a displacement r in a diffusion time td is obtained under the assumption that the diffusion-encoding gradient g has an infinitesimal duration. However, this assumption may not always hold, particularly in human MRI where the diffusion-encoding gradient duration delta is typically of the same order of magnitude as the time offset Delta between encoding gradients. In this case, finite-delta effects complicate the interpretation of displacement probabilities measured in q-space MRI, and the form by which the signal intensity relates to them. By considering the displacement-specific dephasing, , of a set of spins accumulating a constant displacement vector r in the total time Delta+delta during which diffusion is encoded, the probability recovered by a finite-delta q-space experiment can be interpreted. It is shown theoretically that a data analysis using a modified q-space index q=gammadeltaetag, with gamma the gyromagnetic ratio and eta=square root (Delta-delta/3)/(Delta+delta), recovers the correct displacement probability distribution if diffusion is multi-Gaussian free diffusion. With this analysis, we show that the displacement distribution P(r,texp) is measured at the experimental diffusion-encoding time texp=Delta+delta, and not at the reduced diffusion time tr=Delta-delta/3 as is generally assumed in the NMR and MRI literature. It is also shown that, by defining a probability P(y,Delta) that a time tdeltac then eta is not equal to square root (Delta-delta/3)/(Delta+delta) which implies that we can no longer obtain the correct displacement probability from the displacement distribution. In the case that /g/=18 mT/m and Delta-delta=5 ms, the parameter deltac in ms is given by "deltac=0.49a2+0.24" where a is the sphere's radius expressed in microm. Simulation of q-space restricted diffusion MRI experiments indicate that if eta=square root (Delta-delta/3)/(Delta+delta), the recovered displacement probability is always better than the Gaussian approximation, and the measured diffusion coefficient matches the diffusion coefficient at time texp=Delta+delta better than it matches the diffusion coefficient at time tr=Delta-delta/3. These results indicate that q-space MRI measurements of displacement probability distributions are theoretically possible in biological tissues using finite-duration diffusion-encoding gradients provided certain compartment size and diffusion encoding gradient duration constraints are met.

Use of Shannon information in treatment of high resolution diffusion MRI.

Diffusion MRI allows the obtaining of an approximation of the water displacement's probability density function (PDF) and orientation distribution function (ODF). Examples of techniques used in obtaining these distributions being q-space imaging (QSI), and q-ball imaging (QBI), respectively. Shannon information quantifies the discriminative power of a symbol based on its probability. We quantified the information amount of a white matter fiber bundle being used to discriminate those fibers using specific diffusion MRI data treatment techniques. The equations developed are new and it is also described how they will help in future experimental calculations. An example of experimental ODF surfaces and ODF based white matter fiber tracking in living humans is also shown to highlight possible future advantages of Shannon information usage in describing crossing white matter fiber bundles.

Obsessive-compulsive disorder as a visual processing impairment.

OCD has been hypothesized to involve the failures in both cognitive and behavioral inhibitory processes. There is evidence that the hyperactivation of cortical-subcortical pathways may be involved in the failure of these inhibitory systems associated with OCD. Despite this consensus on the role of frontal-subcortical pathways in OCD, recent studies have been showing that brain regions other than the frontal-subcortical loops may be needed to understand the different cognitive and emotional deficits in OCD. Some studies have been finding evidence for decreased metabolic activity in areas such as left inferior parietal and parieto-occipital junction suggesting the possible existence of visual processing deficits. While there has been inconsistent data regarding visual processing in OCD, recent studies have been claiming that these patients have abnormal patterns of visual processing social rich stimuli, particularly emotional arousing stimuli. Thus, in this article, we hypothesize that the fronto-subcortical activation consistently found in OCD may be due to a deactivation of occipital/parietal regions associated with visual-perceptual processing of incoming social rich stimuli. Additionally, this dissociation may be more evident as the emotional intensity of the social stimulus increases.

MRI diffusion tensor tracking of a new amygdalo-fusiform and hippocampo-fusiform pathway system in humans.

PURPOSE: To use MRI diffusion-tensor tracking (DTT) to test for the presence of unknown neuronal fiber pathways interconnecting the mid-fusiform cortex and anteromedial temporal lobe in humans. Such pathways are hypothesized to exist because these regions coactivate in functional MRI (fMRI) studies of emotion-valued faces and words, suggesting a functional link that could be mediated by neuronal connections. MATERIALS AND METHODS: A total of 15 normal human subjects were studied using unbiased DTT approaches designed for probing unknown pathways, including whole-brain seeding and large pathway-selection volumes. Several quality-control steps verified the results. RESULTS: Parallel amygdalo-fusiform and hippocampo-fusiform pathways were found in all subjects. The pathways begin/end at the mid-fusiform gyrus above the lateral occipitotemporal sulcus bilaterally. The superior pathway ends/begins at the superolateral amygdala. The inferior pathway crosses medially and ends/begins at the hippocampal head. The pathways are left-lateralized, with consistently larger cross-sectional area, higher anisotropy, and lower minimum eigenvalue (D-min) on the left, where D-min assesses intrinsic cross-fiber diffusivity independent of curvature. CONCLUSION: A previously-undescribed pathway system interconnecting the mid-fusiform region with the amygdala/hippocampus has been revealed. This pathway system may be important for recognition, memory consolidation, and emotional modulation of face, object, and lexical information, which may be disrupted in conditions such as Alzheimer's disease.