Type 2 diabetes (T2DM) patients develop vascular complications and have increased risk for neurophysiological impairment. Vascular pathophysiology may alter the blood flow regulation in cerebral microvasculature, affecting neurovascular coupling. Reduced fMRI signal can result from decreased neuronal activation or disrupted neurovascular coupling. The uncertainty about pathophysiological mechanisms (neurodegenerative, vascular, or both) underlying brain function impairments remains. In this cross-sectional study, we investigated if the hemodynamic response function (HRF) in lesion-free brains of patients is altered by measuring BOLD (Blood Oxygenation Level-Dependent) response to visual motion stimuli. We used a standard block design to examine the BOLD response and an event-related deconvolution approach. Importantly, the latter allowed for the first time to directly extract the true shape of HRF without any assumption and probe neurovascular coupling, using performance-matched stimuli. We discovered a change in HRF in early stages of diabetes. T2DM patients show significantly different fMRI response profiles. Our visual paradigm therefore demonstrated impaired neurovascular coupling in intact brain tissue. This implies that functional studies in T2DM require the definition of HRF, only achievable with deconvolution in event-related experiments. Further investigation of the mechanisms underlying impaired neurovascular coupling is needed to understand and potentially prevent the progression of brain function decrements in diabetes.

Neurofibromatosis Type 1 (NF1) is a common genetic condition associated with cognitive dysfunction. However, the pathophysiology of the NF1 cognitive deficits is not well understood. Abnormal brain structure, including increased total brain volume, white matter (WM) and grey matter (GM) abnormalities have been reported in the NF1 brain. These previous studies employed univariate model-driven methods preventing detection of subtle and spatially distributed differences in brain anatomy. Multivariate pattern analysis allows the combination of information from multiple spatial locations yielding a discriminative power beyond that of single voxels. Here we investigated for the first time subtle anomalies in the NF1 brain, using a multivariate data-driven classification approach. We used support vector machines (SVM) to classify whole-brain GM and WM segments of structural T1 -weighted MRI scans from 39 participants with NF1 and 60 non-affected individuals, divided in children/adolescents and adults groups. We also employed voxel-based morphometry (VBM) as a univariate gold standard to study brain structural differences. SVM classifiers correctly classified 94% of cases (sensitivity 92%; specificity 96%) revealing the existence of brain structural anomalies that discriminate NF1 individuals from controls. Accordingly, VBM analysis revealed structural differences in agreement with the SVM weight maps representing the most relevant brain regions for group discrimination. These included the hippocampus, basal ganglia, thalamus, and visual cortex. This multivariate data-driven analysis thus identified subtle anomalies in brain structure in the absence of visible pathology. Our results provide further insight into the neuroanatomical correlates of known features of the cognitive phenotype of NF1.

Neurofibromatosis type 1 (NF1) is one of the most common single gene disorders affecting the human nervous system with a high incidence of cognitive deficits, particularly visuospatial. Nevertheless, neurophysiological alterations in low-level visual processing that could be relevant to explain the cognitive phenotype are poorly understood. Here we used functional magnetic resonance imaging (fMRI) to study early cortical visual pathways in children and adults with NF1. We employed two distinct stimulus types differing in contrast and spatial and temporal frequencies to evoke relatively different activation of the magnocellular (M) and parvocellular (P) pathways. Hemodynamic responses were investigated in retinotopically-defined regions V1, V2 and V3 and then over the acquired cortical volume. Relative to matched control subjects, patients with NF1 showed deficient activation of the low-level visual cortex to both stimulus types. Importantly, this finding was observed for children and adults with NF1, indicating that low-level visual processing deficits do not ameliorate with age. Moreover, only during M-biased stimulation patients with NF1 failed to deactivate or even activated anterior and posterior midline regions of the default mode network. The observation that the magnocellular visual pathway is impaired in NF1 in early visual processing and is specifically associated with a deficient deactivation of the default mode network may provide a neural explanation for high-order cognitive deficits present in NF1, particularly visuospatial and attentional. A link between magnocellular and default mode network processing may generalize to neuropsychiatric disorders where such deficits have been separately identified.

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It remains an open question whether long-range disambiguation of ambiguous surface motion can be achieved in early visual cortex or instead in higher level regions, which concerns object/surface segmentation/integration mechanisms. We used a bistable moving stimulus that can be perceived as a pattern comprehending both visual hemi-fields moving coherently downward or as two widely segregated nonoverlapping component objects (in each visual hemi-field) moving separately inward. This paradigm requires long-range integration across the vertical meridian leading to interhemispheric binding. Our fMRI study (n = 30) revealed a close relation between activity in hMT+ and perceptual switches involving interhemispheric segregation/integration of motion signals, crucially under nonlocal conditions where components do not overlap and belong to distinct hemispheres. Higher signal changes were found in hMT+ in response to spatially segregated component (incoherent) percepts than to pattern (coherent) percepts. This did not occur in early visual cortex, unlike apparent motion, which does not entail surface segmentation. We also identified a role for top-down mechanisms in state transitions. Deconvolution analysis of switch-related changes revealed prefrontal, insula, and cingulate areas, with the right superior parietal lobule (SPL) being particularly involved. We observed that directed influences could emerge either from left or right hMT+ during bistable motion integration/segregation. SPL also exhibited significant directed functional connectivity with hMT+, during perceptual state maintenance (Granger causality analysis). Our results suggest that long-range interhemispheric binding of ambiguous motion representations mainly reflect bottom-up processes from hMT+ during perceptual state maintenance. In contrast, state transitions maybe influenced by high-level regions such as the SPL. Hum Brain Mapp 38:4882-4897, 2017. © 2017 Wiley Periodicals, Inc.