Functional reorganization of memory processing in the hippocampus is associated with neuroprotector GLP-1 levels in type 2 diabetes.

Type 2 diabetes (T2D) often impairs memory functions, suggesting specific vulnerability of the hippocampus. In vivo neuroimaging studies relating encoding and retrieval of memory information with endogenous neuroprotection are lacking. The neuroprotector glucagon-like peptide (GLP-1) has a high receptor density in anterior/ventral hippocampus, as shown by animal models. Using an innovative event-related fMRI design in 34 participants we investigated patterns of hippocampal activity in T2D (n = 17) without mild cognitive impairment (MCI) versus healthy controls (n = 17) during an episodic memory task. We directly measured neurovascular coupling by estimating the hemodynamic response function using event-related analysis related to encoding and retrieval of episodic information in the hippocampus. We applied a mixed-effects general linear model analysis and a two-factor ANOVA to test for group differences. Significant between-group differences were found for memory encoding, showing evidence for functional reorganization: T2D patients showed an augmented activation in the posterior hippocampus while anterior activation was reduced. The latter was negatively correlated with both GLP-1 pre- and post-breakfast levels, in the absence of grey matter changes. These results suggest that patients with T2D without MCI have pre-symptomatic functional reorganization in brain regions underlying episodic memory, as a function of the concentration of the neuroprotective neuropeptide GLP-1.

A human cortical adaptive mutual inhibition circuit underlying competition for perceptual decision and repetition suppression reversal.

A model based on inhibitory coupling has been proposed to explain perceptual oscillations. This 'adapting reciprocal inhibition' model postulates that it is the strength of inhibitory coupling that determines the fate of competition between percepts. Here, we used an fMRI-based adaptation technique to reveal the influence of neighboring neuronal populations, such as reciprocal inhibition, in motion-selective hMT+/V5. If reciprocal inhibition exists in this region, the following predictions should hold: 1. stimulus-driven response would not simply decrease, as predicted by simple repetition-suppression of neuronal populations, but instead, increase due to the activity from adjacent populations; 2. perceptual decision involving competing representations, should reflect decreased reciprocal inhibition by adaptation; 3. neural activity for the competing percept should also later on increase upon adaptation. Our results confirm these three predictions, showing that a model of perceptual decision based on adapting reciprocal inhibition holds true. Finally, they also show that the net effect of the well-known repetition suppression phenomenon can be reversed by this mechanism.

The longitudinal impact of type 2 diabetes on brain gyrification.

Type 2 diabetes has an effect on brain structure, including cortical gyrification. The significance of these changes is better understood if assessed over time. However, there is a lack of studies assessing longitudinally the effect of this disease with complex aethology in gyrification. While changes in this feature have been associated mainly with genetic legacy, our study allowed to shed light on the effect of the variation of glycaemic profile over time in gyrification in this metabolic disease. In this longitudinal study, we analysed brain anatomical magnetic resonance images of 15 participants with type 2 diabetes and 13 healthy control participants to investigate the impact of this metabolic disease on the gyrification index over a 7-year period. We observed a significant interaction between time and group in six regions, four of which (left precentral gyrus, left gyrus rectus, left subcentral gyrus and sulci and right inferior temporal gyrus) showed an increase in gyrification in type 2 diabetes and a decrease in the control group and the two others (left pericallosal sulcus and right inferior frontal sulcus) the opposite pattern. The variation of the gyrification was correlated with the variation of the glycaemic profile. Following the interaction, the simple main effect of time in each group separately has shown that in the group with diabetes, there were more regions susceptible to alterations of gyrification. In sum, our results raise credit for the possibility that glycaemic control also might influence gyrification in type 2 diabetes.

Functional neuroimaging of responses to multiple sensory stimulations in newborns with perinatal asphyxia.

Background: Functional neuroimaging can provide pathophysiological information in perinatal asphyxia (PA). However, fundamental unresolved questions remain related to the influence of neurovascular coupling (NVC) maturation on functional responses in early development. We aimed to probe the feasibility and compare the responses to multiple sensory stimulations in newborns with PA using functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS). Methods: Responses to visual, auditory, and sensorimotor passive stimulation were measured with fMRI and fNIRS and compared in 18 term newborns with PA and six controls. Results: Most newborns exhibited a positive fMRI response during visual and sensorimotor stimulation, higher in the sensorimotor. An asymmetric pattern (negative in the left hemisphere) was observed in auditory stimulation. The fNIRS response most resembling the adult pattern (positive) in PA occurred during auditory stimulation, in which oxyhemoglobin (HbO) increased, and deoxyhemoglobin (HbR) decreased. Significative differences were found in the HbO and HbR profiles in newborns with PA compared to the controls, more evident in auditory stimulation. Positive correlations between the fMRI BOLD signal and at least one fNIRS channel (HbO) in all stimuli in newborns with PA were identified: the strongest was in the auditory (r=0.704) and the weakest in the sensorimotor (r=0.544); in more fNIRS channels, in the visual. Conclusions: Both techniques are feasible physiological assessment tools, suggesting a distinctive level of maturation in sensory and motor areas. Differences in fNIRS profiles in newborns with PA and controls and the fMRI-fNIRS relationship observed can encourage the fNIRS as a clinically emergent valuable tool.

The role of early functional neuroimaging in predicting neurodevelopmental outcomes in neonatal encephalopathy.

Reliably assessing the early neurodevelopmental outcomes in infants with neonatal encephalopathy (NE) is of utmost importance to advise parents and implement early and personalized interventions. We aimed to evaluate the accuracy of neuroimaging modalities, including functional magnetic resonance imaging (fMRI) in predicting neurodevelopmental outcomes in NE. Eighteen newborns with NE due to presumed perinatal asphyxia (PA) were included in the study, 16 of whom underwent therapeutic hypothermia. Structural magnetic resonance imaging (MRI), and fMRI during passive visual, auditory, and sensorimotor stimulation were acquired between the 10th and 14th day of age. Clinical follow-up protocol included visual and auditory evoked potentials and a detailed neurodevelopmental evaluation at 12 and 18 months of age. Infants were divided according to sensory and neurodevelopmental outcome: severe, moderate disability, or normal. Structural MRI findings were the best predictor of severe disability with an AUC close to 1.0. There were no good predictors to discriminate between moderate disability versus normal outcome. Nevertheless, structural MRI measures showed a significant correlation with the scores of neurodevelopmental assessments. During sensorimotor stimulation, the fMRI signal in the right hemisphere had an AUC of 0.9 to predict absence of cerebral palsy (CP). fMRI measures during auditory and visual stimulation did not predict sensorineural hearing loss or cerebral visual impairment. CONCLUSION: In addition to structural MRI, fMRI with sensorimotor stimulation may open the gate to improve the knowledge of neurodevelopmental/motor prognosis if proven in a larger cohort of newborns with NE. WHAT IS KNOWN: • Establishing an early, accurate neurodevelopmental prognosis in neonatal encephalopathy remains challenging. • Although structural MRI has a central role in neonatal encephalopathy, advanced MRI modalities are gradually being explored to optimize neurodevelopmental outcome knowledge. WHAT IS NEW: • Newborns who later developed cerebral palsy had a trend towards lower fMRI measures in the right sensorimotor area during sensorimotor stimulation. • These preliminary fMRI results may improve future early delineation of motor prognosis in neonatal encephalopathy.

The hemodynamic response function as a type 2 diabetes biomarker: a data-driven approach.

Introduction: There is a need to better understand the neurophysiological changes associated with early brain dysfunction in Type 2 diabetes mellitus (T2DM) before vascular or structural lesions. Our aim was to use a novel unbiased data-driven approach to detect and characterize hemodynamic response function (HRF) alterations in T2DM patients, focusing on their potential as biomarkers. Methods: We meshed task-based event-related (visual speed discrimination) functional magnetic resonance imaging with DL to show, from an unbiased perspective, that T2DM patients' blood-oxygen-level dependent response is altered. Relevance analysis determined which brain regions were more important for discrimination. We combined explainability with deconvolution generalized linear model to provide a more accurate picture of the nature of the neural changes. Results: The proposed approach to discriminate T2DM patients achieved up to 95% accuracy. Higher performance was achieved at higher stimulus (speed) contrast, showing a direct relationship with stimulus properties, and in the hemispherically dominant left visual hemifield, demonstrating biological interpretability. Differences are explained by physiological asymmetries in cortical spatial processing (right hemisphere dominance) and larger neural signal-to-noise ratios related to stimulus contrast. Relevance analysis revealed the most important regions for discrimination, such as extrastriate visual cortex, parietal cortex, and insula. These are disease/task related, providing additional evidence for pathophysiological significance. Our data-driven design allowed us to compute the unbiased HRF without assumptions. Conclusion: We can accurately differentiate T2DM patients using a data-driven classification of the HRF. HRF differences hold promise as biomarkers and could contribute to a deeper understanding of neurophysiological changes associated with T2DM.

A neural network underlying cognitive strategies related to eating, weight and body image concerns.

Concerns about food intake, weight and body shape can trigger negatively loaded emotions, which may prompt the use of cognitive strategies to regulate these emotional states. A novel fMRI task was developed to assess the neurobehavioral correlates of cognitive strategies related to eating, weight and body image concerns, such as self-criticism, avoidance, rumination, and self-reassurance. Fourteen healthy females were presented audio sentences referring to these conditions and instructed to repeat these internally while engaging their thoughts with the content of food or body images. Participants were asked to report the elicited emotion and rate their performance. All cognitive strategies recruited a network including the inferior and superior frontal gyri, orbitofrontal and anterior cingulate cortex, insula, and dorsal striatum. These brain regions are involved in emotional, reward and inhibitory control processing. Representational similarity analysis revealed distinct patterns of neural responses for each cognitive strategy. Additionally, self-report measures showed that self-criticism was positively associated with superior frontal gyrus (SFG) activation. Self-compassion scores were negatively correlated with activations in the insula and right putamen, while self-reassurance scores were negatively associated with activity in the orbitofrontal cortex. These findings identify a neural network underlying cognitive strategies related to eating, weight and body image concerns, where neurobehavioral correlation patterns depend on the cognitive strategy.

A novel morphometric signature of brain alterations in type 2 diabetes: Patterns of changed cortical gyrification.

Type 2 diabetes is a chronic disease that creates atrophic signatures in the brain, including decreases of total and regional volume of grey matter, white matter and cortical thickness. However, there is a lack of studies assessing cortical gyrification in type 2 diabetes. Changes in this emerging feature have been associated mainly with genetic legacy, but environmental factors may also play a role. Here, we investigated alterations of the gyrification index and classical morphometric measures in type 2 diabetes, a late acquired disease with complex aetiology with both underlying genetic and more preponderant environmental factors. In this cross-sectional study, we analysed brain anatomical magnetic resonance images of 86 participants with type 2 diabetes and 40 healthy control participants, to investigate structural alterations in type 2 diabetes, including whole-brain volumetric measures, local alterations of grey matter volume, cortical thickness and the gyrification index. We found concordant significant decrements in total and regional grey matter volume, and cortical thickness. Surprisingly, the cortical gyrification index was found to be mainly increased and mainly located in cortical sensory areas in type 2 diabetes. Moreover, alterations in gyrification correlated with clinical data, suggesting an influence of metabolic profile in alterations of gyrification in type 2 diabetes. Further studies should address causal influences of genetic and/or environmental factors in patterns of cortical gyrification in type 2 diabetes.

The dual nature of the BOLD signal: Responses in visual area hMT+ reflect both input properties and perceptual decision.

Neuroimaging studies have suggested that hMT+ encodes global motion interpretation, but this contradicts the notion that BOLD activity mainly reflects neuronal input. While measuring fMRI responses at 7 Tesla, we used an ambiguous moving stimulus, yielding the perception of two incoherently moving surfaces-component motion-or only one coherently moving surface-pattern motion, to induce perceptual fluctuations and identify perceptual organization size-matched domains in hMT+. Then, moving gratings, exactly matching either the direction of component or pattern motion percepts of the ambiguous stimulus, were shown to the participants to investigate whether response properties reflect the input or decision. If hMT+ responses reflect the input, component motion domains (selective to incoherent percept) should show grating direction stimulus-dependent changes, unlike pattern motion domains (selective to the coherent percept). This hypothesis is based on the known direction-selective nature of inputs in component motion perceptual domains versus non-selectivity in pattern motion perceptual domains. The response amplitude of pattern motion domains did not change with grating direction (consistently with their non-selective input), in contrast to what happened for the component motion domains (consistently with their selective input). However, when we analyzed relative ratio measures they mirrored perceptual interpretation. These findings are consistent with the notion that patterns of BOLD responses reflect both sensory input and perceptual read-out.

Identification of competing neural mechanisms underlying positive and negative perceptual hysteresis in the human visual system.

Hysteresis is a well-known phenomenon in physics that relates changes in a system with its prior history. It is also part of human visual experience (perceptual hysteresis), and two different neural mechanisms might explain it: persistence (a cause of positive hysteresis), which forces to keep a current percept for longer, and adaptation (a cause of negative hysteresis), which in turn favors the switch to a competing percept early on. In this study, we explore the neural correlates underlying these mechanisms and the hypothesis of their competitive balance, by combining behavioral assessment with fMRI. We used machine learning on the behavioral data to distinguish between positive and negative hysteresis, and discovered a neural correlate of persistence at a core region of the ventral attention network, the anterior insula. Our results add to the understanding of perceptual multistability and reveal a possible mechanistic explanation for the regulation of different forms of perceptual hysteresis.

Tracking perceptual decision mechanisms through changes in interhemispheric functional connectivity in human visual cortex.

The role of long-range integration mechanisms underlying visual perceptual binding and their link to interhemispheric functional connectivity, as measured by fMRI, remains elusive. Only inferences on anatomical organization from resting state data paradigms not requiring coherent binding have been achieved. Here, we used a paradigm that allowed us to study such relation between perceptual interpretation and functional connectivity under bistable interhemispheric binding vs. non-binding of visual surfaces. Binding occurs by long-range perceptual integration of motion into a single object across hemifields and non-binding reflects opponent segregation of distinct moving surfaces into each hemifield. We hypothesized that perceptual integration vs. segregation of surface motion, which is achieved in visual area hMT+, is modulated by changes in interhemispheric connectivity in this region. Using 7T fMRI, we found that perceptual long-range integration of bistable motion can be tracked by changes in interhemispheric functional connectivity between left/right hMT+. Increased connectivity was tightly related with long-range perceptual integration. Our results indicate that hMT+ interhemispheric functional connectivity reflects perceptual decision, suggesting its pivotal role on long-range disambiguation of bistable physically constant surface motion. We reveal for the first time, at the scale of fMRI, a relation between interhemispheric functional connectivity and decision based perceptual binding.

Evidence for distinct levels of neural adaptation to both coherent and incoherently moving visual surfaces in visual area hMT.

Visual adaptation describes the processes by which the visual system alters its operating properties in response to changes in the environment. It is one of the mechanisms controlling visual perceptual bistability - when two perceptual solutions are available - by controlling the duration of each percept. Moving plaids are an example of such ambiguity. They can be perceived as two surfaces sliding incoherently over each other or as a single coherent surface. Here, we investigated, using fMRI, whether activity in the human motion complex (hMT+), a region tightly related to the perceptual integration of visual motion, is modulated by distinct forms of visual adaptation to coherent or incoherent perception of moving plaids. Our hypothesis is that exposure to global coherent or incoherent moving stimuli leads to different levels of measurable adaptation, reflected in hMT+ activity. We found that the strength of the measured visual adaptation effect depended on whether subjects integrated (coherent percept) or segregated (incoherent percept) surface motion signals. Visual motion adaptation was significant both for coherent motion and globally incoherent surface motion. Although not as strong as to the coherent percept, visual adaptation due to the incoherent percept also affects hMT+. This shows that adaptation can contribute to regulate percept duration during visual bistability, with distinct weights, depending on the type of percept. Our findings suggest a link between bistability and adaptation mechanisms, both due to coherent and incoherent motion percepts, but in an asymmetric manner. These asymmetric adaptation weights have strong implications in models of perceptual decision and may explain asymmetry of perceptual interpretation periods.

Permutations of functional magnetic resonance imaging classification may not be normally distributed.

A fundamental question that often occurs in statistical tests is the normality of distributions. Countless distributions exist in science and life, but one distribution that is obtained via permutations, usually referred to as permutation distribution, is interesting. Although a permutation distribution should behave in accord with the central limit theorem, if both the independence condition and the identical distribution condition are fulfilled, no studies have corroborated this concurrence in functional magnetic resonance imaging data. In this work, we used Anderson-Darling test to evaluate the accordance level of permutation distributions of classification accuracies to normality expected under central limit theorem. A simulation study has been carried out using functional magnetic resonance imaging data collected, while human subjects responded to visual stimulation paradigms. Two scrambling schemes are evaluated: the first based on permuting both the training and the testing sets and the second on permuting only the testing set. The results showed that, while a normal distribution does not adequately fit to permutation distributions most of the times, it tends to be quite well acceptable when mean classification accuracies averaged over a set of different classifiers is considered. The results also showed that permutation distributions can be probabilistically affected by performing motion correction to functional magnetic resonance imaging data, and thus may weaken the approximation of permutation distributions to a normal law. Such findings, however, have no relation to univariate/univoxel analysis of functional magnetic resonance imaging data. Overall, the results revealed a strong dependence across the folds of cross-validation and across functional magnetic resonance imaging runs and that may hinder the reliability of using cross-validation. The obtained p-values and the drawn confidence level intervals exhibited beyond doubt that different permutation schemes may beget different permutation distributions as well as different levels of accord with central limit theorem. We also found that different permutation schemes can lead to different permutation distributions and that may lead to different assessment of the statistical significance of classification accuracy.

Extending Inferential Group Analysis in Type 2 Diabetic Patients with Multivariate GLM Implemented in SPM8.

BACKGROUND: Although voxel based morphometry studies are still the standard for analyzing brain structure, their dependence on massive univariate inferential methods is a limiting factor. A better understanding of brain pathologies can be achieved by applying inferential multivariate methods, which allow the study of multiple dependent variables, e.g. different imaging modalities of the same subject. OBJECTIVE: Given the widespread use of SPM software in the brain imaging community, the main aim of this work is the implementation of massive multivariate inferential analysis as a toolbox in this software package. applied to the use of T1 and T2 structural data from diabetic patients and controls. This implementation was compared with the traditional ANCOVA in SPM and a similar multivariate GLM toolbox (MRM). METHOD: We implemented the new toolbox and tested it by investigating brain alterations on a cohort of twenty-eight type 2 diabetes patients and twenty-six matched healthy controls, using information from both T1 and T2 weighted structural MRI scans, both separately - using standard univariate VBM - and simultaneously, with multivariate analyses. RESULTS: Univariate VBM replicated predominantly bilateral changes in basal ganglia and insular regions in type 2 diabetes patients. On the other hand, multivariate analyses replicated key findings of univariate results, while also revealing the thalami as additional foci of pathology. CONCLUSION: While the presented algorithm must be further optimized, the proposed toolbox is the first implementation of multivariate statistics in SPM8 as a user-friendly toolbox, which shows great potential and is ready to be validated in other clinical cohorts and modalities.

Early visual cortical structural changes in diabetic patients without diabetic retinopathy.

BACKGROUND: It is known that diabetic patients have changes in cortical morphometry as compared to controls, but it remains to be clarified whether the visual cortex is a disease target, even when diabetes complications such as retinopathy are absent. Therefore, we compared type 2 diabetes patients without diabetic retinopathy with control subjects using magnetic resonance imaging to assess visual cortical changes when retinal damage is not yet present. METHODS: We performed T1-weighted imaging in 24 type 2 diabetes patients without diabetic retinopathy and 27 age- and gender-matched controls to compare gray matter changes in the occipital cortex between groups using voxel based morphometry. RESULTS: Patients without diabetic retinopathy showed reduced gray matter volume in the occipital lobe when compared with controls. CONCLUSIONS: Reduced gray matter volume in the occipital cortex was found in diabetic patients without retinal damage. We conclude that cortical early visual processing regions may be affected in diabetic patients even before retinal damage occurs.

Early disrupted neurovascular coupling and changed event level hemodynamic response function in type 2 diabetes: an fMRI study.

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.

Multivariate pattern analysis reveals subtle brain anomalies relevant to the cognitive phenotype in neurofibromatosis type 1.

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.

Abnormal brain activation in neurofibromatosis type 1: a link between visual processing and the default mode network.

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.