Mapping cognitive function

Data-driven prediction of regional brain metabolism using neuropsychological assessment in Alzheimer's disease and behavioral variant Frontotemporal dementia

BACKGROUND

This study aimed to evaluate the capacity of neuropsychological assessment to predict the regional brain metabolism in a cohort of patients with amnestic Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) using Machine Learning algorithms.

METHODS

We included 360 subjects, consisting of 186 patients with AD, 87 with bvFTD, and 87 cognitively healthy controls. All participants underwent a neuropsychological assessment using the Addenbrooke's Cognitive Examination and the Neuronorma battery, in addition to [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) imaging. We trained Machine Learning algorithms, including artificial neural networks (ANN) and models that incorporate genetic algorithms (GAs), to predict the presence of regional hypometabolism in FDG-PET imaging based on cognitive testing results.

RESULTS

The proposed models demonstrated the ability to predict hypometabolism trends with approximately 70% accuracy in key regions associated with AD and bvFTD. In addition, we showed that incorporating neuropsychological tests provided relevant information for predicting brain hypometabolism. The temporal lobe was the best-predicted region, followed by the parietal, frontal, and some areas in the occipital lobe. Diagnosis played a significant role in the estimation of hypometabolism, and several neuropsychological tests were identified as the most important predictors for different brain regions. In our experiments, classical Machine Learning models, such as support vector machines enhanced by a preliminary feature selection step using GAs outperformed ANNs.

CONCLUSIONS

A successful prediction of regional brain metabolism of patients with AD and bvFTD was achieved based on the results of neuropsychological examination and Machine Learning algorithms. These findings support the neurobiological validity of neuropsychological examination and the feasibility of a topographical diagnosis in patients with neurodegenerative disorders.

Modulation of neural gene networks by estradiol in old rhesus macaque females

The postmenopausal decrease in circulating estradiol (E2) levels has been shown to contribute to several adverse physiological and psychiatric effects. To elucidate the molecular effects of E2 on the brain, we examined differential gene expression and DNA methylation (DNAm) patterns in the nonhuman primate brain following ovariectomy (Ov) and subsequent subcutaneous bioidentical E2 chronic treatment. We identified several dysregulated molecular networks, including MAPK signaling and dopaminergic synapse response, that are associated with ovariectomy and shared across two different brain areas, the occipital cortex (OC) and prefrontal cortex (PFC). The finding that hypomethylation (p = 1.6 × 10-51) and upregulation (p = 3.8 × 10-3) of UBE2M across both brain regions provide strong evidence for molecular differences in the brain induced by E2 depletion. Additionally, differential expression (p = 1.9 × 10-4; interaction p = 3.5 × 10-2) of LTBR in the PFC provides further support for the role E2 plays in the brain, by demonstrating that the regulation of some genes that are altered by ovariectomy may also be modulated by Ov followed by hormone replacement therapy (HRT). These results present real opportunities to understand the specific biological mechanisms that are altered with depleted E2. Given E2's potential role in cognitive decline and neuroinflammation, our findings could lead to the discovery of novel therapeutics to slow cognitive decline. Together, this work represents a major step toward understanding molecular changes in the brain that are caused by ovariectomy and how E2 treatment may revert or protect against the negative neuro-related consequences caused by a depletion in estrogen as women approach menopause.

Modulation of neural gene networks by estradiol in old rhesus macaque females

The postmenopausal decrease in circulating estradiol (E2) levels has been shown to contribute to several adverse physiological and psychiatric effects. To elucidate the molecular effects of E2 on the brain, we examined differential gene expression and DNA methylation (DNAm) patterns in the nonhuman primate brain following ovariectomy (Ov) and subsequent E2 treatment. We identified several dysregulated molecular networks, including MAPK signaling and dopaminergic synapse response, that are associated with ovariectomy and shared across two different brain areas, the occipital cortex (OC) and prefrontal cortex (PFC). The finding that hypomethylation (p=1.6×10-51) and upregulation (p=3.8×10-3) of UBE2M across both brain regions, provide strong evidence for molecular differences in the brain induced by E2 depletion. Additionally, differential expression (p=1.9×10-4; interaction p=3.5×10-2) of LTBR in the PFC, provides further support for the role E2 plays in the brain, by demonstrating that the regulation of some genes that are altered by ovariectomy may also be modulated by Ov followed by hormone replacement therapy (HRT). These results present real opportunities to understand the specific biological mechanisms that are altered with depleted E2. Given E2's potential role in cognitive decline and neuroinflammation, our findings could lead to the discovery of novel therapeutics to slow cognitive decline. Together, this work represents a major step towards understanding molecular changes in the brain that are caused by ovariectomy and how E2 treatment may revert or protect against the negative neuro-related consequences caused by a depletion in estrogen as women approach menopause.

Effects of estradiol supplementation on the brain transcriptome of old rhesus macaques maintained on an obesogenic diet

Obesity, the cessation of ovarian steroids with menopause, and age are risk factors for mood disorders, dementia, and Alzheimer's disease (AD). However, immediate hormone therapy (HT) after menopause may have beneficial effects in different brain regions involved in memory and cognition. To more closely replicate the age, endocrine, and metabolic environment of obese postmenopausal women, either on or off HT, middle-aged female rhesus macaques were ovariectomized/hysterectomized (OvH) and maintained on a high-fat, high-sugar, obesogenic Western-style diet (WSD) for 30 months; half of the animals received HT immediately after OvH and half served as placebo controls. RNAseq of the occipital (OC) and prefrontal cortex (PFC), hippocampus (HIP), and amygdala (AMG) identified 293, 379, 505, and 4993 differentially expressed genes (DEGs), respectively. Pathway enrichment analysis identified an activation of neuroinflammation in OC and HIP, but an inhibition in the AMG with HT. Synaptogenesis, circadian rhythm, mitochondrial dysfunction, mTOR, glutamate, serotonin, GABA, dopamine, epinephrine/norepinephrine, glucocorticoid receptor signaling, neuronal NOS, and amyloid processing were exclusively enriched in AMG. As compared to the placebo control group, most of these signaling pathways are downregulated after HT, suggesting a protective effect of HT in OvH females under a WSD. Overall, our results suggest that a chronic obesogenic diet may induce a wide range of alterations in multiple signaling pathways that are linked to age-associated brain pathology and dementia. In these individuals, HT seems to have a protective effect against neuroinflammation, amyloid beta depositions, and tau tangle formation.

Revisiting the Morphology and Classification of the Paracingulate Gyrus with Commentaries on Ambiguous Cases

The anterior cingulate cortex is considered to play a crucial role in cognitive and affective regulation. However, this area shows a high degree of morphological interindividual variability and asymmetry. It is especially true regarding the paracingulate sulcus and paracingulate gyrus (PCG). Since the reports described in the literature are mainly based on imaging techniques, the goal of this study was to verify the classification of the PCG based on anatomical material. Special attention was given to ambiguous cases. The PCG was absent in 26.4% of specimens. The gyrus was classified as present in 28.3% of cases. The prominent type of the PCG was observed in 37.7% of the total. Occasionally, the gyrus was well-developed and roughly only a few millimeters were missing for classifying the gyrus as prominent, as it ended slightly anterior the level of the VAC. The remaining four cases involved two inconclusive types. We observed that the callosomarginal artery ran within the cingulate sulcus and provided branches that crossed the PCG. Based on Klingler’s dissection technique, we observed a close relationship of the PCG with the superior longitudinal fascicle. The awareness of the anatomical variability observed within the brain cortex is an essential starting point for in-depth research.

The interplay between DNA methylation, folate and neurocognitive development

DNA methylation provides an attractive possible means for propagating the effects of environmental inputs during fetal life and impacting subsequent adult mental health, which is leading to increasing collaboration between molecular biologists, nutritionists and psychiatrists. An area of interest is the potential role of folate, not just in neural tube closure in early pregnancy, but in later major neurodevelopmental events, with consequences for later sociocognitive maturation. Here, we set the scene for recent discoveries by reviewing the major events of neural development during fetal life, with an emphasis on tissues and structures where dynamic methylation changes are known to occur. Following this, we give an indication of some of the major classes of genes targeted by methylation and important for neurological and behavioral development. Finally, we highlight some cognitive disorders where methylation changes are implicated as playing an important role.

The relationship between attention and gait in aging: facts and fallacies

The current study critically assessed the relationship between cognitive functions and gait in nondemented older adults. Quantitative measures of gait (velocity, cadence, and a coefficient of variance in stride length) were assessed in single and dual-task conditions. Three cognitive factors captured the domains of Executive Attention, Verbal IQ, and Memory. Linear regressions showed that Executive Attention was related to velocity in both walking conditions. However, Memory and Verbal IQ were also related to velocity. Memory was related to Cadence in both walking conditions. Executive Attention was related to the coefficient of variance in stride length in both walking conditions. Linear mixed effects models showed that dual-task costs were largest in velocity followed by cadence and the coefficient of variance in stride length. The relationship between cognitive functions and gait depends, in part, on the analytic approach used, gait parameters assessed, and walking condition.

Towards a model-based integration of co-registered electroencephalography/functional magnetic resonance imaging data with realistic neural population meshes

Brain activity can be measured with several non-invasive neuroimaging modalities, but each modality has inherent limitations with respect to resolution, contrast and interpretability. It is hoped that multimodal integration will address these limitations by using the complementary features of already available data. However, purely statistical integration can prove problematic owing to the disparate signal sources. As an alternative, we propose here an advanced neural population model implemented on an anatomically sound cortical mesh with freely adjustable connectivity, which features proper signal expression through a realistic head model for the electroencephalogram (EEG), as well as a haemodynamic model for functional magnetic resonance imaging based on blood oxygen level dependent contrast (fMRI BOLD). It hence allows simultaneous and realistic predictions of EEG and fMRI BOLD from the same underlying model of neural activity. As proof of principle, we investigate here the influence on simulated brain activity of strengthening visual connectivity. In the future we plan to fit multimodal data with this neural population model. This promises novel, model-based insights into the brain's activity in sleep, rest and task conditions.

DataViewer3D: An Open-Source, Cross-Platform Multi-Modal Neuroimaging Data Visualization Tool

Integration and display of results from multiple neuroimaging modalities [e.g. magnetic resonance imaging (MRI), magnetoencephalography, EEG] relies on display of a diverse range of data within a common, defined coordinate frame. DataViewer3D (DV3D) is a multi-modal imaging data visualization tool offering a cross-platform, open-source solution to simultaneous data overlay visualization requirements of imaging studies. While DV3D is primarily a visualization tool, the package allows an analysis approach where results from one imaging modality can guide comparative analysis of another modality in a single coordinate space. DV3D is built on Python, a dynamic object-oriented programming language with support for integration of modular toolkits, and development of cross-platform software for neuroimaging. DV3D harnesses the power of the Visualization Toolkit (VTK) for two-dimensional (2D) and 3D rendering, calling VTK's low level C++ functions from Python. Users interact with data via an intuitive interface that uses Python to bind wxWidgets, which in turn calls the user's operating system dialogs and graphical user interface tools. DV3D currently supports NIfTI-1, ANALYZE and DICOM formats for MRI data display (including statistical data overlay). Formats for other data types are supported. The modularity of DV3D and ease of use of Python allows rapid integration of additional format support and user development. DV3D has been tested on Mac OSX, RedHat Linux and Microsoft Windows XP. DV3D is offered for free download with an extensive set of tutorial resources and example data.