Spatiotemporal Correlation between Amyloid and Tau Accumulations Underlies Cognitive Changes in Aging.

It is poorly known how Aß and tau accumulations associate at the spatiotemporal level in the in vivo human brain to impact cognitive changes in older adults prior to AD symptoms onset. In this study, we used a graph theory-based spatiotemporal analysis to characterize the cortical patterns of Aß and tau deposits and their relationship with cognitive changes in the Harvard Aging Brain Study (HABS) cohort. We found that the temporal accumulations of interlinked Aß and tau pathology display distinctive spatiotemporal correlations associated with early cognitive decline. Notably, we observed that baseline Aß deposits-Thal amyloid phase Ⅱ-related to future increase of tau deposits, Braak stages Ⅰ-Ⅳ, both displaying linkage to the decline in multi-domain cognitive scores. We also found unimodal tau-to-tau and cognitive impairment associations in broad areas of Braak stages Ⅰ-Ⅳ. The unimodal Aß-to-Aß progressions were not associated with cognitive changes. Our results revealed a multifaceted correlation of the spatiotemporal Aß and tau associations with cognitive decline over time, in which tau-to-tau and tau-Aß interactions, and not Aß independently, might be critical contributors to clinical trajectories toward AD in older adults.

Amyloid-ß and tau pathologies relate to distinctive brain dysconnectomics in preclinical autosomal-dominant Alzheimer's disease.

The human brain is composed of functional networks that have a modular topology, where brain regions are organized into communities that form internally dense (segregated) and externally sparse (integrated) subnetworks that underlie higher-order cognitive functioning. It is hypothesized that amyloid-ß and tau pathology in preclinical Alzheimer's disease (AD) spread through functional networks, disrupting neural communication that results in cognitive dysfunction. We used high-resolution (voxel-level) graph-based network analyses to test whether in vivo amyloid-ß and tau burden was associated with the segregation and integration of brain functional connections, and episodic memory, in cognitively unimpaired Presenilin-1 E280A carriers who are expected to develop early-onset AD dementia in ∼13 y on average. Compared to noncarriers, mutation carriers exhibited less functional segregation and integration in posterior default-mode network (DMN) regions, particularly the precuneus, and in the retrospenial cortex, which has been shown to link medial temporal regions and cortical regions of the DMN. Mutation carriers also showed greater functional segregation and integration in regions connected to the salience network, including the striatum and thalamus. Greater tau burden was associated with lower segregated and integrated functional connectivity of DMN regions, particularly the precuneus and medial prefrontal cortex. In turn, greater tau pathology was related to higher segregated and integrated functional connectivity in the retrospenial cortex and the anterior cingulate cortex, a hub of the salience network. These findings enlighten our understanding of how AD-related pathology distinctly alters the brain's functional architecture in the preclinical stage, possibly contributing to pathology propagation and ultimately resulting in dementia.

Machine learning classification of functional neurological disorder using structural brain MRI features.

BACKGROUND: Brain imaging studies investigating grey matter in functional neurological disorder (FND) have used univariate approaches to report group-level differences compared with healthy controls (HCs). However, these findings have limited translatability because they do not differentiate patients from controls at the individual-level. METHODS: 183 participants were prospectively recruited across three groups: 61 patients with mixed FND (FND-mixed), 61 age-matched and sex-matched HCs and 61 age, sex, depression and anxiety-matched psychiatric controls (PCs). Radial basis function support vector machine classifiers with cross-validation were used to distinguish individuals with FND from HCs and PCs using 134 FreeSurfer-derived grey matter MRI features. RESULTS: Patients with FND-mixed were differentiated from HCs with an accuracy of 0.66 (p=0.005; area under the receiving operating characteristic (AUROC)=0.74); this sample was also distinguished from PCs with an accuracy of 0.60 (p=0.038; AUROC=0.56). When focusing on the functional motor disorder subtype (FND-motor, n=46), a classifier robustly differentiated these patients from HCs (accuracy=0.72; p=0.002; AUROC=0.80). FND-motor could not be distinguished from PCs, and the functional seizures subtype (n=23) could not be classified against either control group. Important regions contributing to statistically significant multivariate classifications included the cingulate gyrus, hippocampal subfields and amygdalar nuclei. Correctly versus incorrectly classified participants did not differ across a range of tested psychometric variables. CONCLUSIONS: These findings underscore the interconnection of brain structure and function in the pathophysiology of FND and demonstrate the feasibility of using structural MRI to classify the disorder. Out-of-sample replication and larger-scale classifier efforts incorporating psychiatric and neurological controls are needed.

High-order functional redundancy in ageing explained via alterations in the connectome in a whole-brain model.

The human brain generates a rich repertoire of spatio-temporal activity patterns, which support a wide variety of motor and cognitive functions. These patterns of activity change with age in a multi-factorial manner. One of these factors is the variations in the brain's connectomics that occurs along the lifespan. However, the precise relationship between high-order functional interactions and connnectomics, as well as their variations with age are largely unknown, in part due to the absence of mechanistic models that can efficiently map brain connnectomics to functional connectivity in aging. To investigate this issue, we have built a neurobiologically-realistic whole-brain computational model using both anatomical and functional MRI data from 161 participants ranging from 10 to 80 years old. We show that the differences in high-order functional interactions between age groups can be largely explained by variations in the connectome. Based on this finding, we propose a simple neurodegeneration model that is representative of normal physiological aging. As such, when applied to connectomes of young participant it reproduces the age-variations that occur in the high-order structure of the functional data. Overall, these results begin to disentangle the mechanisms by which structural changes in the connectome lead to functional differences in the ageing brain. Our model can also serve as a starting point for modeling more complex forms of pathological ageing or cognitive deficits.

Central neurogenetic signatures of the visuomotor integration system.

Visuomotor impairments characterize numerous neurological disorders and neurogenetic syndromes, such as autism spectrum disorder (ASD) and Dravet, Fragile X, Prader-Willi, Turner, and Williams syndromes. Despite recent advances in systems neuroscience, the biological basis underlying visuomotor functional impairments associated with these clinical conditions is poorly understood. In this study, we used neuroimaging connectomic approaches to map the visuomotor integration (VMI) system in the human brain and investigated the topology approximation of the VMI network to the Allen Human Brain Atlas, a whole-brain transcriptome-wide atlas of cortical genetic expression. We found the genetic expression of four genes-TBR1, SCN1A, MAGEL2, and CACNB4-to be prominently associated with visuomotor integrators in the human cortex. TBR1 gene transcripts, an ASD gene whose expression is related to neural development of the cortex and the hippocampus, showed a central spatial allocation within the VMI system. Our findings delineate gene expression traits underlying the VMI system in the human cortex, where specific genes, such as TBR1, are likely to play a central role in its neuronal organization, as well as on specific phenotypes of neurogenetic syndromes.

Connectomic-genetic signatures in the cerebral small vessel disease.

Small vessel disease (SVD) is a disorder that causes vascular lesions in the entire parenchyma of the human brain. At present, it is not well understood how primary and secondary damage interact to give rise to the complex scenario of white matter (WM) and grey matter (GM) lesions. Using novel cross-sectional and longitudinal connectomic approaches, we unveil the bidirectional nature of GM and WM changes, that is, primary cortical neurodegeneration that leads to secondary alterations in vascular border zones, and WM lesions that lead to secondary neurodegeneration in cortical projecting areas. We found this GM-WM interaction to be essential for executive cognitive performance. Moreover, we also observed that the interlocked degeneration of GM and WM over time associates with prototypical expression levels of genes potentially linked to SVD. Among these connectomic-genetic intersections, we found that the Androgen Receptor (AR) gene, is a particularly central candidate gene that might confer key vulnerability for brain lesion development in SVD. In conclusion, this study advances in the understanding of the bidirectional relationships between GM and WM lesions, primary and secondary vascular neurodegeneration, and sheds light on the genetic signatures of SVD.

Early-life trauma endophenotypes and brain circuit-gene expression relationships in functional neurological (conversion) disorder.

Functional neurological (conversion) disorder (FND) is a neuropsychiatric condition whereby individuals present with sensorimotor symptoms incompatible with other neurological disorders. Early-life maltreatment (ELM) is a risk factor for developing FND, yet few studies have investigated brain network-trauma relationships in this population. In this neuroimaging-gene expression study, we used two graph theory approaches to elucidate ELM subtype effects on resting-state functional connectivity architecture in 30 patients with motor FND. Twenty-one individuals with comparable depression, anxiety, and ELM scores were used as psychiatric controls. Thereafter, we compared trauma endophenotypes in FND with regional differences in transcriptional gene expression as measured by the Allen Human Brain Atlas (AHBA). In FND patients only, we found that early-life physical abuse severity, and to a lesser extent physical neglect, correlated with corticolimbic weighted-degree functional connectivity. Connectivity profiles influenced by physical abuse occurred in limbic (amygdalar-hippocampal), paralimbic (cingulo-insular and ventromedial prefrontal), and cognitive control (ventrolateral prefrontal) areas, as well as in sensorimotor and visual cortices. These findings held adjusting for individual differences in depression/anxiety, PTSD, and motor phenotypes. In FND, physical abuse also correlated with amygdala and insula coupling to motor cortices. In exploratory analyses, physical abuse correlated connectivity maps overlapped with the AHBA spatial expression of three gene clusters: (i) neuronal morphogenesis and synaptic transmission genes in limbic/paralimbic areas; (ii) locomotory behavior and neuronal generation genes in left-lateralized structures; and (iii) nervous system development and cell motility genes in right-lateralized structures. These circuit-specific architectural profiles related to individual differences in childhood physical abuse burden advance our understanding of the pathophysiology of FND.

Cortical thickness in default mode network hubs correlates with clinical features of dissociative seizures.

BACKGROUND: Dissociative seizures (DS) are a common subtype of functional neurological disorder (FND) with an incompletely understood pathophysiology. Here, gray matter variations and their relationship to clinical features were investigated. METHODS: Forty-eight patients with DS without neurological comorbidities and 43 matched clinical control patients with syncope with structural brain MRIs were identified retrospectively. FreeSurfer-based cortical thickness and FSL FIRST-based subcortical volumes were used for quantitative analyses, and all findings were age and sex adjusted, and corrected for multiple comparisons. RESULTS: Groups were not statistically different in cortical thickness or subcortical volumes. For patients with DS, illness duration was inversely correlated with cortical thickness of left-sided anterior and posterior cortical midline structures (perigenual/dorsal anterior cingulate cortex, superior parietal cortex, precuneus), and clusters at the left temporoparietal junction (supramarginal gyrus, postcentral gyrus, superior temporal gyrus), left postcentral gyrus, and right pericalcarine cortex. Dissociative seizure duration was inversely correlated with cortical thickness in the left perigenual anterior cingulate cortex, superior/middle frontal gyri, precentral gyrus and lateral occipital cortex, along with the right isthmus-cingulate and posterior-cingulate, middle temporal gyrus, and precuneus. Seizure frequency did not show any significant correlations. CONCLUSIONS: In patients with DS, illness duration inversely correlated with cortical thickness of left-sided default mode network cortical hubs, while seizure duration correlated with left frontopolar and right posteromedial areas, among others. Etiological factors contributing to neuroanatomical variations in areas related to self-referential processing in patients with DS require more research inquiry.

Creative Connections: Computational Semantic Distance Captures Individual Creativity and Resting-State Functional Connectivity.

Recent studies of creative cognition have revealed interactions between functional brain networks involved in the generation of novel ideas; however, the neural basis of creativity is highly complex and presents a great challenge in the field of cognitive neuroscience, partly because of ambiguity around how to assess creativity. We applied a novel computational method of verbal creativity assessment-semantic distance-and performed weighted degree functional connectivity analyses to explore how individual differences in assembly of resting-state networks are associated with this objective creativity assessment. To measure creative performance, a sample of healthy adults (n = 175) completed a battery of divergent thinking (DT) tasks, in which they were asked to think of unusual uses for everyday objects. Computational semantic models were applied to calculate the semantic distance between objects and responses to obtain an objective measure of DT performance. All participants underwent resting-state imaging, from which we computed voxel-wise connectivity matrices between all gray matter voxels. A linear regression analysis was applied between DT and weighted degree of the connectivity matrices. Our analysis revealed a significant connectivity decrease in the visual-temporal and parietal regions, in relation to increased levels of DT. Link-level analyses showed higher local connectivity within visual regions was associated with lower DT, whereas projections from the precuneus to the right inferior occipital and temporal cortex were positively associated with DT. Our results demonstrate differential patterns of resting-state connectivity associated with individual creative thinking ability, extending past work using a new application to automatically assess creativity via semantic distance.

Unveiling the neuroimaging-genetic intersections in the human brain.

PURPOSE OF REVIEW: The prevalence of new public datasets of brain-wide and single-cell transcriptome data has created new opportunities to link neuroimaging findings with genetic data. The aim of this study is to present the different methodological approaches that have been used to combine this data. RECENT FINDINGS: Drawing from various sources of open access data, several studies have been able to correlate neuroimaging maps with spatial distribution of brain expression. These efforts have enabled researchers to identify functional annotations of related genes, identify specific cell types related to brain phenotypes, study the expression of genes across life span and highlight the importance of selected brain genes in disease genetic networks. SUMMARY: New transcriptome datasets and methodological approaches complement current neuroimaging work and will be crucial to improve our understanding of the biological mechanism that underlies many neurological conditions.

Network interdigitations of Tau and amyloid-beta deposits define cognitive levels in aging.

Amyloid-beta (Aß) plaques and tau neurofibrillary tangles are pathological hallmarks of Alzheimer's disease (AD); their contribution to neurodegeneration and clinical manifestations are critical in understanding preclinical AD. At present, the mechanisms related to Aß and tau pathogenesis leading to cognitive decline in older adults remain largely unknown. Here, we examined graph theory-based positron emission tomography (PET) analytical approaches, within and between tau and Aß PET modalities, and tested the effects on cognitive changes in cognitively normal older adults (CN). Particularly, we focused on the network interdigitations of Aß and tau deposits, along with cognitive test scores in CN at both baseline and 2-year follow-up (FU). We found highly significant Aß-tau network integrations in AD vulnerable areas, as well as significant associations between those Aß-tau interdigitations and general cognitive impairment in CN at baseline and FU. Our findings suggest a distinctive contribution of interlinking network relationships between Aß and tau deposits in heteromodal areas of the human brain. They support a network-based interaction between Aß and tau accumulations as a key factor for cognitive deterioration in CN prior to dementia.

Individual differences in interoceptive accuracy and prediction error in motor functional neurological disorders: A DTI study.

In motor functional neurological disorders (mFND), relationships between interoception (a construct of high theoretical relevance to its pathophysiology) and neuroanatomy have not been previously investigated. This study characterized white matter in mFND patients compared to healthy controls (HCs), and investigated associations between fiber bundle integrity and cardiac interoception. Voxel-based analysis and tractography quantified fractional anisotropy (FA) in 38 mFND patients compared to 38 HCs. Secondary analyses compared functional seizures (FND-seiz; n = 21) or functional movement disorders (n = 17) to HCs. Network lesion mapping identified gray matter origins of implicated fiber bundles. Within-group mFND analyses investigated relationships between FA, heartbeat tracking accuracy and interoceptive trait prediction error (discrepancies between interoceptive accuracy and self-reported bodily awareness). Results were corrected for multiple comparisons, and all findings were adjusted for depression and trait anxiety. mFND and HCs did not show any between-group interoceptive accuracy or FA differences. However, the FND-seiz subgroup compared to HCs showed decreased integrity in right-lateralized tracts: extreme capsule/inferior fronto-occipital fasciculus, arcuate fasciculus, inferior longitudinal fasciculus, and thalamic/striatum to occipital cortex projections. These alterations originated predominantly from the right temporoparietal junction and inferior temporal gyrus. In mFND patients, individual differences in interoceptive accuracy and interoceptive trait prediction error correlated with fiber bundle integrity originating from the insula, temporoparietal junction, putamen and thalamus among other regions. In this first study investigating brain-interoception relationships in mFND, individual differences in interoceptive accuracy and trait prediction error mapped onto multimodal integration-related fiber bundles. Right-lateralized limbic and associative tract disruptions distinguished FND-seiz from HCs.

Transcriptional signatures of synaptic vesicle genes define myotonic dystrophy type I neurodegeneration.

AIM: To delineate the neurogenetic profiles of brain degeneration patterns in myotonic dystrophy type I (DM1). METHODS: In two cohorts of DM1 patients, brain maps of volume loss (VL) and neuropsychological deficits (NDs) were intersected to large-scale transcriptome maps provided by the Allen Human Brain Atlas (AHBA). For validation, neuropathological and RNA analyses were performed in a small series of DM1 brain samples. RESULTS: Twofold: (1) From a list of preselected hypothesis-driven genes, confirmatory analyses found that three genes play a major role in brain degeneration: dystrophin (DMD), alpha-synuclein (SNCA) and the microtubule-associated protein tau (MAPT). Neuropathological analyses confirmed a highly heterogeneous Tau-pathology in DM1, different to the one in Alzheimer's disease. (2) Exploratory analyses revealed gene clusters enriched for key biological processes in the central nervous system, such as synaptic vesicle recycling, localization, endocytosis and exocytosis, and the serotonin and dopamine neurotransmitter pathways. RNA analyses confirmed synaptic vesicle dysfunction. CONCLUSIONS: The combination of large-scale transcriptome interactions with brain imaging and cognitive function sheds light on the neurobiological mechanisms of brain degeneration in DM1 that might help define future therapeutic strategies and research into this condition.

Reduced limbic microstructural integrity in functional neurological disorder.

BACKGROUND: Functional neurological disorder (FND) is a condition at the intersection of neurology and psychiatry. Individuals with FND exhibit corticolimbic abnormalities, yet little is known about the role of white matter tracts in the pathophysiology of FND. This study characterized between-group differences in microstructural integrity, and correlated fiber bundle integrity with symptom severity, physical disability, and illness duration. METHODS: A diffusion tensor imaging (DTI) study was performed in 32 patients with mixed FND compared to 36 healthy controls. Diffusion-weighted magnetic resonance images were collected along with patient-reported symptom severity, physical disability (Short Form Health Survey-36), and illness duration data. Weighted-degree and link-level graph theory and probabilistic tractography analyses characterized fractional anisotropy (FA) values across cortico-subcortical connections. Results were corrected for multiple comparisons. RESULTS: Compared to controls, FND patients showed reduced FA in the stria terminalis/fornix, medial forebrain bundle, extreme capsule, uncinate fasciculus, cingulum bundle, corpus callosum, and striatal-postcentral gyrus projections. Except for the stria terminalis/fornix, these differences remained significant adjusting for depression and anxiety. In within-group analyses, physical disability inversely correlated with stria terminalis/fornix and medial forebrain bundle FA values; illness duration negatively correlated with stria terminalis/fornix white matter integrity. A FND symptom severity composite score did not correlate with FA in patients. CONCLUSIONS: In this first DTI study of mixed FND, microstructural differences were observed in limbic and associative tracts implicated in salience, defensive behaviors, and emotion regulation. These findings advance our understanding of neurocircuit pathways in the pathophysiology of FND.

PTEN Activity Defines an Axis for Plasticity at Cortico-Amygdala Synapses and Influences Social Behavior.

Phosphatase and tensin homolog on chromosome 10 (PTEN) is a tumor suppressor and autism-associated gene that exerts an important influence over neuronal structure and function during development. In addition, it participates in synaptic plasticity processes in adulthood. As an attempt to assess synaptic and developmental mechanisms by which PTEN can modulate cognitive function, we studied the consequences of 2 different genetic manipulations in mice: presence of additional genomic copies of the Pten gene (Ptentg) and knock-in of a truncated Pten gene lacking its PDZ motif (Pten-ΔPDZ), which is required for interaction with synaptic proteins. Ptentg mice exhibit substantial microcephaly, structural hypoconnectivity, enhanced synaptic depression at cortico-amygdala synapses, reduced anxiety, and intensified social interactions. In contrast, Pten-ΔPDZ mice have a much more restricted phenotype, with normal synaptic connectivity, but impaired synaptic depression at cortico-amygdala synapses and virtually abolished social interactions. These results suggest that synaptic actions of PTEN in the amygdala contribute to specific behavioral traits, such as sociability. Also, PTEN appears to function as a bidirectional rheostat in the amygdala: reduction in PTEN activity at synapses is associated with less sociability, whereas enhanced PTEN activity accompanies hypersocial behavior.

Sequence Alterations of Cortical Genes Linked to Individual Connectivity of the Human Brain.

Individual differences in humans are driven by unique brain structural and functional profiles, presumably mediated in part through differential cortical gene expression. However, the relationships between cortical gene expression profiles and individual differences in large-scale neural network organization remain poorly understood. In this study, we aimed to investigate whether the magnitude of sequence alterations in regional cortical genes mapped onto brain areas with high degree of functional connectivity variability across individuals. First, human genetic expression data from the Allen Brain Atlas was used to identify protein-coding genes associated with cortical areas, which delineated the regional genetic signature of specific cortical areas based on sequence alteration profiles. Thereafter, we identified brain regions that manifested high degrees of individual variability by using test-retest functional connectivity magnetic resonance imaging and graph-theory analyses in healthy subjects. We found that rates of genetic sequence alterations shared a distinct spatial topography with cortical regions exhibiting individualized (highly-variable) connectivity profiles. Interestingly, gene expression profiles of brain regions with highly individualized connectivity patterns and elevated number of sequence alterations are devoted to neuropeptide-signaling-pathways and chemical-synaptic-transmission. Our findings support that genetic sequence alterations may underlie important aspects of brain connectome individualities in humans. Significance Statement: The neurobiological underpinnings of our individuality as humans are still an unsolved question. Although the notion that genetic variation drives an individual's brain organization has been previously postulated, specific links between neural connectivity and gene expression profiles have remained elusive. In this study, we identified the magnitude of population-based sequence alterations in discrete cortical regions and compared them to the brain topological distribution of functional connectivity variability across an independent human sample. We discovered that brain regions with high degree of connectional individuality are defined by increased rates of genetic sequence alterations; these findings specifically implicated genes involved in neuropeptide-signaling pathways and chemical-synaptic transmission. These observations support that genetic sequence alterations may underlie important aspects of the emergence of the brain individuality across humans.

Brain circuit-gene expression relationships and neuroplasticity of multisensory cortices in blind children.

Sensory deprivation reorganizes neurocircuits in the human brain. The biological basis of such neuroplastic adaptations remains elusive. In this study, we applied two complementary graph theory-based functional connectivity analyses, one to evaluate whole-brain functional connectivity relationships and the second to specifically delineate distributed network connectivity profiles downstream of primary sensory cortices, to investigate neural reorganization in blind children compared with sighted controls. We also examined the relationship between connectivity changes and neuroplasticity-related gene expression profiles in the cerebral cortex. We observed that multisensory integration areas exhibited enhanced functional connectivity in blind children and that this reorganization was spatially associated with the transcription levels of specific members of the cAMP Response Element Binding protein gene family. Using systems-level analyses, this study advances our understanding of human neuroplasticity and its genetic underpinnings following sensory deprivation.

Corticolimbic fast-tracking: enhanced multimodal integration in functional neurological disorder.

OBJECTIVE: Some individuals with functional neurological disorder (FND) exhibit motor and affective disturbances, along with limbic hyper-reactivity and enhanced motor-limbic connectivity. Given that the multimodal integration network (insula, dorsal cingulate, temporoparietal junction (TPJ)) is implicated in convergent sensorimotor, affective and interoceptive processing, we hypothesised that patients with FND would exhibit altered motor and amygdalar resting-state propagation to this network. Patient-reported symptom severity and clinical outcome were also hypothesised to map onto multimodal integration areas. METHODS: Between-group differences in primary motor and amygdalar nuclei (laterobasal, centromedial) were examined using graph-theory stepwise functional connectivity (SFC) in 30 patients with motor FND compared with 30 healthy controls. Within-group analyses correlated functional propagation profiles with symptom severity and prospectively collected 6-month outcomes as measured by the Screening for Somatoform Symptoms Conversion Disorder subscale and Patient Health Questionnaire-15 composite score. Findings were clusterwise corrected for multiple comparisons. RESULTS: Compared with controls, patients with FND exhibited increased SFC from motor regions to the bilateral posterior insula, TPJ, middle cingulate cortex and putamen. From the right laterobasal amygdala, the FND cohort showed enhanced connectivity to the left anterior insula, periaqueductal grey and hypothalamus among other areas. In within-group analyses, symptom severity correlated with enhanced SFC from the left anterior insula to the right anterior insula and TPJ; increased SFC from the left centromedial amygdala to the right anterior insula correlated with clinical improvement. Within-group associations held controlling for depression, anxiety and antidepressant use. CONCLUSIONS: These neuroimaging findings suggest potential candidate neurocircuit pathways in the pathophysiology of FND.

Structure-function multi-scale connectomics reveals a major role of the fronto-striato-thalamic circuit in brain aging.

Physiological aging affects brain structure and function impacting morphology, connectivity, and performance. However, whether some brain connectivity metrics might reflect the age of an individual is still unclear. Here, we collected brain images from healthy participants (N = 155) ranging from 10 to 80 years to build functional (resting state) and structural (tractography) connectivity matrices, both data sets combined to obtain different connectivity features. We then calculated the brain connectome age-an age estimator resulting from a multi-scale methodology applied to the structure-function connectome, and compared it to the chronological age (ChA). Our results were twofold. First, we found that aging widely affects the connectivity of multiple structures, such as anterior cingulate and medial prefrontal cortices, basal ganglia, thalamus, insula, cingulum, hippocampus, parahippocampus, occipital cortex, fusiform, precuneus, and temporal pole. Second, we found that the connectivity between basal ganglia and thalamus to frontal areas, also known as the fronto-striato-thalamic (FST) circuit, makes the major contribution to age estimation. In conclusion, our results highlight the key role played by the FST circuit in the process of healthy aging. Notably, the same methodology can be generally applied to identify the structural-functional connectivity patterns correlating to other biomarkers than ChA.

Interaction Information Along Lifespan of the Resting Brain Dynamics Reveals a Major Redundant Role of the Default Mode Network.

Interaction Information (II) generalizes the univariate Shannon entropy to triplets of variables, allowing the detection of redundant (R) or synergetic (S) interactions in dynamical networks. Here, we calculated II from functional magnetic resonance imaging data and asked whether R or S vary across brain regions and along lifespan. Preserved along lifespan, we found high overlapping between the pattern of high R and the default mode network, whereas high values of S were overlapping with different cognitive domains, such as spatial and temporal memory, emotion processing and motor skills. Moreover, we have found a robust balance between R and S among different age intervals, indicating informational compensatory mechanisms in brain networks.