Understanding the contribution of the brain white matter pathways to declarative verbal memory processes has been hindered by the lack of an adequate model in humans. An attractive and underexplored approach to study white matter region functionality in the living human brain is through the use of non-aprioristic models which specifically search disrupted white matter pathways. For this purpose, we employed voxel-based lesion-function mapping to correlate white matter lesions on the magnetic resonance images of 46 multiple sclerosis patients with their performance on declarative verbal memory storage and retrieval. White matter correlating with storage was in the temporal lobe-particularly lateral to the hippocampus and in the anterior temporal stem-, in the thalamic region and in the anterior limb of the internal capsule, all on the left hemisphere, and also in the right anterior temporal stem. The same volumes were relevant for retrieval, but to them were added temporo-parieto-frontal paramedian bundles, particularly the cingulum and the fronto-occipital fasciculus. These 3D maps indicate the white matter regions most critically involved in declarative verbal memory in humans.

The Harvard Aging Brain Study is sharing its data with the global research community. The longitudinal dataset consists of a 284-subject cohort with the following modalities acquired: demographics, clinical assessment, comprehensive neuropsychological testing, clinical biomarkers, and neuroimaging. To promote more extensive analyses, imaging data was designed to be compatible with other publicly available datasets. A cloud-based system enables access to interested researchers with blinded data available contingent upon completion of a data usage agreement and administrative approval. Data collection is ongoing and currently in its fifth year.

We sought to determine whether functional connectivity streams that link sensory, attentional, and higher-order cognitive circuits are atypical in attention-deficit/hyperactivity disorder (ADHD). We applied a graph-theory method to the resting-state functional magnetic resonance imaging data of 120 children with ADHD and 120 age-matched typically developing children (TDC). Starting in unimodal primary cortex-visual, auditory, and somatosensory-we used stepwise functional connectivity to calculate functional connectivity paths at discrete numbers of relay stations (or link-step distances). First, we characterized the functional connectivity streams that link sensory, attentional, and higher-order cognitive circuits in TDC and found that systems do not reach the level of integration achieved by adults. Second, we searched for stepwise functional connectivity differences between children with ADHD and TDC. We found that, at the initial steps of sensory functional connectivity streams, patients display significant enhancements of connectivity degree within neighboring areas of primary cortex, while connectivity to attention-regulatory areas is reduced. Third, at subsequent link-step distances from primary sensory cortex, children with ADHD show decreased connectivity to executive processing areas and increased degree of connections to default mode regions. Fourth, in examining medication histories in children with ADHD, we found that children medicated with psychostimulants present functional connectivity streams with higher degree of connectivity to regions subserving attentional and executive processes compared to medication-naïve children. We conclude that predominance of local sensory processing and lesser influx of information to attentional and executive regions may reduce the ability to organize and control the balance between external and internal sources of information in ADHD.

Individuals with body dysmorphic disorder (BDD) and obsessive-compulsive disorder (OCD) are categorized within the same major diagnostic group and both show regional brain hyperactivity in the orbitofrontal cortex (OFC) and the basal ganglia during symptom provocation. While recent studies revealed that degree connectivity of these areas is abnormally high in OCD and positively correlates with symptom severity, no study has investigated degree connectivity in BDD. We used functional magnetic resonance imaging (fMRI) to compare the local and distant degree of functional connectivity in all brain areas between 28 unmedicated BDD participants and 28 demographically matched healthy controls during a face-processing task. Correlational analyses tested for associations between degree connectivity and symptom severity assessed by the BDD version of the Yale-Brown obsessive-compulsive scale (BDD-Y-BOCS). Reduced local amygdalar connectivity was found in participants with BDD. No differences in distant connectivity were found. BDD-Y-BOCS scores significantly correlated with the local connectivity of the posterior-lateral OFC, and distant connectivity of the posterior-lateral and post-central OFC, respectively. These findings represent preliminary evidence that individuals with BDD exhibit brain-behavioral associations related to obsessive thoughts and compulsive behaviors that are highly similar to correlations previously found in OCD, further underscoring their related pathophysiology. This relationship could be further elucidated through investigation of resting-state functional connectivity in BDD, ideally in direct comparison with OCD and other obsessive-compulsive and related disorders.

The fact that people think or behave differently from one another is rooted in individual differences in brain anatomy and connectivity. Here, we used repeated-measurement resting-state functional MRI to explore intersubject variability in connectivity. Individual differences in functional connectivity were heterogeneous across the cortex, with significantly higher variability in heteromodal association cortex and lower variability in unimodal cortices. Intersubject variability in connectivity was significantly correlated with the degree of evolutionary cortical expansion, suggesting a potential evolutionary root of functional variability. The connectivity variability was also related to variability in sulcal depth but not cortical thickness, positively correlated with the degree of long-range connectivity but negatively correlated with local connectivity. A meta-analysis further revealed that regions predicting individual differences in cognitive domains are predominantly located in regions of high connectivity variability. Our findings have potential implications for understanding brain evolution and development, guiding intervention, and interpreting statistical maps in neuroimaging.

The default-mode network (DMN) is a distributed functional-anatomic network implicated in supporting memory. Current resting-state functional connectivity studies in humans remain divided on the exact involvement of medial temporal lobe (MTL) in this network at rest. Notably, it is unclear to what extent the MTL regions involved in successful memory encoding are connected to the cortical nodes of the DMN during resting state. Our findings using functional connectivity MRI analyses of resting-state data indicate that the parahippocampal gyrus (PHG) is the primary hub of the DMN in the MTL during resting state. Also, connectivity of the PHG is distinct from connectivity of hippocampal regions identified by an associative memory-encoding task. We confirmed that several hippocampal encoding regions lack significant functional connectivity with cortical DMN nodes during resting state. Additionally, a mediation analysis showed that resting-state connectivity between the hippocampus and posterior cingulate cortex--a major hub of the DMN--is indirect and mediated by the PHG. Our findings support the hypothesis that the MTL memory system represents a functional subnetwork that relates to the cortical nodes of the DMN through parahippocampal functional connections.

Positron emission tomography (PET) imaging now allows in vivo visualization of both neuropathologic hallmarks of Alzheimer disease (AD): amyloid-β (Aβ) plaques and tau neurofibrillary tangles. Observing their progressive accumulation in the brains of clinically normal older adults is critically important to understand the pathophysiologic cascade leading to AD and to inform the choice of outcome measures in prevention trials.

Resting-state functional connectivity MRI (rs-fcMRI) is a non-invasive imaging technique that has come into increasing use to understand disrupted neural network function in neuropsychiatric disease. However, despite extensive study over the past 15 years, the development of rs-fcMRI as a biomarker has been impeded by a lack of reliable longitudinal rs-fcMRI measures. Here we focus on longitudinal change along the Alzheimer's disease (AD) trajectory and demonstrate the utility of Template Based Rotation (TBR) in detecting differential longitudinal rs-fcMRI change between higher and lower amyloid burden individuals with mildly impaired cognition. Specifically, we examine a small (N = 24), but densely sampled (~5 observations over ~3 years), cohort of symptomatic individuals with serial rs-fcMRI imaging and PiB-PET imaging for β-amyloid pathology. We observed longitudinal decline of the Default Mode and Salience network axis (DMN/SAL) among impaired individuals with high amyloid burden. No other networks showed differential change in high vs. low amyloid individuals over time. The standardized effect size of AD related DMN/SAL change is comparable to the standardized effect size of amyloid-related change on the mini-mental state exam (MMSE) and hippocampal volume (HV). Last, we show that the AD-related change in DMN/SAL connectivity is almost completely independent of change on MMSE or HV, suggesting that rs-fcMRI is sensitive to an aspect of AD progression that is not captured by these other measures. Together these analyses demonstrate that longitudinal rs-fcMRI using TBR can capture disease-relevant network disruption in a clinical population.

We determine whether diminished Learning Over Repeated Exposures (LORE) identifies subtle memory decrements in cognitively unimpaired (CU) older adults with Alzheimer's disease (AD) biomarker burden.

Proteinopathies are key elements in the pathogenesis of age-related neurodegenerative diseases, particularly Alzheimer's disease (AD), with the nature and location of the proteinopathy characterizing much of the disease phenotype. Susceptibility of brain regions to pathology may partly be determined by intrinsic network structure and connectivity. It remains unknown, however, how these networks inform the disease cascade in the context of AD biomarkers, such as beta-amyloid (Aβ), in clinically-normal older adults.The default-mode network (DMN), a prominent intrinsic network, is heavily implicated in AD due to its spatial overlap with AD atrophy patterns and tau deposition. We investigated the influence of baseline Aβ positron emission tomography (PET) signal and intrinsic DMN connectivity on DMN-specific cortical thinning in 120 clinically-normal older adults from the Harvard Aging Brain Study (73 ± 6 years, 58% Female, CDR = 0). Participants underwent11C Pittsburgh Compound-B (PiB) PET, 18F flortaucipir (FTP) PET, and resting-state MRI scans at baselineand longitudinal MRI (3.6 ± 0.96 scans; 5.04 ± 0.8 years). Linear mixed models tested relationships between baseline PiB and DMN connectivity on cortical thinning in a composite of DMN regions. Lower DMN connectivity was associated with faster cortical thinning, but only in those with elevated baseline PiB-PET signal. This relationship was network specific, in that the frontoparietal control network did not account for the observed association. Additionally, the relationship was independent of inferior temporal lobe FTP-PET signal. Our findings provide evidence that compromised DMN connectivity, in the context of preclinical AD, foreshadows neurodegeneration in DMN regions.

We identified a PSEN1 (presenilin 1) mutation carrier from the world's largest autosomal dominant Alzheimer's disease kindred, who did not develop mild cognitive impairment until her seventies, three decades after the expected age of clinical onset. The individual had two copies of the APOE3 Christchurch (R136S) mutation, unusually high brain amyloid levels and limited tau and neurodegenerative measurements. Our findings have implications for the role of APOE in the pathogenesis, treatment and prevention of Alzheimer's disease.

The ability to accurately judge memory efficiency (meta-memory monitoring) for newly learned (episodic) information, is decreased in older adults and even worse in Alzheimer's disease (AD), whereas no differences have been found for semantic meta-memory. The pathological substrates of this phenomenon are poorly understood. Here, we examine the association between meta-memory monitoring for episodic and semantic information to the two major proteinopathies in AD: amyloid (Aβ) and tau pathology in a group of cognitively unimpaired older adults. All participants underwent multi-tracer PET and meta-memory monitoring was assessed using a feeling-of-knowing (FOK) task for non-famous (episodic) and famous (semantic) face-name pairs. Whole brain voxel-wise correlations between meta-memory and PET data were conducted (controlling for memory), as well as confirmatory region-of-interest analyses. Participants had reduced episodic FOK compared to semantic FOK. Decreased episodic FOK was related to tauopathy in the medial temporal lobe regions, including the entorhinal cortex and temporal pole, whereas decreased semantic FOK was related to increased tau in regions associated with the semantic knowledge network. No association was found with Aβ-pathology. Alterations in the ability to accurately judge memory efficiency (in the absence of memory decline) may be a sensitive clinical indicator of AD pathophysiology in the pre-symptomatic phase.

Alzheimer's disease (AD) is associated with brain network dysfunction. Network-based investigations of brain connectivity have mainly focused on alterations in the strength of connectivity; however, the network breakdown in AD spectrum is a complex scenario in which multiple pathways of connectivity are affected. To integrate connectivity changes that occur under AD-related conditions, here we developed a novel metric that computes the connectivity distance between cortical regions at the voxel level (or nodes). We studied 114 individuals with mild cognitive impairment, 24 with AD, and 27 healthy controls. Results showed that areas of the default mode network, salience network, and frontoparietal network display a remarkable network separation, or greater connectivity distances, from the rest of the brain. Furthermore, this greater connectivity distance was associated with lower global cognition. Overall, the investigation of AD-related changes in paths and distances of connectivity provides a novel framework for characterizing subjects with cognitive impairment; a framework that integrates the overall network topology changes of the brain and avoids biases toward unreferenced connectivity effects.

Alzheimer's disease (AD) heritability is enriched in glial genes, but how and when cell-type-specific genetic risk contributes to AD remains unclear. Here, we derive cell-type-specific AD polygenic risk scores (ADPRS) from two extensively characterized datasets. In an autopsy dataset spanning all stages of AD (n=1,457), astrocytic (Ast) ADPRS was associated with both diffuse and neuritic Aβ plaques, while microglial (Mic) ADPRS was associated with neuritic Aβ plaques, microglial activation, tau, and cognitive decline. Causal modeling analyses further clarified these relationships. In an independent neuroimaging dataset of cognitively unimpaired elderly (n=2,921), Ast-ADPRS were associated with Aβ, and Mic-ADPRS was associated with Aβ and tau, showing a consistent pattern with the autopsy dataset. Oligodendrocytic and excitatory neuronal ADPRSs were associated with tau, but only in the autopsy dataset including symptomatic AD cases. Together, our study provides human genetic evidence implicating multiple glial cell types in AD pathophysiology, starting from the preclinical stage.

We investigated the effect of baseline Aβ, sex, and APOE on longitudinal tau accumulation in cerebrospinal fluid (CSF) in clinically normal older adults. Two hundred thirty-nine participants (aged 56-89 years, clinical dementia rating = 0) underwent serial CSF collection for Aβ1-42, total-tau (t-tau) and phospho-tau181P (p-tau). We used preprocessed data from fully automated Roche Elecsys immunoassays. A series of linear regressions were used to examine cross-sectional effects of Aβ1-42, sex, and APOEε4 on baseline CSF tau and linear mixed models for longitudinal changes in CSF tau. Cross-sectionally, CSF t-tau and p-tau were associated with abnormal Aβ1-42 and APOEε4 but not with sex. Longitudinally, low baseline CSF Aβ1-42 levels, but not APOEε4 or sex, predicted faster p-tau accumulation. The relationship between baseline CSF Aβ1-42 and tau accumulation was strongest in APOEε4 carriers, and particularly female carriers, relative to other groups. The current findings support an association between baseline CSF Aβ1-42 and changes in CSF tau. Elevated risk in females, apparent only in carriers, reinforces findings of sex-related vulnerability in those with genetic predisposition for Alzheimer's disease.

There is a growing need in clinical research domains for direct comparability between amyloid-beta (Aβ) Positron Emission Tomography (PET) measures obtained via different radiotracers and processing methodologies. Previous efforts to provide a common measurement scale fail to account for non-linearities between measurement scales that can arise from these differences. We introduce a new application of distribution mapping, based on well established statistical orthodoxy, that we call Nonlinear Distribution Mapping (NoDiM). NoDiM uses cumulative distribution functions to derive mappings between Aβ-PET measurements from different tracers and processing streams that align data based on their location in their respective distributions.

Loneliness is a perception of social and emotional isolation that increases in prevalence among older adults during the eighth decade of life. Loneliness has been associated with higher brain amyloid-β deposition, a biologic marker of Alzheimer's disease, in cognitively normal older adults, suggesting a link with preclinical Alzheimer's disease pathophysiology. This study examined whether greater loneliness was associated with tau pathology, the other defining feature of Alzheimer's disease, in 117 cognitively normal older adults. Using flortaucipir positron emission tomography, we measured tau pathology in the entorhinal cortex, a region of initial accumulation in aging adults with or without elevated amyloid-β, and in the inferior temporal cortex, a region of early accumulation typically associated with elevated amyloid-β and memory impairment. Loneliness was measured by self-report using the 3-item UCLA-loneliness scale. We found that higher tau pathology in the right entorhinal cortex was associated with greater loneliness, controlling for age, sex, and apolipoprotein E ε4, the Alzheimer's disease genetic risk marker. This association remained significant after further adjustment for socioeconomic status, social network, depression and anxiety scores, and memory performance. There was no association of inferior temporal cortical or left entorhinal tau pathology with loneliness. Exploratory whole-brain surface maps supported these findings and identified additional clusters correlating loneliness and tau in the right fusiform gyrus. These results provide further support for loneliness as a socioemotional symptom in preclinical Alzheimer's disease.

Autosomal dominant Alzheimer's disease (ADAD) is distinguished from late-onset AD by early striatal amyloid-β deposition. To determine whether striatal Pittsburgh compound B (PiB)-PET measurements of amyloid-β can help predict disease severity in ADAD, we compared relationships of striatal and neocortical PiB-PET to age, tau-PET, and memory performance in the Colombian Presenilin 1 E280A kindred.

Advanced aging negatively impacts memory performance. Brain aging has been associated with shrinkage in medial temporal lobe structures essential for memory--including hippocampus and entorhinal cortex--and with deficits in default-mode network connectivity. Yet, whether and how these imaging markers are relevant to age-related memory deficits remains a topic of debate. Using a sample of 182 older (age 74.6 ± 6.2 years) and 66 young (age 22.2 ± 3.6 years) participants, this study examined relationships among memory performance, hippocampus volume, entorhinal cortex thickness, and default-mode network connectivity across aging. All imaging markers and memory were significantly different between young and older groups. Each imaging marker significantly mediated the relationship between age and memory performance and collectively accounted for most of the variance in age-related memory performance. Within older participants, default-mode connectivity and hippocampus volume were independently associated with memory. Structural equation modeling of cross-sectional data within older participants suggest that entorhinal thinning may occur before reduced default-mode connectivity and hippocampal volume loss, which in turn lead to deficits in memory performance.

Working memory relies on information processing by several well-identified gray matter regions. However, the white matter regions and pathways involved in this cognitive process remain unknown. An attractive and underexplored approach to study white matter connectivity in cognitive functions is through the use of non-aprioristic models, which specifically search disrupted white matter pathways. For this purpose, we used voxel-based lesion-function mapping to correlate white matter lesions on the magnetic resonance images of 54 multiple sclerosis patients with their performance on a verbal working memory task. With this approach, we have identified critical white matter regions involved in verbal working memory in humans. They are located in the cingulum, parieto-frontal pathways and thalamo-cortical projections, with a left-sided predominance, as well as the right cerebellar white matter. Our study provides direct evidence on the white matter pathways subserving verbal working memory in the human brain.