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Predictive staging models of Alzheimer’s disease broadly fall into one of two categories: cortical origin versus subcortical origin. Using multimodal biomarkers and longitudinal structural imaging in two large independent datasets, Fernández-Cabello et al. find robust evidence in favour of the latter., Alzheimer’s disease neurodegeneration is thought to spread across anatomically and functionally connected brain regions. However, the precise sequence of spread remains ambiguous. The prevailing model used to guide in vivo human neuroimaging and non-human animal research assumes that Alzheimer’s degeneration starts in the entorhinal cortices, before spreading to the temporoparietal cortex. Challenging this model, we previously provided evidence that in vivo markers of neurodegeneration within the nucleus basalis of Meynert (NbM), a subregion of the basal forebrain heavily populated by cortically projecting cholinergic neurons, precedes and predicts entorhinal degeneration. There have been few systematic attempts at directly comparing staging models using in vivo longitudinal biomarker data, and none to our knowledge testing if comparative evidence generalizes across independent samples. Here we addressed the sequence of pathological staging in Alzheimer’s disease using two independent samples of the Alzheimer’s Disease Neuroimaging Initiative (n1 = 284; n2 = 553) with harmonized CSF assays of amyloid-β and hyperphosphorylated tau (pTau), and longitudinal structural MRI data over 2 years. We derived measures of grey matter degeneration in a priori NbM and the entorhinal cortical regions of interest. To examine the spreading of degeneration, we used a predictive modelling strategy that tests whether baseline grey matter volume in a seed region accounts for longitudinal change in a target region. We demonstrated that predictive spread favoured the NbM→entorhinal over the entorhinal→NbM model. This evidence generalized across the independent samples. We also showed that CSF concentrations of pTau/amyloid-β moderated the observed predictive relationship, consistent with evidence in rodent models of an underlying trans-synaptic mechanism of pathophysiological spread. The moderating effect of CSF was robust to additional factors, including clinical diagnosis. We then applied our predictive modelling strategy to an exploratory whole-brain voxel-wise analysis to examine the spatial specificity of the NbM→entorhinal model. We found that smaller baseline NbM volumes predicted greater degeneration in localized regions of the entorhinal and perirhinal cortices. By contrast, smaller baseline entorhinal volumes predicted degeneration in the medial temporal cortex, recapitulating a prior influential staging model. Our findings suggest that degeneration of the basal forebrain cholinergic projection system is a robust and reliable upstream event of entorhinal and neocortical degeneration, calling into question a prevailing view of Alzheimer’s disease pathogenesis.

The neural processes that support inhibitory control in the face of stimuli with a history of reward association are not yet well understood. Yet, the ability to flexibly adapt behavior to changing reward-contingency contexts is important for daily functioning and warrants further investigation. This study aimed to characterize neural and behavioral impacts of stimuli with a history of conditioned reward association on motor inhibitory control in healthy young adults by investigating group-level effects as well as individual variation in the ability to inhibit responses to stimuli with a reward history. Participants (N = 41) first completed a reward conditioning phase, during which responses to rewarded stimuli were associated with money and responses to unrewarded stimuli were not. Rewarded and unrewarded stimuli from training were carried forward as No-Go targets in a subsequent go/no-go task to test the effect of reward history on inhibitory control. Participants underwent functional brain imaging during the go/no-go portion of the task. On average, a history of reward conditioning disrupted inhibitory control. Compared to inhibition of responses to stimuli with no reward history, trials that required inhibition of responses to previously rewarded stimuli were associated with greater activity in frontal and striatal regions, including the inferior frontal gyrus, insula, striatum, and thalamus. Activity in the insula and thalamus during false alarms and in the ventromedial prefrontal cortex during correctly withheld trials predicted behavioral performance on the task. Overall, these results suggest that reward history serves to disrupt inhibitory control and provide evidence for diverging roles of the insula and ventromedial prefrontal cortex while inhibiting responses to stimuli with a reward history.

There is increasing interest in measuring large-scale functional-anatomic brain networks. This is fueled by the continued development over the last two decades of novel sophisticated neuroimaging procedures for assessment of brain networks in humans. Among multiple brain networks, the most frequently investigated system is the so-called default network. This network was originally identified as a set of brain regions consistently deactivated during tasks that require externally oriented attention. Later imaging studies showed that this network is active during internally focused cognitive processes such as moral decision making and planning of future behavior and also that it can reliably be identified during resting conditions. A growing number of studies indicate that various brain disorders are associated with dysfunction of brain networks, leading to the notion that measures of functional network integrity may serve as marker of neurologic and psychiatric disease states. For instance, disconnection of default network regions seems evident in very early stages of Alzheimer’s disease, and a striking topographical overlap has been shown between default network regions and the spatial distribution of different diagnostic markers of Alzheimer’s disease such as amyloid deposition, hypometabolism, and brain atrophy. In this chapter, we summarize the most important milestones from discovery of the default network by means of neuroimaging procedures to promising clinical applications and possible pitfalls of functional network measures.

Technological advances in multimodal wearable and connected devices have enabled the measurement of human movement and physiology in naturalistic settings. The ability to collect continuous activity monitoring data with digital devices in real-world environments has opened unprecedented opportunity to establish clinical digital phenotypes across diseases. Many traditional assessments of physical function utilized in clinical trials are limited because they are episodic, therefore, cannot capture the day-to-day temporal fluctuations and longitudinal changes in activity that individuals experience. In order to understand the sensitivity of gait speed as a potential endpoint for clinical trials, we investigated the use of digital devices during traditional clinical assessments and in real-world environments in a group of healthy younger (n = 33, 18–40 years) and older (n = 32, 65–85 years) adults. We observed good agreement between gait speed estimated using a lumbar-mounted accelerometer and gold standard system during the performance of traditional gait assessment task in-lab, and saw discrepancies between in-lab and at-home gait speed. We found that gait speed estimated in-lab, with or without digital devices, failed to differentiate between the age groups, whereas gait speed derived during at-home monitoring was able to distinguish the age groups. Furthermore, we found that only three days of at-home monitoring was sufficient to reliably estimate gait speed in our population, and still capture age-related group differences. Our results suggest that gait speed derived from activities during daily life using data from wearable devices may have the potential to transform clinical trials by non-invasively and unobtrusively providing a more objective and naturalistic measure of functional ability.

Inhibitory control, the capacity to suppress an inappropriate response, is a process employed for guiding action selection in the service of goal-directed behavior. Under neutral circumstances, inhibitory control success improves from childhood to adulthood and has been associated with developmental shifts in functional activation and connectivity of the PFC. However, the ability to exercise inhibitory control is challenged in certain contexts by including appetitive cues, a phenomenon that may be particularly pronounced in youths. Here, we examine the magnitude and temporal persistence of learned value's influence on inhibitory control in a cross-sectional sample of 8- to 25-year-olds. Participants first underwent conditioning of a motor approach response to two initially neutral cues, with one cue reinforced with monetary reward and the other with no monetary outcome. Subsequently, during fMRI, participants reencountered these cues as no-go targets in a nonreinforced go/no-go paradigm. Although the influence of learned value increasingly disrupted inhibitory control with increasing age, in young adults this pattern remitted over the course of the task, whereas during adolescence the impairing effect of reward history persisted. Successful no-go performance to the previously rewarded target was related to greater recruitment of the right inferior frontal gyrus and age-related increase in functional connectivity between the inferior frontal gyrus and the ventromedial PFC for the previously rewarded no-go target over the control target. Together, results indicate the complex influence of value on goals over development relies upon the increased coordination of distinct higher-order regions in the PFC.

The fornix bundle is a major white matter pathway of the hippocampus. While volume of the hippocampus has been a primary imaging biomarker of Alzheimer's disease progression, recent research has suggested that the volume and microstructural characteristics of the fornix bundle connecting the hippocampus could add relevant information for diagnosing and staging Alzheimer's disease. Using a robust fornix bundle isolation technique in native diffusion space, this study investigated whether diffusion measurements of the fornix differed between normal older adults and Alzheimer's disease patients when controlling for volume measurements. Data were collected using high gradient multi-shell diffusion-weighted MRI from a Siemens CONNECTOM scanner in 23 Alzheimer's disease and 23 age- and sex-matched control older adults (age range = 53–92). These data were used to reconstruct a continuous fornix bundle in every participant's native diffusion space, from which tract-derived volumetric and diffusion metrics were extracted and compared between groups. Diffusion metrics included those from a tensor model and from a generalized q-sampling imaging model. Results showed no significant differences in tract-derived fornix volumes but did show altered diffusion metrics within tissue classified as the fornix in the Alzheimer's disease group. Comparisons to a manual tracing method indicated the same pattern of results and high correlations between the methods. These results suggest that in Alzheimer's disease, diffusion characteristics may provide more sensitive measures of fornix degeneration than do volume measures and may be a potential early marker for loss of medial temporal lobe connectivity., Highlights • An enhanced method for measurement of continuous fornix bundles is described. • Diffusion characteristics of the fornix were degraded in Alzheimer's disease. • Alzheimer's disease primarily affected the crus and body of the fornix. • Diffusion differences were observed controlling for fornix volume differences.

Diffusion MRI tractography produces massive sets of streamlines that need to be clustered into anatomically meaningful white-matter bundles. Conventional clustering techniques group streamlines based on their proximity in Euclidean space. We have developed AnatomiCuts, an unsupervised method for clustering tractography streamlines based on their neighboring anatomical structures, rather than their coordinates in Euclidean space. In this work, we show that the anatomical similarity metric used in AnatomiCuts can be extended to find corresponding clusters across subjects and across hemispheres, without inter-subject or inter-hemispheric registration. Our proposed approach enables group-wise tract cluster analysis, as well as studies of hemispheric asymmetry. We evaluate our approach on data from the pilot MGH-Harvard-USC Lifespan Human Connectome project, showing improved correspondence in tract clusters across 184 subjects aged 8-90. Our method shows up to 38% improvement in the overlap of corresponding clusters when comparing subjects with large age differences. The techniques presented here do not require registration to a template and can thus be applied to populations with large inter-subject variability, e.g., due to brain development, aging, or neurological disorders.

Alzheimer’s disease neuropathology is thought to spread across anatomically and functionally connected brain regions. However, the precise sequence of spread remains ambiguous. The prevailing model posits that Alzheimer’s neurodegeneration starts in the entorhinal cortices, before spreading to temporoparietal cortex. Challenging this model, we previously provided evidence that degeneration within the nucleus basalis of Meynert (NbM), a subregion of the basal forebrain heavily populated by cortically projecting cholinergic neurons, precedes and predicts entorhinal degeneration (Schmitz and Spreng, 2016). There have been few systematic attempts at directly comparing staging models using in vivo longitudinal biomarker data, and determining if these comparisons generalize across independent samples. Here we addressed the sequence of pathological staging in Alzheimer’s disease using two independent samples of the Alzheimer’s Disease Neuroimaging Initiative (N1 = 284; N2 = 553) with harmonized CSF assays of amyloid (Aβ) and hyperphosphorylated tau (pTau), and longitudinal structural MRI data over two years. We derived measures of gray matter degeneration in a priori NbM and the entorhinal regions of interest. To examine the spreading of degeneration, we used a predictive modelling strategy which tests whether baseline gray matter volume in a seed region accounts for longitudinal change in a target region. We demonstrated that predictive pathological spread favored the NbM→entorhinal over the entorhinal→NbM model. This evidence generalized across the independent samples (N1: r=0.20, p=0.03; N2: r=0.37, pt826=2.55, p=0.01). The moderating effect of CSF was robust to additional factors, including clinical diagnosis (t826=1.65, p=0.49). We then applied our predictive modelling strategy to an exploratory whole-brain voxel-wise analysis to examine the spatial specificity of the NbM→entorhinal model. We found that smaller baseline NbM volumes predicted greater degeneration in localized regions of the entorhinal and perirhinal cortices. By contrast, smaller baseline entorhinal volumes predicted degeneration in the medial temporal cortex, recapitulating the prevailing staging model. Our findings suggest that degeneration of the basal forebrain cholinergic projection system is a robust and reliable upstream event of entorhinal and neocortical degeneration, calling into question the prevailing view of Alzheimer’s disease pathogenesis.

Examination of large-scale distributed networks within the individual reveals details of cortical network organization that are absent in group-averaged studies. One recent discovery is that a distributed transmodal network, often referred to as the “default network,” comprises two closely interdigitated networks, only one of which is coupled to posterior parahippocampal cortex. Not all studies of individuals have identified the same networks, and questions remain about the degree to which the two networks are separate, particularly within regions hypothesized to be interconnected hubs. In this study we replicate the observation of network separation across analytical (seed-based connectivity and parcellation) and data projection (volume and surface) methods in two individuals each scanned 31 times. Additionally, three individuals were examined with high-resolution (7T; 1.35 mm) functional magnetic resonance imaging to gain further insight into the anatomical details. The two networks were identified with separate regions localized to adjacent portions of the cortical ribbon, sometimes inside the same sulcus. Midline regions previously implicated as hubs revealed near complete spatial separation of the two networks, displaying a complex spatial topography in the posterior cingulate and precuneus. The network coupled to parahippocampal cortex also revealed a separate region directly within the hippocampus, at or near the subiculum. These collective results support that the default network is composed of at least two spatially juxtaposed networks. Fine spatial details and juxtapositions of the two networks can be identified within individuals at high resolution, providing insight into the network organization of association cortex and placing further constraints on interpretation of group-averaged neuroimaging data. NEW & NOTEWORTHY Recent evidence has emerged that canonical large-scale networks such as the “default network” fractionate into parallel distributed networks when defined within individuals. This research uses high-resolution imaging to show that the networks possess juxtapositions sometimes evident inside the same sulcus and within regions that have been previously hypothesized to be network hubs. Distinct circumscribed regions of one network were also resolved in the hippocampal formation, at or near the parahippocampal cortex and subiculum.

Prior studies have identified white matter abnormalities in Alzheimer's disease (AD). Yet, cross-sectional studies in normal older individuals show little evidence for an association between markers of AD risk (APOE4 genotype and amyloid deposition), and white matter integrity. Here, 108 normal older adults (age, 66-87) with assessments of apolipoprotein e4 (APOE4) genotype and assessment of amyloid burden by positron emission tomography underwent diffusion tensor imaging scans for measuring white matter integrity at 2 time points, on average 2.6 years apart. Linear mixed-effects models showed that amyloid burden at baseline was associated with steeper decline in fractional anisotropy in the parahippocampal cingulum (p0.05). This association was not significant between baseline measures suggesting that longitudinal analyses can provide novel insights that are not detectable in cross-sectional designs. Amyloid-related changes in hippocampus volume did not explain the association between amyloid burden and change in fractional anisotropy. The results suggest that accumulation of cortical amyloid and white matter changes in parahippocampal cingulum are not independent processes in individuals at increased risk for AD.

During adolescence, rapid development and reorganization of the dopaminergic system supports increasingly sophisticated reward learning and the ability to exert behavioral control. Disruptions in the ability to exert control over previously rewarded behavior may underlie some forms of adolescent psychopathology. Specifically, symptoms of externalizing psychopathology may be associated with difficulties in flexibly adapting behavior in the context of reward. However, the direct interaction of cognitive control and reward learning in adolescent psychopathology symptoms has not yet been investigated. The present study used a Research Domain Criteria framework to investigate whether behavioral and neuronal indices of inhibition to previously rewarded stimuli underlie individual differences in externalizing symptoms in N = 61 typically developing adolescents. Using a task that integrates the Monetary Incentive Delay and Go-No-Go paradigms, we observed a positive association between externalizing symptoms and activation of the left middle frontal gyrus during response inhibition to cues with a history of reward. These associations were robust to controls for internalizing symptoms and neural recruitment during inhibition of cues with no reward history. Our findings suggest that inhibitory control over stimuli with a history of reward may be a useful marker for future inquiry into the development of externalizing psychopathology in adolescence.

Examination of large-scale distributed networks within the individual reveals details of cortical network organization that are absent in group-averaged studies. One recent discovery is that a distributed transmodal network, often referred to as the ‘default network’, is comprised of two separate but closely interdigitated networks, only one of which is coupled to posterior parahippocampal cortex. Not all studies of individuals have identified the same networks and questions remain about the degree to which the two networks are separate, particularly within regions hypothesized to be interconnected hubs. Here we replicate the observation of network separation across analytical (seed-based connectivity and parcellation) and data projection (volume and surface) methods in 2 individuals each scanned 31 times. Additionally, 3 individuals were examined with high-resolution fMRI to gain further insight into the anatomical details. The two networks were identified with separate regions localized to adjacent portions of the cortical ribbon, sometimes inside the same sulcus. Midline regions previously implicated as hubs revealed near complete spatial separation of the two networks, displaying a complex spatial topography in the posterior cingulate and precuneus. The network coupled to parahippocampal cortex also revealed a separate region directly within the hippocampus at or near the subiculum. These collective results support that the default network is composed of at least two spatially juxtaposed networks. Fine spatial details and juxta-positions of the two networks can be identified within individuals at high resolution, providing insight into the network organization of association cortex and placing further constraints on interpretation of group-averaged neuroimaging data.

Background Patients with bipolar depression are characterized by dysregulation across the full spectrum of mood, differentiating them from patients with unipolar depression. The ability to switch neural resources among the default mode network, salience network, and executive control network (ECN) has been proposed as a key mechanism for adaptive mood regulation. The anterior insula is implicated in the modulation of functional network switching. Differential connectivity between anterior insula and functional networks may provide insights into pathophysiological differences between bipolar and unipolar mood disorders, with implications for diagnosis and treatment. Methods Resting-state functional magnetic resonance imaging data were collected from 98 subjects (35 unipolar, 24 bipolar, and 39 healthy control subjects). Pearson correlations were computed between bilateral insula seed regions and a priori defined target regions from the default mode network, salience network, and ECN. After r-to-z transformation, a one-way multivariate analysis of covariance was conducted to identify significant differences in connectivity between groups. Post hoc pairwise comparisons were conducted and Bonferroni corrections were applied. Receiver-operating characteristics were computed to assess diagnostic sensitivity. Results Patients with bipolar depression evidenced significantly altered right anterior insula functional connectivity with the inferior parietal lobule of the ECN relative to patients with unipolar depression and control subjects. Right anterior insula–inferior parietal lobule connectivity significantly discriminated patients with bipolar depression. Conclusions Impaired functional connectivity between the anterior insula and the inferior parietal lobule of the ECN distinguishes patients with bipolar depression from those with unipolar depression and healthy control subjects. This finding highlights a pathophysiological mechanism with potential as a therapeutic target and a clinical biomarker for bipolar disorder, exhibiting reasonable sensitivity and specificity.

Attention-deficit/hyperactivity disorder (ADHD) is increasingly understood as a disorder of spontaneous brain-network interactions. The default mode network (DMN), implicated in ADHD-linked behaviors including mind-wandering and attentional fluctuations, has been shown to exhibit abnormal spontaneous functional connectivity (FC) within-network and with other networks (salience, dorsal attention and frontoparietal) in ADHD. Although the cerebellum has been implicated in the pathophysiology of ADHD, it remains unknown whether cerebellar areas of the DMN (CerDMN) exhibit altered FC with cortical networks in ADHD. Here, 23 adults with ADHD and 23 age-, IQ-, and sex-matched controls underwent resting state fMRI. The mean time series of CerDMN areas was extracted, and FC with the whole brain was calculated. Whole-brain between-group differences in FC were assessed. Additionally, relationships between inattention and individual differences in FC were assessed for between-group interactions. In ADHD, CerDMN areas showed positive FC (in contrast to average FC in the negative direction in controls) with widespread regions of salience, dorsal attention and sensorimotor networks. ADHD individuals also exhibited higher FC (more positive correlation) of CerDMN areas with frontoparietal and visual network regions. Within the control group, but not in ADHD, participants with higher inattention had higher FC between CerDMN and regions in the visual and dorsal attention networks. This work provides novel evidence of impaired CerDMN coupling with cortical networks in ADHD and highlights a role of cerebro-cerebellar interactions in cognitive function. These data provide support for the potential targeting of CerDMN areas for therapeutic interventions in ADHD.

Trance is an absorptive state of consciousness characterized by narrowed awareness of external surroundings and has long been used—for example, by shamans—to gain insight. Shamans across cultures often induce trance by listening to rhythmic drumming. Using functional magnetic resonance imaging (fMRI), we examined the brain-network configuration associated with trance. Experienced shamanic practitioners (n = 15) listened to rhythmic drumming, and either entered a trance state or remained in a nontrance state during 8-min scans. We analyzed changes in network connectivity. Trance was associated with higher eigenvector centrality (i.e., stronger hubs) in 3 regions: posterior cingulate cortex (PCC), dorsal anterior cingulate cortex (dACC), and left insula/operculum. Seed-based analysis revealed increased coactivation of the PCC (a default network hub involved in internally oriented cognitive states) with the dACC and insula (control-network regions involved in maintaining relevant neural streams). This coactivation suggests that an internally oriented neural stream was amplified by the modulatory control network. Additionally, during trance, seeds within the auditory pathway were less connected, possibly indicating perceptual decoupling and suppression of the repetitive auditory stimuli. In sum, trance involved coactive default and control networks, and decoupled sensory processing. This network reconfiguration may promote an extended internal train of thought wherein integration and insight can occur.

Head motion reduces data quality of neuroimaging data. In three functional magnetic resonance imaging (MRI) experiments we demonstrate that people make less head movements under task than resting-state conditions. In Experiment 1, we observed less head motion during a memory encoding task than during the resting-state condition. In Experiment 2, using publicly shared data from the UCLA Consortium for Neuropsychiatric Phenomics LA5c Study, we again found less head motion during several active task conditions than during a resting-state condition, although some task conditions also showed comparable motion. In the healthy controls, we found more head motion in men than in women and more motion with increasing age. When comparing clinical groups, we found that patients with a clinical diagnosis of bipolar disorder, or schizophrenia, move more compared to healthy controls or patients with ADHD. Both these experiments had a fixed acquisition order across participants, and we could not rule out that a first or last scan during a session might be particularly prone to more head motion. Therefore, we conducted Experiment 3, in which we collected several task and resting-state fMRI runs with an acquisition order counter-balanced. The results of Experiment 3 show again less head motion during several task conditions than during rest. Together these experiments demonstrate that small head motions occur during MRI even with careful instruction to remain still and fixation with foam pillows, but that head motion is lower when participants are engaged in a cognitive task. These finding may inform the choice of functional runs when studying difficult-to-scan populations, such as children or certain patient populations. Our findings also indicate that differences in head motion complicate direct comparisons of measures of functional neuronal networks between task and resting-state fMRI because of potential differences in data quality. In practice, a task to reduce head motion might be especially useful when acquiring structural MRI data such as T1/T2-weighted and diffusion MRI in research and clinical settings.

Functional connectivity magnetic resonance imaging (fcMRI) is a powerful tool for understanding the network level organization of the brain in research settings and is increasingly being used to study large-scale neuronal network degeneration in clinical trial settings. Presently, a variety of techniques, including seed-based correlation analysis and group independent components analysis (with either dual regression or back projection) are commonly employed to compute functional connectivity metrics. In the present report, we introduce template based rotation,(1) a novel analytic approach optimized for use with a priori network parcellations, which may be particularly useful in clinical trial settings. Template based rotation was designed to leverage the stable spatial patterns of intrinsic connectivity derived from out-of-sample datasets by mapping data from novel sessions onto the previously defined a priori templates. We first demonstrate the feasibility of using previously defined a priori templates in connectivity analyses, and then compare the performance of template based rotation to seed based and dual regression methods by applying these analytic approaches to an fMRI dataset of normal young and elderly subjects. We observed that template based rotation and dual regression are approximately equivalent in detecting fcMRI differences between young and old subjects, demonstrating similar effect sizes for group differences and similar reliability metrics across 12 cortical networks. Both template based rotation and dual-regression demonstrated larger effect sizes and comparable reliabilities as compared to seed based correlation analysis, though all three methods yielded similar patterns of network differences. When performing inter-network and sub-network connectivity analyses, we observed that template based rotation offered greater flexibility, larger group differences, and more stable connectivity estimates as compared to dual regression and seed based analyses. This flexibility owes to the reduced spatial and temporal orthogonality constraints of template based rotation as compared to dual regression. These results suggest that template based rotation can provide a useful alternative to existing fcMRI analytic methods, particularly in clinical trial settings where predefined outcome measures and conserved network descriptions across groups are at a premium.

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 sub-network that relates to the cortical nodes of the DMN through parahippocampal functional connections.

Advanced aging is associated with reduced attentional control and less flexible information processing. Here, the origins of these cognitive effects were explored using a functional magnetic resonance imaging task that systematically varied demands to shift attention and inhibit irrelevant information across task blocks. Prefrontal and parietal regions previously implicated in attentional control were recruited by the task and most so for the most demanding task configurations. A subset of older individuals did not modulate activity in frontal and parietal regions in response to changing task requirements. Older adults who did not dynamically modulate activity underperformed their peers and scored more poorly on neuropsychological measures of executive function and speed of processing. Examining 2 markers of preclinical pathology in older adults revealed that white matter hyperintensities (WMHs), but not high amyloid burden, were associated with failure to modulate activity in response to changing task demands. In contrast, high amyloid burden was associated with alterations in default network activity. These results suggest failure to modulate frontal and parietal activity reflects a disruptive process in advanced aging associated with specific neuropathologic processes.

Disruption of functional connectivity between brain regions may represent an early functional consequence of β-amyloid pathology prior to clinical Alzheimer's disease. We aimed to investigate if non-demented older individuals with increased amyloid burden demonstrate disruptions of functional whole-brain connectivity in cortical hubs (brain regions typically highly connected to multiple other brain areas) and if these disruptions are associated with neuronal dysfunction as measured with fluorodeoxyglucose-positron emission tomography. In healthy subjects without cognitive symptoms and patients with mild cognitive impairment, we used positron emission tomography to assess amyloid burden and cerebral glucose metabolism, structural magnetic resonance imaging to quantify atrophy and novel resting state functional magnetic resonance imaging processing methods to calculate whole-brain connectivity. Significant disruptions of whole-brain connectivity were found in amyloid-positive patients with mild cognitive impairment in typical cortical hubs (posterior cingulate cortex/precuneus), strongly overlapping with regional hypometabolism. Subtle connectivity disruptions and hypometabolism were already present in amyloid-positive asymptomatic subjects. Voxel-based morphometry measures indicate that these findings were not solely a consequence of regional atrophy. Whole-brain connectivity values and metabolism showed a positive correlation with each other and a negative correlation with amyloid burden. These results indicate that disruption of functional connectivity and hypometabolism may represent early functional consequences of emerging molecular Alzheimer's disease pathology, evolving prior to clinical onset of dementia. The spatial overlap between hypometabolism and disruption of connectivity in cortical hubs points to a particular susceptibility of these regions to early Alzheimer's-type neurodegeneration and may reflect a link between synaptic dysfunction and functional disconnection.

Coherent fluctuations of spontaneous brain activity are present in distinct functional-anatomic brain systems during undirected wakefulness. However, the behavioral significance of this spontaneous activity has only begun to be investigated. Our previous studies have demonstrated that successful memory formation requires coordinated neural activity in a distributed memory network including the hippocampus and posteromedial cortices, specifically the precuneus and posterior cingulate (PPC), thought to be integral nodes of the default network. In this study, we examined whether intrinsic connectivity during the resting state between the hippocampus and PPC can predict individual differences in the performance of an associative memory task among cognitively intact older individuals. The intrinsic connectivity, between regions within the hippocampus and PPC that were maximally engaged during a subsequent memory fMRI task, was measured during a period of rest prior to the performance of the memory paradigm. Stronger connectivity between the hippocampal and posteromedial regions during rest predicted better performance on the memory task. Furthermore, hippocampal-PPC intrinsic connectivity was also significantly correlated with episodic memory measures on neuropsychological tests, but not with performance in non-memory domains. Whole brain exploratory analyses further confirmed the spatial specificity of the relationship between hippocampal-default network posteromedial cortical connectivity and memory performance in older subjects. Our findings provide support for the hypothesis that one of the functions of this large-scale brain network is to subserve episodic memory processes. Research is ongoing to determine if impaired connectivity between these regions may serve as a predictor of memory decline related to early Alzheimer’s disease.

De ontwikkeling van beeldvormende technieken zoals positron emission tomography (PET) en magnetic resonance imaging (MRI) heeft in de afgelopen decennia een grote impuls gegeven aan de vermeerdering van kennis over het functioneren van het brein. Talloze hersenfuncties zijn inmiddels onderzocht. In experimenten wordt vaak activiteit in het brein tijdens het uitvoeren van een bepaalde taak vergeleken met activiteit tijdens rust. De laatste jaren is er echter een groeiende belangstelling voor een netwerk van hersengebieden dat juist actief blijkt tijdens rust. Als een proefpersoon de opdracht krijgt om in de scanner te liggen en niets te doen, is een netwerk van gebieden actief dat default mode network of brain function wordt genoemd, het functionele basisnetwerk van de hersenen. Dit netwerk blijkt onder andere een rol te spelen bij het denken aan gebeurtenissen in het verleden, het zich voorstellen van de mentale staat van anderen en het zich inbeelden van toekomstige handelingen.

Recent large-scale longitudinal aging studies question earlier claims that higher education protects against cognitive decline in older age. In the present study, the authors addressed this issue by determining whether educational level had an attenuating effect on the rate of cognitive change assessed with a broad range of neuropsychological tests in a community sample of 872 healthy individuals aged 49 to 81 years at baseline. The participants were followed for 6 years and were tested 3 times (at baseline and at 3 and 6 years after baseline). Results of linear mixed-model analyses showed that education had no significant effect on cognitive change over time. These results are discussed in terms of the age range of the sample, definition and range of education, cognitive measures used, length of the study and number of consecutive assessments, and confounding effect of health, The findings question the extent of the presumed protective effects of higher education on cognitive decline during normal aging.

In this paper we investigate the use of data driven clustering methods for functional connectivity analysis in fMRI. In particular, we consider the K-Means and Spectral Clustering algorithms as alternatives to the commonly used Seed-Based Analysis. To enable clustering of the entire brain volume, we use the Nystrom Method to approximate the necessary spectral decompositions. We apply K-Means, Spectral Clustering and Seed-Based Analysis to resting-state fMRI data collected from 45 healthy young adults. Without placing any a priori constraints, both clustering methods yield partitions that are associated with brain systems previously identified via Seed-Based Analysis. Our empirical results suggest that clustering provides a valuable tool for functional connectivity analysis.

The amygdala is a hub in emotional processing, including that of negative affect. Healthy men and women have distinct differences in amygdala responses, potentially setting the stage for the observed sex differences in the prevalence of fear, anxiety, and pain disorders. Here, we examined how amygdala subnuclei resting-state functional connectivity is affected by sex, as well as explored how the functional connectivity is related to estrogen levels. Resting-state functional connectivity was measured using functional magnetic resonance imaging (fMRI) with seeds placed in the left and right laterobasal (LB) and centromedial (CM) amygdala. Sex differences were studied in 48 healthy men and 48 healthy women, matched for age, while the association with estrogen was analyzed in a subsample of 24 women, for whom hormone levels had been assessed. For the hormone analyses, the subsample was further divided into a lower and higher estrogen levels group based on a median split. We found distinct sex differences in the LB and CM amygdala resting-state functional connectivity, as well as preliminary evidence for an association between estrogen levels and connectivity patterns. These results are potentially valuable in explaining why women are more afflicted by conditions of negative affect than are men, and could imply a mechanistic role for estrogen in modulating emotion.

Attention-deficit/hyperactivity disorder (ADHD) is increasingly understood as a disorder of spontaneous brain-network interactions. The default mode network (DMN), implicated in ADHD-linked behaviors including mind-wandering and attentional fluctuations, has been shown to exhibit abnormal spontaneous functional connectivity (FC) within-network and with other networks (salience, dorsal attention and frontoparietal) in ADHD. Although the cerebellum has been implicated in the pathophysiology of ADHD, it remains unknown whether cerebellar areas of the DMN (CerDMN) exhibit altered FC with cortical networks in ADHD. Here, 23 adults with ADHD and 23 age-, IQ-, and sex-matched controls underwent resting state fMRI. The mean time series of CerDMN areas was extracted, and FC with the whole brain was calculated. Whole-brain between-group differences in FC were assessed. Additionally, relationships between inattention and individual differences in FC were assessed for between-group interactions. In ADHD, CerDMN areas showed positive FC (in contrast to average FC in the negative direction in controls) with widespread regions of salience, dorsal attention and sensorimotor networks. ADHD individuals also exhibited higher FC (more positive correlation) of CerDMN areas with frontoparietal and visual network regions. Within the control group, but not in ADHD, participants with higher inattention had higher FC between CerDMN and regions in the visual and dorsal attention networks. This work provides novel evidence of impaired CerDMN coupling with cortical networks in ADHD and highlights a role of the cerebro-cerebellar interactions in cognitive function. These data provide support for the potential targeting of CerDMN areas for therapeutic interventions in ADHD.

The MGH-USC CONNECTOM MRI scanner housed at the Massachusetts General Hospital (MGH) is a major hardware innovation of the Human Connectome Project (HCP). The 3T CONNECTOM scanner is capable of producing a magnetic field gradient of up to 300 mT/m strength for in vivo human brain imaging, which greatly shortens the time spent on diffusion encoding, and decreases the signal loss due to T2 decay. To demonstrate the capability of the novel gradient system, data of healthy adult participants were acquired for this MGH-USC Adult Diffusion Dataset (N=35), minimally preprocessed, and shared through the Laboratory of Neuro Imaging Image Data Archive (LONI IDA) and the WU-Minn Connectome Database (ConnectomeDB). Another purpose of sharing the data is to facilitate methodological studies of diffusion MRI (dMRI) analyses utilizing high diffusion contrast, which perhaps is not easily feasible with standard MR gradient system. In addition, acquisition of the MGH-Harvard-USC Lifespan Dataset is currently underway to include 120 healthy participants ranging from 8 to 90 years old, which will also be shared through LONI IDA and ConnectomeDB. Here we describe the efforts of the MGH-USC HCP consortium in acquiring and sharing the ultra-high b-value diffusion MRI data and provide a report on data preprocessing and access. We conclude with a demonstration of the example data, along with results of standard diffusion analyses, including q-ball Orientation Distribution Function (ODF) reconstruction and tractography.

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.

The past decade of cognitive neuroscience and neuroimaging research has yielded several critical insights into the organization of the human brain, in particular, the existence of multiple large-scale functional networks. Several of these networks map easily onto conventional notions regarding brain–behavior relationships, such as intrinsic networks subserving motor, sensory, and language function. Perhaps the least intuitive network and arguably the most salient for the study of dementia is a set of brain regions, including the posterior cingulate, precuneus, lateral parietal, lateral temporal, and medial prefrontal cortices, collectively known as the default mode network (DMN). This nomenclature arose from the initial observation in PET studies that these regions show the greatest activity during the resting or “default” state, and demonstrate a marked decrease in activity during cognitive tasks involving externally directed attention.1,2 Multiple fMRI studies, during both cognitive tasks and resting state, have confirmed strong intercorrelations among the DMN cortical regions, as well as functional connectivity with the hippocampus and related structures within medial temporal lobe. The DMN is known to subserve a number of key memory processes, including episodic encoding and retrieval, autobiographical and metamemory processes, as well as other complex cognitive constructs, including moral decision-making and “theory of mind.” In this issue of Neurology ®, Petrella et al.3 report that DMN connectivity was significantly lower in a group of patients with mild cognitive impairment (MCI) who subsequently progressed to a diagnosis of Alzheimer disease (AD) over a period of 2–3 years, compared to patients with MCI who did not decline. Importantly, the study also demonstrated that DMN connectivity provided additional information in predicting the likelihood of progression among the patients with MCI, above and beyond age, Mini-Mental State Examination score, and gray matter volume at baseline. Interestingly, DMN connectivity did not remain a significant predictor …

Purpose The present multimodal neuroimaging study examined whether amyloid pathology and glucose metabolism are related to cortical volume loss over time in Alzheimer's disease (AD) patients and healthy elderly controls. Methods Structural MRI scans of eleven AD patients and ten controls were available at baseline and follow-up (mean interval 2.5 years). Change in brain structure over time was defined as percent change of cortical volume within seven a-priori defined regions that typically show the strongest structural loss in AD. In addition, two PET scans were performed at baseline: [C-11] PIB to assess amyloid-beta plaque load and [18F]FDG to assess glucose metabolism. [11C] PIB binding and [18F]FDG uptake were measured in the precuneus, a region in which both amyloid deposition and glucose hypometabolism occur early in the course of AD. Results While amyloid-beta plaque load at baseline was not related to cortical volume loss over time in either group, glucose metabolism within the group of AD patients was significantly related to volume loss over time (rho=0.56, p

two years before conversion, atrophy has spread to large parts of the temporal and frontal lobes, much of the cingulate gyrus and parts of the orbitofrontal region. Twelve months before conversion, atrophy is present over all the cortex except the occipital lobe and the sensory-motor areas. Six months later and at conversion this pattern persists, but with more severe atrophy.Conclusions: Focal atrophy can be observed in patients with MCI three years before they are diagnosedwith clinically definite AD. The atrophy accelerates during the MCI stage and affects the entire cortex except the occipital and sensory-motor cortex at the time of diagnosis —not unlike the progressive patterns of amyloid deposition described by Braak [7].References: [1] Petersen, R.C., et al. (2001) Current concepts in mild cognitive impairment. Arch Neurol 58, 1985-1992. [2] Coup e, P., et al. (2008), ‘An Optimized Blockwise NonLocal Means Denoising Filter for 3-D Magnetic Resonance Images’. IEEE Trans Med Im 27(4), 425– 441. [3] Sled, J.G., et al. (1998), ‘A nonparametric method for automatic correction of intensity nonuniformity in MRI data’, IEEE Trans Med Im 17(1), 87-97. [4] Collins, D.L., et al. (1994), ’Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space’ J Comp Ass Tom 18(2), 192-205. [5] Eskildsen, S.F., et al. (2012), ‘BEaST: Brain Extraction based on nonlocal Segmentation Technique’, NeuroImage 59(3), 2362-2373. [6] Eskildsen, S.F., et al. (2006), ‘Active surface approach for extraction of the human cerebral cortex from MRI’, LNCS 4191, 823-830. [7] Braak, H & Braak E, (1991), ‘Neuropathological staging of Alzheimer-related changes’, Acta Neuropathologica 82, 239-259.

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 sub-network that relates to the cortical nodes of the DMN through parahippocampal functional connections.

Background: Previous studies have revealed that functional magnetic resonance imaging (fMRI) blood oxygen level-dependent (BOLD) signal in specific brain regions correlates with cross-sectional performance on standardized clinical trial measures in Alzheimer’s disease (AD); however, the relationship between longitudinal change in fMRI-BOLD signal and neuropsychological performance remains unknown. Objective: To identify changes in regional fMRI-BOLD activity that tracks change in neuropsychological performance in mild AD dementia over 6 months. Methods: Twenty-four subjects (mean age 71.6) with mild AD dementia (mean Mini Mental State Examination 21.7, Global Clinical Dementia Rating 1.0) on stable donepezil dosing participated in two task-related fMRI sessions consisting of a face-name paired associative encoding memory paradigm 24 weeks apart during a randomized placebo-controlled pharmaco-fMRI drug study. Regression analysis was used to identify regions where the change in fMRI activity for Novel > Repeated stimulus contrast was associated with the change scores on postscan memory tests and the Free and Cued Selective Reminding Test (FCSRT). Results: Correlations between changes in postscan memory accuracy and changes in fMRI activity were observed in regions including the angular gyrus, parahippocampal gyrus, inferior frontal gyrus and cerebellum. Correlations between changes in FCSRT-free recall and changes in fMRI were observed in regions including the inferior parietal lobule, precuneus, hippocampus and parahippocampal gyrus. Conclusion: Changes in encoding-related fMRI activity in regions implicated in mnemonic networks correlated with changes in psychometric measures of episodic memory retrieval performed outside the scanner. These exploratory results support the potential of fMRI activity to track cognitive change and detect signals of short-term pharmacologic effect in early-phase AD studies.

Resting state functional connectivity MRI (fcMRI) is widely used to investigate brain networks that exhibit correlated fluctuations. While fcMRI does not provide direct measurement of anatomic connectivity, accumulating evidence suggests it is sufficiently constrained by anatomy to allow the architecture of distinct brain systems to be characterized. fcMRI is particularly useful for characterizing large-scale systems that span distributed areas (e.g., polysynaptic cortical pathways, cerebro-cerebellar circuits, cortical-thalamic circuits) and has complementary strengths when contrasted with the other major tool available for human connectomics—high angular resolution diffusion imaging (HARDI). We review what is known about fcMRI and then explore fcMRI data reliability, effects of preprocessing, analysis procedures, and effects of different acquisition parameters across six studies ( n = 98) to provide recommendations for optimization. Run length (2–12 min), run structure (1 12-min run or 2 6-min runs), temporal resolution (2.5 or 5.0 s), spatial resolution (2 or 3 mm), and the task (fixation, eyes closed rest, eyes open rest, continuous word-classification) were varied. Results revealed moderate to high test-retest reliability. Run structure, temporal resolution, and spatial resolution minimally influenced fcMRI results while fixation and eyes open rest yielded stronger correlations as contrasted to other task conditions. Commonly used preprocessing steps involving regression of nuisance signals minimized nonspecific (noise) correlations including those associated with respiration. The most surprising finding was that estimates of correlation strengths stabilized with acquisition times as brief as 5 min. The brevity and robustness of fcMRI positions it as a powerful tool for large-scale explorations of genetic influences on brain architecture. We conclude by discussing the strengths and limitations of fcMRI and how it can be combined with HARDI techniques to support the emerging field of human connectomics.