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Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an artificial intelligence (AI) model that harnesses a broad array of data, including demographics, individual and family medical history, medication use, neuropsychological assessments, functional evaluations and multimodal neuroimaging, to identify the etiologies contributing to dementia in individuals. The study, drawing on 51,269 participants across 9 independent, geographically diverse datasets, facilitated the identification of 10 distinct dementia etiologies. It aligns diagnoses with similar management strategies, ensuring robust predictions even with incomplete data. Our model achieved a microaveraged area under the receiver operating characteristic curve (AUROC) of 0.94 in classifying individuals with normal cognition, mild cognitive impairment and dementia. Also, the microaveraged AUROC was 0.96 in differentiating the dementia etiologies. Our model demonstrated proficiency in addressing mixed dementia cases, with a mean AUROC of 0.78 for two co-occurring pathologies. In a randomly selected subset of 100 cases, the AUROC of neurologist assessments augmented by our AI model exceeded neurologist-only evaluations by 26.25%. Furthermore, our model predictions aligned with biomarker evidence and its associations with different proteinopathies were substantiated through postmortem findings. Our framework has the potential to be integrated as a screening tool for dementia in clinical settings and drug trials. Further prospective studies are needed to confirm its ability to improve patient care.
ABSTRACT
Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an AI model that harnesses a broad array of data, including demographics, individual and family medical history, medication use, neuropsychological assessments, functional evaluations, and multimodal neuroimaging, to identify the etiologies contributing to dementia in individuals. The study, drawing on 51,269 participants across 9 independent, geographically diverse datasets, facilitated the identification of 10 distinct dementia etiologies. It aligns diagnoses with similar management strategies, ensuring robust predictions even with incomplete data. Our model achieved a micro-averaged area under the receiver operating characteristic curve (AUROC) of 0.94 in classifying individuals with normal cognition, mild cognitive impairment and dementia. Also, the micro-averaged AUROC was 0.96 in differentiating the dementia etiologies. Our model demonstrated proficiency in addressing mixed dementia cases, with a mean AUROC of 0.78 for two co-occurring pathologies. In a randomly selected subset of 100 cases, the AUROC of neurologist assessments augmented by our AI model exceeded neurologist-only evaluations by 26.25%. Furthermore, our model predictions aligned with biomarker evidence and its associations with different proteinopathies were substantiated through postmortem findings. Our framework has the potential to be integrated as a screening tool for dementia in various clinical settings and drug trials, with promising implications for person-level management.
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OBJECTIVE: To evaluate whether preterm infants with prenatal opioid exposure had differences in brain size on head ultrasounds (HUS) in comparison to non-exposed infants. STUDY DESIGN: Preterm infants ≤34 weeks with prenatal opioid exposure (n = 47) and matched non-exposed infants (n = 62) with early HUSs were examined. Fifteen brain measurements were made and linear regression models performed to evaluate differences. RESULTS: Brain measurements were smaller in the right ventricular index [ß = -0.18 mm (95% CI -0.32, -0.03]), left ventricular index [ß = -0.04 mm (95% CI -0.08, -0.003)], left basal ganglia insula [ß = -0.10 mm (95% CI -0.15, -0.04)], right basal ganglia insula [ß = -0.08 mm (95% CI -0.14, -0.03)], corpus callosum fastigium length [ß = -0.16 mm (95% CI -0.25, -0.06)], intracranial height index [ß = -0.31 mm (95% CI -0.44, -0.18)], and transcerebellar measurements [ß = -0.13 (95% CI -0.25, -0.02)] in the opioid-exposed group. CONCLUSIONS: Preterm infants with prenatal opioid exposure have smaller brain sizes compared to non-exposed infants, potentially increasing their risk for neurodevelopmental abnormalities.
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A central goal of modern magnetic resonance imaging (MRI) is to reduce the time required to produce high-quality images. Efforts have included hardware and software innovations such as parallel imaging, compressed sensing, and deep learning-based reconstruction. Here, we propose and demonstrate a Bayesian method to build statistical libraries of magnetic resonance (MR) images in k-space and use these libraries to identify optimal subsampling paths and reconstruction processes. Specifically, we compute a multivariate normal distribution based upon Gaussian processes using a publicly available library of T1-weighted images of healthy brains. We combine this library with physics-informed envelope functions to only retain meaningful correlations in k-space. This covariance function is then used to select a series of ring-shaped subsampling paths using Bayesian optimization such that they optimally explore space while remaining practically realizable in commercial MRI systems. Combining optimized subsampling paths found for a range of images, we compute a generalized sampling path that, when used for novel images, produces superlative structural similarity and error in comparison to previously reported reconstruction processes (i.e. 96.3% structural similarity and < 0.003 normalized mean squared error from sampling only 12.5% of the k-space data). Finally, we use this reconstruction process on pathological data without retraining to show that reconstructed images are clinically useful for stroke identification. Since the model trained on images of healthy brains could be directly used for predictions in pathological brains without retraining, it shows the inherent transferability of this approach and opens doors to its widespread use.
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BACKGROUND: Cerebral small vessel disease (SVD) is common in older people and causes lacunar stroke and vascular cognitive impairment. Risk factors include old age, hypertension and variants in the genes COL4A1/COL4A2 encoding collagen alpha-1(IV) and alpha-2(IV), here termed collagen-IV, which are core components of the basement membrane. We tested the hypothesis that increased vascular collagen-IV associates with clinical hypertension and with SVD in older persons and with chronic hypertension in young and aged primates and genetically hypertensive rats. METHODS: We quantified vascular collagen-IV immunolabeling in small arteries in a cohort of older persons with minimal Alzheimer pathology (N=52; 21F/31M, age 82.8±6.95 years). We also studied archive tissue from young (age range 6.2-8.3 years) and older (17.0-22.7 years) primates (M mulatta) and compared chronically hypertensive animals (18 months aortic stenosis) with normotensives. We also compared genetically hypertensive and normotensive rats (aged 10-12 months). RESULTS: Collagen-IV immunolabeling in cerebral small arteries of older persons was negatively associated with radiological SVD severity (ρ: -0.427, P=0.005) but was not related to history of hypertension. General linear models confirmed the negative association of lower collagen-IV with radiological SVD (P<0.017), including age as a covariate and either clinical hypertension (P<0.030) or neuropathological SVD diagnosis (P<0.022) as fixed factors. Reduced vascular collagen-IV was accompanied by accumulation of fibrillar collagens (types I and III) as indicated by immunogold electron microscopy. In young and aged primates, brain collagen-IV was elevated in older normotensive relative to young normotensive animals (P=0.029) but was not associated with hypertension. Genetically hypertensive rats did not differ from normotensive rats in terms of arterial collagen-IV. CONCLUSIONS: Our cross-species data provide novel insight into sporadic SVD pathogenesis, supporting insufficient (rather than excessive) arterial collagen-IV in SVD, accompanied by matrix remodeling with elevated fibrillar collagen deposition. They also indicate that hypertension, a major risk factor for SVD, does not act by causing accumulation of brain vascular collagen-IV.
Subject(s)
Cerebral Small Vessel Diseases , Hypertension , Stroke, Lacunar , Animals , Rats , Cerebral Small Vessel Diseases/complications , Stroke, Lacunar/complications , Hypertension/complications , Brain/pathology , Blood Pressure , Collagen Type IV/geneticsABSTRACT
BACKGROUND AND OBJECTIVES: Late neuropathologies of repetitive head impacts from contact sports can include chronic traumatic encephalopathy (CTE) and white matter degeneration. White matter hyperintensities (WMH) on fluid-attenuated inversion recovery (FLAIR) MRI scans are often viewed as microvascular disease from vascular risk, but might have unique underlying pathologies and risk factors in the setting of repetitive head impacts. We investigated the neuropathologic correlates of antemortem WMH in brain donors exposed to repetitive head impacts. The association between WMH and repetitive head impact exposure and informant-reported cognitive and daily function were tested. METHODS: This imaging-pathologic correlation study included symptomatic male decedents exposed to repetitive head impacts. Donors had antemortem FLAIR scans from medical records and were without evidence of CNS neoplasm, large vessel infarcts, hemorrhage, or encephalomalacia. WMH were quantified using log-transformed values for total lesion volume (TLV), calculated using the lesion prediction algorithm from the Lesion Segmentation Toolbox. Neuropathologic assessments included semiquantitative ratings of white matter rarefaction, cerebrovascular disease, hyperphosphorylated tau (p-tau) severity (CTE stage, dorsolateral frontal cortex), and ß-amyloid (Aß). Among football players, years of play was a proxy for repetitive head impact exposure. Retrospective informant-reported cognitive and daily function were assessed using the Cognitive Difficulties Scale (CDS) and Functional Activities Questionnaire (FAQ). Regression models controlled for demographics, diabetes, hypertension, and MRI resolution. Statistical significance was defined as p ≤ 0.05. RESULTS: The sample included 75 donors: 67 football players and 8 nonfootball contact sport athletes or military veterans. Dementia was the most common MRI indication (64%). Fifty-three (70.7%) had CTE at autopsy. Log TLV was associated with white matter rarefaction (odds ratio [OR] 2.32, 95% confidence interval [CI] 1.03, 5.24; p = 0.04), arteriolosclerosis (OR 2.38, 95% CI 1.02, 5.52; p = 0.04), CTE stage (OR 2.58, 95% CI 1.17, 5.71; p = 0.02), and dorsolateral frontal p-tau severity (OR 3.03, 95% CI 1.32, 6.97; p = 0.01). There was no association with Aß. More years of football play was associated with log TLV (unstandardized ß 0.04, 95% CI 0.01, 0.06; p = 0.01). Greater log TLV correlated with higher FAQ (unstandardized ß 4.94, 95% CI 0.42, 8.57; p = 0.03) and CDS scores (unstandardized ß 15.35, 95% CI -0.27, 30.97; p = 0.05). DISCUSSION: WMH might capture long-term white matter pathologies from repetitive head impacts, including those from white matter rarefaction and p-tau, in addition to microvascular disease. Prospective imaging-pathologic correlation studies are needed. CLASSIFICATION OF EVIDENCE: This study provides Class IV evidence of associations between FLAIR white matter hyperintensities and neuropathologic changes (white matter rarefaction, arteriolosclerosis, p-tau accumulation), years of American football play, and reported cognitive symptoms in symptomatic brain donors exposed to repetitive head impacts.
Subject(s)
White Matter , Brain/diagnostic imaging , Brain/pathology , Humans , Magnetic Resonance Imaging , Male , Prospective Studies , Retrospective Studies , White Matter/diagnostic imaging , White Matter/pathologyABSTRACT
BACKGROUND: Chronic traumatic encephalopathy (CTE), a neurodegenerative tauopathy, cannot currently be diagnosed during life. Atrophy patterns on magnetic resonance imaging could be an effective in vivo biomarker of CTE, but have not been characterized. Mechanisms of neurodegeneration in CTE are unknown. Here, we characterized macrostructural magnetic resonance imaging features of brain donors with autopsy-confirmed CTE. The association between hyperphosphorylated tau (p-tau) and atrophy on magnetic resonance imaging was examined. METHODS: Magnetic resonance imaging scans were obtained by medical record requests for 55 deceased symptomatic men with autopsy-confirmed CTE and 31 men (n = 11 deceased) with normal cognition at the time of the scan, all >60 years Three neuroradiologists visually rated regional atrophy and microvascular disease (0 [none]-4 [severe]), microbleeds, and cavum septum pellucidum presence. Neuropathologists rated tau severity and atrophy at autopsy using semi-quantitative scales. RESULTS: Compared to unimpaired males, donors with CTE (45/55=stage III/IV) had greater atrophy of the orbital-frontal (mean diff.=1.29), dorsolateral frontal (mean diff.=1.31), superior frontal (mean diff.=1.05), anterior temporal (mean diff.=1.57), and medial temporal lobes (mean diff.=1.60), and larger lateral (mean diff.=1.72) and third (mean diff.=0.80) ventricles, controlling for age at scan (ps<0.05). There were no effects for posterior atrophy or microvascular disease. Donors with CTE had increased odds of a cavum septum pellucidum (OR = 6.7, p < 0.05). Among donors with CTE, greater tau severity across 14 regions corresponded to greater atrophy on magnetic resonance imaging (beta = 0.68, p < 0.01). CONCLUSIONS: These findings support frontal-temporal atrophy as a magnetic resonance imaging finding of CTE and show p-tau accumulation is associated with atrophy in CTE.
Subject(s)
Chronic Traumatic Encephalopathy , Atrophy/pathology , Autopsy , Brain/metabolism , Chronic Traumatic Encephalopathy/pathology , Humans , Magnetic Resonance Imaging/methods , Male , tau Proteins/metabolismABSTRACT
The goal of this study was to investigate whether alterations in cerebral microvasculature, as measured by cerebral blood volume (CBV), contribute to age- and hypertension-related impairments in cognitive function with a focus on executive function and memory. Data were collected on 19 male rhesus monkeys ranging from 6.4 to 21.6 years of age. Hypertension was induced through surgical coarctation of the thoracic aorta. We assessed whether performance on tasks of memory and executive function corresponded to CBV in either the hippocampus or prefrontal cortex. We found a relationship between duration of hypertension and CBV in the gray matter of the prefrontal cortex, but not the hippocampus. No relationships were found with the degree of hypertension or age. Increased prefrontal CBV was related to greater impairment in executive function while hippocampal CBV was not related to memory performance. These findings suggest that duration, but not severity, of hypertension or age are important factors underlying alterations in brain microvasculature and that executive function is more vulnerable than memory function. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
Subject(s)
Gray Matter , Hypertension , Aging , Animals , Cerebral Blood Volume , Cognition , Humans , Macaca mulatta , Magnetic Resonance Imaging , Male , Neuropsychological TestsABSTRACT
Background Multidetector CT (MDCT) enables rapid and accurate diagnosis of head and neck (HN) injuries in patients with blunt trauma (BT). However, MDCT is overused, and appropriate selection of patients for imaging could improve workflow. Purpose To investigate the effect of implementing clinical triaging algorithms on use of MDCT in the HN in patients who have sustained BT. Materials and Methods In this retrospective study, patients aged 15 years or older with BT admitted between October 28, 2007, and December 31, 2013, were included. Patients were divided into pre- and postalgorithm groups. The institutional trauma registry and picture archiving and communication system reports were reviewed to determine which patients underwent MDCT of the head, MDCT of the cervical spine (CS), and MDCT angiography of the HN at admission and whether these examinations yielded positive results. Injury Severity Score, Acute Physiology and Chronic Health Evaluation II score (only those patients in the intensive care unit), length of hospital stay (LOS), length of intensive care unit stay (ICULOS), and mortality were obtained from the trauma registry. Results A total of 8999 patients (mean age, 45 years ± 20 [standard deviation]; age range, 15-101 years; 6027 male) were included in this study. A lower percentage of the postalgorithm group versus the prealgorithm group underwent MDCT of the head (55.8% [2774 of 4969 patients]; 95% CI: 54.4, 57.2 vs 64.2% [2589 of 4030 patients]; 95% CI: 62.8, 65.7; P < .001) and CS (49.4% [2452 of 4969 patients]; 95% CI: 48.0, 50.7 vs 60.5% [2438 of 4030 patients]; 95% CI: 59.0, 62.0; P < .001) but not MDCT angiography of the HN (9.7% [480 of 4969 patients]; 95% CI: 8.9, 10.5 vs 9.8% [393 of 4030 patients]; 95% CI: 8.9, 10.7; P > .99). Pre- versus postalgorithm groups did not differ in LOS (mean, 4.8 days ± 7.1 vs 4.5 days ± 7.1, respectively; P = .42), ICULOS (mean, 4.6 days ± 6.6 vs 4.8 days ± 6.7, respectively; P > .99), or mortality (2.9% [118 of 4030 patients]; 95% CI: 2.5, 3.5; vs 2.8% [141 of 4969 patients]; 95% CI: 2.4, 3.3; respectively; P > .99). Conclusion Implementation of a clinical triaging algorithm resulted in decreased use of multidetector CT of the head and cervical spine in patients who experienced blunt trauma, without increased adverse outcomes. © RSNA, 2021 See also the editorial by Munera and Martin in this issue.
Subject(s)
Craniocerebral Trauma/diagnostic imaging , Multidetector Computed Tomography/statistics & numerical data , Neck Injuries/diagnostic imaging , Triage/methods , Wounds, Nonpenetrating/diagnostic imaging , APACHE , Adolescent , Adult , Aged , Aged, 80 and over , Algorithms , Craniocerebral Trauma/mortality , Female , Humans , Injury Severity Score , Length of Stay/statistics & numerical data , Male , Middle Aged , Neck Injuries/mortality , Patient Selection , Retrospective Studies , Wounds, Nonpenetrating/mortalityABSTRACT
BACKGROUND AND PURPOSE: Cervical spine injury is common in the setting of blunt trauma and there is consensus that cervical spine CT (CSCT) is the image modality of choice for initial evaluation for blunt trauma related injuries of the cervical spine. However, there is disagreement in the literature with regards to further evaluation of blunt trauma patients with cervical spine MRI (CSMRI) after negative CSCT when there is persistent clinical concern for occult trauma related injury. The purpose of this study is to examine the utility of CSMRI for detection of occult injury in blunt trauma patients after negative CSCT. MATERIALS AND METHODS: We reviewed records for 7,301 patients admitted for blunt trauma (November 2007-December 2013) and identified 259 who underwent CSMRI after a negative CSCT. These CSMRIs were reviewed to determine the number and type of significant CT occult injuries identified and clinical indications that led to CSMRI acquisition. RESULTS AND CONCLUSIONS: CSMRI detected significant injuries following negative CSCT in 31% (81/259) of patients. There were 15 cord contusions/infarcts, 9 bone contusions/fractures, 7 spinal canal hemorrhages and 66 soft tissue injuries. Upper extremity neurological deficit had greatest positive predictive value (PPV) for detection of CT-occult injury on CSMRI of 43% (23/53), followed by equivocal CSCT findings (38%, 18/47), presence of extra-cervical injuries (34%, 20/58), midline cervical tenderness (20%, 17/85), and isolated lower extremity neurological deficit (0%, 0/16). CSMRI is recommended following negative CSCT in the evaluation of blunt cervical spine trauma when appropriate clinical concerns are present.
Subject(s)
Wounds, Nonpenetrating , Cervical Vertebrae/diagnostic imaging , Humans , Magnetic Resonance Imaging , Spinal Canal , Tomography, X-Ray Computed , Wounds, Nonpenetrating/diagnostic imagingABSTRACT
Background Gadolinium retention after repeated gadolinium-based contrast agent (GBCA) exposure has been reported in subcortical gray matter. However, gadolinium retention in the cerebral cortex has not been systematically investigated. Purpose To determine whether and where gadolinium is retained in rat and human cerebral cortex. Materials and Methods The cerebral cortex in Sprague-Dawley rats treated with gadopentetate dimeglumine (three doses over 4 weeks; cumulative gadolinium dose, 7.2 mmol per kilogram of body weight; n = 6) or saline (n = 6) was examined with antemortem MRI. Two human donors with repeated GBCA exposure (three and 15 doses; 1 and 5 months after exposure), including gadopentetate dimeglumine, and two GBCA-naive donors were also evaluated. Elemental brain maps (gadolinium, phosphorus, zinc, copper, iron) for rat and human brains were constructed by using laser ablation inductively coupled plasma mass spectrometry. Results Gadopentetate dimeglumine-treated rats showed region-, subregion-, and layer-specific gadolinium retention in the neocortex (anterior cingulate cortex: mean gadolinium concentration, 0.28 µg â g-1 ± 0.04 [standard error of the mean]) that was comparable (P > .05) to retention in the allocortex (mean gadolinium concentration, 0.33 µg â g-1 ± 0.04 in piriform cortex, 0.24 µg â g-1 ± 0.04 in dentate gyrus, 0.17 µg â g-1 ± 0.04 in hippocampus) and subcortical structures (0.47 µg â g-1 ± 0.10 in facial nucleus, 0.39 µg â g-1 ± 0.10 in choroid plexus, 0.29 µg â g-1 ± 0.05 in caudate-putamen, 0.26 µg â g-1 ± 0.05 in reticular nucleus of the thalamus, 0.24 µg â g-1 ± 0.04 in vestibular nucleus) and significantly greater than that in the cerebellum (0.17 µg â g-1 ± 0.03, P = .01) and white matter tracts (anterior commissure: 0.05 µg â g-1 ± 0.01, P = .002; corpus callosum: 0.05 µg â g-1 ± 0.02, P = .001; cranial nerve: 0.02 µg â g-1 ± 0.01, P = .004). Retained gadolinium colocalized with parenchymal iron. T1-weighted MRI signal intensification was not observed. Gadolinium retention was detected in the cerebral cortex, pia mater, and pia-ensheathed leptomeningeal vessels in two GBCA-exposed human brains but not in two GBCA-naive human brains. Conclusion Repeated gadopentetate dimeglumine exposure is associated with gadolinium retention in specific regions, subregions, and layers of cerebral cortex that are critical for higher cognition, affect, and behavior regulation, sensorimotor coordination, and executive function. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Kanal in this issue.
Subject(s)
Cerebral Cortex/metabolism , Contrast Media/pharmacokinetics , Gadolinium DTPA/pharmacokinetics , Administration, Intravenous , Adult , Animals , Contrast Media/administration & dosage , Female , Gadolinium DTPA/administration & dosage , Humans , Male , Mass Spectrometry/methods , Middle Aged , Models, Animal , Rats , Rats, Sprague-DawleyABSTRACT
Initial results are reported on automated detection of intracranial hemorrhage from CT, which would be valuable in a computer-aided diagnosis system to help the radiologist detect subtle hemorrhages. Previous work has taken a classic approach involving multiple steps of alignment, image processing, image corrections, handcrafted feature extraction, and classification. Our current work instead uses a deep convolutional neural network to simultaneously learn features and classification, eliminating the multiple hand-tuned steps. Performance is improved by computing the mean output for rotations of the input image. Postprocessing is additionally applied to the CNN output to significantly improve specificity. The database consists of 134 CT cases (4,300 images), divided into 60, 5, and 69 cases for training, validation, and test. Each case typically includes multiple hemorrhages. Performance on the test set was 81% sensitivity per lesion (34/42 lesions) and 98% specificity per case (45/46 cases). The sensitivity is comparable to previous results (on different datasets), but with a significantly higher specificity. In addition, insights are shared to improve performance as the database is expanded.
Subject(s)
Deep Learning , Diagnosis, Computer-Assisted , Image Processing, Computer-Assisted , Intracranial Hemorrhages/diagnostic imaging , Neural Networks, Computer , Databases, Factual , Humans , Sensitivity and SpecificityABSTRACT
MR imaging with diffusion-weighted imaging has been essential in the evaluation of acute stroke but is also crucial for the diagnosis, treatment, and follow-up in patients with various nonischemic disorders, including infectious processes, trauma, toxic/metabolic disorders, and other abnormalities. This article reviews various disorders with diffusion abnormality that can be commonly seen in the emergency setting.
Subject(s)
Magnetic Resonance Imaging , Stroke/diagnostic imaging , Stroke/etiology , Acute Disease , Emergency Service, Hospital , HumansABSTRACT
BACKGROUND: Disease models are useful for prospective studies of pathology, identification of molecular and cellular mechanisms, pre-clinical testing of interventions, and validation of clinical biomarkers. Here, we review animal models relevant to vascular cognitive impairment (VCI). A synopsis of each model was initially presented by expert practitioners. Synopses were refined by the authors, and subsequently by the scientific committee of a recent conference (International Conference on Vascular Dementia 2015). Only peer-reviewed sources were cited. METHODS: We included models that mimic VCI-related brain lesions (white matter hypoperfusion injury, focal ischaemia, cerebral amyloid angiopathy) or reproduce VCI risk factors (old age, hypertension, hyperhomocysteinemia, high-salt/high-fat diet) or reproduce genetic causes of VCI (CADASIL-causing Notch3 mutations). CONCLUSIONS: We concluded that (1) translational models may reflect a VCI-relevant pathological process, while not fully replicating a human disease spectrum; (2) rodent models of VCI are limited by paucity of white matter; and (3) further translational models, and improved cognitive testing instruments, are required.
Subject(s)
Dementia, Vascular/pathology , Disease Models, Animal , Animals , Brain/pathology , Dementia, Vascular/genetics , Risk FactorsABSTRACT
Recent neurophysiological and functional neuroimaging studies suggest that the memory decline found with normal aging is not solely due to regional disruptions in the hippocampus, but also is brought about by alterations in the functional coupling between the hippocampus and long-distance neocortical regions. However, the anatomical basis for this functional "dyscoupling" has not been fully revealed. In this study, we applied a multimodal magnetic resonance imaging technique to noninvasively examine the large-scale anatomical and functional hippocampal network of a group of middle aged rhesus monkeys. Using diffusion spectrum imaging, we have found that monkeys with lower memory performance had weaker structural white matter connections between the hippocampus and neocortical association areas. Resting state functional imaging revealed somewhat of an opposite result. Monkeys with low memory performance displayed elevated coupling strengths in the network between the hippocampus and the neocortical areas. Taken together with recent findings, this contradictory pattern may be the result of either underlying physiological burden or abnormal neuronal decoupling due to the structural alterations, which induce a neuronal compensation mechanism for the structural loss or interference on task related neuronal activation, respectively.