The use of an anterior-posterior atrophy index to distinguish Alzheimer's disease from frontotemporal disorders: an automated volumetric MRI Study.

BACKGROUND: Alzheimer's disease (AD) and frontotemporal dementia (FTD) require different treatments. Since clinical presentation can be nuanced, imaging biomarkers aid in diagnosis. Automated software such as Neuroreader (NR) provides volumetric imaging data, and indices between anterior and posterior brain areas have proven useful in distinguishing dementia subtypes in research cohorts. Existing indices are complex and require further validation in clinical settings. PURPOSE: To provide initial validation for a simplified anterior-posterior index (API) from NR in distinguishing FTD and AD in a clinical cohort. MATERIAL AND METHODS: A retrospective chart review was completed. We derived a simplified API: API = (logVA/VP-µ)/σ where VA is weighted volume of frontal and temporal lobes and VP of parietal and occipital lobes. µ and σ are the mean and standard deviation of logVA/VP computed for AD participants. Receiver operating characteristic (ROC) curves and regression analyses assessed the efficacy of the API versus brain areas in predicting diagnosis of AD versus FTD. RESULTS: A total of 39 participants with FTD and 78 participants with AD were included. The API had an excellent performance in distinguishing AD from FTD with an area under the ROC curve of 0.82 and a positive association with diagnostic classification on logistic regression analysis (B = 1.491, P < 0.001). CONCLUSION: The API successfully distinguished AD and FTD with excellent performance. The results provide preliminary validation of the API in a clinical setting.

Predicting progression from mild cognitive impairment to Alzheimer's disease on an individual subject basis by applying the CARE index across different independent cohorts.

The purposes of this study are to investigate whether the Characterizing Alzheimer's disease Risk Events (CARE) index can accurately predict progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) on an individual subject basis, and to investigate whether this model can be generalized to an independent cohort. Using an event-based probabilistic model approach to integrate widely available biomarkers from behavioral data and brain structural and functional imaging, we calculated the CARE index. We then applied the CARE index to identify which MCI individuals from the ADNI dataset progressed to AD during a three-year follow-up period. Subsequently, the CARE index was generalized to the prediction of MCI individuals from an independent Nanjing Aging and Dementia Study (NADS) dataset during the same time period. The CARE index achieved high prediction performance with 80.4% accuracy, 75% sensitivity, 82% specificity, and 0.809 area under the receiver operating characteristic (ROC) curve (AUC) on MCI subjects from the ADNI dataset over three years, and a highly validated prediction performance with 87.5% accuracy, 81% sensitivity, 90% specificity, and 0.861 AUC on MCI subjects from the NADS dataset. In conclusion, the CARE index is highly accurate, sufficiently robust, and generalized for predicting which MCI individuals will develop AD over a three-year period. This suggests that the CARE index can be usefully applied to select individuals with MCI for clinical trials and to identify which individuals will convert from MCI to AD for administration of early disease-modifying treatment.

Intrinsic inter-network brain dysfunction correlates with symptom dimensions in late-life depression.

Prior studies have demonstrated dysfunctions within the core neurocognitive networks (the executive control [ECN], default mode [DMN] and salience [SN] networks) in late-life depression (LLD). Whether inter-network dysfunctional connectivity is present in LLD, and if such disruptions are associated with core symptom dimensions is unknown. A cross-sectional resting-state functional connectivity magnetic resonance imaging investigation was conducted of LLD (n = 39) and age- and gender-equated healthy comparison (HC) (n = 29) participants. Dual regression independent component analysis approach was used to identify components that represented the ECN, DMN and SN. The intrinsic inter-network connectivity was compared between LLD and HC participants and the relationship of inter-network connectivity abnormalities with dimensional measures was examined. Relative to HC participants, LLD subjects showed decreased inter-network connectivity between the bilateral ECN and default mode subcortical (thalamus, basal ganglia and ventral striatum) networks, and the left ECN and SN insula component; and increased inter-network connections between the left ECN and posterior DMN and salience (dorsal anterior cingulate) network components. Distinct inter-network connectivity abnormalities correlated with depression and anxiety severity, and executive dysfunction in LLD participants. LLD subjects also showed pronounced intra-network connectivity differences within the ECN, whereas fewer but significant DMN and SN disruptions were also detected. Investigating the intrinsic inter-network functional connectivity could provide a mechanistic framework to better understand the neural basis that underlies core symptom dimensions in LLD. Inter-network connectivity measures have the potential to be neuroimaging biomarkers of symptom dimensions comprising LLD, and may assist in developing symptom-specific treatment algorithms.

Staging Alzheimer's Disease Risk by Sequencing Brain Function and Structure, Cerebrospinal Fluid, and Cognition Biomarkers.

This study aims to develop a composite biomarker that can accurately measure the sequential biological stages of Alzheimer's disease (AD) on an individual level. We selected 144 subjects from the Alzheimer's Disease Neuroimaging Initiative 2 datasets. Ten biomarkers, from brain function and structure, cerebrospinal fluid, and cognitive performance, were integrated using the event-based probabilistic model to estimate their optimal temporal sequence (Soptimal). We identified the numerical order of the Soptimal as the characterizing Alzheimer's disease risk events (CARE) index to measure disease stage. The results show that, in the Soptimal, hippocampal and posterior cingulate cortex network biomarkers occur first, followed by aberrant cerebrospinal fluid amyloid-ß and p-tau levels, then cognitive deficit, and finally regional gray matter loss and fusiform network abnormality. The CARE index significantly correlates with disease severity and exhibits high reliability. Our findings demonstrate that use of the CARE index would advance AD stage measurement across the whole AD continuum and facilitate personalized treatment of AD.

Amygdala network dysfunction in late-life depression phenotypes: Relationships with symptom dimensions.

The amygdala, a crucial hub of the emotional processing neural system, has been implicated in late-life depression (LLD) pathophysiology. However, the overlapping and diverging amygdala network function abnormalities underlying two clinical LLD phenotypes (i.e., LLD alone and LLD with mild cognitive impairment [LLD-MCI]) are unknown. The aim of this study is to investigate the amygdala functional connectivity (FC) differences between LLD alone, LLD-MCI and healthy controls, and to examine the relationships between amygdala network dysfunction and symptom dimensions. A resting-state functional connectivity magnetic resonance imaging study was conducted to probe amygdala FC in a total of 63 elderly participants (LLD [n = 22], LLD-MCI [n = 15], and age- and gender-equated healthy older adults [n = 26]) using a seed-based voxelwise R-fcMRI approach. LLD-only adults showed increased FC in the posterior default mode and vermis, and diminished connections in the fronto-parietal, salience and temporal areas, relative to controls. The LLD-MCI participants showed diminished FC in the default mode, cognitive control, salience and visual regions, whereas increased FC was limited to lateral parietal cortex compared with healthy controls. The LLD-MCI group also showed diminished FC in the occipital and posterior default mode areas, relative to the LLD-only group. Distinct amygdala FC abnormalities that explain depressive and anxiety symptom severity, and executive functioning were identified. The amygdala FC impairments may distinguish LLD phenotypes. These functional network abnormalities may also explain the heterogeneity seen in the LLD clinical presentations.

Disrupted small world topology and modular organisation of functional networks in late-life depression with and without amnestic mild cognitive impairment.

BACKGROUND: The topological architecture of the whole-brain functional networks in those with and without late-life depression (LLD) and amnestic mild cognitive impairment (aMCI) are unknown. AIMS: To investigate the differences in the small-world measures and the modular community structure of the functional networks between patients with LLD and aMCI when occurring alone or in combination and cognitively healthy non-depressed controls. METHODS: 79 elderly participants (LLD (n=23), aMCI (n=18), comorbid LLD and aMCI (n=13), and controls (n=25)) completed neuropsychiatric assessments. Graph theoretical methods were employed on resting-state functional connectivity MRI data. RESULTS: LLD and aMCI comorbidity was associated with the greatest disruptions in functional integration measures (decreased global efficiency and increased path length); both LLD groups showed abnormal functional segregation (reduced local efficiency). The modular network organisation was most variable in the comorbid group, followed by patients with LLD-only. Decreased mean global, local and nodal efficiency metrics were associated with greater depressive symptom severity but not memory performance. CONCLUSIONS: Considering the whole brain as a complex network may provide unique insights on the neurobiological underpinnings of LLD with and without cognitive impairment.

Aberrant functional connectivity in Papez circuit correlates with memory performance in cognitively intact middle-aged APOE4 carriers.

The main objective of this study is to detect the early changes in resting-state Papez circuit functional connectivity using the hippocampus as the seed, and to determine the associations between altered functional connectivity (FC) and the episodic memory performance in cognitively intact middle-aged apolipoprotein E4 (APOE4) carriers who are at risk of Alzheimer's disease (AD). Forty-six cognitively intact, middle-aged participants, including 20 APOE4 carriers and 26 age-, sex-, and education-matched noncarriers were studied. The resting-state FC of the hippocampus (HFC) was compared between APOE4 carriers and noncarriers. APOE4 carriers showed significantly decreased FC in brain areas that involve learning and memory functions, including the frontal, cingulate, thalamus and basal ganglia regions. Multiple linear regression analysis showed significant correlations between HFC and the episodic memory performance. Conjunction analysis between neural correlates of memory and altered HFC showed the overlapping regions, especially the subcortical regions such as thalamus, caudate nucleus, and cingulate cortices involved in the Papez circuit. Thus, changes in connectivity in the Papez circuit may be used as an early risk detection for AD.

Effects of the coexistence of late-life depression and mild cognitive impairment on white matter microstructure.

BACKGROUND AND OBJECTIVE: Late-life depression (LLD) and amnestic mild cognitive impairment (aMCI) are associated with white matter (WM) disruptions of the fronto-limbic and interhemispheric tracts implicated in mood regulation and episodic memory functions. This work investigates the extent of these WM abnormalities in patients LLD and aMCI when these diseases occur alone and when they coexist. MATERIALS AND METHODS: Eighty-four subjects separated into cognitively normal (n=33), LLD (n=20), aMCI (n=18), and comorbid aMCI and LLD (n=13) completed Diffusion Tensor Imaging (DTI) scans. Tract-based spatial statistics was employed to skeletonize multiple DTI indices of the cingulum, corpus callosum, fornix and uncinate fasciculus. Analysis of covariance and post-hoc tests compared group differences. Multiple linear regressions were performed between DTI and behavioral measures for the whole sample and within individual patient groups. RESULTS: Divergent microstructural disruptions were identified in LLD- and aMCI-only groups, whereas the comorbid group showed widespread abnormalities especially in the hippocampal cingulum and fornix tracts. The LLD groups also showed significant disruptions in the uncinate fasciculus and corpus callosal tracts. Higher depressive symptom and lower episodic memory scores were associated with increased diffusivity measures in the fornix and hippocampal cingulum across all subjects. CONCLUSIONS: Widespread WM microstructural disruptions are present when LLD and aMCI are comorbid -especially in the medial temporal lobe tracts. These WM disruptions may be a marker of disease severity. Also, multiple DTI parameters should be used when evaluating the WM fiber integrity in LLD and aMCI.

Late-life depression, mild cognitive impairment and hippocampal functional network architecture.

Late-life depression (LLD) and amnestic mild cognitive impairment (aMCI) are associated with medial temporal lobe structural abnormalities. However, the hippocampal functional connectivity (HFC) similarities and differences related to these syndromes when they occur alone or coexist are unclear. Resting-state functional connectivity MRI (R-fMRI) technique was used to measure left and right HFC in 72 elderly participants (LLD [n = 18], aMCI [n = 17], LLD with comorbid aMCI [n = 12], and healthy controls [n = 25]). The main and interactive relationships of LLD and aMCI on the HFC networks were determined, after controlling for age, gender, education and gray matter volumes. The effects of depressive symptoms and episodic memory deficits on the hippocampal functional connections also were assessed. While increased and decreased left and right HFC with several cortical and subcortical structures involved in mood regulation were related to LLD, aMCI was associated with globally diminished connectivity. Significant LLD-aMCI interactions on the right HFC networks were seen in the brain regions critical for emotion processing and higher-order cognitive functions. In the interactive brain regions, LLD and aMCI were associated with diminished hippocampal functional connections, whereas the comorbid group demonstrated enhanced connectivity. Main and interactive effects of depressive symptoms and episodic memory performance were also associated with bilateral HFC network abnormalities. In conclusion, these findings indicate that discrete hippocampal functional network abnormalities are associated with LLD and aMCI when they occur alone. However, when these conditions coexist, more pronounced vulnerabilities of the hippocampal networks occur, which may be a marker of disease severity and impending cognitive decline. By utilizing R-fMRI technique, this study provides novel insights into the neural mechanisms underlying LLD and aMCI in the functional network level.

Functional network endophenotypes unravel the effects of apolipoprotein E epsilon 4 in middle-aged adults.

Apolipoprotein E-ε4 (APOE-ε4) accentuates memory decline, structural volume loss and cerebral amyloid deposition in cognitively healthy adults. We investigated whether APOE-ε4 carriers will show disruptions in the intrinsic cognitive networks, including the default mode (DMN), executive control (ECN) and salience (SN) networks, relative to noncarriers in middle-aged healthy adults; and the extent to which episodic-memory performance is related to the altered functional connectivity (Fc) in these networks. Resting-state functional connectivity MRI (R-fMRI) was used to measure the differences in the DMN, ECN and SN Fc between 20 APOE-ε4 carriers and 26 noncarriers. Multiple linear regression analyses were performed to determine the relationship between episodic-memory performance and Fc differences in the three resting-state networks across all subjects. There were no significant differences in the demographic and neuropsychological characteristics and the gray-matter volumes in the carriers and noncarriers. While mostly diminished DMN and ECN functional connectivities were seen, enhanced connections to the DMN structures were found in the SN in ε4 carriers. Altered DMN and ECN were associated with episodic memory performance. Significant Fc differences in the brain networks implicated in cognition were seen in middle-aged individuals with a genetic risk for AD, in the absence of cognitive decline and gray-matter atrophy. Prospective studies are essential to elucidate the potential of R-fMRI technique as a biomarker for predicting conversion from normal to early AD in healthy APOE-ε4 carriers.

The co-existence of geriatric depression and amnestic mild cognitive impairment detrimentally affect gray matter volumes: voxel-based morphometry study.

While late-life depression (LLD) and amnestic mild cognitive impairment (aMCI), alone and in combination, is associated with an increased risk of incident Alzheimer's disease (AD), the neurobiological mechanisms of this link are unclear. We examined the main and interactive effects of LLD and aMCI on the gray matter (GM) volumes in 72 physically healthy participants aged 60 and older. Participants were separated into normal controls, cognitively normal depressed, non-depressed aMCI, and depressed aMCI groups. Optimized voxel-based morphometry estimated GM volumes. The main and interactive effects of LLD and aMCI, and of depressive symptoms and episodic memory deficits on the GM volumes were analyzed. While decreased GM volumes in the mood regulating circuitry structures were associated with depression, GM atrophy in regions essential for various cognitive performance were related to aMCI. LLD-aMCI interactions were associated with widespread subcortical and cortical GM volume loss of brain structures implicated in AD. The interactions between episodic memory deficits and depressive symptom severity are associated with volume loss in right inferior frontal gyrus/anterior insula and left medial frontal gyrus clusters. Our findings suggest that the co-existence of these clinical phenotypes is a potential marker for higher risk of AD.

A clustering-based method to detect functional connectivity differences.

Recently, resting-state functional magnetic resonance imaging (R-fMRI) has emerged as a powerful tool for investigating functional brain organization changes in a variety of neurological and psychiatric disorders. However, the current techniques may need further development to better define the reference brain networks for quantifying the functional connectivity differences between normal and diseased subject groups. In this study, we introduced a new clustering-based method that can clearly define the reference clusters. By employing group difference information to guide the clustering, the voxels within the reference clusters will have homogeneous functional connectivity changes above predefined levels. This method identified functional clusters that were significantly different between the amnestic mild cognitively impaired (aMCI) and age-matched cognitively normal (CN) subjects. The results indicated that the distribution of the clusters and their functionally disconnected regions resembled the altered memory network regions previously identified in task fMRI studies. In conclusion, the new clustering method provides an advanced approach for studying functional brain organization changes associated with brain diseases.

Changes in regional cerebral blood flow and functional connectivity in the cholinergic pathway associated with cognitive performance in subjects with mild Alzheimer's disease after 12-week donepezil treatment.

Acetylcholinesterase inhibitors (AChEIs), such as donepezil, have been shown to improve cognition in mild to moderate Alzheimer's disease (AD) patients. In this paper, our goal is to determine the relationship between altered cerebral blood flow (CBF) and intrinsic functional network connectivity changes in mild AD patients before and after 12-week donepezil treatment. An integrative neuroimaging approach was employed by combining pseudocontinuous arterial spin labeling (pCASL) MRI and resting-state functional MRI (R-fMRI) methods to determine the changes in CBF and functional connectivity (FC) in the cholinergic pathway. Linear regression analyses determined the correlations of the regional CBF alterations and functional connectivity changes with cognitive responses. These were measured with the Mini-Mental Status Examination (MMSE) scores and Alzheimer's disease Assessment Scale-Cognitive subscale (ADAS-cog) scores. Our results show that the regional CBF in mild AD subjects after donepezil treatment was significantly increased in the middle cingulate cortex (MCC) and posterior cingulate cortex (PCC), which are the neural substrates of the medial cholinergic pathway. In both brain regions, the baseline CBF and its changes after treatment were significantly correlated with the behavioral changes in ADAS-cog scores. The intrinsic FC was significantly enhanced in the medial cholinergic pathway network in the brain areas of the parahippocampal, temporal, parietal and prefrontal cortices. Finally, the FC changes in the medial prefrontal areas demonstrated an association with the CBF level in the MCC and the PCC, and also were correlated with ADAS-cog score changes. These findings indicate that regional CBF and FC network changes in the medial cholinergic pathway were associated with cognitive performance. It also is suggested that the combined pCASL-MRI and R-fMRI methods could be used to detect regional CBF and FC changes when using drug treatments in mild AD subjects.

Neural basis of the association between depressive symptoms and memory deficits in nondemented subjects: resting-state fMRI study.

Depressive symptoms often coexist with memory deficits in older adults and also are associated with incident cognitive decline in the elderly. However, little is known about the neural correlates of the association between depressive symptoms and memory deficits in nondemented elderly. Fifteen amnestic mild cognitive impairment (aMCI) and 20 cognitively normal (CN) subjects completed resting-state functional magnetic resonance imaging (R-fMRI) scans. Multiple linear regression analysis was performed to test the main effects of the Geriatric Depression Scale (GDS) and Rey Auditory Verbal Learning Test delayed recall (RAVLT-DR) scores, and their interaction on the intrinsic amygdala functional connectivity (AFC) network activity. Severer depressive symptoms and memory deficits were found in the aMCI group than in the CN group. Partial correlation analysis identified that the RAVLT-DR scores were significantly correlated with the AFC network in the bilateral dorsolateral prefrontal cortex (DLPFC), dorsomedial and anterior prefrontal cortex, posterior cingulate cortex (PCC), middle occipital gyrus, right inferior parietal cortex, and left middle temporal gyrus (MTG). The GDS scores were positively correlated with the AFC network in the bilateral PCC and MTG, and left DLPFC. The interactive effects of the GDS and RAVLT-DR scores on the AFC network were seen in the bilateral PCC, MTG, and left DLPFC. These findings not only supported that there were interactive neural links between depressive symptoms and memory functions in nondemented elderly at the system level, but also demonstrated that R-fMRI has advantages in investigating the interactive nature of different neural networks involved in complex functions, such as emotion and cognition.

Recovery of hippocampal network connectivity correlates with cognitive improvement in mild Alzheimer's disease patients treated with donepezil assessed by resting-state fMRI.

PURPOSE: To identify the neural correlates of cognitive improvement in mild Alzheimer's disease (AD) subjects following 12 weeks of donepezil treatment. MATERIALS AND METHODS: Resting-state functional connectivity magnetic resonance imaging (R-fMRI) was used to measure the hippocampal functional connectivity (HFC) in 14 mild AD and 18 age-matched normal (CN) subjects. AD subjects were scanned at baseline and after donepezil treatment. CN subjects were scanned only at baseline as a reference to identify regions correlated or anticorrelated to the hippocampus. Before each scan, participants underwent cognitive, behavioral, and functional assessments. RESULTS: After donepezil treatment, neural correlates of cognitive improvement measured by Mini-Mental State Examination scores were identified in the left parahippocampus, dorsolateral prefrontal cortex (DLPFC), and inferior frontal gyrus. Improvement in AD Assessment Scale-cognitive subscale scores correlated with the HFC changes in the left DLPFC and middle frontal gyrus. Stronger recovery in the network connectivity was associated with cognitive improvement. CONCLUSION: R-fMRI may provide novel insights into the brain's responses to AD treatment in clinical pharmacological trials, and also may predict clinical response.

Neural correlates of the interactive relationship between memory deficits and depressive symptoms in nondemented elderly: resting fMRI study.

Prospective studies have shown an association between depressive symptoms and cognitive impairment among older adults. However, the neural correlates of this relationship are poorly understood. Our aim was to examine whether interactive effects of memory deficits and depressive symptoms are present in the memory-associated functional networks, in nondemented elderly subjects. Fifteen subjects with amnestic mild cognitive impairment (aMCI) and 20 age-matched normal (CN) elderly subjects participated in this cross-sectional study. Resting-state functional connectivity MRI (R-fMRI) measured the hippocampal functional connectivity (HFC) alterations between the two groups. Voxelwise linear regression analysis was performed to correlate hippocampal network strength with the Rey Auditory Verbal Learning Test delayed recall and the Geriatric Depression Scale scores, after adjusting for age and group effects. Poorer memory performance was associated with decreased positively correlated HFC connectivity in the specific frontal lobe and default mode network (DMN) structures. Poorer memory performance also was associated with decreased anticorrelated HFC connectivity in the bilateral inferior parietal and right dorsolateral prefrontal cortices. In contrast, greater depressive symptom severity was associated with increased HFC connectivity in several frontal lobes and DMN regions. Depressive symptoms and memory functions had interactive effects on the HFC, in the frontal, temporal, and PCC structures. Our findings suggest that the R-fMRI technique can be used to examine the changes in functional neural networks where memory deficits and depressive symptoms coexist in the geriatric population.

Proton magnetic resonance spectroscopy of the hippocampus in patients with mild cognitive impairment: a pilot study.

OBJECTIVE: To assess the brain metabolites in the hippocampus of patients with mild cognitive impairment (MCI) using proton magnetic resonance spectroscopy at 0.5 T. METHODS: Absolute concentrations and ratios to creatine of N-acetyl aspartate, myoinositol, glutamate + glutamine, and choline were measured in the right and left hippocampus of 5 MCI patients and 5 control subjects. RESULTS: In MCI subjects, reduced N-acetyl aspartate was found in the right hippocampus (P = 0.01), and increased myoinositol was found in the left hippocampus (P = 0.02). Myoinositol/N-acetyl aspartate ratios were higher in the right (P = 0.03) and left (P = 0.01) hippocampus of MCI subjects. No significant difference in the concentration of glutamate + glutamine was observed between the control and MCI groups. CONCLUSIONS: An increase in myoinositol and a decrease in N-acetyl aspartate may be observed in the preclinical stages of dementia. Ratio measurements of these metabolites may serve as a biomarker for MCI.

Task-modulation of functional synchrony between spontaneous low-frequency oscillations in the human brain detected by fMRI.

Recent developments in functional MRI (fMRI) technology with high spatial and temporal resolution have made it possible to noninvasively detect spontaneous low-frequency oscillations (SLOs) and quantify their functional synchrony in the human brain. In the present fMRI study the dynamic characteristics of the functional synchrony between SLOs were quantitatively determined by the phase shift index (PSI). With the use of an fMRI-guided voxel-selection method, the SLOs and their functional synchrony were found to be modulated by different memory tasks. The results demonstrate that SLOs in episodic memory-related circuitry have significantly higher synchrony during the performance of declarative memory-encoding activities compared to nondeclarative memory-encoding activities. It is suggested that the dynamic property of SLOs and the quantitative assessment of their functional synchrony could be utilized as a biomarker to noninvasively characterize localized pathophysiological functions in the human brain.

Alzheimer Disease: evaluation of a functional MR imaging index as a marker.

PURPOSE: To measure changes in functional synchrony in the hippocampus in patients with mild cognitive impairment (MCI) and Alzheimer disease (AD). MATERIALS AND METHODS: Three subject groups (nine cognitively healthy elderly control subjects, 10 patients with probable AD, and five subjects with MCI) underwent resting-state functional magnetic resonance (MR) imaging for measurement of functional synchrony in the hippocampus. Functional synchrony was defined and quantified as the mean of the cross-correlation coefficients of spontaneous low frequency (COSLOF) components between possible pairs of voxel time courses in a brain region, or the COSLOF index. The two-tailed Student t test was used to determine differences in the COSLOF index between the control group, the probable AD group, and the MCI group. An operating characteristic curve was calculated to graphically depict the tradeoff between sensitivity and specificity of the COSLOF index. RESULTS: Functional synchrony quantified with the COSLOF index was obtained in AD, MCI, and control subjects. COSLOF index values were significantly lower in AD patients than in control subjects (t = 4.32, P <.0012). For MCI subjects, COSLOF index values were significantly higher than those of AD patients (t = -2.4052, P <.047) but significantly lower than those of control subjects (t = 2.257, P <.043). The exponential-class curve significantly fits the relationship between the COSLOF index and the Mini-Mental Status Examination score (chi(2) = 20.4), indicating the rapid decrease in cognitive capacity below a threshold of the COSLOF index. CONCLUSION: Our results suggest that the COSLOF index could be used as a noninvasive quantitative marker for the preclinical stage of AD.