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The incomplete-hippocampal-inversion (IHI), also known as malrotation, is an atypical anatomical pattern of the hippocampus, which has been reported in healthy subjects in different studies. However, extensive characterization of IHI in a large sample has not yet been performed. Furthermore, it is unclear whether IHI are restricted to the medial-temporal lobe or are associated with more extensive anatomical changes. Here, we studied the characteristics of IHI in a community-based sample of 2008 subjects of the IMAGEN database and their association with extra-hippocampal anatomical variations. The presence of IHI was assessed on T1-weighted anatomical magnetic resonance imaging (MRI) using visual criteria. We assessed the association of IHI with other anatomical changes throughout the brain using automatic morphometry of cortical sulci. We found that IHI were much more frequent in the left hippocampus (left: 17%, right: 6%, χ(2)-test, p < 10(-28)). Compared to subjects without IHI, subjects with IHI displayed morphological changes in several sulci located mainly in the limbic lobe. Our results demonstrate that IHI are a common left-sided phenomenon in normal subjects and that they are associated with morphological changes outside the medial temporal lobe.

Cannabis use in adolescence may be characterized by differences in the neural basis of affective processing. In this study, we used an fMRI affective face processing task to compare a large group (n=70) of 14-year olds with a history of cannabis use to a group (n=70) of never-using controls matched on numerous characteristics including IQ, SES, alcohol and cigarette use. The task contained short movies displaying angry and neutral faces. Results indicated that cannabis users had greater reactivity in the bilateral amygdalae to angry faces than neutral faces, an effect that was not observed in their abstinent peers. In contrast, activity levels in the cannabis users in cortical areas including the right temporal-parietal junction and bilateral dorsolateral prefrontal cortex did not discriminate between the two face conditions, but did differ in controls. Results did not change after excluding subjects with any psychiatric symptomology. Given the high density of cannabinoid receptors in the amygdala, our findings suggest cannabis use in early adolescence is associated with hypersensitivity to signals of threat. Hypersensitivity to negative affect in adolescence may place the subject at-risk for mood disorders in adulthood., (Copyright © 2015. Published by Elsevier Ltd.)

Objective: Neuroimaging findings have been reported in regions of the brain associated with emotion in both adults and adolescents with depression, but few studies have investigated whether such brain alterations can be detected in adolescents with subthreshold depression, a condition at risk for major depressive disorder. In this study, we searched for differences in brain structure at age 14 years in adolescents with subthreshold depression and their relation to depression at age 16 years., Method: High-resolution structural magnetic resonance imaging was used to assess adolescents with self-reported subthreshold depression (n = 119) and healthy control adolescents (n = 461), all recruited from a community-based sample. Regional gray and white matter volumes were compared across groups using whole-brain voxel-based morphometry. The relationship between subthreshold depression at baseline and depression outcome was explored using causal mediation analyses to search for mediating effects of regional brain volumes., Results: Adolescents with subthreshold depression had smaller gray matter volume in the ventromedial prefrontal and rostral anterior cingulate cortices and caudates, and smaller white matter volumes in the anterior limb of internal capsules, left forceps minor, and right cingulum. In girls, but not in boys, the relation between subthreshold depression at baseline and high depression score at follow-up was mediated by medial-prefrontal gray matter volume., Conclusion: Subthreshold depression in early adolescence might be associated with smaller gray and white matter volumes in regions of the frontal-striatal-limbic affective circuit, and the occurrence of depression in girls with subthreshold depression might be influenced by medial-prefrontal gray matter volume. However, these findings should be interpreted with caution because of the limitations of the clinical assessment methods., (Copyright © 2015 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.)

During rest, brain activity is synchronized between different regions widely distributed throughout the brain, forming functional networks. However, the molecular mechanisms supporting functional connectivity remain undefined. We show that functional brain networks defined with resting-state functional magnetic resonance imaging can be recapitulated by using measures of correlated gene expression in a post mortem brain tissue data set. The set of 136 genes we identify is significantly enriched for ion channels. Polymorphisms in this set of genes significantly affect resting-state functional connectivity in a large sample of healthy adolescents. Expression levels of these genes are also significantly associated with axonal connectivity in the mouse. The results provide convergent, multimodal evidence that resting-state functional networks correlate with the orchestrated activity of dozens of genes linked to ion channel activity and synaptic function., (Copyright © 2015, American Association for the Advancement of Science.)

Objective: To investigate the role of personality factors and attentional biases towards emotional faces, in establishing concurrent and prospective risk for mental disorder diagnosis in adolescence., Method: Data were obtained as part of the IMAGEN study, conducted across 8 European sites, with a community sample of 2257 adolescents. At 14 years, participants completed an emotional variant of the dot-probe task, as well two personality measures, namely the Substance Use Risk Profile Scale and the revised NEO Personality Inventory. At 14 and 16 years, participants and their parents were interviewed to determine symptoms of mental disorders., Results: Personality traits were general and specific risk indicators for mental disorders at 14 years. Increased specificity was obtained when investigating the likelihood of mental disorders over a 2-year period, with the Substance Use Risk Profile Scale showing incremental validity over the NEO Personality Inventory. Attentional biases to emotional faces did not characterise or predict mental disorders examined in the current sample., Discussion: Personality traits can indicate concurrent and prospective risk for mental disorders in a community youth sample, and identify at-risk youth beyond the impact of baseline symptoms. This study does not support the hypothesis that attentional biases mediate the relationship between personality and psychopathology in a community sample. Task and sample characteristics that contribute to differing results among studies are discussed.

Multi-subject datasets used in neuroimaging group studies have a complex structure, as they exhibit non-stationary statistical properties across regions and display various artifacts. While studies with small sample sizes can rarely be shown to deviate from standard hypotheses (such as the normality of the residuals) due to the poor sensitivity of normality tests with low degrees of freedom, large-scale studies (e.g. >100 subjects) exhibit more obvious deviations from these hypotheses and call for more refined models for statistical inference. Here, we demonstrate the benefits of robust regression as a tool for analyzing large neuroimaging cohorts. First, we use an analytic test based on robust parameter estimates; based on simulations, this procedure is shown to provide an accurate statistical control without resorting to permutations. Second, we show that robust regression yields more detections than standard algorithms using as an example an imaging genetics study with 392 subjects. Third, we show that robust regression can avoid false positives in a large-scale analysis of brain-behavior relationships with over 1500 subjects. Finally we embed robust regression in the Randomized Parcellation Based Inference (RPBI) method and demonstrate that this combination further improves the sensitivity of tests carried out across the whole brain. Altogether, our results show that robust procedures provide important advantages in large-scale neuroimaging group studies., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Background: Attention orienting is a cognitive process that facilitates the movement of attention focus from one location to another: this may be impaired in autism spectrum disorder (ASD). Dorsal and ventral attention networks (DAN and VAN) sub-serve the process of attention orienting. This study investigated the functional connectivity of attention orienting in these networks in ASD using the Posner Cueing Task., Method: Twenty-one adolescents with ASD and 21 age and IQ matched controls underwent functional magnetic resonance imaging. A psychophysical interaction (PPI) analysis was implemented to investigate task-dependent functional connectivity, measuring synchronicity of brain regions during the task. Regions of interest (ROI) were selected to explore functional connectivity in the DAN during cue-only conditions and in the VAN during invalid and valid trials., Results: Behaviourally, the ASD and control groups performed the task in a similar manner. Functional MRI results indicated that the ASD and control groups activated similar brain regions. During invalid trials (VAN), the ASD group showed significant positive functional connectivity to multiple brain regions, whilst the control group demonstrated negative connectivity. During valid trials (VAN), the two groups also showed contrasting patterns of connectivity. In the cue-only conditions (DAN), the ASD group showed weaker functional connectivity., Conclusion: The DAN analysis suggests that the ASD group has weaker coherence between brain areas involved in goal-driven, endogenous attention control. The strong positive functional connectivity exhibited by the ASD group in the VAN during the invalid trials suggests that individuals with ASD may generate compensatory mechanisms to achieve neurotypical behaviour. These results support the theory of abnormal cortical connectivity in autism., (© 2014 International Society for Autism Research, Wiley Periodicals, Inc.)

Background: Neuroimaging is an increasingly important tool in the diagnostic workup of dementia. Neurologists, geriatricians, and old-age psychiatrists are involved in key tasks in the diagnostic process, frequently referring patients with suspected dementia for neuroimaging., Methods: The research design was a postal survey of all geriatricians, old-age psychiatrists, and neurologists in the Republic of Ireland (N = 176) as identified by the Irish Medical Directory 2011-2012 and supplementary listings., Results: Almost 65% of specialists did not have access to 2-[18F]fluoro-2-deoxy-D-glucose positron emission (FDG-PET) or FDG-PET/computed tomography (CT), and 80.3% did not have access to perfusion hexamethylpropyleneamine oxime single-photon emission computed tomography (SPECT) or dopaminergic iodine-123-radiolabeled 2β-carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl) nortropane SPECT. Most specialists (88.7%) referred patients with mild cognitive impairment or suspected dementia for magnetic resonance imaging (MRI), 81.7% referred for CT, and 26.8% for FDG-PET or FDG-PET/CT. Only 44.6% of respondents were aware of dementia-specific protocols for referrals for neuroimaging., Conclusion: Specialist access to imaging modalities other than CT and MRI is restricted. Improved access may affect patient treatment and care.

It is known that the default mode network (DMN) may be modulated by a cognitive task and by performance level. Changes in the DMN have been examined by investigating resting-state activation levels, but there have been very few studies examining the modulation of effective connectivity of the DMN during a task in healthy older subjects. In this study, the authors examined how effective connectivity changed in the DMN between rest and during a memory task. The authors also investigated whether there was any relationship between effective connectivity modulation in the DMN and memory performance, to establish whether variations in cognitive performance are related to neural network effective connectivity, either at rest or during task performance. Twenty-eight healthy older participants underwent a resting-state functional magnetic resonance imaging scan and an emotional face-name encoding task. Effective connectivity analyses were performed on the DMN to examine the effective connectivity modulation in these two different conditions. During the resting state, there was strong self-influence in the regions of the DMN, while the main regions with statistically significant cross-regional effective connectivity were the posterior cingulate cortex (PCC) and the hippocampus (HP). During the memory task, the self-influence effective connectivities remained statistically significant across the DMN, and there were statistically significant effective connectivities from the PCC, HP, amygdala (AM), and parahippocampal region to other DMN regions. The authors found that effective connectivities from PCC, HP, and AM (in both resting state and during task) were linearly correlated to memory performance. The results suggest that superior memory ability in this older cohort was associated with effective connectivity both at rest and during the memory task of three DMN regions, which are also known to be important for memory function.

Catecholamine-0-methyl-transferase (COMT) gene variation effects on prefrontal blood oxygenation-level-dependent (BOLD) activation are robust; however, despite observations that COMT is estrogenically catabolized, sex differences in its prefrontal repercussions remain unclear. Here, in a large sample of healthy adolescents stratified by sex and Val(158)Met genotype (n=1133), we examine BOLD responses during performance of the stop-signal task in right-hemispheric prefrontal regions fundamental to inhibitory control. A significant sex-by-genotype interaction was observed in pre-SMA during successful-inhibition trials and in both pre-SMA and inferior frontal cortex during failed-inhibition trials with Val homozygotes displaying elevated activation compared with other genotypes in males but not in females. BOLD activation in the same regions significantly mediated the relationship between COMT genotype and inhibitory proficiency as indexed by stop-signal reaction time in males alone. These sexually dimorphic effects of COMT on inhibitory brain activation have important implications for our understanding of the contrasting patterns of prefrontally governed psychopathology observed in males and females.

Motivation is important for learning and cognition. Although dopaminergic (D2) transmission in the ventral striatum (VS) is associated with motivation, learning, and cognition are more strongly associated with function of the dorsal striatum, including activation in the caudate nucleus. A recent study found an interaction between intrinsic motivation and the DRD2/ANKK1 polymorphism (rs1800497), suggesting that A-carriers of rs1800497 are significantly more sensitive to motivation in order to improve during working memory (WM) training. Using data from the two large-scale imaging genetic data sets, IMAGEN (n=1080, age 13-15 years) and BrainChild (n∼300, age 6-27), we investigated whether rs1800497 is associated with WM. In the IMAGEN data set, we tested whether VS/caudate activation during reward anticipation was associated with WM performance and whether rs1800497 and VS/caudate activation interact to affect WM performance. We found that rs1800497 was associated with WM performance in IMAGEN and BrainChild. Higher VS and caudate activation during reward processing were significantly associated with higher WM performance (p<0.0001). An interaction was found between the DRD2/ANKK1 polymorphism rs1800497 and VS activation during reward anticipation on WM (p<0.01), such that carriers of the minor allele (A) showed a significant correlation between VS activation and WM, whereas the GG-homozygotes did not, suggesting that the effect of VS BOLD on WM is modified by inter-individual genetic differences related to D2 dopaminergic transmission.

Background: In this multicenter study, we investigated a possible association between the APOE ε4 allele and white matter (WM) integrity in Alzheimer's disease (AD) using diffusion tensor imaging (DTI)., Methods: We analyzed fractional anisotropy (FA) and mean diffusivity (MD) as indices of WM integrity in 70 AD patients (35 APOE ε4 carriers, 35 noncarriers) and 56 healthy control (HC) subjects (28 APOE ε4 carriers, 28 noncarriers). APOE ε4 carriers and noncarriers were matched for age and gender within each diagnostic group., Results: We found significant effects of diagnosis (Pcorrected < .05 [FWE]; i.e., smaller FA values and larger MD values in AD patients compared with HCs) and significant effects (P < .001) of APOE ε4 carrier status on MD in HCs but not in AD subjects., Conclusions: The results indicate that APOE ε4 has a moderate effect on WM integrity in HCs, but no effect on WM integrity in manifest AD., (Copyright © 2014 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.)

Neuroimaging group analyses are used to relate inter-subject signal differences observed in brain imaging with behavioral or genetic variables and to assess risks factors of brain diseases. The lack of stability and of sensitivity of current voxel-based analysis schemes may however lead to non-reproducible results. We introduce a new approach to overcome the limitations of standard methods, in which active voxels are detected according to a consensus on several random parcellations of the brain images, while a permutation test controls the false positive risk. Both on synthetic and real data, this approach shows higher sensitivity, better accuracy and higher reproducibility than state-of-the-art methods. In a neuroimaging-genetic application, we find that it succeeds in detecting a significant association between a genetic variant next to the COMT gene and the BOLD signal in the left thalamus for a functional Magnetic Resonance Imaging contrast associated with incorrect responses of the subjects from a Stop Signal Task protocol., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Primary progressive aphasia (PPA) is characterized by left hemispheric frontotemporal cortical atrophy. Evidence from anatomical studies suggests that the nucleus subputaminalis (NSP), a subnucleus of the cholinergic basal forebrain, may be involved in the pathological process of PPA. Therefore, we studied the pattern of cortical and basal forebrain atrophy in 10 patients with a clinical diagnosis of PPA and 18 healthy age-matched controls using high-resolution magnetic resonance imaging (MRI). We determined the cholinergic basal forebrain nuclei according to Mesulam's nomenclature and the NSP in MRI reference space based on histological sections and the MRI scan of a post-mortem brain in cranio. Using voxel-based analysis, we found left hemispheric cortical atrophy in PPA patients compared with controls, including prefrontal, lateral temporal and medial temporal lobe areas. We detected cholinergic basal forebrain atrophy in left predominant localizations of Ch4p, Ch4am, Ch4al, Ch3 and NSP. For the first time, we have described the pattern of basal forebrain atrophy in PPA and confirmed the involvement of NSP that had been predicted based on theoretical considerations. Our findings may enhance understanding of the role of cholinergic degeneration for the regional specificity of the cortical destruction leading to the syndrome of PPA., (© 2013 Elsevier Ireland Ltd. All rights reserved.)

With the prevalence of Alzheimer's disease (AD) predicted to increase substantially over the coming decades, the development of effective biomarkers for the early detection of the disease is paramount. In this short review, the main neuroimaging techniques which have shown potential as biomarkers for AD are introduced, with a focus on MRI. Structural MRI measures of the hippocampus and medial temporal lobe are still the most clinically validated biomarkers for AD, but newer techniques such as functional MRI and diffusion tensor imaging offer great scope in tracking changes in the brain, particularly in functional and structural connectivity, which may precede gray matter atrophy. These new advances in neuroimaging methods require further development and crucially, standardization; however, before they are used as biomarkers to aid in the diagnosis of AD.

During adolescence social relationships become increasingly important. Establishing and maintaining these relationships requires understanding of emotional stimuli, such as facial emotions. A failure to adequately interpret emotional facial expressions has previously been associated with various mental disorders that emerge during adolescence. The current study examined sex differences in emotional face processing during adolescence. Participants were adolescents (n = 1951) with a target age of 14, who completed a forced-choice emotion discrimination task. The stimuli used comprised morphed faces that contained a blend of two emotions in varying intensities (11 stimuli per set of emotions). Adolescent girls showed faster and more sensitive perception of facial emotions than boys. However, both adolescent boys and girls were most sensitive to variations in emotion intensity in faces combining happiness and sadness, and least sensitive to changes in faces comprising fear and anger. Furthermore, both sexes overidentified happiness and anger. However, the overidentification of happiness was stronger in boys. These findings were not influenced by individual differences in the level of pubertal maturation. These results indicate that male and female adolescents differ in their ability to identify emotions in morphed faces containing emotional blends. The findings provide information for clinical studies examining whether sex differences in emotional processing are related to sex differences in the prevalence of psychiatric disorders within this age group.

Resting fluctuations in the blood oxygenation level-dependent signal have attracted considerable interest for their sensitivity to pathological brain processes. However, these analyses are susceptible to confound by nonneural physiological factors such as vasculature, breathing, and head movement which is a concern when investigating elderly or pathological groups. Here, we used simultaneous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) (EEG/fMRI) to constrain the analysis of resting state networks (RSNs) and identify aging differences. Four of 26 RSNs showed fMRI and EEG/fMRI group differences; anterior default-mode network, left frontal-parietal network, bilateral middle frontal, and postcentral gyri. Seven RSNs showed only EEG/fMRI differences suggesting the combination of these 2 methods might be more sensitive to age-related neural changes than fMRI alone. Five RSNs showed only fMRI differences and might reflect nonneural group differences. Activity within some EEG/fMRI RSNs was better explained by neuropsychological measures (Mini Mental State Examination and Stroop) than age. These results support previous studies suggesting that age-related changes in specific RSNs are neural in origin, and show that changes in some RSNs relate better to elderly cognition than age., (Copyright © 2013 Elsevier Inc. All rights reserved.)

Arousal and valence play key roles in emotional perception, with normal aging leading to changes in the neural substrates supporting valence processing. The objective of this study was to investigate normal age-related changes in the neural substrates of emotional arousal processing. Twenty-three young and 23 older, healthy women underwent functional magnetic resonance imaging as they viewed images which were neutral or positive in valence and which varied in arousal level from low to high. Using a parametric modulation approach, we examined how the blood oxygen-level dependent signal varied with single trial subjective ratings of valence and arousal, and whether this differed with age. In accordance with previous studies we found that the older group showed greater activation in response to positive valence, in the left amygdala, left middle temporal gyrus and right lingual gyrus. In contrast however, they showed reduced reactivity to emotional arousal, in occipital and temporal visual cortices bilaterally, the left inferior parietal cortex, and the supplementary motor area bilaterally. This study represents the first of its kind to clearly dissociate how aging affects the neural correlates of emotional arousal and valence. The changes in arousal processing may in part be mediated by the functional reorganization evident in the aging brain, such as reduced activation of the posterior cortices as described by the posterior-anterior shift in ageing (PASA) effect., (Copyright © 2013 Elsevier Inc. All rights reserved.)

The diagnosis of Alzheimer's disease (AD) is presently going through a paradigm shift from disease categories to dimensions and toward the implementation of biomarkers to support identification of predementia and even preclinical asymptomatic stages of the disease. We outline the methodological basis of presently available biomarkers and technological methodologies in AD, including exploratory and hypothesis-based plasma and blood candidates, cerebrospinal fluid markers of amyloid load and axonal destruction, and imaging markers of amyloid deposition, synaptic dysfunction, cortical functional and structural disconnection, and regional atrophy. We integrate biomarker findings into a comprehensive model of AD pathogenesis from healthy aging to cognitive decline, the resilience to cerebral amyloid load (RECAL) matrix. The RECAL framework integrates factors of risk and resilience to cerebral amyloid load for individual risk prediction. We show the clinical consequences when the RECAL matrix is operationalized into a diagnostic algorithm both for individual counseling of subjects and for the identification of at risk samples for primary and secondary preventive trials. We discuss the implication of biomarkers for the identification of prodromal AD for the primary care system that seems presently not even prepared to cope with the increasing number of subjects afflicted with late stage AD dementia, let alone future cohorts of subjects searching counseling or treatment of predementia and asymptomatic stages of AD. The paradigm shift in AD diagnosis and its operationalization into a diagnostic framework will have major implications for our understanding of disease pathogenesis. Now, for the first time, we have access to in vivo markers of key events in AD pathogenesis integrated into a heuristic framework that makes strong predictions on pattern of multimodal biomarkers in different stages of AD. Critical testing of these predictions will help us to modify or even falsify the currently hold assumptions on the pathogenesis of AD based on in vivo evidence in humans.

The current study tested the accuracy of primary MRI and cerebrospinal fluid (CSF) biomarker candidates and neuropsychological tests for predicting the conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) dementia. In a cross-validation paradigm, predictor models were estimated in the training set of AD (N = 81) and elderly control subjects (N = 101). A combination of CSF t-tau/Aβ(1-4) ratio and MRI biomarkers or neuropsychological tests (free recall and trail making test B (TMT-B)) showed the best statistical fit in the AD vs. HC comparison, reaching a classification accuracy of up to 64% when applied to the prediction of MCI conversion (3.3-year observation interval, mean = 2.3 years). However, several single-predictor models showed a predictive accuracy of MCI conversion comparable to that of any multipredictor model. The best single predictors were right entorhinal cortex (prediction accuracy = 68.5% (95% CI (59.5, 77.4))) and TMT-B test (prediction accuracy 64.6% (95% CI (55.5, 73.4%))). In conclusion, short-term conversion to AD is predicted by single marker models to a comparable degree as by multimarker models in amnestic MCI subjects., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Purpose: To evaluate the feasibility of multicenter tractography of the cingulate bundle (CB) in Alzheimer's disease (AD)., Materials and Methods: Automated deterministic tractography of the CB was applied to scans of 45 patients with probable AD and 58 healthy controls (HC) acquired with Siemens Sonata (1.5T; 60 gradients), Trio (3T; 61 gradients), and Avanto (1.5T; 30 gradients). Diagnosis and center effects on the tracking indices fractional anisotropy (FA), mean diffusivity (MD), track density, and volume were estimated with analysis of variance., Results: The multicenter coefficients of variance (CVs) in HC and AD patients were 7% and 7% for FA, 10% and 8% for MD, 18% and 20% for density, and 21% and 21% for volume. Multicenter and single-center CVs were within a similar range. Significant center effects declined in the order MD > FA > density > volume. After adjustment for center and age, the AD group showed significantly higher MD (P < 0.001) and lower FA (P < 0.05) as compared with the HC group., Conclusion: Despite strong center effects, we detected significantly altered microstructural integrity of the CB in AD patients. Diffusion-tensor imaging indices of the CB as obtained by automated tractography might qualify as a biologically sustained surrogate marker for diagnostic and monitoring purposes in multicenter AD trials., (Copyright © 2012 Wiley Periodicals, Inc.)

Functional magnetic resonance imaging (fMRI) of default mode network (DMN) brain activity during resting is recently gaining attention as a potential noninvasive biomarker to diagnose incipient Alzheimer's disease. The aim of this study was to determine which method of data processing provides highest diagnostic power and to define metrics to further optimize the diagnostic value. fMRI was acquired in 21 healthy subjects, 17 subjects with mild cognitive impairment and 15 patients with Alzheimer's disease (AD) and data evaluated both with volumes of interest (VOI)-based signal time course evaluations and independent component analyses (ICA). The first approach determines the amount of DMN region interconnectivity (as expressed with correlation coefficients); the second method determines the magnitude of DMN coactivation. Apolipoprotein E (ApoE) genotyping was available in 41 of the subjects examined. Diagnostic power (expressed as accuracy) of data of a single DMN region in independent component analyses was 64%, that of a single correlation of time courses between 2 DMN regions was 71%, respectively. With multivariate analyses combining both methods of analysis and data from various regions, accuracy could be increased to 97% (sensitivity 100%, specificity 95%). In nondemented subjects, no significant differences in activity within DMN could be detected comparing ApoE ε4 allele carriers and ApoE ε4 allele noncarriers. However, there were some indications that fMRI might yield useful information given a larger sample. Time course correlation analyses seem to outperform independent component analyses in the identification of patients with Alzheimer's disease. However, multivariate analyses combining both methods of analysis by considering the activity of various parts of the DMN as well as the interconnectivity between these regions are required to achieve optimal and clinically acceptable diagnostic power., (Copyright © 2012 Elsevier Inc. All rights reserved.)

During the last two decades, imaging of neural activation has become an invaluable tool for assessing the functional organization of the human brain in vivo. Due to its widespread application in neuroscience, functional neuroimaging has raised the interest of clinical researchers in its possible use as a diagnostic biomarker. A hallmark feature of many neurodegenerative diseases is their chronic non-linear dynamic and highly complex preclinical course. Neurodegenerative diseases unfold over years to decades through clinically silent and asymptomatic stages of early adaptive, compensatory to pathophysiological (i.e. actively neurodegenerative) and decompensatory mechanisms in the brain - phases that are increasingly being considered as critical for primary and secondary preventive and therapeutic measures. Emerging evidence supports the concept of a potentially fully reversible functional phase that may precede the onset of micro- and macrostructural and cognitive decline, a potentially late-stage "neurodegenerative" phase of a primary neurodegenerative disorder. Alzheimer's disease serves as an ideal model to test this hypothesis supported by the neural network model of the healthy and diseased brain. Being highly dynamic in nature, brain activation and neuronal network functional connectivity represent not only candidate diagnostic but also candidate surrogate markers for interventional trials. Potential caveats of functional imaging are critically reviewed with focus on confound variables such as altered neurovascular coupling as well as parameters related to task- and study design., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

The objective of this review is to evaluate recent advances in functional magnetic resonance imaging (fMRI) research in Alzheimer's disease for the development of therapeutic agents. The basic building block underpinning cognition is a brain network. The measured brain activity serves as an integrator of the various components, from genes to structural integrity, that impact the function of networks underpinning cognition. Specific networks can be interrogated using cognitive paradigms such as a learning task or a working memory task. In addition, recent advances in our understanding of neural networks allow one to investigate the function of a brain network by investigating the inherent coherency of the brain networks that can be measured during resting state. The coherent resting state networks allow testing in cognitively impaired patients that may not be possible with the use of cognitive paradigms. In particular the default mode network (DMN) includes the medial temporal lobe and posterior cingulate, two key regions that support episodic memory function and are impaired in the earliest stages of Alzheimer's disease (AD). By investigating the effects of a prospective drug compound on this network, it could illuminate the specificity of the compound with a network supporting memory function. This could provide valuable information on the methods of action at physiological and behaviourally relevant levels. Utilizing fMRI opens up new areas of research and a new approach for drug development, as it is an integrative tool to investigate entire networks within the brain. The network based approach provides a new independent method from previous ones to translate preclinical knowledge into the clinical domain., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

Alzheimer disease (AD) is one of the most prevalent chronic medical conditions affecting the elderly population. The effectiveness of approved antidementia drugs, however, is limited-licensed AD medications provide only moderate relief of clinical symptoms. Cognitive intervention is a noninvasive therapy that could aid prevention and treatment of AD. Data suggest that specifically designed cognitive interventions could impart therapeutic benefits to patients with AD that are associated with substantial biological changes within the brain. Moreover, evidence indicates that a combination of pharmacological and non-pharmacological interventions could provide greater relief of clinical symptoms than either intervention given alone. Functional and structural MRI studies have increased our understanding of the underlying neurobiological mechanisms of aging and neurodegeneration, but the use of neuroimaging to investigate the effect of cognitive intervention on the brain remains largely unexplored. This Review provides an overview of the use of cognitive intervention in the healthy elderly population and patients with AD, and summarizes emerging findings that provide evidence for the effectiveness of this approach. Finally, we present recommendations for future research on the use of cognitive interventions in AD and discuss potential effects of this therapy on disease modification.

Resting state functional magnetic resonance imaging (fMRI) reveals a distinct network of correlated brain function representing a default mode state of the human brain. The underlying structural basis of this functional connectivity pattern is still widely unexplored. We combined fractional anisotropy measures of fiber tract integrity derived from diffusion tensor imaging (DTI) and resting state fMRI data obtained at 3 Tesla from 20 healthy elderly subjects (56 to 83 years of age) to determine white matter microstructure underlying default mode connectivity. We hypothesized that the functional connectivity between the posterior cingulate and hippocampus from resting state fMRI data would be associated with the white matter microstructure in the cingulate bundle and fiber tracts connecting posterior cingulate gyrus with lateral temporal lobes, medial temporal lobes, and precuneus. This was demonstrated at the p<0.001 level using a voxel-based multivariate analysis of covariance (MANCOVA) approach. In addition, we used a data-driven technique of joint independent component analysis (ICA) that uncovers spatial pattern that are linked across modalities. It revealed a pattern of white matter tracts including cingulate bundle and associated fiber tracts resembling the findings from the hypothesis-driven analysis and was linked to the pattern of default mode network (DMN) connectivity in the resting state fMRI data. Our findings support the notion that the functional connectivity between the posterior cingulate and hippocampus and the functional connectivity across the entire DMN is based on distinct pattern of anatomical connectivity within the cerebral white matter., (Copyright (c) 2009 Elsevier Inc. All rights reserved.)

Background: The orbitofrontal cortex (OFC) plays a crucial role in emotion-processing circuits and should therefore also be included in models of the pathophysiology of major depression. The aim of this study was to compare the functional connectivity of the OFC during emotion processing in patients with major depression and healthy control subjects., Methods: Twenty-five untreated patients with major depression and 15 healthy control subjects were investigated using a functional magnetic resonance imaging face-matching task., Results: Dorsal anterior cingulate cortex, precuneus, and cerebellum activity showed less connectivity with the OFC in patients than in control subjects. In contrast, functional connectivity between the OFC and the right dorsolateral prefrontal cortex (DLPFC), right inferior frontal operculum, and left motor areas was increased in patients compared with healthy control subjects., Conclusions: The OFC plays a key role in the pathophysiology of major depression. The observed imbalance of OFC connectivity seems to represent a neural mechanism of the processing bias. From a neurobiological point of view, the uncoupling of precuneus and gyrus cinguli activity from the OFC might be associated with problems in the regulation of self-schemas, whereas the increased connectivity of the DLPFC to the OFC might represent a higher neural response to negative stimuli.

Findings derived from neuroimaging of the structural and functional organization of the human brain have led to the widely supported hypothesis that neuronal networks of temporally coordinated brain activity across different regional brain structures underpin cognitive function. Failure of integration within a network leads to cognitive dysfunction. The current discussion on Alzheimer's disease (AD) argues that it presents in part a disconnection syndrome. Studies using functional magnetic resonance imaging, positron emission tomography and electroencephalography demonstrate that synchronicity of brain activity is altered in AD and correlates with cognitive deficits. Moreover, recent advances in diffusion tensor imaging have made it possible to track axonal projections across the brain, revealing substantial regional impairment in fiber-tract integrity in AD. Accumulating evidence points towards a network breakdown reflecting disconnection at both the structural and functional system level. The exact relationship among these multiple mechanistic variables and their contribution to cognitive alterations and ultimately decline is yet unknown. Focused research efforts aimed at the integration of both function and structure hold great promise not only in improving our understanding of cognition but also of its characteristic progressive metamorphosis in complex chronic neurodegenerative disorders such as AD.

Visual perception has been shown to be altered in Alzheimer disease (AD) patients, and it is associated with decreased cognitive function. Galantamine is an active cholinergic agent, which has been shown to lead to improved cognition in mild to moderate AD patients. This study examined brain activation in a group of mild AD patients after a 3-month open-label treatment with galantamine. The objective was to examine the changes in brain activation due to treatment. There were 2 tasks to visual perception. The first task was a face-matching task to test the activation along the ventral visual pathway, and the second task was a location-matching task to test neuronal function along the dorsal pathway. Brain activation was measured using functional magnetic resonance imaging. There were 5 mild AD patients in the study. There were no differences in the task performance and in the cognitive scores of the Consortium to Establish a Registry for Alzheimer's Disease battery before and after treatment. In the location-matching task, we found a statistically significant decrease in activation along the dorsal visual pathway after galantamine treatment. A previous study found that AD patients had higher activation in the location-matching task compared with healthy controls. There were no differences in activation for the face-matching task after treatment. Our data indicate that treatment with galantamine leads to more efficient visual processing of stimuli or changes the compensatory mechanism in the AD patients. A visual perception task recruiting the dorsal visual system may be useful as a biomarker of treatment effects.

Background: In the earliest clinical stages of Alzheimer's disease (AD) when symptoms are mild, clinical diagnosis can be difficult. AD pathology most likely precedes symptoms. Biomarkers can serve as early diagnostic indicators or as markers of preclinical pathologic change. Candidate biomarkers derived from structural and functional neuroimaging and those measured in cerebrospinal fluid (CSF) and plasma show the greatest promise. Unbiased exploratory approaches, eg, proteomics or cortical thickness analysis, could yield novel biomarkers. The objective of this article was to review recent progress in selected imaging and neurochemical biomarkers for early diagnosis, classification, progression, and prediction of AD., Methods: We performed a survey of recent research, focusing on core biomarker candidates in AD., Results: A number of in vivo neurochemistry and neuroimaging techniques, which can reliably assess aspects of physiology, pathology, chemistry, and neuroanatomy, hold promise as biomarkers. These neurobiologic measures appear to relate closely to pathophysiologic, neuropathologic, and clinical data, such as hyperphosphorylation of tau, amyloid beta (Abeta) metabolism, lipid peroxidation, pattern and rate of atrophy, loss of neuronal integrity, functional and cognitive decline, as well as risk of future decline. Current advances in the neuroimaging of mediotemporal, neocortical, and subcortical areas of the brain of mild cognitive impairment (MCI) and AD subjects are presented. CSF levels of Abeta42, tau, and hyperphosphorylated tau protein (p-tau) can distinguish subjects with MCI who are likely to progress to AD. They also show preclinical alterations that predict later development of early AD symptoms. Studies on plasma Abeta are not entirely consistent, but recent findings suggest that decreased plasma Abeta42 relative to Abeta40 might increase the risk of AD. Increased production of Abeta in aging is suggested by elevation of BACE1 protein and enzyme activity in the brain and CSF of subjects with MCI. CSF tau and p-tau are increased in MCI as well and show predictive value. Other biomarkers might indicate components of a cascade initiated by Abeta, such as oxidative stress or inflammation. These merit further study in MCI and earlier., Conclusions: A number of neuroimaging candidate markers are promising, such as hippocampus and entorhinal cortex volumes, basal forebrain nuclei, cortical thickness, deformation-based and voxel-based morphometry, structural and effective connectivity by using diffusion tensor imaging, tractography, and functional magnetic resonance imaging. CSF Abeta42, BACE1, total tau, and p-tau are substantially altered in MCI and clinical AD. Other interesting novel marker candidates derived from blood are being currently proposed (phase I). Biomarker discovery through proteomic approaches requires further research. Large-scale international controlled multicenter trials (such as the U.S., European, Australian, and Japanese Alzheimer's Disease Neuroimaging Initiative and the German Dementia Network) are engaged in phase III development of the core feasible imaging and CSF biomarker candidates in AD. Biomarkers are in the process of implementation as primary outcome variables into regulatory guideline documents regarding study design and approval for compounds claiming disease modification.

Automated deformation-based analysis of MRI scans can be used to detect specific pattern of brain atrophy in Alzheimer's disease (AD), but it still lacks an established model to derive the individual risk of AD in at-risk subjects, such as patients with mild cognitive impairment (MCI). We applied principal component analysis to deformation maps derived from MRI scans of 32 AD patients, 18 elderly healthy controls and 24 MCI patients. Principal component scores were used to discriminate between AD patients and controls and between MCI converters and MCI non-converters. We found a significant regional pattern of atrophy (p<0.001) in medial temporal lobes, neocortical association areas, thalamus and basal ganglia and corresponding widening of cerebrospinal fluid (CSF) spaces (p<0.001) in AD patients compared to controls. Accuracy was 81% for CSF- and 83% for brain-based deformation maps to separate AD patients from controls. Nine out of 24 MCI patients converted to AD during clinical follow-up. Discrimination between MCI converters and non-converters reached 80% accuracy based on CSF maps and 73% accuracy based on brain maps. In a logistic regression model, principal component scores based on CSF maps predicted clinical outcome in MCI patients even after controlling for age, gender, MMSE score and time of follow-up. Our findings indicate that multivariate network analysis of deformation maps detects typical features of AD pathology and provides a powerful tool to predict conversion into AD in non-demented at risk patients.

Functional MRI during face matching shows activation of the ventral visual stream, including the ventral temporal lobes and fusiform gyrus. In contrast, a location-matching task activates the dorsal visual stream, compromising parietal lobe areas. The morphological basis of the functional coupling between brain regions may be related to the distribution of neuron numbers and neuropil density, but has not yet been demonstrated in the living human brain. Regional neuron density can indirectly be assessed in vivo using structural MRI. The progression of Alzheimer's disease pathology along specific functional systems provides an in vivo lesion model to determine the interaction between reduced neuron numbers and reduced neuronal activation. In this study, we determined correlations between activation of the fusiform gyrus in fMRI during face matching and cortical grey matter density derived from structural MRI in 17 healthy elderly subjects (mean age = 67.5 years, SD = 4.5 years, 10 women) and 16 patients with amnestic mild cognitive impairment (MCI) (mean age = 69.9 years, SD = 8.0 years, 8 women), a predementia stage of Alzheimer's disease. Independently of diagnosis, stronger activation of the fusiform gyrus was correlated with larger grey matter density in the fusiform gyrus, inferior and middle temporal gyrus, parahippocampal gyrus and dorsolateral prefrontal cortex. In contrast, smaller activation of the fusiform gyrus was associated with larger grey matter density in the inferior parietal lobule, post-central gyrus and dorsolateral prefrontal cortex. Compared to controls, MCI patients had more pronounced positive correlations in the ventral temporal lobes and more pronounced negative correlations in the parietal lobes. Our data suggest that fusiform activation is positively correlated with cortical grey matter density of brain areas belonging to the ventral visual stream and negatively correlated with grey matter density of brain areas belonging to the dorsal visual stream and that, these effects are more pronounced in MCI patients than in controls. These findings support the notion that the functional segregation within the visual system is based on the distribution of cortical grey matter volumes, possibly reflecting the spatial distribution of neuron density.

Axonal and dendritic integrity is affected early in Alzheimer's disease (AD). Studies using region of interest or voxel-based analysis of diffusion tensor imaging data found significant decline of fractional anisotropy, a marker of fiber tract integrity, in selected white matter areas. We applied a multivariate network analysis based on principal component analysis to fractional anisotropy maps derived from diffusion-weighted scans from 15 AD patients, and 14 elderly healthy controls. Fractional anisotropy maps were obtained from an EPI diffusion sequence using parallel imaging to reduce distortion artifacts. We used high-dimensional image warping to control for partial volume effects due to white matter atrophy in AD. We found a significant regional pattern of fiber changes (p < 0.01) indicating that the integrity of intracortical projecting fiber tracts (including corpus callosum, cingulum and fornix, and frontal, temporal and occipital lobe white matter areas) was reduced, whereas extracortical projecting fiber tracts, including the pyramidal and extrapyramidal systems and somatosensory projections, were relatively preserved in AD. Effects of a univariate analysis were almost entirely contained within the multivariate effect. Our findings illustrate the use of a multivariate approach to fractional anisotropy data that takes advantage of the highly organized structure of anisotropy maps, and is independent of multiple comparison correction and partial volume effects. In agreement with post-mortem evidence, our study demonstrates dissociation between intracortical and extracortical projecting fiber systems in AD in the living human brain.

In the present study, we applied the Support Vector Machine (SVM) algorithm to perform multivariate classification of brain states from whole functional magnetic resonance imaging (fMRI) volumes without prior selection of spatial features. In addition, we did a comparative analysis between the SVM and the Fisher Linear Discriminant (FLD) classifier. We applied the methods to two multisubject attention experiments: a face matching and a location matching task. We demonstrate that SVM outperforms FLD in classification performance as well as in robustness of the spatial maps obtained (i.e. discriminating volumes). In addition, the SVM discrimination maps had greater overlap with the general linear model (GLM) analysis compared to the FLD. The analysis presents two phases: during the training, the classifier algorithm finds the set of regions by which the two brain states can be best distinguished from each other. In the next phase, the test phase, given an fMRI volume from a new subject, the classifier predicts the subject's instantaneous brain state.

Alzheimer's disease is characterized by the degeneration and loss of cholinergic neurones in the nucleus basalis Meynert, located within the substantia innominata at the ventral surface of the basal forebrain. An in vivo measure of morphological changes in the nucleus basalis Meynert would be of high relevance to better understand the structural correlate of cholinergic dysfunction in Alzheimer's disease. In this study, we applied a newly developed automated technique of image regression analysis, implemented through code written in Matlab 5.3 (MathWorks, Natick, MA), to the analysis of proton density weighted structural MRI of the basal forebrain from 13 patients with Alzheimer's disease (mean age = 77.5 years, SD = 4.4 years, 8 women) and 12 healthy elderly subjects (mean age = 62.3 years, SD = 5.6 years, 6 women). This technique allows searching a large portion of the substantia innominata for signal changes. We used corresponding MRI and histological sections of a post mortem brain to map the locations of basal forebrain cholinergic nuclei into the MRI standard space. Additionally, we used voxel-based morphometry, implemented in SPM2 (Wellcome Department of Imaging Neuroscience, London, UK) to determine correlations between signal changes in the substantia innominata and cortical grey matter atrophy in the patients with Alzheimer's disease. When matching the locations of signal reductions in the in vivo MRI to the template of basal nuclei based on the postmortem brain, signal intensity was decreased in areas corresponding to anterior lateral and anterior medial nucleus basalis Meynert and increased in the third ventricle, the transverse fissure and the optic tract in patients with Alzheimer's disease compared with controls. The reduction of the signal intensity in an area corresponding to the anterior lateral nucleus basalis Meynert was significantly correlated with reduced grey matter concentration in the bilateral prefrontal cortex, inferior parietal lobule and cingulate gyrus. Our findings suggest that signal changes occur in patients with Alzheimer's disease in the substantia innominata which may be related to the loss or degeneration of cholinergic neurones and correspond to regional cortical grey matter atrophy. If replicated in an independent sample, our technique may be useful to detect degeneration of basal forebrain cholinergic neurones in vivo.

Background: It is a challenge to reliably measure the lobar volumes from magnetic resonance imaging (MRI) data., Objective: Description of a landmark-based method for volumetric segmentation of the brain into the four cerebral lobes from MR images., Method: The segmentation method relies on a combination of anatomical landmarks and geometrical definitions. The first step, described previously, is a segmentation of the four lobes on the surface of the brain. The internal borders between the lobes are defined on the axial slices of the brain. The intra- and inter- rater reliability was determined from the MRI scans of a group of 10 healthy control subjects measured by 2 independent raters., Results: The intra-rater relative error (and intra-class correlation coefficient) of the lobar volume measures ranged from 0.81% to 3.85% (from 0.97 to 0.99). The inter-rater relative error (and intra-class correlation coefficient) ranged from 0.55% to 3.09% (from 0.94 to 0.99)., Conclusion: This technique has been shown to have high intra- and inter-rater reliability. The current method provides a method to obtain volumetric estimates of the 4 cerebral lobes.

Studies using positron emission tomography (PET) have reported that global and regional values for cerebral blood flow and metabolic rates for glucose (CMRglc and rCMRglc) decline with age in humans. We wished to determine if such decreases could have reflected a partial volume effect (PVE) of cerebral atrophy in the elderly, rather than "intrinsic" reductions per gram brain. We used PET to compare rCMRglc, before and after correcting for the PVE, between 13 healthy older men (aged: 55-82 years) and 11 healthy young men (aged: 22-34 years). PET was performed with 18F-fluoro-2-deoxy-d-glucose while the subjects were in the "resting" state (eyes covered and ears plugged with cotton). The PET scans were normalized to a common brain volume after superimposing them on the subjects' tissue segmented magnetic resonance scans. Analysis showed that rCMRglc in the absence of a PVE correction was significantly less in the older group in insular, frontal, superior temporal cortical, and thalamic regions. Statistical significant differences in rCMRglc, however, were absent after the PVE correction. Thus, statistically significant age reductions in regional brain glucose metabolism, corrected for brain atrophy, are not detectable in healthy normotensive men scanned while in the resting state.

The apolipoprotein E-epsilon4 allele confers an increased susceptibility to age-related memory problems and Alzheimer's disease. Abnormalities in the cholinergic system are also likely contributors to memory deficits associated with aging and AD. To determine the effect of the APOE-epsilon4 allele on the muscarinic component of the cholinergic system of aging subjects, 10 healthy subjects with APOE-epsilon4 alleles (APOE-epsilon4+) and 10 without (APOE-epsilon4-), ranging in age from 52 to 75 years, were tomographically scanned with the F-18-labeled muscarinic-2 (M2) selective agonist, 3-(3-(3-[(18)F]Flouropropyl)thio)-1,2,5-thiadiazol-4-yl)-1,2,5,6-tetrahydro-1-methylpyridine ([(18)F]FP-TZTP). The distribution volumes (V(T)) of [(18)F]FP-TZTP were determined by compartmental modeling of partial volume and free fraction corrected PET scans. Regional cerebral blood flow (rCBF) measurements with H(2) (15)O were also performed. Global Gray V(T) (840 +/- 155 ml plasma/ml tissue) was greater in APOE-epsilon4+ subjects than APOE-epsilon4- subjects (660 +/- 113 ml plasma/ml tissue, P = 0.01), and previously studied younger subjects. There were no significant differences between the groups with respect to rCBF, but within the APOE-epsilon4+ group there was a trend for subjects with the higher Global Gray V(T)s to have lower Global Gray CBFs (r = -0.65, P < 0.06). A lower concentration of acetylcholine in the synapse of APOE-epsilon4+ older individuals is a likely explanation for the greater [(18)F]FP-TZTP distribution volumes.

Arachidonic acid (AA) is an important second messenger involved in signal transduction mediated by phospholipase A2. The goal of this study was to establish an in vivo quantitative method to examine the role of AA in this signaling process in the human brain. A simple irreversible uptake model was derived from rat studies and modified for positron emission tomography (PET) to quantify the incorporation rate K* of [11C]AA into brain. Dynamic 60-minute three-dimensional scans and arterial input functions were acquired in 8 young healthy adults studied at rest. Brain radioactivity was corrected for uptake of the metabolite [11C]CO2. K* and cerebral blood volume (Vb) were estimated pixel-by-pixel and were calculated in regions of interest. K* equaled 5.6+/-1.2 and 2.6+/-0.5 microL x min(-1) x mL(-1) in gray and white matter, respectively. K* and Vb values were found to be unchanged with data analysis periods from 20 to 60 minutes. Thus, PET can be used to obtain quantitative images of the incorporation rate K* of [11C]AA in the human brain. As brain incorporation of labeled AA has been shown in awake rats to be increased by pharmacological activation associated with phospholipase A2-signaling, PET and [11C]AA may be useful to measure signal transduction in the human brain.

This review outlines ethical, legal, and practical issues related to conducting functional imaging research with Alzheimer's disease (AD) patients. Imaging techniques, with an emphasis on functional MRI and positron emission tomography, are compared and contrasted with respect to the manner in which they can be applied to issues of clinical relevance to AD. Methodological difficulties are raised to assist with critical evaluation of current imaging results. Various potential clinical applications of functional imaging are briefly reviewed and discussed with respect to associated ethical conflicts.