Residency:Brigham and Women's Hospital Harvard Medical School (2000) MA
Medical Education:Columbia University (1996) NY
Internship:Columbia Presbyterian Medical Center (1997) NY
Residency:Massachusetts General Hospital (2000) MA
Fellowship:Stanford University School of Medicine (2001) CA
Board Certification: Neurology, American Board of Psychiatry and Neurology (2003)
Current Research and Scholarly Interests
Dr. Greicius' research involves the use of functional MRI in conjunction with other imaging modalities to detect and characterize neural networks in healthy adults and patients with neuropsychiatric disorders. The main research objective is to develop novel imaging biomarkers that will enhance the understanding, diagnosis, and treatment of disorders such as Alzheimer's disease, major depression, and schizophrenia.
Independent Studies (8)
- Directed Reading in Neurology and Neurological Science
NENS 299 (Aut, Win, Spr, Sum)
- Directed Reading in Neurosciences
NEPR 299 (Win, Spr, Sum)
- Early Clinical Experience in Neurology and Neurological Sciences
NENS 280 (Aut, Win, Spr, Sum)
- Graduate Research
NENS 399 (Aut, Win, Spr, Sum)
- Graduate Research
NEPR 399 (Win, Spr, Sum)
- Medical Scholars Research
NENS 370 (Aut, Win, Spr, Sum)
- Out-of-Department Advanced Research Laboratory in Experimental Biology
BIO 199X (Aut, Win, Spr)
- Undergraduate Research
NENS 199 (Aut, Win, Spr, Sum)
- Directed Reading in Neurology and Neurological Science
Optimization of rs-fMRI Pre-processing for Enhanced Signal-Noise Separation, Test-Retest Reliability, and Group Discrimination
2015; 117: 67-79
Resting-state functional magnetic resonance imaging (rs-fMRI) has become an increasingly important tool in mapping the functional networks of the brain. This tool has been used to examine network changes induced by cognitive and emotional states, neurological traits, and neuropsychiatric disorders. However, noise that remains in the rs-fMRI data after preprocessing has limited the reliability of individual-subject results, wherein scanner artifacts, subject movements, and other noise sources induce non-neural temporal correlations in the blood oxygen level-dependent (BOLD) timeseries. Numerous preprocessing methods have been proposed to isolate and remove these confounds; however, the field has not coalesced around a standard preprocessing pipeline. In comparisons, these preprocessing methods are often assessed with only a single metric of rs-fMRI data quality, such as reliability, without considering other aspects in tandem, such as signal-to-noise ratio and group discriminability. The present study seeks to identify the data preprocessing pipeline that optimizes rs-fMRI data across multiple outcome measures. Specifically, we aim to minimize the noise in the data and maximize result reliability, while retaining the unique features that characterize distinct groups. We examine how these metrics are influenced by bandpass filter selection and noise regression in four datasets, totaling 181 rs-fMRI scans and 38 subject-driven memory scans. Additionally, we perform two different rs-fMRI analysis methods - dual regression and region-of-interest based functional connectivity - and highlight the preprocessing parameters that optimize both approaches. Our results expand upon previous reports of individual-scan reliability, and demonstrate that preprocessing parameter selection can significantly change the noisiness, reliability, and heterogeneity of rs-fMRI data. The application of our findings to rs-fMRI data analysis should improve the validity and reliability of rs-fMRI results, both at the individual-subject level and the group level.
View details for DOI 10.1016/j.neuroimage.2015.05.015
View details for Web of Science ID 000358045100007
View details for PubMedID 25987368
- Correlated gene expression supports synchronous activity in brain networks SCIENCE 2015; 348 (6240): 1241-1244
BRAIN NETWORKS. Correlated gene expression supports synchronous activity in brain networks.
2015; 348 (6240): 1241-1244
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.
View details for DOI 10.1126/science.1255905
View details for PubMedID 26068849
Introducing co-activation pattern metrics to quantify spontaneous brain network dynamics
2015; 111: 476-488
Recently, fMRI researchers have begun to realize that the brain's intrinsic network patterns may undergo substantial changes during a single resting state (RS) scan. However, despite the growing interest in brain dynamics, metrics that can quantify the variability of network patterns are still quite limited. Here, we first introduce various quantification metrics based on the extension of co-activation pattern (CAP) analysis, a recently proposed point-process analysis that tracks state alternations at each individual time frame and relies on very few assumptions; then apply these proposed metrics to quantify changes of brain dynamics during a sustained 2-back working memory (WM) task compared to rest. We focus on the functional connectivity of two prominent RS networks, the default-mode network (DMN) and executive control network (ECN). We first demonstrate less variability of global Pearson correlations with respect to the two chosen networks using a sliding-window approach during WM task compared to rest; then we show that the macroscopic decrease in variations in correlations during a WM task is also well characterized by the combined effect of a reduced number of dominant CAPs, increased spatial consistency across CAPs, and increased fractional contributions of a few dominant CAPs. These CAP metrics may provide alternative and more straightforward quantitative means of characterizing brain network dynamics than time-windowed correlation analyses.
View details for DOI 10.1016/j.neuroimage.2015.01.057
View details for Web of Science ID 000352224100042
View details for PubMedID 25662866
Bootstrapped Permutation Test for Multiresponse Inference on Brain Behavior Associations.
Information processing in medical imaging : proceedings of the ... conference
2015; 24: 113-124
Despite that diagnosis of neurological disorders commonly involves a collection of behavioral assessments, most neuroimaging studies investigating the associations between brain and behavior largely analyze each behavioral measure in isolation. To jointly model multiple behavioral scores, sparse multiresponse regression (SMR) is often used. However, directly applying SMR without statistically controlling for false positives could result in many spurious findings. For models, such as SMR, where the distribution of the model parameters is unknown, permutation test and stability selection are typically used to control for false positives. In this paper, we present another technique for inferring statistically significant features from models with unknown parameter distribution. We refer to this technique as bootstrapped permutation test (BPT), which uses Studentized statistics to exploit the intuition that the variability in parameter estimates associated with relevant features would likely be higher with responses permuted. On synthetic data, we show that BPT provides higher sensitivity in identifying relevant features from the SMR model than permutation test and stability selection, while retaining strong control on the false positive rate. We further apply BPT to study the associations between brain connectivity estimated from pseudo-rest fMRI data of 1139 fourteen year olds and behavioral measures related to ADHD. Significant connections are found between brain networks known to be implicated in the behavioral tasks involved. Moreover, we validate the identified connections by fitting a regression model on pseudo-rest data with only those connections and applying this model on resting state fMRI data of 337 left out subjects to predict their behavioral scores. The predicted scores significantly correlate with the actual scores, hence verifying the behavioral relevance of the found connections.
View details for PubMedID 26221670
Disentangling Dynamic Networks: Separated and Joint Expressions of Functional Connectivity Patterns in Time
HUMAN BRAIN MAPPING
2014; 35 (12): 5984-5995
Resting-state functional connectivity (FC) is highly variable across the duration of a scan. Groups of coevolving connections, or reproducible patterns of dynamic FC (dFC), have been revealed in fluctuating FC by applying unsupervised learning techniques. Based on results from k-means clustering and sliding-window correlations, it has recently been hypothesized that dFC may cycle through several discrete FC states. Alternatively, it has been proposed to represent dFC as a linear combination of multiple FC patterns using principal component analysis. As it is unclear whether sparse or nonsparse combinations of FC patterns are most appropriate, and as this affects their interpretation and use as markers of cognitive processing, the goal of our study was to evaluate the impact of sparsity by performing an empirical evaluation of simulated, task-based, and resting-state dFC. To this aim, we applied matrix factorizations subject to variable constraints in the temporal domain and studied both the reproducibility of ensuing representations of dFC and the expression of FC patterns over time. During subject-driven tasks, dFC was well described by alternating FC states in accordance with the nature of the data. The estimated FC patterns showed a rich structure with combinations of known functional networks enabling accurate identification of three different tasks. During rest, dFC was better described by multiple FC patterns that overlap. The executive control networks, which are critical for working memory, appeared grouped alternately with externally or internally oriented networks. These results suggest that combinations of FC patterns can provide a meaningful way to disentangle resting-state dFC.
View details for DOI 10.1002/hbm.22599
View details for Web of Science ID 000344398900019
View details for PubMedID 25081921
Apolipoprotein E, gender, and Alzheimer's disease: an overlooked, but potent and promising interaction
BRAIN IMAGING AND BEHAVIOR
2014; 8 (2): 262-273
Alzheimer's disease (AD) is an increasingly prevalent, fatal neurodegenerative disease that has proven resistant, thus far, to all attempts to prevent it, forestall it, or slow its progression. The ε4 allele of the Apolipoprotein E gene (APOE4) is a potent genetic risk factor for sporadic and late-onset familial AD. While the link between APOE4 and AD is strong, many expected effects, like increasing the risk of conversion from MCI to AD, have not been widely replicable. One critical, and commonly overlooked, feature of the APOE4 link to AD is that several lines of evidence suggest it is far more pronounced in women than in men. Here we review previous literature on the APOE4 by gender interaction with a particular focus on imaging-related studies.
View details for DOI 10.1007/s11682-013-9272-x
View details for Web of Science ID 000335765700009
Sex Modifies the APOE-Related Risk of Developing Alzheimer Disease
ANNALS OF NEUROLOGY
2014; 75 (4): 563-573
The APOE4 allele is the strongest genetic risk factor for sporadic Alzheimer disease (AD). Case-control studies suggest the APOE4 link to AD is stronger in women. We examined the APOE4-by-sex interaction in conversion risk (from healthy aging to mild cognitive impairment (MCI)/AD or from MCI to AD) and cerebrospinal fluid (CSF) biomarker levels.Cox proportional hazards analysis was used to compute hazard ratios (HRs) for an APOE-by-sex interaction on conversion in controls (n = 5,496) and MCI patients (n = 2,588). The interaction was also tested in CSF biomarker levels of 980 subjects from the Alzheimer's Disease Neuroimaging Initiative.Among controls, male and female carriers were more likely to convert to MCI/AD, but the effect was stronger in women (HR = 1.81 for women; HR = 1.27 for men; interaction: p = 0.011). The interaction remained significant in a predefined subanalysis restricted to APOE3/3 and APOE3/4 genotypes. Among MCI patients, both male and female APOE4 carriers were more likely to convert to AD (HR = 2.16 for women; HR = 1.64 for men); the interaction was not significant (p = 0.14). In the subanalysis restricted to APOE3/3 and APOE3/4 genotypes, the interaction was significant (p = 0.02; HR = 2.17 for women; HR = 1.51 for men). The APOE4-by-sex interaction on biomarker levels was significant for MCI patients for total tau and the tau-to-Aβ ratio (p = 0.009 and p = 0.02, respectively; more AD-like in women).APOE4 confers greater AD risk in women. Biomarker results suggest that increased APOE-related risk in women may be associated with tau pathology. These findings have important clinical implications and suggest novel research approaches into AD pathogenesis.
View details for DOI 10.1002/ana.24135
View details for Web of Science ID 000335234200011
Transport on Riemannian manifold for functional connectivity-based classification.
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
2014; 17: 405-412
We present a Riemannian approach for classifying fMRI connectivity patterns before and after intervention in longitudinal studies. A fundamental difficulty with using connectivity as features is that covariance matrices live on the positive semi-definite cone, which renders their elements inter-related. The implicit independent feature assumption in most classifier learning algorithms is thus violated. In this paper, we propose a matrix whitening transport for projecting the covariance estimates onto a common tangent space to reduce the statistical dependencies between their elements. We show on real data that our approach provides significantly higher classification accuracy than directly using Pearson's correlation. We further propose a non-parametric scheme for identifying significantly discriminative connections from classifier weights. Using this scheme, a number of neuroanatomically meaningful connections are found, whereas no significant connections are detected with pure permutation testing.
View details for PubMedID 25485405
Transport on Riemannian Manifold for Functional Connectivity-Based Classification
MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI 2014, PT II
2014; 8674: 405-412
View details for Web of Science ID 000347686400051
The Will to Persevere Induced by Electrical Stimulation of the Human Cingulate Gyrus
2013; 80 (6): 1359-1367
Anterior cingulate cortex (ACC) is known to be involved in functions such as emotion, pain, and cognitive control. While studies in humans and nonhuman mammals have advanced our understanding of ACC function, the subjective correlates of ACC activity have remained largely unexplored. In the current study, we show that electrical charge delivery in the anterior midcingulate cortex (aMCC) elicits autonomic changes and the expectation of an imminent challenge coupled with a determined attitude to overcome it. Seed-based, resting-state connectivity analysis revealed that the site of stimulation in both patients was at the core of a large-scale distributed network linking aMCC to the frontoinsular and frontopolar as well as some subcortical regions. This report provides compelling, first-person accounts of electrical stimulation of this brain network and suggests its possible involvement in psychopathological conditions that are characterized by a reduced capacity to endure psychological or physical distress.
View details for DOI 10.1016/j.neuron.2013.10.057
View details for Web of Science ID 000328919200006
View details for PubMedID 24316296
Identifying Large-Scale Brain Networks in Fragile X Syndrome
2013; 70 (11): 1215-1223
Fragile X syndrome (FXS) is an X-linked neurogenetic disorder characterized by a cognitive and behavioral phenotype resembling features of autism spectrum disorder. Until now, research has focused largely on identifying regional differences in brain structure and function between individuals with FXS and various control groups. Very little is known about the large-scale brain networks that may underlie the cognitive and behavioral symptoms of FXS.To identify large-scale, resting-state networks in FXS that differ from control individuals matched on age, IQ, and severity of behavioral and cognitive symptoms.Cross-sectional, in vivo neuroimaging study conducted in an academic medical center. Participants (aged 10-23 years) included 17 males and females with FXS and 16 males and females serving as controls.Univariate voxel-based morphometric analyses, fractional amplitude of low-frequency fluctuations (fALFF) analysis, and group-independent component analysis with dual regression.Patients with FXS showed decreased functional connectivity in the salience, precuneus, left executive control, language, and visuospatial networks compared with controls. Decreased fALFF in the bilateral insular, precuneus, and anterior cingulate cortices also was found in patients with FXS compared with control participants. Furthermore, fALFF in the left insular cortex was significantly positively correlated with IQ in patients with FXS. Decreased gray matter density, resting-state connectivity, and fALFF converged in the left insular cortex in patients with FXS.Fragile X syndrome results in widespread reductions in functional connectivity across multiple cognitive and affective brain networks. Converging structural and functional abnormalities in the left insular cortex, a region also implicated in individuals diagnosed with autism spectrum disorder, suggests that insula integrity and connectivity may be compromised in FXS. This method could prove useful in establishing an imaging biomarker for FXS.
View details for DOI 10.1001/jamapsychiatry.2013.247
View details for Web of Science ID 000328948700014
Disordered reward processing and functional connectivity in trichotillomania: A pilot study
JOURNAL OF PSYCHIATRIC RESEARCH
2013; 47 (9): 1264-1272
The neurobiology of Trichotillomania is poorly understood, although there is increasing evidence to suggest that TTM may involve alterations of reward processing. The current study represents the first exploration of reward processing in TTM and the first resting state fMRI study in TTM. We incorporate both event-related fMRI using a monetary incentive delay (MID) task, and resting state fMRI, using two complementary resting state analysis methodologies (functional connectivity to the nucleus accumbens and dual regression within a reward network) in a pilot study to investigate differences in reward processing between TTM and healthy controls (HC).21 unmedicated subjects with TTM and 14 HC subjects underwent resting state fMRI scans. A subset (13 TTM and 12 HC) also performed the MID task.For the MID task, TTM subjects showed relatively decreased nucleus accumbens (NAcc) activation to reward anticipation, but relative over-activity of the NAcc to both gain and loss outcomes. Resting state functional connectivity analysis showed decreased connectivity of the dorsal anterior cingulate (dACC) to the NAcc in TTM. Dual regression analysis of a reward network identified through independent component analysis (ICA) also showed decreased dACC connectivity and more prominently decreased basolateral amygdala connectivity within the reward network in TTM.Disordered reward processing at the level of NAcc, also involving decreased modulatory input from the dACC and the basolateral amygdala may play a role in the pathophysiology of TTM.
View details for DOI 10.1016/j.jpsychires.2013.05.014
View details for Web of Science ID 000322413800021
View details for PubMedID 23777938
Intrinsic connectivity networks in healthy subjects explain clinical variability in Alzheimer's disease
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2013; 110 (28): 11606-11611
Although previous studies have emphasized the vulnerability of the default mode network (DMN) in Alzheimer's disease (AD), little is known about the involvement of other functional networks and their relationship to clinical phenotype. To test whether clinicoanatomic heterogeneity in AD is driven by the involvement of specific networks, network connectivity was assessed in healthy subjects by seeding regions commonly and specifically atrophied in three clinical AD variants: early-onset AD (age at onset, <65 y; memory and executive deficits), logopenic variant primary progressive aphasia (language deficits), and posterior cortical atrophy (visuospatial deficits). Four-millimeter seed regions of interest were used to obtain intrinsic connectivity maps in 131 healthy controls (age, 65.5 ± 3.5 y). Atrophy patterns in independent cohorts of AD variant patients and their correspondence to connectivity networks in controls were also assessed. The connectivity maps of commonly atrophied regions of interest support posterior DMN and precuneus network involvement across AD variants, whereas seeding regions specifically atrophied in each AD variant revealed distinct, syndrome-specific connectivity patterns. Goodness-of-fit analysis of each connectivity map with network templates showed the highest correspondence between the early-onset AD seed connectivity map and anterior salience and right executive-control networks, the logopenic aphasia seed connectivity map and the language network, and the posterior cortical atrophy seed connectivity map and the higher visual network. Connectivity maps derived from controls matched regions commonly and specifically atrophied in the patients. Our findings indicate that the posterior DMN and precuneus network are commonly affected in AD variants, whereas syndrome-specific neurodegenerative patterns are driven by the involvement of specific networks outside the DMN.
View details for DOI 10.1073/pnas.1221536110
View details for Web of Science ID 000321827000086
View details for PubMedID 23798398
Altered resting state network activity in complex regional pain syndrome
CHURCHILL LIVINGSTONE. 2013: S48-S48
View details for Web of Science ID 000317639400189
Diverging patterns of amyloid deposition and hypometabolism in clinical variants of probable Alzheimer's disease
2013; 136: 844-858
The factors driving clinical heterogeneity in Alzheimer's disease are not well understood. This study assessed the relationship between amyloid deposition, glucose metabolism and clinical phenotype in Alzheimer's disease, and investigated how these relate to the involvement of functional networks. The study included 17 patients with early-onset Alzheimer's disease (age at onset <65 years), 12 patients with logopenic variant primary progressive aphasia and 13 patients with posterior cortical atrophy [whole Alzheimer's disease group: age = 61.5 years (standard deviation 6.5 years), 55% male]. Thirty healthy control subjects [age = 70.8 (3.3) years, 47% male] were also included. Subjects underwent positron emission tomography with (11)C-labelled Pittsburgh compound B and (18)F-labelled fluorodeoxyglucose. All patients met National Institute on Ageing-Alzheimer's Association criteria for probable Alzheimer's disease and showed evidence of amyloid deposition on (11)C-labelled Pittsburgh compound B positron emission tomography. We hypothesized that hypometabolism patterns would differ across variants, reflecting involvement of specific functional networks, whereas amyloid patterns would be diffuse and similar across variants. We tested these hypotheses using three complimentary approaches: (i) mass-univariate voxel-wise group comparison of (18)F-labelled fluorodeoxyglucose and (11)C-labelled Pittsburgh compound B; (ii) generation of covariance maps across all subjects with Alzheimer's disease from seed regions of interest specifically atrophied in each variant, and comparison of these maps to functional network templates; and (iii) extraction of (11)C-labelled Pittsburgh compound B and (18)F-labelled fluorodeoxyglucose values from functional network templates. Alzheimer's disease clinical groups showed syndrome-specific (18)F-labelled fluorodeoxyglucose patterns, with greater parieto-occipital involvement in posterior cortical atrophy, and asymmetric involvement of left temporoparietal regions in logopenic variant primary progressive aphasia. In contrast, all Alzheimer's disease variants showed diffuse patterns of (11)C-labelled Pittsburgh compound B binding, with posterior cortical atrophy additionally showing elevated uptake in occipital cortex compared with early-onset Alzheimer's disease. The seed region of interest covariance analysis revealed distinct (18)F-labelled fluorodeoxyglucose correlation patterns that greatly overlapped with the right executive-control network for the early-onset Alzheimer's disease region of interest, the left language network for the logopenic variant primary progressive aphasia region of interest, and the higher visual network for the posterior cortical atrophy region of interest. In contrast, (11)C-labelled Pittsburgh compound B covariance maps for each region of interest were diffuse. Finally, (18)F-labelled fluorodeoxyglucose was similarly reduced in all Alzheimer's disease variants in the dorsal and left ventral default mode network, whereas significant differences were found in the right ventral default mode, right executive-control (both lower in early-onset Alzheimer's disease and posterior cortical atrophy than logopenic variant primary progressive aphasia) and higher-order visual network (lower in posterior cortical atrophy than in early-onset Alzheimer's disease and logopenic variant primary progressive aphasia), with a trend towards lower (18)F-labelled fluorodeoxyglucose also found in the left language network in logopenic variant primary progressive aphasia. There were no differences in (11)C-labelled Pittsburgh compound B binding between syndromes in any of the networks. Our data suggest that Alzheimer's disease syndromes are associated with degeneration of specific functional networks, and that fibrillar amyloid-? deposition explains at most a small amount of the clinico-anatomic heterogeneity in Alzheimer's disease.
View details for DOI 10.1093/brain/aws327
View details for Web of Science ID 000315624700016
View details for PubMedID 23358601
Sporadic Jakob-Creutzfeldt Disease Presenting as Primary Progressive Aphasia
2013; 70 (2): 254-257
To report the clinical, neuropsychological, linguistic, imaging, and neuropathological features of a unique case of sporadic Jakob-Creutzfeldt disease in which the patient presented with a logopenic variant of primary progressive aphasia.Case report.Large referral center for atypical memory and aging disorders, particularly Jakob-Creutzfeldt disease.Patient presenting with logopenic variant primary progressive aphasia initially thought to be due to Alzheimer disease.Despite the long, slow 3.5-year course, the patient was shown to have pathology-proven sporadic Jakob-Creutzfeldt disease.These findings expand the differential of primary progressive aphasia to include prion disease.
View details for DOI 10.1001/2013.jamaneurol.139
View details for Web of Science ID 000316801300016
View details for PubMedID 23400721
- Two test statistics for cross-modal graph community significance 2013 3RD INTERNATIONAL WORKSHOP ON PATTERN RECOGNITION IN NEUROIMAGING (PRNI 2013) 2013: 70-73
Neuroimaging insights into network-based neurodegeneration
CURRENT OPINION IN NEUROLOGY
2012; 25 (6): 727-734
Convergent evidence from a number of neuroscience disciplines supports the hypothesis that Alzheimer's disease and other neurodegenerative disorders progress along brain networks. This review considers the role of neuroimaging in strengthening the case for network-based neurodegeneration and elucidating potential mechanisms.Advances in functional and structural MRI have recently enabled the delineation of multiple large-scale distributed brain networks. The application of these network-imaging modalities to neurodegenerative disease has shown that specific disorders appear to progress along specific networks. Recent work applying theoretical measures of network efficiency to in-vivo network imaging has allowed for the development and evaluation of models of disease spread along networks. Novel MRI acquisition and analysis methods are paving the way for in-vivo assessment of the layer-specific microcircuits first targeted by neurodegenerative diseases. These methodological advances coupled with large, longitudinal studies of subjects progressing from healthy aging into dementia will enable a detailed understanding of the seeding and spread of these disorders.Neuroimaging has provided ample evidence that neurodegenerative disorders progress along brain networks, and is now beginning to elucidate how they do so.
View details for DOI 10.1097/WCO.0b013e32835a26b3
View details for Web of Science ID 000311364500013
View details for PubMedID 23108250
- Introduction to the Special Issue on Connectivity NEUROIMAGE 2012; 62 (4): 2181-2181
Efficacy of Transcranial Magnetic Stimulation Targets for Depression Is Related to Intrinsic Functional Connectivity with the Subgenual Cingulate
2012; 72 (7): 595-603
Transcranial magnetic stimulation (TMS) to the left dorsolateral prefrontal cortex (DLPFC) is used clinically for the treatment of depression. However, the antidepressant mechanism remains unknown and its therapeutic efficacy remains limited. Recent data suggest that some left DLPFC targets are more effective than others; however, the reasons for this heterogeneity and how to capitalize on this information remain unclear.Intrinsic (resting state) functional magnetic resonance imaging data from 98 normal subjects were used to compute functional connectivity with various left DLPFC TMS targets employed in the literature. Differences in functional connectivity related to differences in previously reported clinical efficacy were identified. This information was translated into a connectivity-based targeting strategy to identify optimized left DLPFC TMS coordinates. Results in normal subjects were tested for reproducibility in an independent cohort of 13 patients with depression.Differences in functional connectivity were related to previously reported differences in clinical efficacy across a distributed set of cortical and limbic regions. Dorsolateral prefrontal cortex TMS sites with better clinical efficacy were more negatively correlated (anticorrelated) with the subgenual cingulate. Optimum connectivity-based stimulation coordinates were identified in Brodmann area 46. Results were reproducible in patients with depression.Reported antidepressant efficacy of different left DLPFC TMS sites is related to the anticorrelation of each site with the subgenual cingulate, potentially lending insight into the antidepressant mechanism of TMS and suggesting a role for intrinsically anticorrelated networks in depression. These results can be translated into a connectivity-based targeting strategy for focal brain stimulation that might be used to optimize clinical response.
View details for DOI 10.1016/j.biopsych.2012.04.028
View details for Web of Science ID 000308714000014
View details for PubMedID 22658708
Gender Modulates the APOE epsilon 4 Effect in Healthy Older Adults: Convergent Evidence from Functional Brain Connectivity and Spinal Fluid Tau Levels
JOURNAL OF NEUROSCIENCE
2012; 32 (24): 8254-8262
We examined whether the effect of the apolipoprotein E (APOE) genotype on functional brain connectivity is modulated by gender in healthy older human adults. Our results confirm significantly decreased connectivity in the default mode network in healthy older APOE ?4 carriers compared with ?3 homozygotes. More important, further testing revealed a significant interaction between APOE genotype and gender in the precuneus, a major default mode hub. Female ?4 carriers showed significantly reduced default mode connectivity compared with either female ?3 homozygotes or male ?4 carriers, whereas male ?4 carriers differed minimally from male ?3 homozygotes. An additional analysis in an independent sample of healthy elderly using an independent marker of Alzheimer's disease, i.e., spinal fluid levels of tau, provided corresponding evidence for this gender-by-APOE interaction. Together, these results converge with previous work showing a higher prevalence of the ?4 allele among women with Alzheimer's disease and, critically, demonstrate that this interaction between APOE genotype and gender is detectable in the preclinical period.
View details for DOI 10.1523/JNEUROSCI.0305-12.2012
View details for Web of Science ID 000305295600017
View details for PubMedID 22699906
Functional connectivity tracks clinical deterioration in Alzheimer's disease
NEUROBIOLOGY OF AGING
2012; 33 (4)
While resting state functional connectivity has been shown to decrease in patients with mild and/or moderate Alzheimer's disease, it is not yet known how functional connectivity changes in patients as the disease progresses. Furthermore, it has been noted that the default mode network is not as homogenous as previously assumed and several fractionations of the network have been proposed. Here, we separately investigated the modulation of 3 default mode subnetworks, as identified with group independent component analysis, by comparing Alzheimer's disease patients to healthy controls and by assessing connectivity changes over time. Our results showed decreased connectivity at baseline in patients versus controls in the posterior default mode network, and increased connectivity in the anterior and ventral default mode networks. At follow-up, functional connectivity decreased across all default mode systems in patients. Our results suggest that earlier in the disease, regions of the posterior default mode network start to disengage whereas regions within the anterior and ventral networks enhance their connectivity. However, as the disease progresses, connectivity within all systems eventually deteriorates.
View details for DOI 10.1016/j.neurobiolaging.2011.06.024
View details for Web of Science ID 000301506800029
View details for PubMedID 21840627
Decoding Subject-Driven Cognitive States with Whole-Brain Connectivity Patterns
2012; 22 (1): 158-165
Decoding specific cognitive states from brain activity constitutes a major goal of neuroscience. Previous studies of brain-state classification have focused largely on decoding brief, discrete events and have required the timing of these events to be known. To date, methods for decoding more continuous and purely subject-driven cognitive states have not been available. Here, we demonstrate that free-streaming subject-driven cognitive states can be decoded using a novel whole-brain functional connectivity analysis. Ninety functional regions of interest (ROIs) were defined across 14 large-scale resting-state brain networks to generate a 3960 cell matrix reflecting whole-brain connectivity. We trained a classifier to identify specific patterns of whole-brain connectivity as subjects rested quietly, remembered the events of their day, subtracted numbers, or (silently) sang lyrics. In a leave-one-out cross-validation, the classifier identified these 4 cognitive states with 84% accuracy. More critically, the classifier achieved 85% accuracy when identifying these states in a second, independent cohort of subjects. Classification accuracy remained high with imaging runs as short as 30-60 s. At all temporal intervals assessed, the 90 functionally defined ROIs outperformed a set of 112 commonly used structural ROIs in classifying cognitive states. This approach should enable decoding a myriad of subject-driven cognitive states from brief imaging data samples.
View details for DOI 10.1093/cercor/bhr099
View details for Web of Science ID 000298190500014
View details for PubMedID 21616982
Relationships between Beta-Amyloid and Functional Connectivity in Different Components of the Default Mode Network in Aging
2011; 21 (10): 2399-2407
Although beta-amyloid (Aβ) deposition is a characteristic feature of Alzheimer's disease (AD), this pathology is commonly found in elderly normal controls (NC). The pattern of Aβ deposition as detected with Pittsburgh compound-B positron emission tomography (PIB-PET) imaging shows substantial spatial overlap with the default mode network (DMN), a group of brain regions that typically deactivates during externally driven cognitive tasks. In this study, we show that DMN functional connectivity (FC) during rest is altered with increasing levels of PIB uptake in NC. Specifically, FC decreases were identified in regions implicated in episodic memory (EM) processing (posteromedial cortex, ventral medial prefrontal cortex, and angular gyrus), whereas connectivity increases were detected in dorsal and anterior medial prefrontal and lateral temporal cortices. This pattern of decreases is consistent with previous studies that suggest heightened vulnerability of EM-related brain regions in AD, whereas the observed increases in FC may reflect a compensatory response.
View details for DOI 10.1093/cercor/bhr025
View details for Web of Science ID 000294808800020
View details for PubMedID 21383234
Differential electrophysiological response during rest, self-referential, and non-self-referential tasks in human posteromedial cortex
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2011; 108 (7): 3023-3028
The electrophysiological basis for higher brain activity during rest and internally directed cognition within the human default mode network (DMN) remains largely unknown. Here we use intracranial recordings in the human posteromedial cortex (PMC), a core node within the DMN, during conditions of cued rest, autobiographical judgments, and arithmetic processing. We found a heterogeneous profile of PMC responses in functional, spatial, and temporal domains. Although the majority of PMC sites showed increased broad gamma band activity (30-180 Hz) during rest, some PMC sites, proximal to the retrosplenial cortex, responded selectively to autobiographical stimuli. However, no site responded to both conditions, even though they were located within the boundaries of the DMN identified with resting-state functional imaging and similarly deactivated during arithmetic processing. These findings, which provide electrophysiological evidence for heterogeneity within the core of the DMN, will have important implications for neuroimaging studies of the DMN.
View details for DOI 10.1073/pnas.1017098108
View details for Web of Science ID 000287377000073
View details for PubMedID 21282630
Breakdown of within- and between-network Resting State Functional Magnetic Resonance Imaging Connectivity during Propofol-induced Loss of Consciousness
2010; 113 (5): 1038-1053
Mechanisms of anesthesia-induced loss of consciousness remain poorly understood. Resting-state functional magnetic resonance imaging allows investigating whole-brain connectivity changes during pharmacological modulation of the level of consciousness.Low-frequency spontaneous blood oxygen level-dependent fluctuations were measured in 19 healthy volunteers during wakefulness, mild sedation, deep sedation with clinical unconsciousness, and subsequent recovery of consciousness.Propofol-induced decrease in consciousness linearly correlates with decreased corticocortical and thalamocortical connectivity in frontoparietal networks (i.e., default- and executive-control networks). Furthermore, during propofol-induced unconsciousness, a negative correlation was identified between thalamic and cortical activity in these networks. Finally, negative correlations between default network and lateral frontoparietal cortices activity, present during wakefulness, decreased proportionally to propofol-induced loss of consciousness. In contrast, connectivity was globally preserved in low-level sensory cortices, (i.e., in auditory and visual networks across sedation stages). This was paired with preserved thalamocortical connectivity in these networks. Rather, waning of consciousness was associated with a loss of cross-modal interactions between visual and auditory networks.Our results shed light on the functional significance of spontaneous brain activity fluctuations observed in functional magnetic resonance imaging. They suggest that propofol-induced unconsciousness could be linked to a breakdown of cerebral temporal architecture that modifies both within- and between-network connectivity and thus prevents communication between low-level sensory and higher-order frontoparietal cortices, thought to be necessary for perception of external stimuli. They emphasize the importance of thalamocortical connectivity in higher-order cognitive brain networks in the genesis of conscious perception.
View details for Web of Science ID 000283671300010
View details for PubMedID 20885292
Dissociable Connectivity within Human Angular Gyrus and Intraparietal Sulcus: Evidence from Functional and Structural Connectivity
2010; 20 (11): 2636-2646
The inferior parietal lobule (IPL) of the human brain is a heterogeneous region involved in visuospatial attention, memory, and mathematical cognition. Detailed description of connectivity profiles of subdivisions within the IPL is critical for accurate interpretation of functional neuroimaging studies involving this region. We separately examined functional and structural connectivity of the angular gyrus (AG) and the intraparietal sulcus (IPS) using probabilistic cytoarchitectonic maps. Regions-of-interest (ROIs) included anterior and posterior AG subregions (PGa, PGp) and 3 IPS subregions (hIP2, hIP1, and hIP3). Resting-state functional connectivity analyses showed that PGa was more strongly linked to basal ganglia, ventral premotor areas, and ventrolateral prefrontal cortex, while PGp was more strongly connected with ventromedial prefrontal cortex, posterior cingulate, and hippocampus-regions comprising the default mode network. The anterior-most IPS ROIs, hIP2 and hIP1, were linked with ventral premotor and middle frontal gyrus, while the posterior-most IPS ROI, hIP3, showed connectivity with extrastriate visual areas. In addition, hIP1 was connected with the insula. Tractography using diffusion tensor imaging revealed structural connectivity between most of these functionally connected regions. Our findings provide evidence for functional heterogeneity of cytoarchitectonically defined subdivisions within IPL and offer a novel framework for synthesis and interpretation of the task-related activations and deactivations involving the IPL during cognition.
View details for DOI 10.1093/cercor/bhq011
View details for Web of Science ID 000282750600013
View details for PubMedID 20154013
Development of functional and structural connectivity within the default mode network in young children
2010; 52 (1): 290-301
Functional and structural maturation of networks comprised of discrete regions is an important aspect of brain development. The default-mode network (DMN) is a prominent network which includes the posterior cingulate cortex (PCC), medial prefrontal cortex (mPFC), medial temporal lobes (MTL), and angular gyrus (AG). Despite increasing interest in DMN function, little is known about its maturation from childhood to adulthood. Here we examine developmental changes in DMN connectivity using a multimodal imaging approach by combining resting-state fMRI, voxel-based morphometry and diffusion tensor imaging-based tractography. We found that the DMN undergoes significant developmental changes in functional and structural connectivity, but these changes are not uniform across all DMN nodes. Convergent structural and functional connectivity analyses suggest that PCC-mPFC connectivity along the cingulum bundle is the most immature link in the DMN of children. Both PCC and mPFC also showed gray matter volume differences, as well as prominent macrostructural and microstructural differences in the dorsal cingulum bundle linking these regions. Notably, structural connectivity between PCC and left MTL was either weak or non-existent in children, even though functional connectivity did not differ from that of adults. These results imply that functional connectivity in children can reach adult-like levels despite weak structural connectivity. We propose that maturation of PCC-mPFC structural connectivity plays an important role in the development of self-related and social-cognitive functions that emerge during adolescence. More generally, our study demonstrates how quantitative multimodal analysis of anatomy and connectivity allows us to better characterize the heterogeneous development and maturation of brain networks.
View details for DOI 10.1016/j.neuroimage.2010.04.009
View details for Web of Science ID 000278637700029
View details for PubMedID 20385244
- Functional magnetic resonance imaging and estrogen effects on the brain: cautious interpretation of a BOLD finding MENOPAUSE-THE JOURNAL OF THE NORTH AMERICAN MENOPAUSE SOCIETY 2010; 17 (4): 669-671
Divergent network connectivity changes in behavioural variant frontotemporal dementia and Alzheimer's disease
2010; 133: 1352-1367
Resting-state or intrinsic connectivity network functional magnetic resonance imaging provides a new tool for mapping large-scale neural network function and dysfunction. Recently, we showed that behavioural variant frontotemporal dementia and Alzheimer's disease cause atrophy within two major networks, an anterior 'Salience Network' (atrophied in behavioural variant frontotemporal dementia) and a posterior 'Default Mode Network' (atrophied in Alzheimer's disease). These networks exhibit an anti-correlated relationship with each other in the healthy brain. The two diseases also feature divergent symptom-deficit profiles, with behavioural variant frontotemporal dementia undermining social-emotional function and preserving or enhancing visuospatial skills, and Alzheimer's disease showing the inverse pattern. We hypothesized that these disorders would exert opposing connectivity effects within the Salience Network (disrupted in behavioural variant frontotemporal dementia but enhanced in Alzheimer's disease) and the Default Mode Network (disrupted in Alzheimer's disease but enhanced in behavioural variant frontotemporal dementia). With task-free functional magnetic resonance imaging, we tested these ideas in behavioural variant frontotemporal dementia, Alzheimer's disease and healthy age-matched controls (n = 12 per group), using independent component analyses to generate group-level network contrasts. As predicted, behavioural variant frontotemporal dementia attenuated Salience Network connectivity, most notably in frontoinsular, cingulate, striatal, thalamic and brainstem nodes, but enhanced connectivity within the Default Mode Network. Alzheimer's disease, in contrast, reduced Default Mode Network connectivity to posterior hippocampus, medial cingulo-parieto-occipital regions and the dorsal raphe nucleus, but intensified Salience Network connectivity. Specific regions of connectivity disruption within each targeted network predicted intrinsic connectivity enhancement within the reciprocal network. In behavioural variant frontotemporal dementia, clinical severity correlated with loss of right frontoinsular Salience Network connectivity and with biparietal Default Mode Network connectivity enhancement. Based on these results, we explored whether a combined index of Salience Network and Default Mode Network connectivity might discriminate between the three groups. Linear discriminant analysis achieved 92% clinical classification accuracy, including 100% separation of behavioural variant frontotemporal dementia and Alzheimer's disease. Patients whose clinical diagnoses were supported by molecular imaging, genetics, or pathology showed 100% separation using this method, including four diagnostically equivocal 'test' patients not used to train the algorithm. Overall, the findings suggest that behavioural variant frontotemporal dementia and Alzheimer's disease lead to divergent network connectivity patterns, consistent with known reciprocal network interactions and the strength and deficit profiles of the two disorders. Further developed, intrinsic connectivity network signatures may provide simple, inexpensive, and non-invasive biomarkers for dementia differential diagnosis and disease monitoring.
View details for DOI 10.1093/brain/awq075
View details for Web of Science ID 000277225700015
View details for PubMedID 20410145
Episodic encephalopathy due to an occult spinal vascular malformation complicated by superficial siderosis
CLINICAL NEUROLOGY AND NEUROSURGERY
2010; 112 (1): 82-84
Superficial siderosis (SS) of the central nervous system is a rare condition caused by chronic subarachnoid hemorrhage. Clinical manifestations typically include sensorineural hearing loss and cerebellar ataxia. Recurrent episodic encephalopathy in the setting of SS has not been reported. We describe a unique case of SS in a 67-year-old man with an 8-year history of episodic encephalopathy associated with headache and vomiting. The patient also had a history of progressive dementia, ataxia, and myelopathy. A diagnosis of superficial siderosis was made after magnetic resonance gradient-echo images showed diffuse hemosiderin staining over the cerebellum and cerebral convexities. No intracerebral source of hemorrhage was identified. The patient therefore underwent gadolinium-enhanced spinal MRI which suggested a possible vascular malformation. A therapeutic laminectomy subsequently confirmed an arteriovenous fistula which was resected. In SS, there are often long delays between symptom onset and definitive diagnosis. Early identification is facilitated by magnetic resonance imaging with gradient-echo sequences. When no source of hemorrhage is identified intracranially, then total spinal cord imaging is indicated to assess for an occult source of hemorrhage as occurred in our case.
View details for DOI 10.1016/j.clineuro.2009.09.005
View details for Web of Science ID 000273933700017
View details for PubMedID 19857921
Default network connectivity reflects the level of consciousness in non-communicative brain-damaged patients
2010; 133: 161-171
The 'default network' is defined as a set of areas, encompassing posterior-cingulate/precuneus, anterior cingulate/mesiofrontal cortex and temporo-parietal junctions, that show more activity at rest than during attention-demanding tasks. Recent studies have shown that it is possible to reliably identify this network in the absence of any task, by resting state functional magnetic resonance imaging connectivity analyses in healthy volunteers. However, the functional significance of these spontaneous brain activity fluctuations remains unclear. The aim of this study was to test if the integrity of this resting-state connectivity pattern in the default network would differ in different pathological alterations of consciousness. Fourteen non-communicative brain-damaged patients and 14 healthy controls participated in the study. Connectivity was investigated using probabilistic independent component analysis, and an automated template-matching component selection approach. Connectivity in all default network areas was found to be negatively correlated with the degree of clinical consciousness impairment, ranging from healthy controls and locked-in syndrome to minimally conscious, vegetative then coma patients. Furthermore, precuneus connectivity was found to be significantly stronger in minimally conscious patients as compared with unconscious patients. Locked-in syndrome patient's default network connectivity was not significantly different from controls. Our results show that default network connectivity is decreased in severely brain-damaged patients, in proportion to their degree of consciousness impairment. Future prospective studies in a larger patient population are needed in order to evaluate the prognostic value of the presented methodology.
View details for DOI 10.1093/brain/awp313
View details for Web of Science ID 000273492800014
View details for PubMedID 20034928
Clinical applications of resting state functional connectivity.
Frontiers in systems neuroscience
2010; 4: 19-?
During resting conditions the brain remains functionally and metabolically active. One manifestation of this activity that has become an important research tool is spontaneous fluctuations in the blood oxygen level-dependent (BOLD) signal of functional magnetic resonance imaging (fMRI). The identification of correlation patterns in these spontaneous fluctuations has been termed resting state functional connectivity (fcMRI) and has the potential to greatly increase the translation of fMRI into clinical care. In this article we review the advantages of the resting state signal for clinical applications including detailed discussion of signal to noise considerations. We include guidelines for performing resting state research on clinical populations, outline the different areas for clinical application, and identify important barriers to be addressed to facilitate the translation of resting state fcMRI into the clinical realm.
View details for DOI 10.3389/fnsys.2010.00019
View details for PubMedID 20592951
Disrupted Amygdalar Subregion Functional Connectivity and Evidence of a Compensatory Network in Generalized Anxiety Disorder
ARCHIVES OF GENERAL PSYCHIATRY
2009; 66 (12): 1361-1372
Little is known about the neural abnormalities underlying generalized anxiety disorder (GAD). Studies in other anxiety disorders have implicated the amygdala, but work in GAD has yielded conflicting results. The amygdala is composed of distinct subregions that interact with dissociable brain networks, which have been studied only in experimental animals. A functional connectivity approach at the subregional level may therefore yield novel insights into GAD.To determine whether distinct connectivity patterns can be reliably identified for the basolateral (BLA) and centromedial (CMA) subregions of the human amygdala, and to examine subregional connectivity patterns and potential compensatory amygdalar connectivity in GAD.Cross-sectional study.Academic medical center.Two cohorts of healthy control subjects (consisting of 17 and 31 subjects) and 16 patients with GAD.Functional connectivity with cytoarchitectonically determined BLA and CMA regions of interest, measured during functional magnetic resonance imaging performed while subjects were resting quietly in the scanner. Amygdalar gray matter volume was also investigated with voxel-based morphometry.Reproducible subregional differences in large-scale connectivity were identified in both cohorts of healthy controls. The BLA was differentially connected with primary and higher-order sensory and medial prefrontal cortices. The CMA was connected with the midbrain, thalamus, and cerebellum. In GAD patients, BLA and CMA connectivity patterns were significantly less distinct, and increased gray matter volume was noted primarily in the CMA. Across the subregions, GAD patients had increased connectivity with a previously characterized frontoparietal executive control network and decreased connectivity with an insula- and cingulate-based salience network.Our findings provide new insights into the functional neuroanatomy of the human amygdala and converge with connectivity studies in experimental animals. In GAD, we find evidence of an intra-amygdalar abnormality and engagement of a compensatory frontoparietal executive control network, consistent with cognitive theories of GAD.
View details for Web of Science ID 000272494700011
View details for PubMedID 19996041
Greater than the sum of its parts: a review of studies combining structural connectivity and resting-state functional connectivity
BRAIN STRUCTURE & FUNCTION
2009; 213 (6): 525-533
It is commonly assumed that functional brain connectivity reflects structural brain connectivity. The exact relationship between structure and function, however, might not be straightforward. In this review we aim to examine how our understanding of the relationship between structure and function in the 'resting' brain has advanced over the last several years. We discuss eight articles that directly compare resting-state functional connectivity with structural connectivity and three clinical case studies of patients with limited white matter connections between the cerebral hemispheres. All studies examined show largely convergent results: the strength of resting-state functional connectivity is positively correlated with structural connectivity strength. However, functional connectivity is also observed between regions where there is little or no structural connectivity, which most likely indicates functional correlations mediated by indirect structural connections (i.e. via a third region). As the methodologies for measuring structural and functional connectivity continue to improve and their complementary strengths are applied in parallel, we can expect important advances in our diagnostic and prognostic capacities in diseases like Alzheimer's, multiple sclerosis, and stroke.
View details for DOI 10.1007/s00429-009-0208-6
View details for Web of Science ID 000270437600004
View details for PubMedID 19565262
Distinct Cerebellar Contributions to Intrinsic Connectivity Networks
JOURNAL OF NEUROSCIENCE
2009; 29 (26): 8586-8594
Convergent data from various scientific approaches strongly implicate cerebellar systems in nonmotor functions. The functional anatomy of these systems has been pieced together from disparate sources, such as animal studies, lesion studies in humans, and structural and functional imaging studies in humans. To better define this distinct functional anatomy, in the current study we delineate the role of the cerebellum in several nonmotor systems simultaneously and in the same subjects using resting state functional connectivity MRI. Independent component analysis was applied to resting state data from two independent datasets to identify common cerebellar contributions to several previously identified intrinsic connectivity networks (ICNs) involved in executive control, episodic memory/self-reflection, salience detection, and sensorimotor function. We found distinct cerebellar contributions to each of these ICNs. The neocerebellum participates in (1) the right and left executive control networks (especially crus I and II), (2) the salience network (lobule VI), and (3) the default-mode network (lobule IX). Little to no overlap was detected between these cerebellar regions and the sensorimotor cerebellum (lobules V-VI). Clusters were also located in pontine and dentate nuclei, prominent points of convergence for cerebellar input and output, respectively. The results suggest that the most phylogenetically recent part of the cerebellum, particularly crus I and II, make contributions to parallel cortico-cerebellar loops involved in executive control, salience detection, and episodic memory/self-reflection. The largest portions of the neocerebellum take part in the executive control network implicated in higher cognitive functions such as working memory.
View details for DOI 10.1523/JNEUROSCI.1868-09.2009
View details for Web of Science ID 000267613400030
View details for PubMedID 19571149
Neurodegenerative Diseases Target Large-Scale Human Brain Networks
2009; 62 (1): 42-52
During development, the healthy human brain constructs a host of large-scale, distributed, function-critical neural networks. Neurodegenerative diseases have been thought to target these systems, but this hypothesis has not been systematically tested in living humans. We used network-sensitive neuroimaging methods to show that five different neurodegenerative syndromes cause circumscribed atrophy within five distinct, healthy, human intrinsic functional connectivity networks. We further discovered a direct link between intrinsic connectivity and gray matter structure. Across healthy individuals, nodes within each functional network exhibited tightly correlated gray matter volumes. The findings suggest that human neural networks can be defined by synchronous baseline activity, a unified corticotrophic fate, and selective vulnerability to neurodegenerative illness. Future studies may clarify how these complex systems are assembled during development and undermined by disease.
View details for DOI 10.1016/j.neuron.2009.03.024
View details for Web of Science ID 000265346700008
View details for PubMedID 19376066
Resting-State Functional Connectivity Reflects Structural Connectivity in the Default Mode Network
2009; 19 (1): 72-78
Resting-state functional connectivity magnetic resonance imaging (fcMRI) studies constitute a growing proportion of functional brain imaging publications. This approach detects temporal correlations in spontaneous blood oxygen level-dependent (BOLD) signal oscillations while subjects rest quietly in the scanner. Although distinct resting-state networks related to vision, language, executive processing, and other sensory and cognitive domains have been identified, considerable skepticism remains as to whether resting-state functional connectivity maps reflect neural connectivity or simply track BOLD signal correlations driven by nonneural artifact. Here we combine diffusion tensor imaging (DTI) tractography with resting-state fcMRI to test the hypothesis that resting-state functional connectivity reflects structural connectivity. These 2 modalities were used to investigate connectivity within the default mode network, a set of brain regions--including medial prefrontal cortex (MPFC), medial temporal lobes (MTLs), and posterior cingulate cortex (PCC)/retropslenial cortex (RSC)--implicated in episodic memory processing. Using seed regions from the functional connectivity maps, the DTI analysis revealed robust structural connections between the MTLs and the retrosplenial cortex whereas tracts from the MPFC contacted the PCC (just rostral to the RSC). The results demonstrate that resting-state functional connectivity reflects structural connectivity and that combining modalities can enrich our understanding of these canonical brain networks.
View details for DOI 10.1093/cercor/bhn059
View details for Web of Science ID 000261679400007
View details for PubMedID 18403396
Resting-state functional connectivity in neuropsychiatric disorders
CURRENT OPINION IN NEUROLOGY
2008; 21 (4): 424-430
This review considers recent advances in the application of resting-state functional magnetic resonance imaging to the study of neuropsychiatric disorders.Resting-state functional magnetic resonance imaging is a relatively novel technique that has several potential advantages over task-activation functional magnetic resonance imaging in terms of its clinical applicability. A number of research groups have begun to investigate the use of resting-state functional magnetic resonance imaging in a variety of neuropsychiatric disorders including Alzheimer's disease, depression, and schizophrenia. Although preliminary results have been fairly consistent in some disorders (for example, Alzheimer's disease) they have been less reproducible in others (schizophrenia). Resting-state connectivity has been shown to correlate with behavioral performance and emotional measures. It's potential as a biomarker of disease and an early objective marker of treatment response is genuine but still to be realized.Resting-state functional magnetic resonance imaging has made some strides in the clinical realm but significant advances are required before it can be used in a meaningful way at the single-patient level.
View details for Web of Science ID 000257823200006
View details for PubMedID 18607202
Default-mode function and task-induced deactivation have overlapping brain substrates in children
2008; 41 (4): 1493-1503
The regions that comprise the functionally connected resting-state default-mode network (DMN) in adults appear to be the same as those that are characterized by task-induced decreases in blood-oxygen-level-dependent (BOLD) signal. Independent component analysis can be used to produce a picture of the DMN as an individual rests quietly in the scanner. Contrasts across conditions in which cognitive load is parametrically modulated can delineate neural structures that have decreases in activation in response to high-demand task conditions. Examination of the degree to which these networks subsume dissociable brain substrates, and of the degree to which they overlap, provides insight concerning their purpose, function, and the nature of their associations. Few studies have examined the DMN in children, and none have tested whether the neural regions that comprise the DMN during a resting condition are the same regions that show reduced activity when children engage in cognitive tasks. In this paper we describe regions that show both task-related decreases and spontaneous intrinsic activity at rest in children, and we examine the co-localization of these networks. We describe ways in which the DMN in 7-12-year-old children is both similar to and different from the DMN in adults; moreover, we document that task-induced deactivations and default-mode resting-state activity in children share common neural substrates. It appears, therefore, that even before adolescence a core aspect of task-induced deactivation involves reallocating processing resources that are active at rest. We describe how future studies assessing the development of these systems would benefit from examining these constructs as part of one continuous system.
View details for DOI 10.1016/j.neuroimage.2008.03.029
View details for Web of Science ID 000256620400029
View details for PubMedID 18482851
Persistent default-mode network connectivity during light sedation
HUMAN BRAIN MAPPING
2008; 29 (7): 839-847
The default-mode network (DMN) is a set of specific brain regions whose activity, predominant in the resting-state, is attenuated during cognitively demanding, externally-cued tasks. The cognitive correlates of this network have proven difficult to interrogate, but one hypothesis is that regions in the network process episodic memories and semantic knowledge integral to internally-generated mental activity. Here, we compare default-mode functional connectivity in the same group of subjects during rest and conscious sedation with midazolam, a state characterized by anterograde amnesia and a reduced level of consciousness. Although the DMN showed functional connectivity during both rest and conscious sedation, a direct comparison found that there was significantly reduced functional connectivity in the posterior cingulate cortex during conscious sedation. These results confirm that low-frequency oscillations in the DMN persist and remain highly correlated even at reduced levels of consciousness. We hypothesize that focal reductions in DMN connectivity, as shown here in the posterior cingulate cortex, may represent a stable correlate of reduced consciousness.
View details for DOI 10.1002/hbm.20537
View details for Web of Science ID 000256674400012
View details for PubMedID 18219620
A cross-modal system linking primary auditory and visual cortices: Evidence from intrinsic fMRI connectivity analysis
HUMAN BRAIN MAPPING
2008; 29 (7): 848-857
Recent anatomical and electrophysiological evidence in primates indicates the presence of direct connections between primary auditory and primary visual cortex that constitute cross-modal systems. We examined the intrinsic functional connectivity (fcMRI) of putative primary auditory cortex in 32 young adults during resting state scanning. We found that the medial Heschl's gyrus was strongly coupled, in particular, to visual cortex along the anterior banks of the calcarine fissure. This observation was confirmed using novel group-level, tensor-based independent components analysis. fcMRI analysis revealed that although overall coupling between the auditory and visual cortex was significantly reduced when subjects performed a visual perception task, coupling between the anterior calcarine cortex and auditory cortex was not disrupted. These results suggest that primary auditory cortex has a functionally distinct relationship with the anterior visual cortex, which is known to represent the peripheral visual field. Our study provides novel, fcMRI-based, support for a neural system involving low-level auditory and visual cortices.
View details for DOI 10.1002/hbm.20560
View details for Web of Science ID 000256674400013
View details for PubMedID 18412133
Network analysis of intrinsic functional brain connectivity in Alzheimer's disease
PLOS COMPUTATIONAL BIOLOGY
2008; 4 (6)
Functional brain networks detected in task-free ("resting-state") functional magnetic resonance imaging (fMRI) have a small-world architecture that reflects a robust functional organization of the brain. Here, we examined whether this functional organization is disrupted in Alzheimer's disease (AD). Task-free fMRI data from 21 AD subjects and 18 age-matched controls were obtained. Wavelet analysis was applied to the fMRI data to compute frequency-dependent correlation matrices. Correlation matrices were thresholded to create 90-node undirected-graphs of functional brain networks. Small-world metrics (characteristic path length and clustering coefficient) were computed using graph analytical methods. In the low frequency interval 0.01 to 0.05 Hz, functional brain networks in controls showed small-world organization of brain activity, characterized by a high clustering coefficient and a low characteristic path length. In contrast, functional brain networks in AD showed loss of small-world properties, characterized by a significantly lower clustering coefficient (p<0.01), indicative of disrupted local connectivity. Clustering coefficients for the left and right hippocampus were significantly lower (p<0.01) in the AD group compared to the control group. Furthermore, the clustering coefficient distinguished AD participants from the controls with a sensitivity of 72% and specificity of 78%. Our study provides new evidence that there is disrupted organization of functional brain networks in AD. Small-world metrics can characterize the functional organization of the brain in AD, and our findings further suggest that these network measures may be useful as an imaging-based biomarker to distinguish AD from healthy aging.
View details for DOI 10.1371/journal.pcbi.1000100
View details for Web of Science ID 000259786700013
View details for PubMedID 18584043
Divergent social functioning in behavioral variant frontotemporal dementia and Alzheimer disease: Reciprocal networks and neuronal evolution
ALZHEIMER DISEASE & ASSOCIATED DISORDERS
2007; 21 (4): S50-S57
Behavioral variant frontotemporal dementia (bvFTD) disrupts our most human social and emotional functions. Early in the disease, patients show focal anterior cingulate cortex (ACC) and orbital frontoinsula (FI) degeneration, accentuated in the right hemisphere. The ACC and FI, though sometimes considered ancient in phylogeny, feature a large bipolar projection neuron, the von Economo neuron (VEN), which is found only in humans, apes, and selected whales-all large-brained mammals with complex social structures. In contrast to bvFTD, Alzheimer disease (AD) often spares social functioning, and the ACC and FI, until late in its course, damaging instead a posterior hippocampal-cingulo-temporal-parietal network involved in episodic memory retrieval. These divergent patterns of functional and regional impairment remain mysterious despite extensive molecular-level characterization of bvFTD and AD. In this report, we further develop the hypothesis that VENs drive the regional vulnerability pattern seen in bvFTD, citing recent evidence from functional imaging in healthy humans, and also structural imaging and quantitative neuropathology data from bvFTD and AD. Our most recent findings suggest that bvFTD and AD target distinct, anticorrelated intrinsic connectivity networks and that bvFTD-related VEN injury occurs throughout the ACC-FI network. We suggest that the regional and neuronal vulnerability patterns seen in bvFTD and AD underlie the divergent impact of these disorders on recently evolved social-emotional functions.
View details for Web of Science ID 000251536500016
View details for PubMedID 18090425
Resting-state functional connectivity in major depression: Abnormally increased contributions from subgenual cingulate cortex and thalamus
2007; 62 (5): 429-437
Positron emission tomography (PET) studies of major depression have revealed resting-state abnormalities in the prefrontal and cingulate cortices. Recently, fMRI has been adapted to examine connectivity within a specific resting-state neural network--the default-mode network--that includes medial prefrontal and anterior cingulate cortices. The goal of this study was to examine resting-state, default-mode network functional connectivity in subjects with major depression and in healthy controls.Twenty-eight subjects with major depression and 20 healthy controls underwent 5-min fMRI scans while resting quietly. Independent component analysis was used to isolate the default-mode network in each subject. Group maps of the default-mode network were compared. A within-group analysis was performed in the depressed group to explore effects of depression refractoriness on functional connectivity.Resting-state subgenual cingulate and thalamic functional connectivity with the default-mode network were significantly greater in the depressed subjects. Within the depressed group, the length of the current depressive episode correlated positively with functional connectivity in the subgenual cingulate.This is the first study to explore default-mode functional connectivity in major depression. The findings provide cross-modality confirmation of PET studies demonstrating increased thalamic and subgenual cingulate activity in major depression. Further, the within-subject connectivity analysis employed here brings these previously isolated regions of hypermetabolism into the context of a disordered neural network. The correlation between refractoriness and subgenual cingulate functional connectivity within the network suggests that a quantitative, resting-state fMRI measure could be used to guide therapy in individual subjects.
View details for DOI 10.1016/j.biopsych.2006.09.020
View details for Web of Science ID 000249042800009
View details for PubMedID 17210143
Dissociable intrinsic connectivity networks for salience processing and executive control
JOURNAL OF NEUROSCIENCE
2007; 27 (9): 2349-2356
Variations in neural circuitry, inherited or acquired, may underlie important individual differences in thought, feeling, and action patterns. Here, we used task-free connectivity analyses to isolate and characterize two distinct networks typically coactivated during functional MRI tasks. We identified a "salience network," anchored by dorsal anterior cingulate (dACC) and orbital frontoinsular cortices with robust connectivity to subcortical and limbic structures, and an "executive-control network" that links dorsolateral frontal and parietal neocortices. These intrinsic connectivity networks showed dissociable correlations with functions measured outside the scanner. Prescan anxiety ratings correlated with intrinsic functional connectivity of the dACC node of the salience network, but with no region in the executive-control network, whereas executive task performance correlated with lateral parietal nodes of the executive-control network, but with no region in the salience network. Our findings suggest that task-free analysis of intrinsic connectivity networks may help elucidate the neural architectures that support fundamental aspects of human behavior.
View details for DOI 10.1523/JNEUROSCI.5587-06.2007
View details for Web of Science ID 000244758500023
View details for PubMedID 17329432
Prospects for prediction - Ethics analysis of neuroimaging in Alzheimer's disease
IMAGING AND THE AGING BRAIN
2007; 1097: 278-295
This article focuses on the prospects and ethics of using neuroimaging to predict Alzheimer's disease (AD). It is motivated by consideration of the historical roles of science in medicine and society, and considerations specifically contemporary of capabilities in imaging and aging, and the benefits and hope they bring. A general consensus is that combinations of imaging methods will ultimately be most fruitful in predicting disease. Their roll-out into translational practice will not be free of complexity, however, as culture and values differ in terms of what defines benefit and risk, who will benefit and who is at risk, what methods must be in place to assure the maximum safety, comfort, and protection of subjects and patients, and educational and policy needs. Proactive planning for the ethical and societal implications of predicting diseases of the aging brain is critical and will benefit all stakeholders-researchers, patients and families, health care providers, and policy makers.
View details for DOI 10.1196/annals.1379.030
View details for Web of Science ID 000245814800025
View details for PubMedID 17413029
Non-fluent progressive aphasia, depression, and OCD in a woman with progressive supranuclear palsy: Neuroanatomical and neuropathological correlations
2006; 12 (6): 332-338
This paper details the case of a 64-year-old woman who presented to the psychiatry service with worsening mood in the context of a diagnosis of obsessive-compulsive disorder (OCD). On further examination she was found to have clinical findings consistent with frontotemporal lobar degeneration of the non-fluent progressive aphasia subtype. At post-mortem she was found to have progressive supranuclear palsy. We argue, in retrospect, that her OCD was likely prodromal to the development of her dementia. This case highlights the fact that frontotemporal lobar degeneration/progressive supranuclear palsy (FTLD/PSP) and other "tauopathies" represent a complex group of neurodegenerative disorders that may masquerade for many years as refractory psychiatric disorders.
View details for DOI 10.1080/13554790601125957
View details for Web of Science ID 000242985900003
View details for PubMedID 17182396
Default-mode activity during a passive sensory task: Uncoupled from deactivation but impacting activation
JOURNAL OF COGNITIVE NEUROSCIENCE
2004; 16 (9): 1484-1492
Deactivation refers to increased neural activity during low-demand tasks or rest compared with high-demand tasks. Several groups have reported that a particular set of brain regions, including the posterior cingulate cortex and the medial prefrontal cortex, among others, is consistently deactivated. Taken together, these typically deactivated brain regions appear to constitute a default-mode network of brain activity that predominates in the absence of a demanding external task. Examining a passive, block-design sensory task with a standard deactivation analysis (rest epochs vs. stimulus epochs), we demonstrate that the default-mode network is undetectable in one run and only partially detectable in a second run. Using independent component analysis, however, we were able to detect the full default-mode network in both runs and to demonstrate that, in the majority of subjects, it persisted across both rest and stimulus epochs, uncoupled from the task waveform, and so mostly undetectable as deactivation. We also replicate an earlier finding that the default-mode network includes the hippocampus suggesting that episodic memory is incorporated in default-mode cognitive processing. Furthermore, we show that the more a subject's default-mode activity was correlated with the rest epochs (and "deactivated" during stimulus epochs), the greater that subject's activation to the visual and auditory stimuli. We conclude that activity in the default-mode network may persist through both experimental and rest epochs if the experiment is not sufficiently challenging. Time-series analysis of default-mode activity provides a measure of the degree to which a task engages a subject and whether it is sufficient to interrupt the processes--presumably cognitive, internally generated, and involving episodic memory--mediated by the default-mode network.
View details for Web of Science ID 000225712000003
View details for PubMedID 15601513
Reduced basal forebrain and hippocampal activation during memory encoding in girls with fragile X syndrome
2004; 15 (10): 1579-1583
Fragile X syndrome (FraX), the most common heritable cause of developmental disability, is associated with IQ, memory, and visuospatial processing deficits. The fragile X gene (FMR1) is prominently transcribed in two regions critical to memory encoding and attention: the hippocampus and the basal forebrain. To probe functional MRI activation abnormalities associated with the disorder, girls with FraX and age-matched, normally-developing girls were scanned during a test of visual memory encoding. While there were considerable similarities in activation patterns between the two groups, the girls with FraX showed significantly less activation in the hippocampus and the basal forebrain. This is the first study, to our knowledge, demonstrating functional deficits in FraX subjects in brain regions known to have the highest FMR1 transcription.
View details for DOI 10.1097/01.wnr.0000134472.44362.be
View details for Web of Science ID 000225140700010
View details for PubMedID 15232287
Default-mode network activity distinguishes Alzheimer's disease from healthy aging: Evidence from functional MRI
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2004; 101 (13): 4637-4642
Recent functional imaging studies have revealed coactivation in a distributed network of cortical regions that characterizes the resting state, or default mode, of the human brain. Among the brain regions implicated in this network, several, including the posterior cingulate cortex and inferior parietal lobes, have also shown decreased metabolism early in the course of Alzheimer's disease (AD). We reasoned that default-mode network activity might therefore be abnormal in AD. To test this hypothesis, we used independent component analysis to isolate the network in a group of 13 subjects with mild AD and in a group of 13 age-matched elderly controls as they performed a simple sensory-motor processing task. Three important findings are reported. Prominent coactivation of the hippocampus, detected in all groups, suggests that the default-mode network is closely involved with episodic memory processing. The AD group showed decreased resting-state activity in the posterior cingulate and hippocampus, suggesting that disrupted connectivity between these two regions accounts for the posterior cingulate hypometabolism commonly detected in positron emission tomography studies of early AD. Finally, a goodness-of-fit analysis applied at the individual subject level suggests that activity in the default-mode network may ultimately prove a sensitive and specific biomarker for incipient AD.
View details for DOI 10.1073/pnas.0308627101
View details for Web of Science ID 000220648700056
View details for PubMedID 15070770
Blockade of central cholinergic receptors impairs new learning and increases proactive interference in a word paired-associate memory task
2004; 118 (1): 223-236
Experimental data and computational models suggest that blockade of muscarinic cholinergic receptors impairs paired-associate learning and increases proactive interference (E. DeRosa & M. E. Hasselmo, 2000; M. E. Hasselmo & J. M. Bower, 1993). The results presented here provide evidence in humans supporting these hypotheses. Young healthy subjects first learned baseline word pairs (A-B) and, after a delay, learned additional overlapping (A-C) and nonoverlapping (D-E) word pairs. As predicted, when compared with subjects who received the active placebo glycopyrrolate (4 microg/kg) and subjects who were not injected, those who received scopolamine (8 microg/kg) showed (a) overall impairment in new word paired-associate learning, but no impairment in cued recall of previously learned associates; and (b) greater impairment in learning overlapping (A-C) compared with nonoverlapping (D-E) paired associates.
View details for DOI 10.1037/0735-7044.118.1.223
View details for Web of Science ID 000188981400023
View details for PubMedID 14979800
Humor modulates the mesolimbic reward centers
2003; 40 (5): 1041-1048
Humor plays an essential role in many facets of human life including psychological, social, and somatic functioning. Recently, neuroimaging has been applied to this critical human attribute, shedding light on the affective, cognitive, and motor networks involved in humor processing. To date, however, researchers have failed to demonstrate the subcortical correlates of the most fundamental feature of humor-reward. In an effort to elucidate the neurobiological substrate that subserves the reward components of humor, we undertook a high-field (3 Tesla) event-related functional MRI study. Here we demonstrate that humor modulates activity in several cortical regions, and we present new evidence that humor engages a network of subcortical regions including the nucleus accumbens, a key component of the mesolimbic dopaminergic reward system. Further, the degree of humor intensity was positively correlated with BOLD signal intensity in these regions. Together, these findings offer new insight into the neural basis of salutary aspects of humor.
View details for Web of Science ID 000187042200020
View details for PubMedID 14659102
Comparison of fMRI activation at 3 and 1.5 T during perceptual, cognitive, and affective processing
2003; 18 (4): 813-826
Previous studies comparing fMRI data acquired at 1.5 T and higher field strengths have focused on examining signal increases in the visual and motor cortices. No information is, however, available on the relative gain, or the comparability of data, obtained at higher field strengths for other brain regions such as the prefrontal and other association cortices. In the present study, we investigated fMRI activation at 1.5 and 3 T during visual perception, visuospatial working memory, and affect-processing tasks. A 23% increase in striate and extrastriate activation volume was observed at 3 T compared with that for 1.5 T during the visual perception task. During the working memory task significant increases in activation volume were observed in frontal and parietal association cortices as well as subcortical structures, including the caudate, globus pallidus, putamen, and thalamus. Increases in working memory-related activation volume of 82, 73, 83, and 36% were observed in the left frontal, right frontal, left parietal, and right parietal lobes, respectively, for 3 T compared with 1.5 T. These increases were characterized by increased activation at 3 T in several prefrontal and parietal cortex regions that showed activation at 1.5 T. More importantly, at 3 T, activation was detected in several regions, such as the ventral aspects of the inferior frontal gyrus, orbitofrontal gyrus, and lingual gyrus, which did not show significant activation at 1.5 T. No difference in height or extent of activation was detected between the two scanners in the amygdala during affect processing. Signal dropout in the amygdala from susceptibility artifact was greater at 3 T, with a 12% dropout at 3 T compared with a 9% dropout at 1.5 T. The spatial smoothness of T2* images was greater at 3 T by less than 1 mm, suggesting that the greater extent of activation at 3 T beyond these spatial scales was not due primarily to increased intrinsic spatial correlations at 3 T. Rather, the increase in percentage of voxels activated reflects increased sensitivity for detection of brain activation at higher field strength. In summary, our findings suggest that functional imaging of prefrontal and other association cortices can benefit significantly from higher magnetic field strength.
View details for DOI 10.1016/S1053-8119(03)00002-8
View details for Web of Science ID 000182606000001
View details for PubMedID 12725758
Neuroimaging in developmental disorders
CURRENT OPINION IN NEUROLOGY
2003; 16 (2): 143-146
This review considers the role of neuroimaging in developmental disorders by highlighting recent studies in two distinct, but overlapping, developmental disorders: autism and fragile X syndrome.After a decade of conflicting results in neuroimaging studies of autism, recent studies have provided some convergent data. One well-replicated finding is that autistic subjects have larger brains. Further, this enlargement, present as early as 3 years of age, appears to represent accelerated growth in infancy and may be followed by slowed growth in late childhood. Other findings are discussed but considered preliminary in the absence of converging evidence or replication studies. Recent work in fragile X syndrome suggests aberrant fronto-striatal and fronto-parietal networks and relates these abnormalities "forward" to behavior and "backward" to decreased protein expression.As the field of neuroimaging has matured, it has revealed its promise as a safe, reliable, in-vivo tool in the study of developmental disorders. By insisting on larger, more homogeneous patient groups and longitudinal rather than cross-sectional studies, the field is poised to fulfill its ultimate role of linking defects in molecular biology to aberrant behavior.
View details for DOI 10.1097/01.wco.0000063763.15877.d2
View details for Web of Science ID 000182542200004
View details for PubMedID 12644740
Functional connectivity in the resting brain: A network analysis of the default mode hypothesis
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
2003; 100 (1): 253-258
Functional imaging studies have shown that certain brain regions, including posterior cingulate cortex (PCC) and ventral anterior cingulate cortex (vACC), consistently show greater activity during resting states than during cognitive tasks. This finding led to the hypothesis that these regions constitute a network supporting a default mode of brain function. In this study, we investigate three questions pertaining to this hypothesis: Does such a resting-state network exist in the human brain? Is it modulated during simple sensory processing? How is it modulated during cognitive processing? To address these questions, we defined PCC and vACC regions that showed decreased activity during a cognitive (working memory) task, then examined their functional connectivity during rest. PCC was strongly coupled with vACC and several other brain regions implicated in the default mode network. Next, we examined the functional connectivity of PCC and vACC during a visual processing task and show that the resultant connectivity maps are virtually identical to those obtained during rest. Last, we defined three lateral prefrontal regions showing increased activity during the cognitive task and examined their resting-state connectivity. We report significant inverse correlations among all three lateral prefrontal regions and PCC, suggesting a mechanism for attenuation of default mode network activity during cognitive processing. This study constitutes, to our knowledge, the first resting-state connectivity analysis of the default mode and provides the most compelling evidence to date for the existence of a cohesive default mode network. Our findings also provide insight into how this network is modulated by task demands and what functions it might subserve.
View details for DOI 10.1073/pnas.0135058100
View details for Web of Science ID 000180307100046
View details for PubMedID 12506194
Regional analysis of hippocampal activation during memory encoding and retrieval: fMRI study
2003; 13 (1): 164-174
Investigators have recently begun to examine the differential role of subregions of the hippocampus in episodic memory. Two distinct models have gained prominence in the field. One model, outlined by Moser and Moser (Hippocampus 1998;8:608-619), based mainly on animal studies, has proposed that episodic memory is subserved by the posterior two-thirds of the hippocampus alone. A second model, derived by Lepage et al. (Hippocampus 1998;8:313-322) from their review of 52 PET studies, has suggested that the anterior hippocampus is activated by memory encoding while the posterior hippocampus is activated by memory retrieval. Functional magnetic resonance imaging (fMRI) studies have tended to show limited activation in the anteriormost regions of the hippocampus, providing support for the Moser and Moser model. A potential confounding factor in these fMRI studies, however, is that susceptibility artifact may differentially reduce signal in the anterior versus the posterior hippocampus. In the present study, we examined activation differences between hippocampal subregions during encoding and retrieval of words and interpreted our findings within the context of these two models. We also examined the extent to which susceptibility artifact affects the analysis and interpretation of hippocampal activation by demonstrating its differential effect on the anterior versus the posterior hippocampus. Both voxel-by-voxel and region-of-interest analyses were conducted, allowing us to quantify differences between the anterior and posterior aspects of the hippocampus. We detected significant hippocampal activation in both the encoding and retrieval conditions. Our data do not provide evidence for regional anatomic differences in activation between encoding and retrieval. The data do suggest that, even after accounting for susceptibility artifact, both encoding and retrieval of verbal stimuli activate the middle and posterior hippocampus more strongly than the anterior hippocampus. Finally, this study is the first to quantify the effects of susceptibility-induced signal loss on hippocampal activation and suggests that this artifact has significantly biased the interpretation of earlier fMRI studies.
View details for DOI 10.1002/hipo.10064
View details for Web of Science ID 000181005800014
View details for PubMedID 12625466
Presenile dementia syndromes: an update on taxonomy and diagnosis
JOURNAL OF NEUROLOGY NEUROSURGERY AND PSYCHIATRY
2002; 72 (6): 691-700
The four major degenerative dementias that often begin in presenescence: are reviewed. These are Alzheimer's disease, frontotemporal dementia, dementia with Lewy bodies, and Creutzfeldt-Jakob disease. Their epidemiological, genetic, and clinical features are reviewed, and controversies in taxonomy arising from recent discoveries described. Particular attention is given to the pathological role of protein aggregation, which appears to be a factor in each disease.
View details for Web of Science ID 000175891300005
View details for PubMedID 12023408