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Jesse A. Brown

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13 papers

1 author row

YNICL Journal 2023 Journal Article

Increasing empathic concern relates to salience network hyperconnectivity in cognitively healthy older adults with elevated amyloid-β burden

Tiffany E. Chow
Christina R. Veziris
Renaud La Joie
Alex J. Lee
Jesse A. Brown
Jennifer S. Yokoyama
Katherine P. Rankin
Joel H. Kramer

Enhanced emotional empathy, the ability to share others' affective experiences, can be a feature of Alzheimer's disease (AD), but whether emotional empathy increases in the preclinical phase of the disease is unknown. We measured emotional empathy over time (range = 0 - 7.3 years, mean = 2.4 years) in 86 older adults during a period in which they were cognitively healthy, functionally normal, and free of dementia symptoms. For each participant, we computed longitudinal trajectories for empathic concern (i.e., an other-oriented form of emotional empathy that promotes prosocial actions) and emotional contagion (i.e., a self-focused form of emotional empathy often accompanied by feelings of distress) from informant ratings of participants' empathy on the Interpersonal Reactivity Index. Amyloid-β (Aβ) positron emission tomography (PET) scans were used to classify participants as either Aβ positive (Aβ+, n = 23) or negative (Aβ-, n = 63) based on Aβ-PET cortical binding. Participants also underwent structural and task-free functional magnetic resonance imaging approximately two years on average after their last empathy assessment, at which time most participants remained cognitively healthy. Results indicated that empathic concern, but not emotional contagion, increased more over time in Aβ+ participants than in Aβ- participants despite no initial group difference at the first measurement. Higher connectivity between certain salience network node-pairs (i.e., pregenual anterior cingulate cortex and periaqueductal gray) predicted longitudinal increases in empathic concern in the Aβ+ group but not in the Aβ- group. The Aβ+ participants also had higher overall salience network connectivity than Aβ- participants despite no differences in gray matter volume. These results suggest gains in empathic concern may be a very early feature of AD pathophysiology that relates to hyperconnectivity in the salience network, a system that supports emotion generation and interoception. A better understanding of emotional empathy trajectories in the early stages of AD pathophysiology will broaden the lens on preclinical AD changes and help clinicians to identify older adults who should be screened for AD biomarkers.

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YNIMG Journal 2022 Journal Article

A dynamic gradient architecture generates brain activity states

Jesse A. Brown
Alex J. Lee
Lorenzo Pasquini
William W. Seeley

The human brain exhibits a diverse yet constrained range of activity states. While these states can be faithfully represented in a low-dimensional latent space, our understanding of the constitutive functional anatomy is still evolving. Here we applied dimensionality reduction to task-free and task fMRI data to address whether latent dimensions reflect intrinsic systems and if so, how these systems may interact to generate different activity states. We find that each dimension represents a dynamic activity gradient, including a primary unipolar sensory-association gradient underlying the global signal. The gradients appear stable across individuals and cognitive states, while recapitulating key functional connectivity properties including anticorrelation, modularity, and regional hubness. We then use dynamical systems modeling to show that gradients causally interact via state-specific coupling parameters to create distinct brain activity patterns. Together, these findings indicate that a set of dynamic, intrinsic spatial gradients interact to determine the repertoire of possible brain activity states.

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YNIMG Journal 2020 Journal Article

State and trait characteristics of anterior insula time-varying functional connectivity

Lorenzo Pasquini
Gianina Toller
Adam Staffaroni
Jesse A. Brown
Jersey Deng
Alex Lee
Katarzyna Kurcyus
Suzanne M. Shdo

The human anterior insula (aINS) is a topographically organized brain region, in which ventral portions contribute to socio-emotional function through limbic and autonomic connections, whereas the dorsal aINS contributes to cognitive processes through frontal and parietal connections. Open questions remain, however, regarding how aINS connectivity varies over time. We implemented a novel approach combining seed-to-whole-brain sliding-window functional connectivity MRI and k-means clustering to assess time-varying functional connectivity of aINS subregions. We studied three independent large samples of healthy participants and longitudinal datasets to assess inter- and intra-subject stability, and related aINS time-varying functional connectivity profiles to dispositional empathy. We identified four robust aINS time-varying functional connectivity modes that displayed both “state” and “trait” characteristics: while modes featuring connectivity to sensory regions were modulated by eye closure, modes featuring connectivity to higher cognitive and emotional processing regions were stable over time and related to empathy measures.

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YNICL Journal 2019 Journal Article

Divergent patterns of loss of interpersonal warmth in frontotemporal dementia syndromes are predicted by altered intrinsic network connectivity

Gianina Toller
Winson F.Z. Yang
Jesse A. Brown
Kamalini G. Ranasinghe
Suzanne M. Shdo
Joel H. Kramer
William W. Seeley
Bruce L. Miller

Loss of warmth is well-documented in behavioral variant frontotemporal dementia (bvFTD) and semantic variant primary progressive aphasia (svPPA) at a group level, and has been linked to salience (SN) and semantic-appraisal (SAN) network atrophy. However, clinical observations of individual patients show much greater heterogeneity, thus measuring this clinical variability and identifying the underlying neurologic mechanisms is a critical step for understanding the symptom profile of any one patient. We used reliable change indexes with premorbid and current informant-based evaluations to characterize patterns of change on the warmth subscale of the Interpersonal Adjective Scale (IAS) questionnaire in 132 patients (21 bvFTD, 19 svPPA, 22 nonfluent variant primary progressive aphasia [nfvPPA], 37 Alzheimer's disease [AD]) and 33 healthy older adults. We investigated whether individual differences in warmth change were reflected in SN or SAN functional connectivity, or structural volume of individual brain regions in these two networks. Though one subset of patients showed significant drop in warmth to abnormally low levels (bvFTD: 38%; svPPA: 21%; nfvPPA: 5%; AD: 11%), a second subset significantly dropped but remained within the clinically normal range (bvFTD: 33%; svPPA: 21%; nfvPPA: 9%; AD: 5%), and a third subset did not drop and stayed in the clinically normal range (bvFTD: 29%; svPPA: 58%; nfvPPA: 86%; AD: 84%). Furthermore, interpersonal warmth score was strongly predicted by SN functional connectivity (p < .01), but not by SAN functional connectivity or by structural volume in these networks. Our results extend earlier group-level findings by showing wide individual variability in degree of disease-related reduction of interpersonal warmth and SN functional connectivity in bvFTD and svPPA, and highlight new approaches to revealing how brain connectivity predicts behavior on an individual patient level. Our findings suggest that measures of interpersonal warmth can provide important clinical information about changes in underlying brain networks, and help clinicians and clinical researchers better identify which bvFTD and svPPA patients are at greater risk for interpersonal disruption.

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YNICL Journal 2019 Journal Article

Intrinsic connectivity networks in posterior cortical atrophy: A role for the pulvinar?

Carolyn A. Fredericks
Jesse A. Brown
Jersey Deng
Abigail Kramer
Rik Ossenkoppele
Katherine Rankin
Joel H. Kramer
Bruce L. Miller

BACKGROUND: Posterior cortical atrophy (PCA) is a clinical variant of Alzheimer's disease (AD) that presents with progressive visuospatial symptoms. While amnestic AD is characterized by disrupted default mode network (DMN) connectivity with corresponding increases in salience network (SN) connectivity, a visuospatial network appears to be disrupted early in PCA. Based on PCA patients' clinical features, we hypothesized that, in addition to early decreased integrity within the visuospatial network, patients with PCA would show increases in SN connectivity despite relative preservation of DMN. As the lateral pulvinar nucleus of the thalamus has direct anatomical connections with striate and extrastriate cortex and DMN, and the medial pulvinar is anatomically interconnected with SN, we further hypothesized that lateral and medial pulvinar nuclei might be implicated in intrinsic connectivity changes in PCA. METHODS: 26 patients with PCA and 64 matched controls were recruited through UCSF Memory and Aging Center research programs. Each completed a standardized neuropsychological battery, structural MRI, and task-free fMRI. Seed-based functional correlations were used to probe networks of interest, including those seeded by the medial and lateral pulvinar thalamic nuclei, across the whole brain, and functional data analyses were adjusted for brain atrophy. RESULTS: Patients with PCA showed disproportionate deficits in the visuospatial domain; they also showed preserved social sensitivity and endorsed more depressive symptoms than HCs. PCA patients had significant parietooccipital atrophy accompanied by widespread connectivity decreases within the visuospatial network, enhanced connectivity between some structures in SN, and enhanced connectivity between key nodes of the DMN compared to controls. Increased SN connectivity correlated with a measure of social sensitivity, and increased DMN connectivity correlated with short-term memory performance. Medial pulvinar connectivity increases in PCA were topographically similar to SN (anterior insula) connectivity increases, while lateral pulvinar connectivity increases were similar to DMN (posterior cingulate) connectivity increases. CONCLUSIONS: PCA is characterized by preserved to heightened connectivity in the SN and DMN despite decreased visuospatial network connectivity. The spatial similarity of medial and lateral pulvinar connectivity changes to those seen in the SN and DMN suggests a role for the pulvinar in intrinsic connectivity network changes in PCA.

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YNICL Journal 2019 Journal Article

Machine learning based hierarchical classification of frontotemporal dementia and Alzheimer's disease

Jun Pyo Kim
Jeonghun Kim
Yu Hyun Park
Seong Beom Park
Jin San Lee
Sole Yoo
Eun-Joo Kim
Hee Jin Kim

BACKGROUND: In a clinical setting, an individual subject classification model rather than a group analysis would be more informative. Specifically, the subtlety of cortical atrophy in some frontotemporal dementia (FTD) patients and overlapping patterns of atrophy among three FTD clinical syndromes including behavioral variant FTD (bvFTD), non-fluent/agrammatic variant primary progressive aphasia (nfvPPA), and semantic variant PPA (svPPA) give rise to the need for classification models at the individual level. In this study, we aimed to classify each individual subject into one of the diagnostic categories in a hierarchical manner by employing a machine learning-based classification method. METHODS: We recruited 143 patients with FTD, 50 patients with Alzheimer's disease (AD) dementia, and 146 cognitively normal subjects. All subjects underwent a three-dimensional volumetric brain magnetic resonance imaging (MRI) scan, and cortical thickness was measured using FreeSurfer. We applied the Laplace Beltrami operator to reduce noise in the cortical thickness data and to reduce the dimension of the feature vector. Classifiers were constructed by applying both principal component analysis and linear discriminant analysis to the cortical thickness data. For the hierarchical classification, we trained four classifiers using different pairs of groups: Step 1 - CN vs. FTD + AD, Step 2 - FTD vs. AD, Step 3 - bvFTD vs. PPA, Step 4 - svPPA vs. nfvPPA. To evaluate the classification performance for each step, we used a10-fold cross-validation approach, performed 1000 times for reliability. RESULTS: The classification accuracy of the entire hierarchical classification tree was 75.8%, which was higher than that of the non-hierarchical classifier (73.0%). The classification accuracies of steps 1-4 were 86.1%, 90.8%, 86.9%, and 92.1%, respectively. Changes in the right frontotemporal area were critical for discriminating behavioral variant FTD from PPA. The left frontal lobe discriminated nfvPPA from svPPA, while the bilateral anterior temporal regions were critical for identifying svPPA. CONCLUSIONS: In the present study, our automated classifier successfully classified FTD clinical subtypes with good to excellent accuracy. Our classifier may help clinicians diagnose FTD subtypes with subtle cortical atrophy and facilitate appropriate specific interventions.

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YNICL Journal 2019 Journal Article

Tau covariance patterns in Alzheimer's disease patients match intrinsic connectivity networks in the healthy brain

Rik Ossenkoppele
Leonardo Iaccarino
Daniel R. Schonhaut
Jesse A. Brown
Renaud La Joie
James P. O'Neil
Mustafa Janabi
Suzanne L. Baker

F]flortaucipir covariance patterns and intrinsic connectivity maps (range Spearman rho's: 0.32-0.78, p < .001), which corresponded with expected functional networks (range goodness-of-fit: 3.8-8.2). The topography of amyloid-β covariance patterns was more diffuse and less network-specific, while glucose hypometabolic patterns were more spatially restricted than tau but overlapped with functional networks. These findings suggest that the spatial patterns of tau and glucose hypometabolism observed in AD resemble the functional organization of the healthy brain, supporting the notion that tau pathology spreads through circumscribed brain networks and drives neurodegeneration.

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YNICL Journal 2019 Journal Article

Thalamo-cortical network hyperconnectivity in preclinical progranulin mutation carriers

Suzee E. Lee
Ana C. Sias
Eena L. Kosik
Taru M. Flagan
Jersey Deng
Stephanie A. Chu
Jesse A. Brown
Anna A. Vidovszky

Mutations in progranulin (GRN) cause heterogeneous clinical syndromes, including behavioral variant frontotemporal dementia (bvFTD), primary progressive aphasia (PPA), corticobasal syndrome (CBS) and Alzheimer-type dementia (AD-type dementia). Human studies have shown that presymptomatic GRN carriers feature reduced connectivity in the salience network, a system targeted in bvFTD. Mice with homozygous deletion of GRN, in contrast, show thalamo-cortical hypersynchrony due to aberrant pruning of inhibitory synapses onto thalamo-cortical projection neurons. No studies have systematically explored the intrinsic connectivity networks (ICNs) targeted by the four GRN-associated clinical syndromes, or have forged clear links between human and mouse model findings. We compared 17 preclinical GRN carriers (14 "presymptomatic" clinically normal and three "prodromal" with mild cognitive symptoms) to healthy controls to assess for differences in cognitive testing and gray matter volume. Using task-free fMRI, we assessed connectivity in the salience network, a non-fluent variant primary progressive aphasia network (nfvPPA), the perirolandic network (CBS), and the default mode network (AD-type dementia). GRN carriers and controls showed similar performance on cognitive testing. Although carriers showed little evidence of brain atrophy, markedly enhanced connectivity emerged in all four networks, and thalamo-cortical hyperconnectivity stood out as a unifying feature. Voxelwise assessment of whole brain degree centrality, an unbiased graph theoretical connectivity metric, confirmed thalamic hyperconnectivity. These results show that human GRN disease and the prevailing GRN mouse model share a thalamo-cortical network hypersynchrony phenotype. Longitudinal studies will determine whether this network physiology represents a compensatory response as carriers approach symptom onset, or an early and sustained preclinical manifestation of lifelong progranulin haploinsufficiency.

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YNICL Journal 2017 Journal Article

Advancing functional dysconnectivity and atrophy in progressive supranuclear palsy

Jesse A. Brown
Alice Y. Hua
Andrew Trujillo
Suneth Attygalle
Richard J. Binney
Salvatore Spina
Suzee E. Lee
Joel H. Kramer

Progressive supranuclear palsy syndrome (PSP-S) results from neurodegeneration within a network of brainstem, subcortical, frontal and parietal cortical brain regions. It is unclear how network dysfunction progresses and relates to longitudinal atrophy and clinical decline. In this study, we evaluated patients with PSP-S (n=12) and healthy control subjects (n=20) at baseline and 6months later. Subjects underwent structural MRI and task-free functional MRI (tf-fMRI) scans and clinical evaluations at both time points. At baseline, voxel based morphometry (VBM) revealed that patients with mild-to-moderate clinical symptoms showed structural atrophy in subcortex and brainstem, prefrontal cortex (PFC; supplementary motor area, paracingulate, dorsal and ventral medial PFC), and parietal cortex (precuneus). Tf-fMRI functional connectivity (FC) was examined in a rostral midbrain tegmentum (rMT)-anchored intrinsic connectivity network that is compromised in PSP-S. In healthy controls, this network contained a medial parietal module, a prefrontal-paralimbic module, and a subcortical-brainstem module. Baseline FC deficits in PSP-S were most severe in rMT network integrative hubs in the prefrontal-paralimbic and subcortical-brainstem modules. Longitudinally, patients with PSP-S had declining intermodular FC between the subcortical-brainstem and parietal modules, while progressive atrophy was observed in subcortical-brainstem regions (midbrain, pallidum) and posterior frontal (perirolandic) cortex. This suggested that later-stage subcortical-posterior cortical change may follow an earlier-stage subcortical-anterior cortical disease process. Clinically, patients with more severe baseline impairment showed greater subsequent prefrontal-parietal cortical FC declines and posterior frontal atrophy rates, while patients with more rapid longitudinal clinical decline showed coupled prefrontal-paralimbic FC decline. VBM and FC can augment disease monitoring in PSP-S by tracking the disease through stages while detecting changes that accompany heterogeneous clinical progression.

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YNICL Journal 2017 Journal Article

Network degeneration and dysfunction in presymptomatic C9ORF72 expansion carriers

Suzee E. Lee
Ana C. Sias
Maria Luisa Mandelli
Jesse A. Brown
Alainna B. Brown
Anna M. Khazenzon
Anna A. Vidovszky
Theodore P. Zanto

Hexanucleotide repeat expansions in C9ORF72 are the most common known genetic cause of familial and sporadic frontotemporal dementia and amyotrophic lateral sclerosis. Previous work has shown that patients with behavioral variant frontotemporal dementia due to C9ORF72 show salience and sensorimotor network disruptions comparable to those seen in sporadic behavioral variant frontotemporal dementia, but it remains unknown how early in the lifespan these and other changes in brain structure and function arise. To gain insights into this question, we compared 15 presymptomatic carriers (age 43. 7±10. 2years, nine females) to matched healthy controls. We used voxel-based morphometry to assess gray matter, diffusion tensor imaging to interrogate white matter tracts, and task-free functional MRI to probe the salience, sensorimotor, default mode, and medial pulvinar thalamus-seeded networks. We further used a retrospective chart review to ascertain psychiatric histories in carriers and their non-carrier family members. Carriers showed normal cognition and behavior despite gray matter volume and brain connectivity deficits that were apparent as early as the fourth decade of life. Gray matter volume deficits were topographically similar though less severe than those in patients with behavioral variant frontotemporal dementia due to C9ORF72, with major foci in cingulate, insula, thalamus, and striatum. Reduced white matter integrity was found in the corpus callosum, cingulum bundles, corticospinal tracts, uncinate fasciculi and inferior longitudinal fasciculi. Intrinsic connectivity deficits were detected in all four networks but most prominent in salience and medial pulvinar thalamus-seeded networks. Carrier and control groups showed comparable relationships between imaging metrics and age, suggesting that deficits emerge during early adulthood. Carriers and non-carrier family members had comparable lifetime histories of psychiatric symptoms. Taken together, the findings suggest that presymptomatic C9ORF72 expansion carriers exhibit functionally compensated brain volume and connectivity deficits that are similar, though less severe, to those reported during the symptomatic phase. The early adulthood emergence of these deficits suggests that they represent aberrant network patterning during development, an early neurodegeneration prodrome, or both.

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YNIMG Journal 2016 Journal Article

Connected brains and minds—The UMCD repository for brain connectivity matrices

Jesse A. Brown
John D. Van Horn

We describe the USC Multimodal Connectivity Database (http: //umcd. humanconnectomeproject. org), an interactive web-based platform for brain connectivity matrix sharing and analysis. The site enables users to download connectivity matrices shared by other users, upload matrices from their own published studies, or select a specific matrix and perform a real-time graph theory-based analysis and visualization of network properties. The data shared on the site span a broad spectrum of functional and structural brain connectivity information from humans across the entire age range (fetal to age 89), representing an array of different neuropsychiatric and neurodegenerative disease populations (autism spectrum disorder, ADHD, and APOE-4 carriers). An analysis combining 7 different datasets shared on the site illustrates the diversity of the data and the potential for yielding deeper insight by assessing new connectivity matrices with respect to population-wide network properties represented in the UMCD.

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YNIMG Journal 2014 Journal Article

Non-negative matrix factorization of multimodal MRI, fMRI and phenotypic data reveals differential changes in default mode subnetworks in ADHD

Ariana Anderson
Pamela K. Douglas
Wesley T. Kerr
Virginia S. Haynes
Alan L. Yuille
Jianwen Xie
Ying Nian Wu
Jesse A. Brown

In the multimodal neuroimaging framework, data on a single subject are collected from inherently different sources such as functional MRI, structural MRI, behavioral and/or phenotypic information. The information each source provides is not independent; a subset of features from each modality maps to one or more common latent dimensions, which can be interpreted using generative models. These latent dimensions, or “topics, ” provide a sparse summary of the generative process behind the features for each individual. Topic modeling, an unsupervised generative model, has been used to map seemingly disparate features to a common domain. We use Non-Negative Matrix Factorization (NMF) to infer the latent structure of multimodal ADHD data containing fMRI, MRI, phenotypic and behavioral measurements. We compare four different NMF algorithms and find that the sparsest decomposition is also the most differentiating between ADHD and healthy patients. We identify dimensions that map to interpretable, recognizable dimensions such as motion, default mode network activity, and other such features of the input data. For example, structural and functional graph theory features related to default mode subnetworks clustered with the ADHD-Inattentive diagnosis. Structural measurements of the default mode network (DMN) regions such as the posterior cingulate, precuneus, and parahippocampal regions were all related to the ADHD-Inattentive diagnosis. Ventral DMN subnetworks may have more functional connections in ADHD-I, while dorsal DMN may have less. ADHD topics are dependent upon diagnostic site, suggesting diagnostic differences across geographic locations. We assess our findings in light of the ADHD-200 classification competition, and contrast our unsupervised, nominated topics with previously published supervised learning methods. Finally, we demonstrate the validity of these latent variables as biomarkers by using them for classification of ADHD in 730 patients. Cumulatively, this manuscript addresses how multimodal data in ADHD can be interpreted by latent dimensions.

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YNIMG Journal 2011 Journal Article

Conserved and variable architecture of human white matter connectivity

Danielle S. Bassett
Jesse A. Brown
Vibhas Deshpande
Jean M. Carlson
Scott T. Grafton

Whole-brain network analysis of diffusion imaging tractography data is an important new tool for quantification of differential connectivity patterns across individuals and between groups. Here we investigate both the conservation of network architectural properties across methodological variation and the reproducibility of individual architecture across multiple scanning sessions. Diffusion spectrum imaging (DSI) and diffusion tensor imaging (DTI) data were both acquired in triplicate from a cohort of healthy young adults. Deterministic tractography was performed on each dataset and inter-regional connectivity matrices were then derived by applying each of three widely used whole-brain parcellation schemes over a range of spatial resolutions. Across acquisitions and preprocessing streams, anatomical brain networks were found to be sparsely connected, hierarchical, and assortative. They also displayed signatures of topo-physical interdependence such as Rentian scaling. Basic connectivity properties and several graph metrics consistently displayed high reproducibility and low variability in both DSI and DTI networks. The relative increased sensitivity of DSI to complex fiber configurations was evident in increased tract counts and network density compared with DTI. In combination, this pattern of results shows that network analysis of human white matter connectivity provides sensitive and temporally stable topological and physical estimates of individual cortical structure across multiple spatial scales.

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