Nikos Makris

YNICL Journal 2026 Journal Article

Study of sex differences in the whole brain white matter using diffusion MRI tractography and suprathreshold fiber cluster statistics

• Fan Zhang
• Jarrett Rushmore
• Yijie Li
• Suheyla Cetin-Karayumak
• Yang Song
• Weidong Cai
• Carl-Fredrik Westin
• James J. Levitt

Sex-specific characteristics demonstrate a substantial influence on the brain white matter, suggesting distinct structural connectivity patterns between females and males. Diffusion MRI tractography is an important tool in assessing white matter connectivity and brain tissue microstructure across different populations. Whole brain tractography analysis for group statistical comparison is a challenging task due to the large number of white matter connections. This work studies whole-brain white matter connectivity differences between females and males using dMRI tractography. We study a large cohort of 707 subjects from the Human Connectome Project Young Adult dataset. By applying a well-established fiber clustering pipeline and a suprathreshold fiber cluster statistical method, we analyze tracts in the cerebral cortex and understudied pathways like those connecting to the cerebellum. We identify several tracts with significant sex differences in terms of their fractional anisotropy and/or mean diffusivity. These include deep tracts like the arcuate fasciculus, corticospinal tract, and corpus callosum, superficial tracts in the frontal lobe, and cerebellar tracts. Finally, a canonical correlation analysis (CCA) that identifies covariance patterns between white matter and behavior measures reveals that these white matter differences are associated with a range of neurobehavioral measures, with the strongest and most consistent associations observed for motor function, suggesting motor circuits as a potential key focus for future research.

YNIMG Journal 2025 Journal Article

DeepNuParc: A novel deep clustering framework for fine-scale parcellation of brain nuclei using diffusion MRI tractography

• Haolin He
• Ce Zhu
• Le Zhang
• Yipeng Liu
• Xiao Xu
• Yuqian Chen
• Leo Zekelman
• Jarrett Rushmore

Brain nuclei are clusters of anatomically distinct neurons that serve as important hubs for processing and relaying information in various neural circuits. Fine-scale parcellation of the brain nuclei is vital for a comprehensive understanding of their anatomico-functional correlations. Diffusion MRI tractography is an advanced imaging technique that can estimate the brain's white matter structural connectivity to potentially reveal the topography of the nuclei of interest for studying their subdivisions. In this work, we present a deep clustering pipeline, namely DeepNuParc, to perform automated, fine-scale parcellation of brain nuclei using diffusion MRI tractography. First, we incorporate a newly proposed deep learning approach to enable accurate segmentation of the nuclei of interest directly on the dMRI data. Next, we design a novel streamline clustering-based structural connectivity feature for a robust representation of voxels within the nuclei. Finally, we improve the popular joint dimensionality reduction and k-means clustering approach to enable nuclei parcellation at a finer scale. We demonstrate DeepNuParc on two important brain structures, i.e. the amygdala and the thalamus, that are known to have multiple anatomically and functionally distinct nucleus subdivisions. Experimental results show that DeepNuParc enables consistent parcellation of the nuclei into multiple parcels across multiple subjects and achieves good correspondence with the widely used coarse-scale atlases. Our code is available at https://github.com/HarlandZZC/deep_nuclei_parcellation.

YNIMG Journal 2023 Journal Article

Deep fiber clustering: Anatomically informed fiber clustering with self-supervised deep learning for fast and effective tractography parcellation

• Yuqian Chen
• Chaoyi Zhang
• Tengfei Xue
• Yang Song
• Nikos Makris
• Yogesh Rathi
• Weidong Cai
• Fan Zhang

White matter fiber clustering is an important strategy for white matter parcellation, which enables quantitative analysis of brain connections in health and disease. In combination with expert neuroanatomical labeling, data-driven white matter fiber clustering is a powerful tool for creating atlases that can model white matter anatomy across individuals. While widely used fiber clustering approaches have shown good performance using classical unsupervised machine learning techniques, recent advances in deep learning reveal a promising direction toward fast and effective fiber clustering. In this work, we propose a novel deep learning framework for white matter fiber clustering, Deep Fiber Clustering (DFC), which solves the unsupervised clustering problem as a self-supervised learning task with a domain-specific pretext task to predict pairwise fiber distances. This process learns a high-dimensional embedding feature representation for each fiber, regardless of the order of fiber points reconstructed during tractography. We design a novel network architecture that represents input fibers as point clouds and allows the incorporation of additional sources of input information from gray matter parcellation. Thus, DFC makes use of combined information about white matter fiber geometry and gray matter anatomy to improve the anatomical coherence of fiber clusters. In addition, DFC conducts outlier removal naturally by rejecting fibers with low cluster assignment probability. We evaluate DFC on three independently acquired cohorts, including data from 220 individuals across genders, ages (young and elderly adults), and different health conditions (healthy control and multiple neuropsychiatric disorders). We compare DFC to several state-of-the-art white matter fiber clustering algorithms. Experimental results demonstrate superior performance of DFC in terms of cluster compactness, generalization ability, anatomical coherence, and computational efficiency.

YNIMG Journal 2022 Journal Article

White matter association tracts underlying language and theory of mind: An investigation of 809 brains from the Human Connectome Project

• Leo R. Zekelman
• Fan Zhang
• Nikos Makris
• Jianzhong He
• Yuqian Chen
• Tengfei Xue
• Daniela Liera
• Daniel L. Drane

Language and theory of mind (ToM) are the cognitive capacities that allow for the successful interpretation and expression of meaning. While functional MRI investigations are able to consistently localize language and ToM to specific cortical regions, diffusion MRI investigations point to an inconsistent and sometimes overlapping set of white matter tracts associated with these two cognitive domains. To further examine the white matter tracts that may underlie these domains, we use a two-tensor tractography method to investigate the white matter microstructure of 809 participants from the Human Connectome Project. 20 association white matter tracts (10 in each hemisphere) are uniquely identified by leveraging a neuroanatomist-curated automated white matter tract atlas. The fractional anisotropy (FA), mean diffusivity (MD), and number of streamlines (NoS) are measured for each white matter tract. Performance on neuropsychological assessments of semantic memory (NIH Toolbox Picture Vocabulary Test, TPVT) and emotion perception (Penn Emotion Recognition Test, PERT) are used to measure critical subcomponents of the language and ToM networks, respectively. Regression models are constructed to examine how structural measurements of left and right white matter tracts influence performance across these two assessments. We find that semantic memory performance is influenced by the number of streamlines of the left superior longitudinal fasciculus III (SLF-III), and emotion perception performance is influenced by the number of streamlines of the right SLF-III. Additionally, we find that performance on both semantic memory & emotion perception is influenced by the FA of the left arcuate fasciculus (AF). The results point to multiple, overlapping white matter tracts that underlie the cognitive domains of language and ToM. Results are discussed in terms of hemispheric dominance and concordance with prior investigations.

YNIMG Journal 2021 Journal Article

The ventral pathway of the human brain: A continuous association tract system

• Cornelius Weiller
• Marco Reisert
• Ivo Peto
• Jürgen Hennig
• Nikos Makris
• Michael Petrides
• Michel Rijntjes
• Karl Egger

The brain hemispheres can be divided into an upper dorsal and a lower ventral system. Each system consists of distinct cortical regions connected via long association tracts. The tracts cross the central sulcus or the limen insulae to connect the frontal lobe with the posterior brain. The dorsal stream is associated with sensorimotor mapping. The ventral stream serves structural analysis and semantics in different domains, as visual, acoustic or space processing. How does the prefrontal cortex, regarded as the platform for the highest level of integration, incorporate information from these different domains? In the current view, the ventral pathway consists of several separate tracts, related to different modalities. Originally the assumption was that the ventral path is a continuum, covering all modalities. The latter would imply a very different anatomical basis for cognitive and clinical models of processing. To further define the ventral connections, we used cutting-edge in vivo global tractography on high-resolution diffusion tensor imaging (DTI) data from 100 normal subjects from the human connectome project and ex vivo preparation of fiber bundles in the extreme capsule of 8 humans using the Klingler technique. Our data showed that ventral stream tracts, traversing through the extreme capsule, form a continuous band of fibers that fan out anteriorly to the prefrontal cortex, and posteriorly to temporal, occipital and parietal cortical regions. Introduction of additional volumes of interest in temporal and occipital lobes differentiated between the inferior fronto-occipital fascicle (IFOF) and uncinate fascicle (UF). Unequivocally, in both experiments, in all subjects a connection between the inferior frontal and middle-to-posterior temporal cortical region, otherwise known as the temporo-frontal extreme capsule fascicle (ECF) from nonhuman primate brain-tracing experiments was identified. In the human brain, this tract connects the language domains of "Broca's area" and "Wernicke's area". The differentiation in the three tracts, IFOF, UF and ECF seems arbitrary, all three pass through the extreme capsule. Our data show that the ventral pathway represents a continuum. The three tracts merge seamlessly and streamlines showed considerable overlap in their anterior and posterior course. Terminal maps identified prefrontal cortex in the frontal lobe and association cortex in temporal, occipital and parietal lobes as streamline endings. This anatomical substrate potentially facilitates the prefrontal cortex to integrate information across different domains and modalities.

YNIMG Journal 2021 Journal Article

Tractography dissection variability: What happens when 42 groups dissect 14 white matter bundles on the same dataset?

• Kurt G. Schilling
• François Rheault
• Laurent Petit
• Colin B. Hansen
• Vishwesh Nath
• Fang-Cheng Yeh
• Gabriel Girard
• Muhamed Barakovic

White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white matter fiber pathways in vivo in human brains. However, like other analyses of complex data, there is considerable variability in segmentation protocols and techniques. This can result in different reconstructions of the same intended white matter pathways, which directly affects tractography results, quantification, and interpretation. In this study, we aim to evaluate and quantify the variability that arises from different protocols for bundle segmentation. Through an open call to users of fiber tractography, including anatomists, clinicians, and algorithm developers, 42 independent teams were given processed sets of human whole-brain streamlines and asked to segment 14 white matter fascicles on six subjects. In total, we received 57 different bundle segmentation protocols, which enabled detailed volume-based and streamline-based analyses of agreement and disagreement among protocols for each fiber pathway. Results show that even when given the exact same sets of underlying streamlines, the variability across protocols for bundle segmentation is greater than all other sources of variability in the virtual dissection process, including variability within protocols and variability across subjects. In order to foster the use of tractography bundle dissection in routine clinical settings, and as a fundamental analytical tool, future endeavors must aim to resolve and reduce this heterogeneity. Although external validation is needed to verify the anatomical accuracy of bundle dissections, reducing heterogeneity is a step towards reproducible research and may be achieved through the use of standard nomenclature and definitions of white matter bundles and well-chosen constraints and decisions in the dissection process.

YNICL Journal 2020 Journal Article

Anatomical assessment of trigeminal nerve tractography using diffusion MRI: A comparison of acquisition b-values and single- and multi-fiber tracking strategies

• Guoqiang Xie
• Fan Zhang
• Laura Leung
• Michael A. Mooney
• Lorenz Epprecht
• Isaiah Norton
• Yogesh Rathi
• Ron Kikinis

BACKGROUND: and conventional diffusion tensor MRI (DTI) tractography methods. Though higher b-value acquisitions and multi-tensor tractography methods are known to be beneficial for tracking brain white matter fiber tracts, there have been no studies conducted to evaluate the performance of these advanced approaches on nerve tracking of the TGN, in particular on tracking different anatomical regions of the TGN. OBJECTIVE: We compare TGN tracking performance using dMRI data with different b-values, in combination with both single- and multi-tensor tractography methods. Our goal is to assess the advantages and limitations of these different strategies for identifying the anatomical regions of the TGN. METHODS: , using single-tensor (1T) and two-tensor (2T) unscented Kalman filter (UKF) tractography. This resulted in a total of six tracking strategies. The TGN was identified using an anatomical region-of-interest (ROI) selection approach. First, in a subset of the dataset we identified ROIs that provided good TGN tracking performance across all tracking strategies. Using these ROIs, the TGN was then tracked in all subjects using the six tracking strategies. An expert rater (GX) visually assessed and scored each TGN based on seven anatomical judgment criteria. These criteria included the presence of multiple expected anatomical segments of the TGN (true positive structures), specifically branch-like structures, cisternal portion, mesencephalic trigeminal tract, and spinal cord tract of the TGN. False positive criteria included the presence of any fibers entering the temporal lobe, the inferior cerebellar peduncle, or the middle cerebellar peduncle. Expert rating scores were analyzed to compare TGN tracking performance across the six tracking strategies. Intra- and inter-rater validation was performed to assess the reliability of the expert TGN rating result. RESULTS: The TGN was selected using two anatomical ROIs (Meckel's Cave and cisternal portion of the TGN). The two-tensor tractography method had significantly better performance on identifying true positive structures, while generating more false positive streamlines in comparison to the single-tensor tractography method. TGN tracking performance was significantly different across the three b-values for almost all structures studied. Tracking performance was reported in terms of the percentage of subjects achieving each anatomical rating criterion. Tracking of the cisternal portion and branching structure of the TGN was generally successful, with the highest performance of over 98% using two-tensor tractography and b = 1000 or b = 2000. However, tracking the smaller mesencephalic and spinal cord tracts of the TGN was quite challenging (highest performance of 37.5% and 57.07%, using two-tensor tractography with b = 1000 and b = 2000, respectively). False positive connections to the temporal lobe (over 38% of subjects for all strategies) and cerebellar peduncles (100% of subjects for all strategies) were prevalent. High joint probability of agreement was obtained in the inter-rater (on average 83%) and intra-rater validation (on average 90%), showing a highly reliable expert rating result. CONCLUSIONS: Overall, the results of the study suggest that researchers and clinicians may benefit from tailoring their acquisition and tracking methodology to the specific anatomical portion of the TGN that is of the greatest interest. For example, tracking of branching structures and TGN-T2 overlap can be best achieved with a two-tensor model and an acquisition using b = 1000 or b = 2000. In general, b = 1000 and b = 2000 acquisitions provided the best-rated tracking results. Further research is needed to improve both sensitivity and specificity of the depiction of the TGN anatomy using dMRI.

YNIMG Journal 2020 Journal Article

Creation of a novel trigeminal tractography atlas for automated trigeminal nerve identification

• Fan Zhang
• Guoqiang Xie
• Laura Leung
• Michael A. Mooney
• Lorenz Epprecht
• Isaiah Norton
• Yogesh Rathi
• Ron Kikinis

Diffusion MRI (dMRI) tractography has been successfully used to study the trigeminal nerves (TGNs) in many clinical and research applications. Currently, identification of the TGN in tractography data requires expert nerve selection using manually drawn regions of interest (ROIs), which is prone to inter-observer variability, time-consuming and carries high clinical and labor costs. To overcome these issues, we propose to create a novel anatomically curated TGN tractography atlas that enables automated identification of the TGN from dMRI tractography. In this paper, we first illustrate the creation of a trigeminal tractography atlas. Leveraging a well-established computational pipeline and expert neuroanatomical knowledge, we generate a data-driven TGN fiber clustering atlas using tractography data from 50 subjects from the Human Connectome Project. Then, we demonstrate the application of the proposed atlas for automated TGN identification in new subjects, without relying on expert ROI placement. Quantitative and visual experiments are performed with comparison to expert TGN identification using dMRI data from two different acquisition sites. We show highly comparable results between the automatically and manually identified TGNs in terms of spatial overlap and visualization, while our proposed method has several advantages. First, our method performs automated TGN identification, and thus it provides an efficient tool to reduce expert labor costs and inter-operator bias relative to expert manual selection. Second, our method is robust to potential imaging artifacts and/or noise that can prevent successful manual ROI placement for TGN selection and hence yields a higher successful TGN identification rate.

YNICL Journal 2020 Journal Article

Middle longitudinal fascicle is associated with semantic processing deficits in primary progressive aphasia

• Chunyan Luo
• Sara Makaretz
• Michael Stepanovic
• George Papadimitriou
• Megan Quimby
• Senthil Palanivelu
• Bradford C. Dickerson
• Nikos Makris

The middle longitudinal fascicle (MdLF) is a recently delineated association cortico-cortical fiber pathway in humans, connecting superior temporal gyrus and temporal pole principally with the angular gyrus, and is likely to be involved in language processing. However, the MdLF has not been studied in language disorders as primary progressive aphasia (PPA). We hypothesized that the MdLF will exhibit evidence of neurodegeneration in PPA patients. In this study, 20 PPA patients and 25 healthy controls were recruited in the Primary Progressive Aphasia program in the Massachusetts General Hospital Frontotemporal Disorders Unit. We used diffusion tensor imaging (DTI) tractography to reconstruct the MdLF and extract tract-specific DTI metrics (fractional anisotropy (FA), radial diffusivity (RD), mean diffusivity (MD) and axial diffusivity (AD)) to assess white matter changes in PPA and their relationship with language impairments. We found severe WM damage in the MdLF in PPA patients, which was principally pronounced in the left hemisphere. Moreover, the WM alterations in the MdLF in the dominant hemisphere were significantly correlated with impairments in word comprehension and naming, but not with articulation and fluency. In addition, asymmetry analysis revealed that the DTI metrics of controls were similar for each hemisphere, whereas PPA patients had clear laterality differences in MD, AD and RD. These findings add new insight into the localization and severity of white matter fiber bundle neurodegeneration in PPA, and provide evidence that degeneration of the MdLF contribute to impairment in semantic processing and lexical retrieval in PPA.

YNICL Journal 2020 Journal Article

Mild traumatic brain injury impacts associations between limbic system microstructure and post-traumatic stress disorder symptomatology

• Valerie J. Sydnor
• Sylvain Bouix
• Ofer Pasternak
• Elisabeth Hartl
• Laura Levin-Gleba
• Benjamin Reid
• Yorghos Tripodis
• Jeffrey P. Guenette

BACKGROUND: Post-traumatic stress disorder (PTSD) is a psychiatric disorder that afflicts many individuals, yet the neuropathological mechanisms that contribute to this disorder remain to be fully determined. Moreover, it is unclear how exposure to mild traumatic brain injury (mTBI), a condition that is often comorbid with PTSD, particularly among military personnel, affects the clinical and neurological presentation of PTSD. To address these issues, the present study explores relationships between PTSD symptom severity and the microstructure of limbic and paralimbic gray matter brain regions, as well as the impact of mTBI comorbidity on these relationships. METHODS: Structural and diffusion MRI data were acquired from 102 male veterans who were diagnosed with current PTSD. Diffusion data were analyzed with free-water imaging to quantify average CSF-corrected fractional anisotropy (FA) and mean diffusivity (MD) in 18 limbic and paralimbic gray matter regions. Associations between PTSD symptom severity and regional average dMRI measures were examined with repeated measures linear mixed models. Associations were studied separately in veterans with PTSD only, and in veterans with PTSD and a history of military mTBI. RESULTS: Analyses revealed that in the PTSD only cohort, more severe symptoms were associated with higher FA in the right amygdala-hippocampus complex, lower FA in the right cingulate cortex, and lower MD in the left medial orbitofrontal cortex. In the PTSD and mTBI cohort, more severe PTSD symptoms were associated with higher FA bilaterally in the amygdala-hippocampus complex, with higher FA bilaterally in the nucleus accumbens, with lower FA bilaterally in the cingulate cortex, and with higher MD in the right amygdala-hippocampus complex. CONCLUSIONS: These findings suggest that the microstructure of limbic and paralimbic brain regions may influence PTSD symptomatology. Further, given the additional associations observed between microstructure and symptom severity in veterans with head trauma, we speculate that mTBI may exacerbate the impact of brain microstructure on PTSD symptoms, especially within regions of the brain known to be vulnerable to chronic stress. A heightened sensitivity to the microstructural environment of the brain could partially explain why individuals with PTSD and mTBI comorbidity experience more severe symptoms and poorer illness prognoses than those without a history of brain injury. The relevance of these microstructural findings to the conceptualization of PTSD as being a disorder of stress-induced neuronal connectivity loss is discussed.

YNICL Journal 2019 Journal Article

Abnormalities in gray matter microstructure in young adults with 22q11.2 deletion syndrome

• Zora Kikinis
• Nikos Makris
• Valerie J. Sydnor
• Sylvain Bouix
• Ofer Pasternak
• Ioana L. Coman
• Kevin M. Antshel
• Wanda Fremont

BACKGROUND: 22q11.2 Deletion Syndrome (22q11DS) is a genetic, neurodevelopmental disorder characterized by a chromosomal deletion and a distinct cognitive profile. Although abnormalities in the macrostructure of the cortex have been identified in individuals with 22q11DS, it is not known if there are additional microstructural changes in gray matter regions in this syndrome, and/or if such microstructural changes are associated with cognitive functioning. METHODS: This study employed a novel diffusion MRI measure, the Heterogeneity of Fractional Anisotropy (HFA), to examine variability in the microstructural organization of the cortex in healthy young adults (N = 30) and those with 22q11DS (N = 56). Diffusion MRI, structural MRI, clinical and cognitive data were acquired. RESULTS: Compared to controls, individuals with 22q11DS evinced increased HFA in cortical association (p = .003, d = 0.86) and paralimbic (p < .0001, d = 1.2) brain areas, whereas no significant differences were found between the two groups in primary cortical brain areas. Additionally, increased HFA of the right paralimbic area was associated with poorer performance on tests of response inhibition, i.e., the Stroop Test (rho = -0.37 p = .005) and the Gordon Diagnostic System Vigilance Commission (rho = -0.41 p = .002) in the 22q11DS group. No significant correlations were found between HFA and cognitive abilities in the healthy control group. CONCLUSIONS: These findings suggest that cortical microstructural disorganization may be a neural correlate of response inhibition in individuals with 22q11DS. Given that the migration pattern of neural crest cells is disrupted at the time of early brain development in 22q11DS, we hypothesize that these neural alterations may be neurodevelopmental in origin, and reflect cortical dysfunction associated with cognitive deficits.

YNIMG Journal 2018 Journal Article

A comparison of three fiber tract delineation methods and their impact on white matter analysis

• Valerie J. Sydnor
• Ana María Rivas-Grajales
• Amanda E. Lyall
• Fan Zhang
• Sylvain Bouix
• Sarina Karmacharya
• Martha E. Shenton
• Carl-Fredrik Westin

Diffusion magnetic resonance imaging (dMRI) is an important method for studying white matter connectivity in the brain in vivo in both healthy and clinical populations. Improvements in dMRI tractography algorithms, which reconstruct macroscopic three-dimensional white matter fiber pathways, have allowed for methodological advances in the study of white matter; however, insufficient attention has been paid to comparing post-tractography methods that extract white matter fiber tracts of interest from whole-brain tractography. Here we conduct a comparison of three representative and conceptually distinct approaches to fiber tract delineation: 1) a manual multiple region of interest-based approach, 2) an atlas-based approach, and 3) a groupwise fiber clustering approach, by employing methods that exemplify these approaches to delineate the arcuate fasciculus, the middle longitudinal fasciculus, and the uncinate fasciculus in 10 healthy male subjects. We enable qualitative comparisons across methods, conduct quantitative evaluations of tract volume, tract length, mean fractional anisotropy, and true positive and true negative rates, and report measures of intra-method and inter-method agreement. We discuss methodological similarities and differences between the three approaches and the major advantages and drawbacks of each, and review research and clinical contexts for which each method may be most apposite. Emphasis is given to the means by which different white matter fiber tract delineation approaches may systematically produce variable results, despite utilizing the same input tractography and reliance on similar anatomical knowledge.

YNIMG Journal 2018 Journal Article

An anatomically curated fiber clustering white matter atlas for consistent white matter tract parcellation across the lifespan

• Fan Zhang
• Ye Wu
• Isaiah Norton
• Laura Rigolo
• Yogesh Rathi
• Nikos Makris
• Lauren J. O'Donnell

This work presents an anatomically curated white matter atlas to enable consistent white matter tract parcellation across different populations. Leveraging a well-established computational pipeline for fiber clustering, we create a tract-based white matter atlas including information from 100 subjects. A novel anatomical annotation method is proposed that leverages population-based brain anatomical information and expert neuroanatomical knowledge to annotate and categorize the fiber clusters. A total of 256 white matter structures are annotated in the proposed atlas, which provides one of the most comprehensive tract-based white matter atlases covering the entire brain to date. These structures are composed of 58 deep white matter tracts including major long range association and projection tracts, commissural tracts, and tracts related to the brainstem and cerebellar connections, plus 198 short and medium range superficial fiber clusters organized into 16 categories according to the brain lobes they connect. Potential false positive connections are annotated in the atlas to enable their exclusion from analysis or visualization. In addition, the proposed atlas allows for a whole brain white matter parcellation into 800 fiber clusters to enable whole brain connectivity analyses. The atlas and related computational tools are open-source and publicly available. We evaluate the proposed atlas using a testing dataset of 584 diffusion MRI scans from multiple independently acquired populations, across genders, the lifespan (1 day–82 years), and different health conditions (healthy control, neuropsychiatric disorders, and brain tumor patients). Experimental results show successful white matter parcellation across subjects from different populations acquired on multiple scanners, irrespective of age, gender or disease indications. Over 99% of the fiber tracts annotated in the atlas were detected in all subjects on average. One advantage in terms of robustness is that the tract-based pipeline does not require any cortical or subcortical segmentations, which can have limited success in young children and patients with brain tumors or other structural lesions. We believe this is the first demonstration of consistent automated white matter tract parcellation across the full lifespan from birth to advanced age.

YNICL Journal 2018 Journal Article

Automated versus manual segmentation of brain region volumes in former football players

• Jeffrey P. Guenette
• Robert A. Stern
• Yorghos Tripodis
• Alicia S. Chua
• Vivian Schultz
• Valerie J. Sydnor
• Nathaniel Somes
• Sarina Karmacharya

Objectives: To determine whether or not automated FreeSurfer segmentation of brain regions considered important in repetitive head trauma can be analyzed accurately without manual correction. Materials and methods: 3 T MR neuroimaging was performed with automated FreeSurfer segmentation and manual correction of 11 brain regions in former National Football League (NFL) players with neurobehavioral symptoms and in control subjects. Automated segmentation and manually-corrected volumes were compared using an intraclass correlation coefficient (ICC). Linear mixed effects regression models were also used to estimate between-group mean volume comparisons and to correlate former NFL player brain volumes with neurobehavioral factors. Results: Eighty-six former NFL players (55.2 ± 8.0 years) and 22 control subjects (57.0 ± 6.6 years) were evaluated. ICC was highly correlated between automated and manually-corrected corpus callosum volumes (0.911), lateral ventricular volumes (right 0.980, left 0.967), and amygdala-hippocampal complex volumes (right 0.713, left 0.731), but less correlated when amygdalae (right -0.170, left -0.090) and hippocampi (right 0.539, left 0.637) volumes were separately delineated and also less correlated for cingulate gyri volumes (right 0.639, left 0.351). Statistically significant differences between former NFL player and controls were identified in 8 of 11 regions with manual correction but in only 4 of 11 regions without such correction. Within NFL players, manually corrected brain volumes were significantly associated with 3 neurobehavioral factors, but a different set of 3 brain regions and neurobehavioral factor correlations was observed for brain region volumes segmented without manual correction. Conclusions: Automated FreeSurfer segmentation of the corpus callosum, lateral ventricles, and amygdala-hippocampus complex may be appropriate for analysis without manual correction. However, FreeSurfer segmentation of the amygdala, hippocampus, and cingulate gyrus need further manual correction prior to performing group comparisons and correlations with neurobehavioral measures.

YNIMG Journal 2018 Journal Article

Investigation into local white matter abnormality in emotional processing and sensorimotor areas using an automatically annotated fiber clustering in major depressive disorder

• Ye Wu
• Fan Zhang
• Nikos Makris
• Yuping Ning
• Isaiah Norton
• Shenglin She
• Hongjun Peng
• Yogesh Rathi

This work presents an automatically annotated fiber cluster (AAFC) method to enable identification of anatomically meaningful white matter structures from the whole brain tractography. The proposed method consists of 1) a study-specific whole brain white matter parcellation using a well-established data-driven groupwise fiber clustering pipeline to segment tractography into multiple fiber clusters, and 2) a novel cluster annotation method to automatically assign an anatomical tract annotation to each fiber cluster by employing cortical parcellation information across multiple subjects. The novelty of the AAFC method is that it leverages group-wise information about the fiber clusters, including their fiber geometry and cortical terminations, to compute a tract anatomical label for each cluster in an automated fashion. We demonstrate the proposed AAFC method in an application of investigating white matter abnormality in emotional processing and sensorimotor areas in major depressive disorder (MDD). Seven tracts of interest related to emotional processing and sensorimotor functions are automatically identified using the proposed AAFC method as well as a comparable method that uses a cortical parcellation alone. Experimental results indicate that our proposed method is more consistent in identifying the tracts across subjects and across hemispheres in terms of the number of fibers. In addition, we perform a between-group statistical analysis in 31 MDD patients and 62 healthy subjects on the identified tracts using our AAFC method. We find statistical differences in diffusion measures in local regions within a fiber tract (e. g. 4 fiber clusters within the identified left hemisphere cingulum bundle (consisting of 14 clusters) are significantly different between the two groups), suggesting the ability of our method in identifying potential abnormality specific to subdivisions of a white matter structure.

YNICL Journal 2018 Journal Article

Sexually dimorphic structural abnormalities in major connections of the medial forebrain bundle in alcoholism

• Ana María Rivas-Grajales
• Kayle S. Sawyer
• Sarina Karmacharya
• George Papadimitriou
• Joan A. Camprodon
• Gordon J. Harris
• Marek Kubicki
• Marlene Oscar-Berman

The mesocorticolimbic system is particularly susceptible to the effects of chronic alcoholism. Disruption of this system has been linked to drug seeking and the development of Reward Deficiency Syndrome, a neurobiological framework for describing the development and relapsing patterns of addictions. In this study, we evaluated the association of alcoholism and sex with major connections of the medial forebrain bundle (MFB), a prominent mesocorticolimbic fiber pathway connecting the ventral tegmental area with the basal forebrain. Given sex differences in clinical consequences of alcohol consumption, we hypothesized that alcoholic men and women would differ in structural abnormalities of the MFB. Diffusion magnetic resonance imaging (dMRI) data were acquired from 30 abstinent long-term alcoholic individuals (ALC; 9 men) and 25 non-alcoholic controls (NC; 8 men). Major connections of the MFB were extracted using multi-tensor tractography. We compared groups on MFB volume, fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD), with hemisphere and sex as independent variables. We also evaluated associations between abnormal structural measures and drinking measures. Analyses revealed significant group-by-sex interactions for FA and RD: while ALC men had lower FA and higher RD compared to NC men, ALC women had higher FA and lower RD compared to NC women. We also detected a significant negative association between FA and number of daily drinks in ALC women. Alcoholism is associated with sexually dimorphic structural abnormalities in the MFB. The results expand upon other findings of differences in brain reward circuitry of alcoholic men and women.

YNIMG Journal 2018 Journal Article

Whole brain white matter connectivity analysis using machine learning: An application to autism

• Fan Zhang
• Peter Savadjiev
• Weidong Cai
• Yang Song
• Yogesh Rathi
• Birkan Tunç
• Drew Parker
• Tina Kapur

In this paper, we propose an automated white matter connectivity analysis method for machine learning classification and characterization of white matter abnormality via identification of discriminative fiber tracts. The proposed method uses diffusion MRI tractography and a data-driven approach to find fiber clusters corresponding to subdivisions of the white matter anatomy. Features extracted from each fiber cluster describe its diffusion properties and are used for machine learning. The method is demonstrated by application to a pediatric neuroimaging dataset from 149 individuals, including 70 children with autism spectrum disorder (ASD) and 79 typically developing controls (TDC). A classification accuracy of 78. 33% is achieved in this cross-validation study. We investigate the discriminative diffusion features based on a two-tensor fiber tracking model. We observe that the mean fractional anisotropy from the second tensor (associated with crossing fibers) is most affected in ASD. We also find that local along-tract (central cores and endpoint regions) differences between ASD and TDC are helpful in differentiating the two groups. These altered diffusion properties in ASD are associated with multiple robustly discriminative fiber clusters, which belong to several major white matter tracts including the corpus callosum, arcuate fasciculus, uncinate fasciculus and aslant tract; and the white matter structures related to the cerebellum, brain stem, and ventral diencephalon. These discriminative fiber clusters, a small part of the whole brain tractography, represent the white matter connections that could be most affected in ASD. Our results indicate the potential of a machine learning pipeline based on white matter fiber clustering.

YNICL Journal 2017 Journal Article

Acupuncture modulates the abnormal brainstem activity in migraine without aura patients

• Zhengjie Li
• Fang Zeng
• Tao Yin
• Lei Lan
• Nikos Makris
• Kristen Jorgenson
• Taipin Guo
• Feng Wu

Migraine is a common neurological disease with a high prevalence and unsatisfactory treatment options. The specific pathophysiological mechanisms of migraine remain unclear, which restricts the development of effective treatments for this prevalent disorder. The aims of this study were to 1) compare the spontaneous brain activity differences between Migraine without Aura (MwoA) patients and healthy controls (HCs), using amplitude of low-frequency fluctuations (ALFF) calculation method, and 2) explore how an effective treatment (verum acupuncture) could modulate the ALFF of MwoA patients. One hundred MwoA patients and forty-six matched HCs were recruited. Patients were randomized to four weeks' verum acupuncture, sham acupuncture, and waiting list groups. Patients had resting state BOLD-fMRI scan before and after treatment, while HCs only had resting state BOLD-fMRI scan at baseline. Headache intensity, headache frequency, self-rating anxiety and self-rating depression were used for clinical efficacy evaluation. Compared with HCs, MwoA patients showed increased ALFF in posterior insula and putamen/caudate, and reduced ALFF in rostral ventromedial medulla (RVM)/trigeminocervical complex (TCC). After longitudinal verum acupuncture treatment, the decreased ALFF of the RVM/TCC was normalized in migraine patients. Verum acupuncture and sham acupuncture have different modulation effects on ALFF of RVM/TCC in migraine patients. Our results suggest that impairment of the homeostasis of the trigeminovascular nociceptive pathway is involved in the neural pathophysiology of migraines. Effective treatments, such as verum acupuncture, could help to restore this imbalance.

YNICL Journal 2017 Journal Article

Machine-learning classification of 22q11.2 deletion syndrome: A diffusion tensor imaging study

• Daniel S. Tylee
• Zora Kikinis
• Thomas P. Quinn
• Kevin M. Antshel
• Wanda Fremont
• Muhammad A. Tahir
• Anni Zhu
• Xue Gong

Chromosome 22q11.2 deletion syndrome (22q11.2DS) is a genetic neurodevelopmental syndrome that has been studied intensively in order to understand relationships between the genetic microdeletion, brain development, cognitive function, and the emergence of psychiatric symptoms. White matter microstructural abnormalities identified using diffusion tensor imaging methods have been reported to affect a variety of neuroanatomical tracts in 22q11.2DS. In the present study, we sought to combine two discovery-based approaches: (1) white matter query language was used to parcellate the brain's white matter into tracts connecting pairs of 34, bilateral cortical regions and (2) the diffusion imaging characteristics of the resulting tracts were analyzed using a machine-learning method called support vector machine in order to optimize the selection of a set of imaging features that maximally discriminated 22q11.2DS and comparison subjects. With this unique approach, we both confirmed previously-recognized 22q11.2DS-related abnormalities in the inferior longitudinal fasciculus (ILF), and identified, for the first time, 22q11.2DS-related anomalies in the middle longitudinal fascicle and the extreme capsule, which may have been overlooked in previous, hypothesis-guided studies. We further observed that, in participants with 22q11.2DS, ILF metrics were significantly associated with positive prodromal symptoms of psychosis.

YNIMG Journal 2016 Journal Article

A joint compressed-sensing and super-resolution approach for very high-resolution diffusion imaging

• Lipeng Ning
• Kawin Setsompop
• Oleg Michailovich
• Nikos Makris
• Martha E. Shenton
• Carl-Fredrik Westin
• Yogesh Rathi

Diffusion MRI (dMRI) can provide invaluable information about the structure of different tissue types in the brain. Standard dMRI acquisitions facilitate a proper analysis (e. g. tracing) of medium-to-large white matter bundles. However, smaller fiber bundles connecting very small cortical or sub-cortical regions cannot be traced accurately in images with large voxel sizes. Yet, the ability to trace such fiber bundles is critical for several applications such as deep brain stimulation and neurosurgery. In this work, we propose a novel acquisition and reconstruction scheme for obtaining high spatial resolution dMRI images using multiple low resolution (LR) images, which is effective in reducing acquisition time while improving the signal-to-noise ratio (SNR). The proposed method called compressed-sensing super resolution reconstruction (CS-SRR), uses multiple overlapping thick-slice dMRI volumes that are under-sampled in q-space to reconstruct diffusion signal with complex orientations. The proposed method combines the twin concepts of compressed sensing and super-resolution to model the diffusion signal (at a given b-value) in a basis of spherical ridgelets with total-variation (TV) regularization to account for signal correlation in neighboring voxels. A computationally efficient algorithm based on the alternating direction method of multipliers (ADMM) is introduced for solving the CS-SRR problem. The performance of the proposed method is quantitatively evaluated on several in-vivo human data sets including a true SRR scenario. Our experimental results demonstrate that the proposed method can be used for reconstructing sub-millimeter super resolution dMRI data with very good data fidelity in clinically feasible acquisition time.

YNIMG Journal 2016 Journal Article

Corrigendum to “A joint compressed-sensing and super-resolution approach for very high-resolution diffusion imaging”

• Lipeng Ning
• Kawin Setsompop
• Oleg Michailovich
• Nikos Makris
• Martha E. Shenton
• Carl-Fredrik Westin
• Yogesh Rathi

YNICL Journal 2016 Journal Article

Location of lesion determines motor vs. cognitive consequences in patients with cerebellar stroke

• Catherine J. Stoodley
• Jason P. MacMore
• Nikos Makris
• Janet C. Sherman
• Jeremy D. Schmahmann

Cerebellar lesions can cause motor deficits and/or the cerebellar cognitive affective syndrome (CCAS; Schmahmann's syndrome). We used voxel-based lesion-symptom mapping to test the hypothesis that the cerebellar motor syndrome results from anterior lobe damage whereas lesions in the posterolateral cerebellum produce the CCAS. Eighteen patients with isolated cerebellar stroke (13 males, 5 females; 20-66 years old) were evaluated using measures of ataxia and neurocognitive ability. Patients showed a wide range of motor and cognitive performance, from normal to severely impaired; individual deficits varied according to lesion location within the cerebellum. Patients with damage to cerebellar lobules III-VI had worse ataxia scores: as predicted, the cerebellar motor syndrome resulted from lesions involving the anterior cerebellum. Poorer performance on fine motor tasks was associated primarily with strokes affecting the anterior lobe extending into lobule VI, with right-handed finger tapping and peg-placement associated with damage to the right cerebellum, and left-handed finger tapping associated with left cerebellar damage. Patients with the CCAS in the absence of cerebellar motor syndrome had damage to posterior lobe regions, with lesions leading to significantly poorer scores on language (e.g. right Crus I and II extending through IX), spatial (bilateral Crus I, Crus II, and right lobule VIII), and executive function measures (lobules VII-VIII). These data reveal clinically significant functional regions underpinning movement and cognition in the cerebellum, with a broad anterior-posterior distinction. Motor and cognitive outcomes following cerebellar damage appear to reflect the disruption of different cerebro-cerebellar motor and cognitive loops.

YNIMG Journal 2013 Journal Article

Volumetric parcellation methodology of the human hypothalamus in neuroimaging: Normative data and sex differences

• Nikos Makris
• Dick F. Swaab
• Andre van der Kouwe
• Brandon Abbs
• Denise Boriel
• Robert J. Handa
• Stuart Tobet
• Jill M. Goldstein

There is increasing evidence regarding the importance of the hypothalamus for understanding sex differences in relation to neurological, psychiatric, endocrine and sleep disorders. Although different in histology, physiology, connections and function, multiple hypothalamic nuclei subserve non-voluntary functions and are nodal points for the purpose of maintaining homeostasis of the organism. Thus, given the critical importance of hypothalamic nuclei and their key multiple roles in regulating basic functions, it is important to develop the ability to conduct in vivo human studies of anatomic structure, volume, connectivity, and function of hypothalamic regions represented at the level of its nuclei. The goals of the present study were to develop a novel method of semi-automated volumetric parcellation for the human hypothalamus that could be used to investigate clinical conditions using MRI and to demonstrate its applicability. The proposed new method subdivides the hypothalamus into five parcels based on visible anatomic landmarks associated with specific nuclear groupings and was confirmed using two ex vivo hypothalami that were imaged in a 7 T (7T) scanner and processed histologically. Imaging results were compared with histology from the same brain. Further, the method was applied to 44 healthy adults (26 men; 18 women, comparable on age, handedness, ethnicity, SES) to derive normative volumes and assess sex differences in hypothalamic regions using 1. 5 T MRI. Men compared to women had a significantly larger total hypothalamus, relative to cerebrum size, similar for both hemispheres, a difference that was primarily driven by the tuberal region, with the sex effect size being largest in the superior tuberal region and, to a lesser extent, inferior tuberal region. Given the critical role of hypothalamic nuclei in multiple chronic diseases and the importance of sex differences, we argue that the use of the novel methodology presented here will allow for critical investigations of these disorders and further delineation of potential treatments, particularly sex-specific approaches to gene and drug discoveries that involve hypothalamic nuclei.

YNIMG Journal 2011 Journal Article

Covariance modeling of MRI brain volumes in memory circuitry in schizophrenia: Sex differences are critical

• Brandon Abbs
• Lichen Liang
• Nikos Makris
• Ming Tsuang
• Larry J. Seidman
• Jill M. Goldstein

Women have consistently demonstrated better verbal memory on tests that evaluate immediate and delayed free recall. In patients with schizophrenia, these verbal memory processes are relatively more preserved in women than men. However an understanding of the brain anatomy of the female advantage for verbal memory is still unclear. 29 females and 59 males with schizophrenia made comparable to 21 female and 27 male healthy volunteers were scanned using structural magnetic resonance imaging (sMRI) in order to assess volumes of regions across the entire brain. Sex differences within and between groups in the covariance structure of memory circuitry regions were evaluated using a novel approach to covariance analysis (the Box M Test). Brain areas of interest included the prefrontal cortex (PFC), inferior parietal lobule (iPAR), anterior cingulate gyrus (ACG), parahippocampus, and hippocampus (HIPP). Results showed significant differences in the covariance matrices of females and males with schizophrenia compared with their healthy counterparts, in particular the relationships between iPAR–PFC, iPAR–ACG, and HIPP–PFC. Sex differences in the iPAR–PFC relationship were significantly associated with sex differences in verbal memory performance. In control women, but not in men ACG volume correlated strongly with memory performance. In schizophrenia, ACG volume was reduced in females, but not in men, relative to controls. Findings suggest that the relationship between iPAR and PFC is particularly important for understanding the relative preservation of verbal memory processing in females with schizophrenia and may compensate for ACG volume reductions. These results illustrate the utility of a unique covariance structure modeling approach that yields important new knowledge for understanding the nature of schizophrenia.

YNIMG Journal 2009 Journal Article

Time-variant fMRI activity in the brainstem and higher structures in response to acupuncture

• Vitaly Napadow
• Rupali Dhond
• Kyungmo Park
• Jieun Kim
• Nikos Makris
• Kenneth K. Kwong
• Richard E. Harris
• Patrick L. Purdon

Acupuncture modulation of activity in the human brainstem is not well known. This structure is plagued by physiological artifact in neuroimaging experiments. In addition, most studies have used short (<15 min) block designs, which miss delayed responses following longer duration stimulation. We used brainstem-focused cardiac-gated fMRI and evaluated time-variant brain response to longer duration (>30 min) stimulation with verum (VA, electro-stimulation at acupoint ST-36) or sham point (SPA, non-acupoint electro-stimulation) acupuncture. Our results provide evidence that acupuncture modulates brainstem nuclei important to endogenous monoaminergic and opioidergic systems. Specifically, VA modulated activity in the substantia nigra (SN), nucleus raphe magnus, locus ceruleus, nucleus cuneiformis, and periaqueductal gray (PAG). Activation in the ventrolateral PAG was greater for VA compared to SPA. Linearly decreasing time-variant activation, suggesting classical habituation, was found in response to both VA and SPA in sensorimotor (SII, posterior insula, premotor cortex) brain regions. However, VA also produced linearly time-variant activity in limbic regions (amygdala, hippocampus, and SN), which was bimodal and not likely habituation — consisting of activation in early blocks, and deactivation by the end of the run. Thus, acupuncture induces different brain response early, compared to 20–30 min after stimulation. We attribute the fMRI differences between VA and SPA to more varied and stronger psychophysical response induced by VA. Our study demonstrates that acupuncture modulation of brainstem structures can be studied non-invasively in humans, allowing for comparison to animal studies. Our protocol also demonstrates a fMRI approach to study habituation and other time-variant phenomena over longer time durations.

YNIMG Journal 2008 Journal Article

Brain correlates of autonomic modulation: Combining heart rate variability with fMRI

• Vitaly Napadow
• Rupali Dhond
• Giulia Conti
• Nikos Makris
• Emery N. Brown
• Riccardo Barbieri

The central autonomic network (CAN) has been described in animal models but has been difficult to elucidate in humans. Potential confounds include physiological noise artifacts affecting brainstem neuroimaging data, and difficulty in deriving non-invasive continuous assessments of autonomic modulation. We have developed and implemented a new method which relates cardiac-gated fMRI timeseries with continuous-time heart rate variability (HRV) to estimate central autonomic processing. As many autonomic structures of interest are in brain regions strongly affected by cardiogenic pulsatility, we chose to cardiac-gate our fMRI acquisition to increase sensitivity. Cardiac-gating introduces T1-variability, which was corrected by transforming fMRI data to a fixed TR using a previously published method [Guimaraes, A. R. , Melcher, J. R. , et al. , 1998. Imaging subcortical auditory activity in humans. Hum. Brain Mapp. 6(1), 33–41]. The electrocardiogram was analyzed with a novel point process adaptive-filter algorithm for computation of the high-frequency (HF) index, reflecting the time-varying dynamics of efferent cardiovagal modulation. Central command of cardiovagal outflow was inferred by using the resample HF timeseries as a regressor to the fMRI data. A grip task was used to perturb the autonomic nervous system. Our combined HRV-fMRI approach demonstrated HF correlation with fMRI activity in the hypothalamus, cerebellum, parabrachial nucleus/locus ceruleus, periaqueductal gray, amygdala, hippocampus, thalamus, and dorsomedial/dorsolateral prefrontal, posterior insular, and middle temporal cortices. While some regions consistent with central cardiovagal control in animal models gave corroborative evidence for our methodology, other mostly higher cortical or limbic-related brain regions may be unique to humans. Our approach should be optimized and applied to study the human brain correlates of autonomic modulation for various stimuli in both physiological and pathological states.

YNIMG Journal 2007 Journal Article

The occipitofrontal fascicle in humans: A quantitative, in vivo, DT-MRI study

• Nikos Makris
• George M. Papadimitriou
• Scott Sorg
• David N. Kennedy
• Verne S. Caviness
• Deepak N. Pandya

Since the existence of the occipitofrontal fascicle (OFF) in humans has remained controversial, we utilized diffusion tensor imaging (DT-MRI)-based segmentation and tractography to investigate its trajectory in vivo in the human. We found that the OFF is distinct from the subcallosal fasciculus or Muratoff's bundle (MB) and extends from the dorsal and medial parts of the occipital lobe as well as the dorsal, medial and inferior parietal lobules to the dorsal and medial part of the prefrontal and premotor regions. In most of its course, it remains parallel to the corpus callosum, the caudate nucleus and the lateral ventricle. In the coronal plane, the OFF is discerned in the core of the white matter medial to the corona radiata and the superior longitudinal fascicle II (SLF II) and lateral to MB and the corpus callosum. The volumetric measurements of the stem portion of the OFF indicate that the OFF is smaller than the SLF II and the cingulum bundle. Since DT-MRI allows the visualization of OFF fibers leading to the projection areas but not to the origin or termination of these fibers, this has been extrapolated from the experimental data in non-human primates. The OFF may have a role in visual spatial processing along with SLF II.

YNIMG Journal 2006 Journal Article

Automated Brainstem Co-registration (ABC) for MRI

• Vitaly Napadow
• Rupali Dhond
• David Kennedy
• Kathleen K.S. Hui
• Nikos Makris

Group data analysis in brainstem neuroimaging is predicated on accurate co-registration of anatomy. As the brainstem is comprised of many functionally heterogeneous nuclei densely situated adjacent to one another, relatively small errors in co-registration can manifest in increased variance or decreased sensitivity (or significance) in detecting activations. We have devised a 2-stage automated, reference mask guided registration technique (Automated Brainstem Co-registration, or ABC) for improved brainstem co-registration. Our approach utilized a brainstem mask dataset to weight an automated co-registration cost function. Our method was validated through measurement of RMS error at 12 manually defined landmarks. These landmarks were also used as guides for a secondary manual co-registration option, intended for outlier individuals that may not adequately co-register with our automated method. Our methodology was tested on 10 healthy human subjects and compared to traditional co-registration techniques (Talairach transform and automated affine transform to the MNI-152 template). We found that ABC had a significantly lower mean RMS error (1. 22 ± 0. 39 mm) than Talairach transform (2. 88 ± 1. 22 mm, μ ± σ) and the global affine (3. 26 ± 0. 81 mm) method. Improved accuracy was also found for our manual-landmark-guided option (1. 51 ± 0. 43 mm). Visualizing individual brainstem borders demonstrated more consistent and uniform overlap for ABC compared to traditional global co-registration techniques. Improved robustness (lower susceptibility to outliers) was demonstrated with ABC through lower inter-subject RMS error variance compared with traditional co-registration methods. The use of easily available and validated tools (AFNI and FSL) for this method should ease adoption by other investigators interested in brainstem data group analysis.

YNIMG Journal 2006 Journal Article

Human cerebral cortex: A system for the integration of volume- and surface-based representations

• Nikos Makris
• Jonathan Kaiser
• Christian Haselgrove
• Larry J. Seidman
• Joseph Biederman
• Denise Boriel
• Eve M. Valera
• George M. Papadimitriou

We describe an MRI-based system for topological analysis followed by measurements of topographic features for the human cerebral cortex that takes as its starting point volumetric segmentation data. This permits interoperation between volume-based and surface-based topographic analysis and extends the functionality of many existing segmentation schemes. We demonstrate the utility of these operations in individual as well as to group analysis. The methodology integrates analyses of cortical segmentation data generated by manual and semi-automated volumetric morphometry routines (such as the program cardviews) with the procedures of the FreeSurfer program to generate a cortical ribbon of the cerebrum and perform cortical topographic measurements (including thickness, surface area and curvature) in individual subjects as well as in subject populations. This system allows the computation of topographical cortical measurements for segmentation data generated from manual and semi-automated volumetric sources other than FreeSurfer. These measurements can be regionally specific and integrated with systems of cortical parcellation that subdivides the neocortex into gyral-based parcellation units (PUs). This system of topographical analysis of the cerebral cortex is consistent with current views of cortical development and neural systems organization of the human and non-human primate brain.

YNIMG Journal 2006 Journal Article

Regional cortical thickness matters in recall after months more than minutes

• Kristine B. Walhovd
• Anders M. Fjell
• Anders M. Dale
• Bruce Fischl
• Brian T. Quinn
• Nikos Makris
• David Salat
• Ivar Reinvang

The aim of this study was to determine the role of regional cortical thickness in recall of verbal material over an extended time period. MRI scans of healthy adults of varying ages were obtained. Two scans were averaged per person to achieve high spatial resolution, and a semi-automated method for continuous measurement of thickness across the entire cortical mantle was employed. Verbal memory tests assessing recall after 5 min, 30 min, and a mean interval of 83 days were administered. A general linear model (GLM) of the effects of thickness at each vertex on the different memory indices was computed, controlling for gender, age, IQ, and intracranial volume. These analyses were repeated with hippocampal volume as an additional variable to be controlled for, to assess to which extent effects of cortical thickness were independent of hippocampal size. Minute effects of cortical thickness were observed with regard to shorter time intervals (5 and 30 min). However, even when controlling for the effects of hippocampal volume, higher recall across months was associated with thicker cortex of distinct areas including parts of the gyrus rectus, the middle frontal gyrus, the parieto-occipital sulcus and the lingual gyrus of both hemispheres. In addition, hemisphere-specific associations were found in parts of the right temporal and parietal lobe as well as parts of the left precuneus. This supports a unique and critical role of the thickness of distinct cortical areas in recall after months, more than after minutes.

YNIMG Journal 2006 Journal Article

Reliability of MRI-derived measurements of human cerebral cortical thickness: The effects of field strength, scanner upgrade and manufacturer

• Xiao Han
• Jorge Jovicich
• David Salat
• Andre van der Kouwe
• Brian Quinn
• Silvester Czanner
• Evelina Busa
• Jenni Pacheco

In vivo MRI-derived measurements of human cerebral cortex thickness are providing novel insights into normal and abnormal neuroanatomy, but little is known about their reliability. We investigated how the reliability of cortical thickness measurements is affected by MRI instrument-related factors, including scanner field strength, manufacturer, upgrade and pulse sequence. Several data processing factors were also studied. Two test–retest data sets were analyzed: 1) 15 healthy older subjects scanned four times at 2-week intervals on three scanners; 2) 5 subjects scanned before and after a major scanner upgrade. Within-scanner variability of global cortical thickness measurements was <0. 03 mm, and the point-wise standard deviation of measurement error was approximately 0. 12 mm. Variability was 0. 15 mm and 0. 17 mm in average, respectively, for cross-scanner (Siemens/GE) and cross-field strength (1. 5 T/3 T) comparisons. Scanner upgrade did not increase variability nor introduce bias. Measurements across field strength, however, were slightly biased (thicker at 3 T). The number of (single vs. multiple averaged) acquisitions had a negligible effect on reliability, but the use of a different pulse sequence had a larger impact, as did different parameters employed in data processing. Sample size estimates indicate that regional cortical thickness difference of 0. 2 mm between two different groups could be identified with as few as 7 subjects per group, and a difference of 0. 1 mm could be detected with 26 subjects per group. These results demonstrate that MRI-derived cortical thickness measures are highly reliable when MRI instrument and data processing factors are controlled but that it is important to consider these factors in the design of multi-site or longitudinal studies, such as clinical drug trials.

YNIMG Journal 2005 Journal Article

MRI-based surface-assisted parcellation of human cerebellar cortex: an anatomically specified method with estimate of reliability

• Nikos Makris
• John E. Schlerf
• Steven M. Hodge
• Christian Haselgrove
• Matthew D. Albaugh
• Larry J. Seidman
• Scott L. Rauch
• Gordon Harris

We revisit here a surface assisted parcellation (SAP) system of the human cerebellar cortex originally described in Makris, N. , Hodge, S. M. , Haselgrove, C. , Kennedy, D. N. , Dale, A. , Fischl, B. , Rosen, B. R. , Harris, G. , Caviness, V. S. , Jr. , Schmahmann, J. D. , 2003. Human cerebellum: surface-assisted cortical parcellation and volumetry with magnetic resonance imaging. J Cogn Neurosci 15, 584–599. This system preserves the topographic and morphologic uniqueness of the individual cerebellum and allows for volumetric analysis and representation of multimodal structural and functional data on the cerebellar cortex. This methodology integrates features of automated routines of the program FreeSurfer as well as semi-automated and manual procedures of the program Cardviews to create 64 cerebellar parcellation units based on fissure information and anatomical landmarks of the cerebellar surface. Using this technique, we undertook the parcellation of ten cerebella by two independent raters. The reliability of the resulting parcellation units (64 total) was high, with an average Intraclass Correlation Coefficient (ICC) of 0. 724 in the vermis and 0. 853 in the hemispheres. Clusters of parcellation units were then created, based on lobar and connectivity data and functional hypotheses. These 36 clusters, when treated as anatomical units, had an average ICC of 0. 933. Whereas the individual units provide a high level of detail and anatomical specificity, the clusters add flexibility to the analysis by providing higher reliability.

YNIMG Journal 2005 Journal Article

The integrated response of the human cerebro-cerebellar and limbic systems to acupuncture stimulation at ST 36 as evidenced by fMRI

• Kathleen K.S. Hui
• Jing Liu
• Ovidiu Marina
• Vitaly Napadow
• Christian Haselgrove
• Kenneth K. Kwong
• David N. Kennedy
• Nikos Makris

Clinical and experimental data indicate that most acupuncture clinical results are mediated by the central nervous system, but the specific effects of acupuncture on the human brain remain unclear. Even less is known about its effects on the cerebellum. This fMRI study demonstrated that manual acupuncture at ST 36 (Stomach 36, Zusanli), a main acupoint on the leg, modulated neural activity at multiple levels of the cerebro-cerebellar and limbic systems. The pattern of hemodynamic response depended on the psychophysical response to needle manipulation. Acupuncture stimulation typically elicited a composite of sensations termed deqi that is related to clinical efficacy according to traditional Chinese medicine. The limbic and paralimbic structures of cortical and subcortical regions in the telencephalon, diencephalon, brainstem and cerebellum demonstrated a concerted attenuation of signal intensity when the subjects experienced deqi. When deqi was mixed with sharp pain, the hemodynamic response was mixed, showing a predominance of signal increases instead. Tactile stimulation as control also elicited a predominance of signal increase in a subset of these regions. The study provides preliminary evidence for an integrated response of the human cerebro-cerebellar and limbic systems to acupuncture stimulation at ST 36 that correlates with the psychophysical response.

YNIMG Journal 2004 Journal Article

Sequence-independent segmentation of magnetic resonance images

• Bruce Fischl
• David H. Salat
• André J.W. van der Kouwe
• Nikos Makris
• Florent Ségonne
• Brian T. Quinn
• Anders M. Dale

We present a set of techniques for embedding the physics of the imaging process that generates a class of magnetic resonance images (MRIs) into a segmentation or registration algorithm. This results in substantial invariance to acquisition parameters, as the effect of these parameters on the contrast properties of various brain structures is explicitly modeled in the segmentation. In addition, the integration of image acquisition with tissue classification allows the derivation of sequences that are optimal for segmentation purposes. Another benefit of these procedures is the generation of probabilistic models of the intrinsic tissue parameters that cause MR contrast (e. g. , T1, proton density, T2*), allowing access to these physiologically relevant parameters that may change with disease or demographic, resulting in nonmorphometric alterations in MR images that are otherwise difficult to detect. Finally, we also present a high band width multiecho FLASH pulse sequence that results in high signal-to-noise ratio with minimal image distortion due to B0 effects. This sequence has the added benefit of allowing the explicit estimation of T2* and of reducing test–retest intensity variability.

YNIMG Journal 2001 Journal Article

Activation and Habituation in Olfaction—An fMRI Study

• Alexander Poellinger
• Robert Thomas
• Peter Lio
• Anne Lee
• Nikos Makris
• Bruce R. Rosen
• Kenneth K. Kwong

This study investigated human BOLD responses in primary and higher order olfactory cortices following presentation of short- and long-duration odorant stimuli using a 3-T MR scanner. The goal was to identify temporal differences in the course of the response that might underlie habituation. A short-duration stimulus (9 s) consistently activated the primary olfactory cortex (POC). After a long stimulus (60 s), the temporal form of the response differed in different parts of the olfactory network: (1) The POC (piriform, entorhinal cortex, amygdala) and, interestingly, the hippocampus and, to a certain degree, the anterior insula show a short, phasic increase in the signal, followed by a prolonged decrease below baseline. (2) In the orbitofrontal cortex a sustained increase in activation was seen. This increase lasted approximately as long as the duration of odorant presentation (∼60 s). (3) The mediodorsal nucleus of the thalamus and the caudate nucleus responded with an increase in signal which returned to baseline after approximately 15 to 30 s. The correlated biphasic hemodynamic response in the POC, hippocampus, and anterior insula during prolonged olfactory stimulation suggests that these three areas may interact closely with each other in the control of habituation. These results extend recent data which showed habituation of the rat piriform cortex and dissociation between the POC and the orbitofrontal cortex.

YNIMG Journal 2001 Journal Article

Automatic segmentation of the structures in the human brain

• Bruce Fischl
• David Salat
• David Kennedy
• Nikos Makris
• Marilyn Albert
• Ron Killiany
• Anders Dale

YNIMG Journal 1999 Journal Article

MRI-Based Topographic Parcellation of Human Cerebral White Matter

• James W. Meyer
• Nikos Makris
• Julianna F. Bates
• Verne S. Caviness
• David N. Kennedy

We describe a virtually automatic comprehensive parcellation of the human cerebral central white matter, which is based upon T1-weighted MRI scans. The system, which is “rule-based, ” is developed from prior anatomic studies of the human brain and experimental studies of connectivity in animals as elaborated in the companion manuscript. Boundaries which delineate anatomic subregions of the white matter are computed from the geometric features of anatomic landmarks visible in the imaging data. The fiber systems of the central white matter are ordered topographically into three compartments, reflecting the inferred arrangements of principal neural systems pathways. These include an outer radiate (fibers principally radially aligned), an intermediate sagittal (fibers principally sagittally aligned), and deep bridging (fibers bridging hemispheres or cortex and deep structures) compartments. Each of these compartments is secondarily parcellated into smaller units to increase the anatomic specificity and spatial resolution of the system. The principal intended uses for this system of anatomic subdivision are for the volumetric characterization of forebrain white matter in normal and abnormal brains and for precision and specificity of localization in focal lesion-deficit correlation studies.

YNIMG Journal 1999 Journal Article

MRI-Based Topographic Parcellation of Human Cerebral White Matter and Nuclei

• Nikos Makris
• James W. Meyer
• Julianna F. Bates
• Edward H. Yeterian
• David N. Kennedy
• Verne S. Caviness

We describe a system for parcellation of the human cerebral white matter and nuclei, based upon magnetic resonance images. An algorithm for subdivision of the cerebral central white matter according to topographic criteria is developed in the companion manuscript. In the present paper we provide a rationale for this system of parcellation of the central white matter and we extend the system of cerebral parcellation to include principal subcortical gray structures such as the thalamus and the basal ganglia. The volumetric measures of the subcortical gray and white matter parcellation units in 20 young adult brains are computed and reported here as well. In addition, with the comprehensive system for cerebral gray and white matter structure parcellation as reference, we formulate a systematics of forebrain connectivity. The degree to which functionally specific brain areas correspond to topographically specific areas is an open empirical issue. The resolution of this issue requires the development of topographically specific anatomic analyses, such as presented in the current system, and the application of such systems to a comprehensive set of functional–anatomic correlation studies in order to establish the degree of structural–functional correspondence. This system is expected to be applied in both cognitive and clinical neuroscience as an MRI-based topographic systematics of human forebrain anatomy with normative volumetric reference and also as a system of reference for the anatomic organization of specific neural systems as disrupted by focal lesions in lesion–deficit correlations.

YNIMG Journal 1998 Journal Article

Medial Paralimbic and Prefrontal Abnormalities in First-Degree Relatives of Schizophrenia Patients: A Cortical Parcellation Analysis

• Larry J. Seidman
• Stephen V. Faraone
• Jill M. Goldstein
• Julie M. Goodman
• Rosemary Toomey
• Jason Tourville
• David Kennedy
• Nikos Makris

YNIMG Journal 1996 Journal Article

An MRI atlas of the human cerebellum in Talairach space

• Jeremy D. Schmahmann
• Julien Doyon
• Colin Holmes
• Nikos Makris
• Michael Petrides
• David Kennedy
• Alan C. Evans

YNIMG Journal 1996 Journal Article

Human cerebellar cortex: MRI-based topographic parcellation for localization and morphometry

• Nikos Makris
• Jeremy D. Schmahmann
• David N. Kennedy
• Randall R. Benson
• Verne S. Caviness

YNIMG Journal 1996 Journal Article

Parcellation of subcortical gray matter structures in the human brain: A morphometric tool with functional applications

• Julianna F. Bates
• James W. Meyer
• Nikos Makris
• David N. Kennedy
• John W. Belliveau
• Verne S. Caviness

YNIMG Journal 1996 Journal Article

The neuroanatomical damage producing selective deficits to first or second order motion in stroke patients provides further evidence for separate mechanisms

• Lucia M. Vaina
• Nikos Makris
• David Kennedy
• Alan Cowey