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Vivek Prabhakaran

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

17 papers

1 author row

YNIMG Journal 2023 Journal Article

Tractography passes the test: Results from the diffusion-simulated connectivity (disco) challenge

Gabriel Girard
Jonathan Rafael-Patiño
Raphaël Truffet
Dogu Baran Aydogan
Nagesh Adluru
Veena A. Nair
Vivek Prabhakaran
Barbara B. Bendlin

Estimating structural connectivity from diffusion-weighted magnetic resonance imaging is a challenging task, partly due to the presence of false-positive connections and the misestimation of connection weights. Building on previous efforts, the MICCAI-CDMRI Diffusion-Simulated Connectivity (DiSCo) challenge was carried out to evaluate state-of-the-art connectivity methods using novel large-scale numerical phantoms. The diffusion signal for the phantoms was obtained from Monte Carlo simulations. The results of the challenge suggest that methods selected by the 14 teams participating in the challenge can provide high correlations between estimated and ground-truth connectivity weights, in complex numerical environments. Additionally, the methods used by the participating teams were able to accurately identify the binary connectivity of the numerical dataset. However, specific false positive and false negative connections were consistently estimated across all methods. Although the challenge dataset doesn't capture the complexity of a real brain, it provided unique data with known macrostructure and microstructure ground-truth properties to facilitate the development of connectivity estimation methods.

YNIMG Journal 2023 Journal Article

Unified topological inference for brain networks in temporal lobe epilepsy using the Wasserstein distance

Moo K. Chung
Camille Garcia Ramos
Felipe Branco de Paiva
Jedidiah Mathis
Vivek Prabhakaran
Veena A. Nair
Mary E. Meyerand
Bruce P. Hermann

Persistent homology offers a powerful tool for extracting hidden topological signals from brain networks. It captures the evolution of topological structures across multiple scales, known as filtrations, thereby revealing topological features that persist over these scales. These features are summarized in persistence diagrams, and their dissimilarity is quantified using the Wasserstein distance. However, the Wasserstein distance does not follow a known distribution, posing challenges for the application of existing parametric statistical models. To tackle this issue, we introduce a unified topological inference framework centered on the Wasserstein distance. Our approach has no explicit model and distributional assumptions. The inference is performed in a completely data driven fashion. We apply this method to resting-state functional magnetic resonance images (rs-fMRI) of temporal lobe epilepsy patients collected from two different sites: the University of Wisconsin-Madison and the Medical College of Wisconsin. Importantly, our topological method is robust to variations due to sex and image acquisition, obviating the need to account for these variables as nuisance covariates. We successfully localize the brain regions that contribute the most to topological differences. A MATLAB package used for all analyses in this study is available at https://github.com/laplcebeltrami/PH-STAT.

YNIMG Journal 2022 Journal Article

Insights from the IronTract challenge: Optimal methods for mapping brain pathways from multi-shell diffusion MRI

Chiara Maffei
Gabriel Girard
Kurt G. Schilling
Dogu Baran Aydogan
Nagesh Adluru
Andrey Zhylka
Ye Wu
Matteo Mancini

Limitations in the accuracy of brain pathways reconstructed by diffusion MRI (dMRI) tractography have received considerable attention. While the technical advances spearheaded by the Human Connectome Project (HCP) led to significant improvements in dMRI data quality, it remains unclear how these data should be analyzed to maximize tractography accuracy. Over a period of two years, we have engaged the dMRI community in the IronTract Challenge, which aims to answer this question by leveraging a unique dataset. Macaque brains that have received both tracer injections and ex vivo dMRI at high spatial and angular resolution allow a comprehensive, quantitative assessment of tractography accuracy on state-of-the-art dMRI acquisition schemes. We find that, when analysis methods are carefully optimized, the HCP scheme can achieve similar accuracy as a more time-consuming, Cartesian-grid scheme. Importantly, we show that simple pre- and post-processing strategies can improve the accuracy and robustness of many tractography methods. Finally, we find that fiber configurations that go beyond crossing (e.g., fanning, branching) are the most challenging for tractography. The IronTract Challenge remains open and we hope that it can serve as a valuable validation tool for both users and developers of dMRI analysis methods.

YNIMG Journal 2022 Journal Article

Late dominance of the right hemisphere during narrative comprehension

Vahab Youssofzadeh
Lisa Conant
Jeffrey Stout
Candida Ustine
Colin Humphries
William L. Gross
Priyanka Shah-Basak
Jed Mathis

PET and fMRI studies suggest that auditory narrative comprehension is supported by a bilateral multilobar cortical network. The superior temporal resolution of magnetoencephalography (MEG) makes it an attractive tool to investigate the dynamics of how different neuroanatomic substrates engage during narrative comprehension. Using beta-band power changes as a marker of cortical engagement, we studied MEG responses during an auditory story comprehension task in 31 healthy adults. The protocol consisted of two runs, each interleaving 7 blocks of the story comprehension task with 15 blocks of an auditorily presented math task as a control for phonological processing, working memory, and attention processes. Sources at the cortical surface were estimated with a frequency-resolved beamformer. Beta-band power was estimated in the frequency range of 16-24 Hz over 1-sec epochs starting from 400 msec after stimulus onset until the end of a story or math problem presentation. These power estimates were compared to 1-second epochs of data before the stimulus block onset. The task-related cortical engagement was inferred from beta-band power decrements. Group-level source activations were statistically compared using non-parametric permutation testing. A story-math contrast of beta-band power changes showed greater bilateral cortical engagement within the fusiform gyrus, inferior and middle temporal gyri, parahippocampal gyrus, and left inferior frontal gyrus (IFG) during story comprehension. A math-story contrast of beta power decrements showed greater bilateral but left-lateralized engagement of the middle frontal gyrus and superior parietal lobule. The evolution of cortical engagement during five temporal windows across the presentation of stories showed significant involvement during the first interval of the narrative of bilateral opercular and insular regions as well as the ventral and lateral temporal cortex, extending more posteriorly on the left and medially on the right. Over time, there continued to be sustained right anterior ventral temporal engagement, with increasing involvement of the right anterior parahippocampal gyrus, STG, MTG, posterior superior temporal sulcus, inferior parietal lobule, frontal operculum, and insula, while left hemisphere engagement decreased. Our findings are consistent with prior imaging studies of narrative comprehension, but in addition, they demonstrate increasing right-lateralized engagement over the course of narratives, suggesting an important role for these right-hemispheric regions in semantic integration as well as social and pragmatic inference processing.

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

Brain aging in temporal lobe epilepsy: Chronological, structural, and functional

Gyujoon Hwang
Bruce Hermann
Veena A. Nair
Lisa L. Conant
Kevin Dabbs
Jed Mathis
Cole J. Cook
Charlene N. Rivera-Bonet

The association of epilepsy with structural brain changes and cognitive abnormalities in midlife has raised concern regarding the possibility of future accelerated brain and cognitive aging and increased risk of later life neurocognitive disorders. To address this issue we examined age-related processes in both structural and functional neuroimaging among individuals with temporal lobe epilepsy (TLE, N = 104) who were participants in the Epilepsy Connectome Project (ECP). Support vector regression (SVR) models were trained from 151 healthy controls and used to predict TLE patients' brain ages. It was found that TLE patients on average have both older structural (+6.6 years) and functional (+8.3 years) brain ages compared to healthy controls. Accelerated functional brain age (functional - chronological age) was mildly correlated (corrected P = 0.07) with complex partial seizure frequency and the number of anti-epileptic drug intake. Functional brain age was a significant correlate of declining cognition (fluid abilities) and partially mediated chronological age-fluid cognition relationships. Chronological age was the only positive predictor of crystallized cognition. Accelerated aging is evident not only in the structural brains of patients with TLE, but also in their functional brains. Understanding the causes of accelerated brain aging in TLE will be clinically important in order to potentially prevent or mitigate their cognitive deficits.

YNICL Journal 2020 Journal Article

Network, clinical and sociodemographic features of cognitive phenotypes in temporal lobe epilepsy

Bruce Hermann
Lisa L. Conant
Cole J. Cook
Gyujoon Hwang
Camille Garcia-Ramos
Kevin Dabbs
Veena A. Nair
Jedidiah Mathis

This study explored the taxonomy of cognitive impairment within temporal lobe epilepsy and characterized the sociodemographic, clinical and neurobiological correlates of identified cognitive phenotypes. 111 temporal lobe epilepsy patients and 83 controls (mean ages 33 and 39, 57% and 61% female, respectively) from the Epilepsy Connectome Project underwent neuropsychological assessment, clinical interview, and high resolution 3T structural and resting-state functional MRI. A comprehensive neuropsychological test battery was reduced to core cognitive domains (language, memory, executive, visuospatial, motor speed) which were then subjected to cluster analysis. The resulting cognitive subgroups were compared in regard to sociodemographic and clinical epilepsy characteristics as well as variations in brain structure and functional connectivity. Three cognitive subgroups were identified (intact, language/memory/executive function impairment, generalized impairment) which differed significantly, in a systematic fashion, across multiple features. The generalized impairment group was characterized by an earlier age at medication initiation (P < 0.05), fewer patient (P < 0.001) and parental years of education (P < 0.05), greater racial diversity (P < 0.05), and greater number of lifetime generalized seizures (P < 0.001). The three groups also differed in an orderly manner across total intracranial (P < 0.001) and bilateral cerebellar cortex volumes (P < 0.01), and rate of bilateral hippocampal atrophy (P < 0.014), but minimally in regional measures of cortical volume or thickness. In contrast, large-scale patterns of cortical-subcortical covariance networks revealed significant differences across groups in global and local measures of community structure and distribution of hubs. Resting-state fMRI revealed stepwise anomalies as a function of cluster membership, with the most abnormal patterns of connectivity evident in the generalized impairment group and no significant differences from controls in the cognitively intact group. Overall, the distinct underlying cognitive phenotypes of temporal lobe epilepsy harbor systematic relationships with clinical, sociodemographic and neuroimaging correlates. Cognitive phenotype variations in patient and familial education and ethnicity, with linked variations in total intracranial volume, raise the question of an early and persisting socioeconomic-status related neurodevelopmental impact, with additional contributions of clinical epilepsy factors (e.g., lifetime generalized seizures). The neuroimaging features of cognitive phenotype membership are most notable for disrupted large scale cortical-subcortical networks and patterns of functional connectivity with bilateral hippocampal and cerebellar atrophy. The cognitive taxonomy of temporal lobe epilepsy appears influenced by features that reflect the combined influence of socioeconomic, neurodevelopmental and neurobiological risk factors.

YNICL Journal 2018 Journal Article

Psychomotor slowing is associated with anomalies in baseline and prospective large scale neural networks in youth with epilepsy

Camille Garcia-Ramos
Kevin Dabbs
Elizabeth Meyerand
Vivek Prabhakaran
David Hsu
Jana Jones
Michael Seidenberg
Bruce Hermann

Purpose: Psychomotor slowing is a common but understudied cognitive impairment in epilepsy. Here we test the hypothesis that psychomotor slowing is associated with alterations in brain status reflected through analysis of large scale structural networks. We test the hypothesis that children with epilepsy with cognitive slowing at diagnosis will exhibit a cross-sectional and prospective pattern of altered brain development. Methods: A total of 78 children (age 8-18) with new/recent onset idiopathic epilepsies underwent 1.5 T MRI with network analysis of cortical, subcortical and cerebellar volumes. Children with epilepsy were divided into slow and fast psychomotor speed groups (adjusted for age, intelligence and epilepsy syndrome). Results: At baseline, slow-speed performers (SSP) presented lower modularity, lower global efficiency, higher transitivity, and lower number of hubs than fast-speed performers (FSP). Community structure in SSP exhibited poor association between cortical regions and both subcortical structures and the cerebellum while FSP presented well-defined communities. Prospectively, SSP displayed lower modularity but higher global efficiency and transitivity compared to FSP. Modules in FSP showed higher integration between and within themselves compared to SSP. SSP showed hubs mainly from frontal and temporal regions while in FSP were spread among frontal, temporal, parietal, subcortical areas and the left cerebellum. Implications: Results suggest the presence of widespread alterations in large scale networks between fast- and slow-speed children with recent onset epilepsies both at baseline and 2 years later. Slower processing speed appears to be a marker of abnormal brain development antecedent to epilepsy onset as well as brain development over the 2 years following diagnosis.

YNICL Journal 2016 Journal Article

Disruptions in cortico-subcortical covariance networks associated with anxiety in new-onset childhood epilepsy

Camille Garcia-Ramos
Jack J Lin
Leonardo Bonilha
Jana E Jones
Daren C Jackson
Vivek Prabhakaran
Bruce P Hermann

Anxiety disorders represent a prevalent psychiatric comorbidity in both adults and children with epilepsy for which the etiology remains controversial. Neurobiological contributions have been suggested, but only limited evidence suggests abnormal brain volumes particularly in children with epilepsy and anxiety. Since the brain develops in an organized fashion, covariance analyses between different brain regions can be investigated as a network and analyzed using graph theory methods. We examined 46 healthy children (HC) and youth with recent onset idiopathic epilepsies with (n =24) and without (n =62) anxiety disorders. Graph theory (GT) analyses based on the covariance between the volumes of 85 cortical/subcortical regions were investigated. Both groups with epilepsy demonstrated less inter-modular relationships in the synchronization of cortical/subcortical volumes compared to controls, with the epilepsy and anxiety group presenting the strongest modular organization. Frontal and occipital regions in non-anxious epilepsy, and areas throughout the brain in children with epilepsy and anxiety, showed the highest centrality compared to controls. Furthermore, most of the nodes correlating to amygdala volumes were subcortical structures, with the exception of the left insula and the right frontal pole, which presented high betweenness centrality (BC); therefore, their influence in the network is not necessarily local but potentially influencing other more distant regions. In conclusion, children with recent onset epilepsy and anxiety demonstrate large scale disruptions in cortical and subcortical brain regions. Network science may not only provide insight into the possible neurobiological correlates of important comorbidities of epilepsy, but also the ways that cortical and subcortical disruption occurs.

YNICL Journal 2016 Journal Article

Hypercapnic evaluation of vascular reactivity in healthy aging and acute stroke via functional MRI

Ryan V. Raut
Veena A. Nair
Justin A. Sattin
Vivek Prabhakaran

Functional MRI (fMRI) is well-established for the study of brain function in healthy populations, although its clinical application has proven more challenging. Specifically, cerebrovascular reactivity (CVR), which allows the assessment of the vascular response that serves as the basis for fMRI, has been shown to be reduced in healthy aging as well as in a range of diseases, including chronic stroke. However, the timing of when this occurs relative to the stroke event is unclear. We used a breath-hold fMRI task to evaluate CVR across gray matter in a group of acute stroke patients (< 10 days from stroke; N = 22) to address this question. These estimates were compared with those from both age-matched (N = 22) and younger (N = 22) healthy controls. As expected, young controls had the greatest mean CVR, as indicated by magnitude and extent of fMRI activation; however, stroke patients did not differ from age-matched controls. Moreover, the ipsilesional and contralesional hemispheres of stroke patients did not differ with respect to any of these measures. These findings suggest that fMRI remains a valid tool within the first few days of a stroke, particularly for group fMRI studies in which findings are compared with healthy subjects of similar age. However, given the relatively high variability in CVR observed in our stroke sample, caution is warranted when interpreting fMRI data from individual patients or a small cohort. We conclude that a breath-hold task can be a useful addition to functional imaging protocols for stroke patients.

YNICL Journal 2015 Journal Article

Usage of fMRI for pre-surgical planning in brain tumor and vascular lesion patients: Task and statistical threshold effects on language lateralization

Tanvi N. Nadkarni
Matthew J. Andreoli
Veena A. Nair
Peng Yin
Brittany M. Young
Bornali Kundu
Joshua Pankratz
Andrew Radtke

BACKGROUND AND PURPOSE: Functional magnetic resonance imaging (fMRI) is a non-invasive pre-surgical tool used to assess localization and lateralization of language function in brain tumor and vascular lesion patients in order to guide neurosurgeons as they devise a surgical approach to treat these lesions. We investigated the effect of varying the statistical thresholds as well as the type of language tasks on functional activation patterns and language lateralization. We hypothesized that language lateralization indices (LIs) would be threshold- and task-dependent. MATERIALS AND METHODS: Imaging data were collected from brain tumor patients (n = 67, average age 48 years) and vascular lesion patients (n = 25, average age 43 years) who received pre-operative fMRI scanning. Both patient groups performed expressive (antonym and/or letter-word generation) and receptive (tumor patients performed text-reading; vascular lesion patients performed text-listening) language tasks. A control group (n = 25, average age 45 years) performed the letter-word generation task. RESULTS: Brain tumor patients showed left-lateralization during the antonym-word generation and text-reading tasks at high threshold values and bilateral activation during the letter-word generation task, irrespective of the threshold values. Vascular lesion patients showed left-lateralization during the antonym and letter-word generation, and text-listening tasks at high threshold values. CONCLUSION: Our results suggest that the type of task and the applied statistical threshold influence LI and that the threshold effects on LI may be task-specific. Thus identifying critical functional regions and computing LIs should be conducted on an individual subject basis, using a continuum of threshold values with different tasks to provide the most accurate information for surgical planning to minimize post-operative language deficits.

YNIMG Journal 2013 Journal Article

The effect of resting condition on resting-state fMRI reliability and consistency: A comparison between resting with eyes open, closed, and fixated

Rémi Patriat
Erin K. Molloy
Timothy B. Meier
Gregory R. Kirk
Veena A. Nair
Mary E. Meyerand
Vivek Prabhakaran
Rasmus M. Birn

Resting-state fMRI (rs-fMRI) has been demonstrated to have moderate to high reliability and produces consistent patterns of connectivity across a wide variety of subjects, sites, and scanners. However, there is no one agreed upon method to acquire rs-fMRI data. Some sites instruct their subjects, or patients, to lie still with their eyes closed, while other sites instruct their subjects to keep their eyes open or even fixating on a cross during scanning. Several studies have compared those three resting conditions based on connectivity strength. In our study, we assess differences in metrics of test–retest reliability (using an intraclass correlation coefficient), and consistency of the rank-order of connections within a subject and the ranks of subjects for a particular connection from one session to another (using Kendall's W tests). Twenty-five healthy subjects were scanned at three different time points for each resting condition, twice the same day and another time two to three months later. Resting-state functional connectivity measures were evaluated in motor, visual, auditory, attention, and default-mode networks, and compared between the different resting conditions. Of the networks examined, only the auditory network resulted in significantly higher connectivity in the eyes closed condition compared to the other two conditions. No significant between-condition differences in connectivity strength were found in default mode, attention, visual, and motor networks. Overall, the differences in reliability and consistency between different resting conditions were relatively small in effect size but results were found to be significant. Across all within-network connections, and within default-mode, attention, and auditory networks statistically significant greater reliability was found when the subjects were lying with their eyes fixated on a cross. In contrast, primary visual network connectivity was most reliable when subjects had their eyes open (and not fixating on a cross).

YNIMG Journal 2013 Journal Article

The effect of scan length on the reliability of resting-state fMRI connectivity estimates

Rasmus M. Birn
Erin K. Molloy
Rémi Patriat
Taurean Parker
Timothy B. Meier
Gregory R. Kirk
Veena A. Nair
M. Elizabeth Meyerand

There has been an increasing use of functional magnetic resonance imaging (fMRI) by the neuroscience community to examine differences in functional connectivity between normal control groups and populations of interest. Understanding the reliability of these functional connections is essential to the study of neurological development and degenerate neuropathological conditions. To date, most research assessing the reliability with which resting-state functional connectivity characterizes the brain's functional networks has been on scans between 3 and 11min in length. In our present study, we examine the test–retest reliability and similarity of resting-state functional connectivity for scans ranging in length from 3 to 27min as well as for time series acquired during the same length of time but excluding half the time points via sampling every second image. Our results show that reliability and similarity can be greatly improved by increasing the scan lengths from 5min up to 13min, and that both the increase in the number of volumes as well as the increase in the length of time over which these volumes was acquired drove this increase in reliability. This improvement in reliability due to scan length is much greater for scans acquired during the same session. Gains in intersession reliability began to diminish after 9–12min, while improvements in intrasession reliability plateaued around 12–16min. Consequently, new techniques that improve reliability across sessions will be important for the interpretation of longitudinal fMRI studies.

YNIMG Journal 2012 Journal Article

Support vector machine classification and characterization of age-related reorganization of functional brain networks

Timothy B. Meier
Alok S. Desphande
Svyatoslav Vergun
Veena A. Nair
Jie Song
Bharat B. Biswal
Mary E. Meyerand
Rasmus M. Birn

Most of what is known about the reorganization of functional brain networks that accompanies normal aging is based on neuroimaging studies in which participants perform specific tasks. In these studies, reorganization is defined by the differences in task activation between young and old adults. However, task activation differences could be the result of differences in task performance, strategy, or motivation, and not necessarily reflect reorganization. Resting-state fMRI provides a method of investigating functional brain networks without such confounds. Here, a support vector machine (SVM) classifier was used in an attempt to differentiate older adults from younger adults based on their resting-state functional connectivity. In addition, the information used by the SVM was investigated to see what functional connections best differentiated younger adult brains from older adult brains. Three separate resting-state scans from 26 younger adults (18–35yrs) and 26 older adults (55–85) were obtained from the International Consortium for Brain Mapping (ICBM) dataset made publically available in the 1000 Functional Connectomes project www. nitrc. org/projects/fcon_1000. 100 seed-regions from four functional networks with 5mm3 radius were defined based on a recent study using machine learning classifiers on adolescent brains. Time-series for every seed-region were averaged and three matrices of z-transformed correlation coefficients were created for each subject corresponding to each individual's three resting-state scans. SVM was then applied using leave-one-out cross-validation. The SVM classifier was 84% accurate in classifying older and younger adult brains. The majority of the connections used by the classifier to distinguish subjects by age came from seed-regions belonging to the sensorimotor and cingulo-opercular networks. These results suggest that age-related decreases in positive correlations within the cingulo-opercular and default networks, and decreases in negative correlations between the default and sensorimotor networks, are the distinguishing characteristics of age-related reorganization.

YNIMG Journal 2006 Journal Article

Neural correlates of cognitive efficiency

Bart Rypma
Jeffrey S. Berger
Vivek Prabhakaran
Benjamin Martin Bly
Daniel Y. Kimberg
Bharat B. Biswal
Mark D'Esposito

Since its inception, experimental psychology has sought to account for individual differences in human performance. Some neuroimaging research, involving complex behavioral paradigms, has suggested that faster-performing individuals show greater neural activity than slower performers. Other research has suggested that faster-performing individuals show less neural activity than slower performers. To examine the neural basis of individual performance differences, we had participants perform a simple speeded-processing task during fMRI scanning. In some prefrontal cortical (PFC) brain regions, faster performers showed less cortical activity than slower performers while in other PFC and parietal regions they showed greater activity. Regional-causality analysis indicated that PFC exerted more influence over other brain regions for slower than for faster individuals. These results suggest that a critical determinant of individual performance differences is the efficiency of interactions between brain regions and that slower individuals may require more prefrontal executive control than faster individuals to perform successfully.

YNIMG Journal 2001 Journal Article

Rostrolateral Prefrontal Cortex Involvement in Relational Integration during Reasoning

Kalina Christoff
Vivek Prabhakaran
Jennifer Dorfman
Zuo Zhao
James K. Kroger
Keith J. Holyoak
John D.E. Gabrieli

Patient and neuroimaging studies indicate that complex reasoning tasks are associated with the prefrontal cortex (PFC). In this study, we tested the hypothesis that the process of relational integration, or considering multiple relations simultaneously, is a component process of complex reasoning that selectively recruits PFC. We used fMRI to examine brain activation during 0-relational, 1-relational, and 2-relational problems adapted from the Raven's Progressive Matrices and hypothesized that PFC would be preferentially recruited by the 2-relational problem type. Event-related responses were modeled by convolving a canonical hemodynamic response function with the response time (RT) associated with each trial. The results across different analyses revealed the same pattern: PFC activation was specific to the comparison between 2- and 1-relational problems and was not observed in the comparison between 1- and 0-relational problems. Furthermore, the process of relational integration was specifically associated with bilateral rostrolateral PFC (RLPFC; lateral area 10) and right dorsolateral PFC (areas 9 and 46). Left RLPFC showed the greatest specificity by remaining preferentially recruited during 2-relational problems even after comparisons were restricted to trials matched for RT and accuracy. The link between RLPFC and the process of relational integration may be due to the associated process of manipulating self-generated information, a process that may characterize RLPFC function.

YNIMG Journal 1999 Journal Article

Load-Dependent Roles of Frontal Brain Regions in the Maintenance of Working Memory

Bart Rypma
Vivek Prabhakaran
John E. Desmond
Gary H. Glover
John D.E. Gabrieli

Brain imaging studies have suggested a critical role for prefrontal cortex in working memory (WM) tasks that require both maintainenance and manipulation of information over time in delayed-response WM tasks. In the present study, functional magnetic resonance imaging (fMRI) was used to examine whether prefrontal areas are activated when only maintenance is required in a delayed-response WM task, without the overt requirement to manipulate the stored information. In two scans, six subjects performed WM tasks in which, on each trial, they (1) encoded 1, 3, or 6 to-be-remembered letters, (2) maintained these letters across a 5-second unfilled delay, and (3) determined whether a single probe letter was or was not part of the memory set. Activation of left caudal inferior frontal gyrus was observed, relative to the 1-letter task, when subjects were required to maintain 3 letters in WM. When subjects were required to maintain 6 letters in WM, additional prefrontal areas, most notably middle and superior frontal gyri, were activated bilaterally. Thus, increasing the amount of to-be-maintained information, without any overt manipulation requirement, resulted in the recruitment of wide-spread frontal-lobe regions. Inferior frontal gyrus activation was left-hemisphere dominant in both the 3- and 6-letter conditions, suggesting that such activation reflected material-specific verbal processes. Activation in middle and superior frontal gyri appeared only in the 6-letter condition and was right-hemisphere dominant, suggesting that such activation reflected material-independent executive processes.