Enhanced brain connectivity in long-term meditation practitioners.
ABSTRACT: Very little is currently known about the cerebral characteristics that underlie the complex processes of meditation as only a limited number of studies have addressed this topic. Research exploring structural connectivity in meditation practitioners is particularly rare. We thus acquired diffusion tensor imaging (DTI) data of high angular and spatial resolution and used atlas-based tract mapping methods to investigate white matter fiber characteristics in a well-matched sample of long-term meditators and controls (n=54). A broad field mapping approach estimated the fractional anisotropy (FA) for twenty different fiber tracts (i.e., nine tracts in each hemisphere and two inter-hemispheric tracts) that were subsequently used as dependent measures. Results showed pronounced structural connectivity in meditators compared to controls throughout the entire brain within major projection pathways, commissural pathways, and association pathways. The largest group differences were observed within the corticospinal tract, the temporal component of the superior longitudinal fasciculus, and the uncinate fasciculus. While cross-sectional studies represent a good starting point for elucidating possible links between meditation and white matter fiber characteristics, longitudinal studies will be necessary to determine the relative contribution of nature and nurture to enhanced structural connectivity in long-term meditators.
Project description:Recent findings suggest a close link between long-term meditation practices and the structure of the corpus callosum. Prior analyses, however, have focused on estimating mean fractional anisotropy (FA) within two large pre-defined callosal tracts only. Additional effects might exist in other, non-explored callosal regions and/or with respect to callosal attributes not captured by estimates of FA. To further explore callosal features in the framework of meditation, we analyzed 30 meditators and 30 controls, carefully matched for sex, age, and handedness. We applied a multimodal imaging approach using diffusion tensor imaging (DTI) in combination with structural magnetic resonance imaging (MRI). Callosal measures of tract-specific FA were complemented with other global (segment-specific) estimates as well as extremely local (point-wise) measures of callosal micro- and macro-structure. Callosal measures were larger in long-term meditators compared to controls, particularly in anterior callosal sections. However, differences achieved significance only when increasing the regional sensitivity of the measurement (i.e., using point-wise measures versus segment-specific measures) and were more prominent for microscopic than macroscopic characteristics (i.e., callosal FA versus callosal thickness). Thicker callosal regions and enhanced FA in meditators might indicate greater connectivity, possibly reflecting increased hemispheric integration during cerebral processes involving (pre)frontal regions. Such a brain organization might be linked to achieving characteristic mental states and skills as associated with meditation, though this hypothesis requires behavioral confirmation. Moreover, longitudinal studies are required to address whether the observed callosal effects are induced by meditation or constitute an innate prerequisite for the start or successful continuation of meditation.
Project description:OBJECTIVE:This study aimed to investigate the characteristic of brain structural connections in glioma patients and further evaluate the relationship between changes in the white matter tracts and cognitive decline. METHODS:This retrospective study included a total of 35 subjects with glioma and 14 demographically matched healthy controls, who underwent diffusion tensor imaging scans and formal neuropsychological assessment tests. Fractional anisotropy (FA) values of white matter tracts were derived from atlas-based analysis to compare group differences. Furthermore, subgroup-level analysis was performed to differentiate the effects of tumor location on white matter tracts. Partial correlation analysis was used to examine the associations between neurocognitive assessments and the integrity of tracts. Region of interest-based network analysis was performed to validate the alteration of structural brain network in subjects with glioma. RESULTS:Compared with controls, subjects with glioma exhibited reduced FA values in the right uncinate fasciculus. Besides, subjects with glioma exhibited worse performance in several cognitive assessments. Partial correlation analysis indicated that the FA value in the right superior longitudinal fasciculus temporal part was significantly positively correlated with scores of visual-spatial abilities in subjects with glioma in the right temporal lobe (r = .932, p = .002). Region of interest-based network analysis revealed that subjects with glioma exhibited reduced FA, fiber length (FL), and fiber number (FN) between specific brain regions compared with controls. CONCLUSION:The present study demonstrated the reduced integrity of white matter tracts and altered structural connectivity in brain networks in patients with glioma. Notably, white matter tracts in the right hemisphere might be vulnerable to the effects of a frontal or temporal lesion and might be associated with deficient cognitive function.
Project description:This paper introduces a Bidirectional Iterative Parcellation (BIP) procedure designed to identify the location and size of connected cortical regions (parcellations) at both ends of a white matter tract in diffusion weighted images. The procedure applies the FSL option "probabilistic tracking with classification targets" in a bidirectional and iterative manner. To assess the utility of BIP, we applied the procedure to the problem of parcellating a limited set of well-established gray matter seed regions associated with the dorsal (arcuate fasciculus/superior longitudinal fasciculus) and ventral (extreme capsule fiber system) white matter tracts in the language networks of 97 participants. These left hemisphere seed regions and the two white matter tracts, along with their right hemisphere homologues, provided an excellent test case for BIP because the resulting parcellations overlap and their connectivity via the arcuate fasciculi and extreme capsule fiber systems are well studied. The procedure yielded both confirmatory and novel findings. Specifically, BIP confirmed that each tract connects within the seed regions in unique, but expected ways. Novel findings included increasingly left-lateralized parcellations associated with the arcuate fasciculus/superior longitudinal fasciculus as a function of age and education. These results demonstrate that BIP is an easily implemented technique that successfully confirmed cortical connectivity patterns predicted in the literature, and has the potential to provide new insights regarding the architecture of the brain.
Project description:To identify structural connectivity change occurring during the first 6 months after traumatic brain injury and to evaluate the utility of diffusion tensor tractography for predicting long-term outcome.The participants were 28 patients with mild to severe traumatic axonal injury and 20 age- and sex-matched healthy control subjects. Neuroimaging was obtained 0-9 days postinjury for acute scans and 6-14 months postinjury for chronic scans. Long-term outcome was evaluated on the day of the chronic scan. Twenty-eight fiber regions of 9 major white matter structures were reconstructed, and reliable tractography measurements were determined and used.Although most (23 of 28) patients had severe brain injury, their long-term outcome ranged from good recovery (16 patients) to moderately (5 patients) and severely disabled (7 patients). In concordance with the diverse outcome, the white matter change in patients was heterogeneous, ranging from improved structural connectivity, through no change, to deteriorated connectivity. At the group level, all 9 fiber tracts deteriorated significantly with 7 (corpus callosum, cingulum, angular bundle, cerebral peduncular fibers, uncinate fasciculus, and inferior longitudinal and fronto-occipital fasciculi) showing structural damage acutely and 2 (fornix body and left arcuate fasciculus) chronically. Importantly, the amount of change in tractography measurements correlated with patients' long-term outcome. Acute tractography measurements were able to predict patients' learning and memory performance; chronic measurements also determined performance on processing speed and executive function.Diffusion tensor tractography is a valuable tool for identifying structural connectivity changes occurring between the acute and chronic stages of traumatic brain injury and for predicting patients' long-term outcome.
Project description:The fragile X mental retardation 1 (FMR1) gene plays an important role in the development and maintenance of neuronal circuits that are essential for cognitive functioning. We explored the functional linkage(s) among lymphocytic FMR1 gene expression, brain structure, and working memory in healthy adult males. We acquired T1-weighted and diffusion tensor imaging from 37 males (18-80 years, mean ± SD= 40.7 ± 17.3 years) with normal FMR1 alleles and performed genetic and working memory assessments. Brain measurements were obtained from fiber tracts important for working memory (i.e. the arcuate fasciculus, anterior cingulum bundle, inferior longitudinal fasciculus, and the genu and anterior body of the corpus callosum), individual voxels, and whole brain. Both FMR1 mRNA and protein (FMRP) levels exhibited significant associations with brain measurements, with FMRP correlating positively with gray matter volume and white matter structural organization, and FMR1 mRNA negatively with white matter structural organization. The correlation was widespread, impacting rostral white matter and 2 working-memory fiber tracts for FMRP, and all cerebral white matter areas except the fornix and cerebellar peduncles and all 4 fiber tracts for FMR1 mRNA. In addition, the levels of FMR1 mRNA as well as the fiber tracts demonstrated a significant correlation with working memory performance. While FMR1 mRNA exhibited a negative correlation with working memory, fiber tract structural organization showed a positive correlation. These findings suggest that the FMR1 gene is a genetic factor common for both working memory and brain structure, and has implications for our understanding of the transmission of intelligence and brain structure.
Project description:The extended face network contains clusters of neurons that perform distinct functions on facial stimuli. Regions in the posterior ventral visual stream appear to perform basic perceptual functions on faces, while more anterior regions, such as the ventral anterior temporal lobe and amygdala, function to link mnemonic and affective information to faces. Anterior and posterior regions are interconnected by a long-range white matter tracts; however, it is not known if variation in connectivity of these pathways explains cognitive performance.Here, we used diffusion imaging and deterministic tractography in a cohort of 28 neurologically normal adults ages 18-28 to examine microstructural properties of visual fiber pathways and their relationship to certain mnemonic and affective functions involved in face processing. We investigated how inter-individual variability in two tracts, the inferior longitudinal fasciculus (ILF) and the inferior fronto-occipital fasciculus (IFOF), related to performance on tests of facial emotion recognition and face memory.Results revealed that microstructure of both tracts predicted variability in behavioral performance indexed by both tasks, suggesting that the ILF and IFOF play a role in facilitating our ability to discriminate emotional expressions in faces, as well as to remember unique faces. Variation in a control tract, the uncinate fasciculus, did not predict performance on these tasks.These results corroborate and extend the findings of previous neuropsychology studies investigating the effects of damage to the ILF and IFOF, and demonstrate that differences in face processing abilities are related to white matter microstructure, even in healthy individuals.
Project description: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.
Project description:FMRI data described here was recorded during resting-state in Mindfulness Meditators (MM) and control participants (see "Task-induced activity and resting-state fluctuations undergo similar alterations in visual and DMN areas of long-term meditators" Berkovich-Ohana et al. (2016)  for details). MM participants were also scanned during meditation. Analyses focused on functional connectivity within and between the default mode network (DMN) and visual network (Vis). Here we show data demonstrating that: 1) Functional connectivity within the DMN and the Visual networks were higher in the control group than in the meditators; 2) Data show an increase for the functional connectivity between the DMN and the Visual networks in the meditators compared to controls; 3) Data demonstrate that functional connectivity both within and between networks reduces during meditation, compared to the resting-state; and 4) A significant negative correlation was found between DMN functional connectivity and meditation expertise. The reader is referred to Berkovich-Ohana et al. (2016)  for further interpretation and discussion.
Project description:A convergent line of neuroscientific evidence suggests that meditation alters the functional and structural plasticity of distributed neural processes underlying attention and emotion. The purpose of this study was to examine the brain structural differences between a well-matched sample of long-term meditators and controls. We employed whole-brain cortical thickness analysis based on magnetic resonance imaging, and diffusion tensor imaging to quantify white matter integrity in the brains of 46 experienced meditators compared with 46 matched meditation-naïve volunteers. Meditators, compared with controls, showed significantly greater cortical thickness in the anterior regions of the brain, located in frontal and temporal areas, including the medial prefrontal cortex, superior frontal cortex, temporal pole and the middle and interior temporal cortices. Significantly thinner cortical thickness was found in the posterior regions of the brain, located in the parietal and occipital areas, including the postcentral cortex, inferior parietal cortex, middle occipital cortex and posterior cingulate cortex. Moreover, in the region adjacent to the medial prefrontal cortex, both higher fractional anisotropy values and greater cortical thickness were observed. Our findings suggest that long-term meditators have structural differences in both gray and white matter.
Project description:BACKGROUND:Advances in white matter tractography enhance neurosurgical planning and glioma resection, but white matter tractography is limited by biological variables such as edema, mass effect, and tract infiltration or selection biases related to regions of interest or fractional anisotropy values. OBJECTIVE:To provide an automated tract identification paradigm that corrects for artifacts created by tumor edema and infiltration and provides a consistent, accurate method of fiber bundle identification. METHODS:An automated tract identification paradigm was developed and evaluated for glioma surgery. A fiber bundle atlas was generated from 6 healthy participants. Fibers of a test set (including 3 healthy participants and 10 patients with brain tumors) were clustered adaptively with this atlas. Reliability of the identified tracts in both groups was assessed by comparison with 2 experts with the Cohen ? used to quantify concurrence. We evaluated 6 major fiber bundles: cingulum bundle, fornix, uncinate fasciculus, arcuate fasciculus, inferior fronto-occipital fasciculus, and inferior longitudinal fasciculus, the last 3 tracts mediating language function. RESULTS:The automated paradigm demonstrated a reliable and practical method to identify white mater tracts, despite mass effect, edema, and tract infiltration. When the tumor demonstrated significant mass effect or shift, the automated approach was useful for providing an initialization to guide the expert with identification of the specific tract of interest. CONCLUSION:We report a reliable paradigm for the automated identification of white matter pathways in patients with gliomas. This approach should enhance the neurosurgical objective of maximal safe resections. ABBREVIATIONS:AF, arcuate fasciculusDTI, diffusion tensor imagingIFOF, inferior fronto-occipital fasciculusILF, inferior longitudinal fasciculusROI, region of interestWM, white matter.