Hae-Jeong Park

Structural and Functional Brain Networks: From Connections to Cognition

Background The human brain presents a puzzling and challenging paradox: Despite a fixed anatomy, characterized by its connectivity, its functional repertoire is vast, enabling action, perception, and cognition. This contrasts with organs like the heart that have a dynamic anatomy but just one function. The resolution of this paradox may reside in the brains network architecture, which organizes local interactions to cope with diverse environmental demands—ensuring adaptability, robustness, resilience to damage, efficient message passing, and diverse functionality from a fixed structure. This review asks how recent advances in understanding brain networks elucidate the brain’s many-to-one (degenerate) function-structure relationships. In other words, how does diverse function arise from an apparently static neuronal architecture? We conclude that the emergence of dynamic functional connectivity, from static structural connections, calls for formal (computational) approaches to neuronal information processing that may resolve the dialectic between structure and function. Schematic of the multiscale hierarchical organization of brain networks. Brain function or cognition can be described as the global integration of local (segregated) neuronal operations that underlies hierarchical message passing among cortical areas, and which is facilitated by hierarchical modular network architectures. Advances Much of our understanding of brain connectivity rests on the way that it is measured and modeled. We consider two complementary approaches: the first has its basis in graph theory that aims to describe the network topology of (undirected) connections of the sort measured by noninvasive brain imaging of anatomical connections and functional connectivity (correlations) between remote sites. This is compared with model-based definitions of context-sensitive (directed) effective connectivity that are grounded in the biophysics of neuronal interactions. Recent topological network analyses of brain circuits suggest that modular and hierarchical structural networks are particularly suited for the functional integration of local (functionally specialized) neuronal operations that underlie cognition. Measurements of spontaneous activity reveal functional connectivity patterns that are similar to structural connectivity, suggesting that structural networks constrain functional networks. However, task-related responses that require context-sensitive integration disclose a divergence between function and structure that appears to rest mainly on long-range connections. In contrast to methods that describe network topology phenomenologically, model-based theoretical and computational approaches focus on the mechanisms of neuronal interactions that accommodate the dynamic reconfiguration of effective connectivity. We highlight the consilience between hierarchical topologies (based on structural and functional connectivity) and the effective connectivity that would be required for hierarchical message passing of the sort suggested by computational neuroscience. Outlook In summary, neuronal interactions represent dynamics on a fixed structural connectivity that underlie cognition and behavior. Such divergence of function from structure is, perhaps, the most intriguing property of the brain and invites intensive future research. By studying the dynamics and self-organization of functional networks, we may gain insight into the true nature of the brain as the embodiment of the mind. The repertoire of functional networks rests upon the (hidden) structural architecture of connections that enables hierarchical functional integration. Understanding these networks will require theoretical models of neuronal processing that underlies cognition. How rich functionality emerges from the invariant structural architecture of the brain remains a major mystery in neuroscience. Recent applications of network theory and theoretical neuroscience to large-scale brain networks have started to dissolve this mystery. Network analyses suggest that hierarchical modular brain networks are particularly suited to facilitate local (segregated) neuronal operations and the global integration of segregated functions. Although functional networks are constrained by structural connections, context-sensitive integration during cognition tasks necessarily entails a divergence between structural and functional networks. This degenerate (many-to-one) function-structure mapping is crucial for understanding the nature of brain networks. The emergence of dynamic functional networks from static structural connections calls for a formal (computational) approach to neuronal information processing that may resolve this dialectic between structure and function.

DTI and MTR abnormalities in schizophrenia: Analysis of white matter integrity

Diffusion tensor imaging (DTI) studies in schizophrenia demonstrate lower anisotropic diffusion within white matter due either to loss of coherence of white matter fiber tracts, to changes in the number and/or density of interconnecting fiber tracts, or to changes in myelination, although methodology as well as localization of such changes differ between studies. The aim of this study is to localize and to specify further DTI abnormalities in schizophrenia by combining DTI with magnetization transfer imaging (MTI), a technique sensitive to myelin and axonal alterations in order to increase specificity of DTI findings. 21 chronic schizophrenics and 26 controls were scanned using Line-Scan-Diffusion-Imaging and T1-weighted techniques with and without a saturation pulse (MT). Diffusion information was used to normalize co-registered maps of fractional anisotropy (FA) and magnetization transfer ratio (MTR) to a study-specific template, using the multi-channel daemon algorithm, designed specifically to deal with multidirectional tensor information. Diffusion anisotropy was decreased in schizophrenia in the following brain regions: the fornix, the corpus callosum, bilaterally in the cingulum bundle, bilaterally in the superior occipito-frontal fasciculus, bilaterally in the internal capsule, in the right inferior occipito-frontal fasciculus and the left arcuate fasciculus. MTR maps demonstrated changes in the corpus callosum, fornix, right internal capsule, and the superior occipito-frontal fasciculus bilaterally; however, no changes were noted in the anterior cingulum bundle, the left internal capsule, the arcuate fasciculus, or inferior occipito-frontal fasciculus. In addition, the right posterior cingulum bundle showed MTR but not FA changes in schizophrenia. These findings suggest that, while some of the diffusion abnormalities in schizophrenia are likely due to abnormal coherence, or organization of the fiber tracts, some of these abnormalities may, in fact, be attributed to or coincide with myelin/axonal disruption.

White matter hemisphere asymmetries in healthy subjects and in schizophrenia: a diffusion tensor MRI study

Hemisphere asymmetry was explored in normal healthy subjects and in patients with schizophrenia using a novel voxel-based tensor analysis applied to fractional anisotropy (FA) of the diffusion tensor. Our voxel-based approach, which requires precise spatial normalization to remove the misalignment of fiber tracts, includes generating a symmetrical group average template of the diffusion tensor by applying nonlinear elastic warping of the demons algorithm. We then normalized all 32 diffusion tensor MRIs from healthy subjects and 23 from schizophrenic subjects to the symmetrical average template. For each brain, six channels of tensor component images and one T2-weighted image were used for registration to match tensor orientation and shape between images. A statistical evaluation of white matter asymmetry was then conducted on the normalized FA images and their flipped images. In controls, we found left-higher-than-right anisotropic asymmetry in the anterior part of the corpus callosum, cingulum bundle, the optic radiation, and the superior cerebellar peduncle, and right-higher-than-left anisotropic asymmetry in the anterior limb of the internal capsule and the anterior limbs prefrontal regions, in the uncinate fasciculus, and in the superior longitudinal fasciculus. In patients, the asymmetry was lower, although still present, in the cingulum bundle and the anterior corpus callosum, and not found in the anterior limb of the internal capsule, the uncinate fasciculus, and the superior cerebellar peduncle compared to healthy subjects. These findings of anisotropic asymmetry pattern differences between healthy controls and patients with schizophrenia are likely related to neurodevelopmental abnormalities in schizophrenia.

Spatial normalization of diffusion tensor MRI using multiple channels

Diffusion Tensor MRI (DT-MRI) can provide important in vivo information for the detection of brain abnormalities in diseases characterized by compromised neural connectivity. To quantify diffusion tensor abnormalities based on voxel-based statistical analysis, spatial normalization is required to minimize the anatomical variability between studied brain structures. In this article, we used a multiple input channel registration algorithm based on a demons algorithm and evaluated the spatial normalization of diffusion tensor image in terms of the input information used for registration. Registration was performed on 16 DT-MRI data sets using different combinations of the channels, including a channel of T2-weighted intensity, a channel of the fractional anisotropy, a channel of the difference of the first and second eigenvalues, two channels of the fractional anisotropy and the trace of tensor, three channels of the eigenvalues of the tensor, and the six channel tensor components. To evaluate the registration of tensor data, we defined two similarity measures, i.e., the endpoint divergence and the mean square error, which we applied to the fiber bundles of target images and registered images at the same seed points in white matter segmentation. We also evaluated the tensor registration by examining the voxel-by-voxel alignment of tensors in a sample of 15 normalized DT-MRIs. In all evaluations, nonlinear warping using six independent tensor components as input channels showed the best performance in effectively normalizing the tract morphology and tensor orientation. We also present a nonlinear method for creating a group diffusion tensor atlas using the average tensor field and the average deformation field, which we believe is a better approach than a strict linear one for representing both tensor distribution and morphological distribution of the population.

Clustering Fiber Traces Using Normalized Cuts

In this paper we present a framework for unsupervised segmentation of white matter fiber traces obtained from diffusion weighted MRI data. Fiber traces are compared pairwise to create a weighted undirected graph which is partitioned into coherent sets using the normalized cut (N cut) criterion. A simple and yet effective method for pairwise comparison of fiber traces is presented which in combination with the N cut criterion is shown to produce plausible segmentations of both synthetic and real fiber trace data. Segmentations are visualized as colored stream-tubes or transformed to a segmentation of voxel space, revealing structures in a way that looks promising for future explorative studies of diffusion weighted MRI data.

Corpus callosal connection mapping using cortical gray matter parcellation and DT-MRI.

Population maps of the corpus callosum (CC) and cortical lobe connections were generated by combining cortical gray matter parcellation with the diffusion tensor fiber tractography of individual subjects. This method is based on the fact that the cortical lobes of both hemispheres are interconnected by the corpus callosal fibers. T1‐weighted structural MRIs and diffusion tensor MRIs (DT‐MRI) of 22 right‐handed, healthy subjects were used. Forty‐seven cortical parcellations in the dorsal prefrontal cortex, ventral prefrontal cortex, sensory‐motor cortex, parietal cortex, temporal cortex, and occipital cortex were semi‐automatically derived from structural MRIs, registered to DT‐MRI, and used to identify callosal fibers. The probabilistic connections to each cortex were mapped on entire mid‐sagittal CC voxels that had anatomical homology between subjects as determined by spatial registration. According to the population maps of the callosal connections, the ventral prefrontal cortex and parts of the dorsal prefrontal cortex both project fibers through the genu and rostrum. The CC regions through which the superior frontal cortex passes extend into the posterior body. Fibers arising from the parietal lobe and occipital lobe run mainly through the splenium, while fibers arising from the sensory‐motor cortex pass through the isthmus. In general, dorsal or medial cortical lobes project fibers through the dorsal region of the CC, while lateral cortical lobes project fibers through the ventral region of the CC. The probabilistic subdivision of the CC by connecting cortical gray matter provides a more precise understanding of the CC. Hum Brain Mapp 2008.

A randomized trial of mesenchymal stem cells in multiple system atrophy

Neuroprotective or regenerative strategies are invaluable in multiple system atrophy (MSA) due to its rapid progression with fatal prognosis. We evaluated the efficacy of autologous mesenchymal stem cells (MSC) in patients with MSA‐cerebellar type (MSA‐C).

Decreased number and function of endothelial progenitor cells in patients with migraine

Objective: Migraine carries an increased risk for cardiovascular and cerebrovascular diseases that cannot be explained by traditional cardiovascular risk factors. The circulating endothelial progenitor cell (EPC) number is a surrogate biologic marker of vascular function, and diminished EPC counts are associated with higher cardiovascular risk. We investigated whether abnormalities in EPC levels and functions are present in migraine patients. Methods: Consecutive headache patients (n =166) were enrolled, including those with tensiontype headache (TTH; n = 74), migraine without aura (MO; n = 67), and migraine with aura (MA; n = 25). EPC colony-forming units in peripheral blood samples and migratory capacity to chemoattractants (stromal cell-derived factor 1 and vascular endothelial growth factor) and cellular senescence levels were assayed in risk factor-matched subjects (n = 6 per group). Results: The TTH group had more cardiovascular risk factors, more headache days, and higher Framingham risk scores than the other two groups. Mean numbers of EPC colony-forming units were 47.8 ± 24.3 in TTH, 20.4 ±22.2 in MO, and 8.6 ± 10.1 in MA patients (p < 0.001 in TTH vs MO; p = 0.001 in MO vs MA). EPC colony counts of normal subjects (n = 37) were not significantly different from those with TTH. Multiple linear regression models identified only MO, MA, and the presence of migraine (MO + MA) as significant predictors of EPC levels. In addition, EPCs from migraine patients (MO and MA) showed reduced migratory capacity and increased cellular senescence compared with EPCs from TTH or normal subjects. Conclusion: Circulating endothelial progenitor cell (EPC) numbers and functions are reduced in migraine patients, suggesting that EPCs can be an underlying link between migraine and cardiovascular risk. GLOSSARY: ACE= angiotensin-converting enzyme;ATR= angiotensin receptor;β-gal= β-galactosidase; BMI= body mass index; CAD= coronary artery disease; CADASIL= cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy; CFU= colony-forming unit; EBM= endothelial basal medium; EPC= endothelial progenitor cell; HDL= high-density lipoprotein; HPF= high-power field; IL= interleukin; KDR= kinase-insert domain receptor; LDL= low-density lipoprotein; MA= migraine with aura; MO= migraine without aura; PBS= phosphate-buffered saline; SA-β-gal= senescence-associated β-galactosidase; SDF-1= stromal cell–derived factor 1; TNF= tumor necrosis factor; TTH= tension-type headache; VEGF= vascular endothelial growth factor.

White matter abnormalities associated with auditory hallucinations in schizophrenia: A combined study of voxel-based analyses of diffusion tensor imaging and structural magnetic resonance imaging

White matter (WM) abnormalities in schizophrenia may offer important clues to a better understanding of the disconnectivity associated with the disorder. The aim of this study was to elucidate a WM basis of auditory hallucinations in schizophrenia through the simultaneous investigation of WM tract integrity and WM density. Diffusion tensor images (DTIs) and structural T1 magnetic resonance images (MRIs) were taken from 15 hallucinating schizophrenic patients, 15 non-hallucinating schizophrenic patients and 22 normal controls. Voxel-based analyses and post-hoc region of interest analyses were obtained to compare the three groups on fractional anisotropy (FA) derived from DTI as well as WM density derived from structural MRIs. In both the hallucinating and non-hallucinating groups, FA of the WM regions was significantly decreased in the left superior longitudinal fasciculus (SLF), whereas WM density was significantly increased in the left inferior longitudinal fasciculus (ILF). The mean FA value of the left frontal part of the SLF was positively correlated with the severity score of auditory hallucinations in the hallucinating patient group. Our findings show that WM changes were mainly observed in the frontal and temporal areas, suggesting that disconnectivity in the left fronto-temporal area may contribute to the pathophysiology of schizophrenia. In addition, pathologic WM changes in this region may be an important step in the development of auditory hallucinations in schizophrenia.

Fornix Integrity and Hippocampal Volume in Male Schizophrenic Patients

BACKGROUND The hippocampus has been shown to be abnormal in schizophrenia. The fornix is one of the main fiber tracts connecting the hippocampus with other brain regions. Few studies have evaluated the fornix in schizophrenia, however. A focus on fornix abnormalities and their association with hippocampal abnormalities might figure importantly in our understanding of the pathophysiology of schizophrenia. METHODS Line-scan diffusion tensor imaging (DTI) was used to evaluate diffusion in the fornix in 24 male patients with chronic schizophrenia and 31 male control subjects. Maps of fractional anisotropy (FA) and mean diffusivity (D(m)), which are indices sensitive to white-matter integrity, were generated to quantify diffusion within the fornix. We used high spatial resolution magnetic resonance imaging (MRI) to measure hippocampal volume. RESULTS FA and cross-sectional area of the fornix were significantly reduced in patients compared with control subjects. D(m) was significantly increased, whereas hippocampal volume was bilaterally reduced in patients. Reduced hippocampal volume was correlated with increased mean D(m) and reduced cross-sectional area of the fornix for patients. Patients also showed a significant correlation between reduced scores on neuropsychologic measures of declarative-episodic memory and reduced hippocampal volumes. CONCLUSIONS These findings demonstrate a disruption in fornix integrity in patients with schizophrenia.