Network specialization during adolescence: Hippocampal effective connectivity in boys and girls.

Adolescence is a complex period of concurrent mental and physical development that facilitates adult functioning at multiple levels. Despite the growing number of neuroimaging studies of cognitive development in adolescence focusing on regional activation patterns, there remains a paucity of information about the functional interactions across these participating regions that are critical for cognitive functioning, including memory. The current study used structural equation modeling (SEM) to determine how interactions among brain regions critical for memory change over the course of adolescence. We obtained functional MRI in 77 individuals aged 8-16 years old, divided into younger (ages 8-10) and older (ages > 11) cohorts, using an incidental encoding memory task to activate hippocampus formation and associated brain networks, as well as behavioral data on memory function. SEM was performed on the imaging data for four groups (younger girls, younger boys, older girls, and older boys) that were subsequently compared using a stacked model approach. Significant differences were seen between the models for these groups. Younger boys had a predominantly posterior distribution of connections originating in primary visual regions and terminating on multi-modal processing regions. In older boys, there was a relatively greater anterior connection distribution, with increased effective connectivity within association and multi-modal processing regions. Connection patterns in younger girls were similar to those of older boys, with a generally anterior-posterior distributed network among sensory, multi-modal, and limbic regions. In contrast, connections in older girls were widely distributed but relatively weaker. Memory performance increased with age, without a significant difference between the sexes. These findings suggest a progressive reorganization among brain regions, with a commensurate increase in efficiency of cognitive functioning, from younger to older individuals in both girls and boys, providing insight into the age- and gender-specific processes at play during this critical transition period.

Loss of intrinsic organization of cerebellar networks in spinocerebellar ataxia type 1: correlates with disease severity and duration.

The spinocerebellar ataxias (SCAs) are a genetically heterogeneous group of cerebellar degenerative disorders, characterized by progressive gait unsteadiness, hand incoordination, and dysarthria. The mutational mechanism in SCA1, a dominantly inherited form of SCA, consists of an expanded trinucleotide CAG repeat. In SCA1, there is loss of Purkinje cells, neuronal loss in dentate nucleus, olives, and pontine nuclei. In the present study, we sought to apply intrinsic functional connectivity analysis combined with diffusion tensor imaging to define the state of cerebellar connectivity in SCA1. Our results on the intrinsic functional connectivity in lateral cerebellum and thalamus showed progressive organizational changes in SCA1 noted as a progressive increase in the absolute value of the correlation coefficients. In the lateral cerebellum, the anatomical organization of functional clusters seen as parasagittal bands in controls is lost, changing to a patchy appearance in SCA1. Lastly, only fractional anisotropy in the superior peduncle and changes in functional organization in thalamus showed a linear dependence to duration and severity of disease. The present pilot work represents an initial effort describing connectivity biomarkers of disease progression in SCA1. The functional changes detected with intrinsic functional analysis and diffusion tensor imaging suggest that disease progression can be analyzed as a disconnection syndrome.

Test-retest reliability in fMRI of language: group and task effects.

This paper explores how the test-retest reliability is modulated by different groups of participants and experimental tasks. A group of 12 healthy participants and a group of nine stroke patients performed the same language imaging experiment twice, test and retest, on different days. The experiment consists of four conditions, one audio condition and three audiovisual conditions in which the hands are either resting, gesturing, or performing self-adaptive movements. Imaging data were analyzed using multiple linear regression and the results were further used to generate receiver operating characteristic (ROC) curves for each condition for each individual subject. By using area under the curve as a comparison index, we found that stroke patients have less reliability across time than healthy participants, and that when the participants gesture during speech, their imaging data are more reliable than when they are performing hand movements that are not speech-associated. Furthermore, inter-subject variability is less in the gesture task than in any of the other three conditions for healthy participants, but not for stroke patients.

Functional Mechanisms of Recovery after Chronic Stroke: Modeling with the Virtual Brain.

We have seen important strides in our understanding of mechanisms underlying stroke recovery, yet effective translational links between basic and applied sciences, as well as from big data to individualized therapies, are needed to truly develop a cure for stroke. We present such an approach using The Virtual Brain (TVB), a neuroinformatics platform that uses empirical neuroimaging data to create dynamic models of an individual's human brain; specifically, we simulate fMRI signals by modeling parameters associated with brain dynamics after stroke. In 20 individuals with stroke and 11 controls, we obtained rest fMRI, T1w, and diffusion tensor imaging (DTI) data. Motor performance was assessed pre-therapy, post-therapy, and 6-12 months post-therapy. Based on individual structural connectomes derived from DTI, the following steps were performed in the TVB platform: (1) optimization of local and global parameters (conduction velocity, global coupling); (2) simulation of BOLD signal using optimized parameter values; (3) validation of simulated time series by comparing frequency, amplitude, and phase of the simulated signal with empirical time series; and (4) multivariate linear regression of model parameters with clinical phenotype. Compared with controls, individuals with stroke demonstrated a consistent reduction in conduction velocity, increased local dynamics, and reduced local inhibitory coupling. A negative relationship between local excitation and motor recovery, and a positive correlation between local dynamics and motor recovery were seen. TVB reveals a disrupted post-stroke system favoring excitation-over-inhibition and local-over-global dynamics, consistent with existing mammal literature on stroke mechanisms. Our results point to the potential of TVB to determine individualized biomarkers of stroke recovery.

The Virtual Brain: Modeling Biological Correlates of Recovery after Chronic Stroke.

There currently remains considerable variability in stroke survivor recovery. To address this, developing individualized treatment has become an important goal in stroke treatment. As a first step, it is necessary to determine brain dynamics associated with stroke and recovery. While recent methods have made strides in this direction, we still lack physiological biomarkers. The Virtual Brain (TVB) is a novel application for modeling brain dynamics that simulates an individual's brain activity by integrating their own neuroimaging data with local biophysical models. Here, we give a detailed description of the TVB modeling process and explore model parameters associated with stroke. In order to establish a parallel between this new type of modeling and those currently in use, in this work we establish an association between a specific TVB parameter (long-range coupling) that increases after stroke with metrics derived from graph analysis. We used TVB to simulate the individual BOLD signals for 20 patients with stroke and 10 healthy controls. We performed graph analysis on their structural connectivity matrices calculating degree centrality, betweenness centrality, and global efficiency. Linear regression analysis demonstrated that long-range coupling is negatively correlated with global efficiency (P = 0.038), but is not correlated with degree centrality or betweenness centrality. Our results suggest that the larger influence of local dynamics seen through the long-range coupling parameter is closely associated with a decreased efficiency of the system. We thus propose that the increase in the long-range parameter in TVB (indicating a bias toward local over global dynamics) is deleterious because it reduces communication as suggested by the decrease in efficiency. The new model platform TVB hence provides a novel perspective to understanding biophysical parameters responsible for global brain dynamics after stroke, allowing the design of focused therapeutic interventions.

In vivo parahippocampal white matter pathology as a biomarker of disease progression to Alzheimer's disease.

Noninvasive diagnostic tests for Alzheimer's disease (AD) are limited. Postmortem diagnosis is based on density and distribution of neurofibrillary tangles (NFTs) and amyloid-rich neuritic plaques. In preclinical stages of AD, the cells of origin for the perforant pathway within the entorhinal cortex are among the first to display NFTs, indicating its compromise in early stages of AD. We used diffusion tensor imaging (DTI) to assess the integrity of the parahippocampal white matter in mild cognitive impairment (MCI) and AD, as a first step in developing a noninvasive tool for early diagnosis. Subjects with AD (N = 9), MCI (N = 8), or no cognitive impairment (NCI; N = 20) underwent DTI-MRI. Fractional anisotropy (FA) and mean (MD) and radial (RD) diffusivity measured from the parahippocampal white matter in AD and NCI subjects differed greatly. Discriminant analysis in the MCI cases assigned statistical membership of 38% of MCI subjects to the AD group. Preliminary data 1 year later showed that all MCI cases assigned to the AD group either met the diagnostic criteria for probable AD or showed significant cognitive decline. Voxelwise analysis in the parahippocampal white matter revealed a progressive change in the DTI patterns in MCI and AD subjects: whereas converted MCI cases showed structural changes restricted to the anterior portions of this region, in AD the pathology was generalized along the entire anterior-posterior axis. The use of DTI for in vivo assessment of the parahippocampal white matter may be useful for identifying individuals with MCI at highest risk for conversion to AD and for assessing disease progression.

A network model of observation and imitation of speech.

Much evidence has now accumulated demonstrating and quantifying the extent of shared regional brain activation for observation and execution of speech. However, the nature of the actual networks that implement these functions, i.e., both the brain regions and the connections among them, and the similarities and differences across these networks has not been elucidated. The current study aims to characterize formally a network for observation and imitation of syllables in the healthy adult brain and to compare their structure and effective connectivity. Eleven healthy participants observed or imitated audiovisual syllables spoken by a human actor. We constructed four structural equation models to characterize the networks for observation and imitation in each of the two hemispheres. Our results show that the network models for observation and imitation comprise the same essential structure but differ in important ways from each other (in both hemispheres) based on connectivity. In particular, our results show that the connections from posterior superior temporal gyrus and sulcus to ventral premotor, ventral premotor to dorsal premotor, and dorsal premotor to primary motor cortex in the left hemisphere are stronger during imitation than during observation. The first two connections are implicated in a putative dorsal stream of speech perception, thought to involve translating auditory speech signals into motor representations. Thus, the current results suggest that flow of information during imitation, starting at the posterior superior temporal cortex and ending in the motor cortex, enhances input to the motor cortex in the service of speech execution.

Age-related connectivity changes in fMRI data from children listening to stories.

The way humans comprehend narrative speech plays an important part in human development and experience. A group of 313 children with ages 5-18 were subjected to a large-scale functional magnetic resonance imaging (fMRI) study in order to investigate the neural correlates of auditory narrative comprehension. The results were analyzed to investigate the age-related brain activity changes involved in the narrative language comprehension circuitry. We found age-related differences in brain activity which may either reflect changes in local neuroplasticity (of the regions involved) in the developing brain or a more global transformation of brain activity related to neuroplasticity. To investigate this issue, Structural Equation Modeling (SEM) was applied to the results obtained from a group independent component analysis (Schmithorst, V.J., Holland, S.K., et al., 2005. Cognitive modules utilized for narrative comprehension in children: a functional magnetic resonance imaging study. NeuroImage) and the age-related differences were examined in terms of changes in path coefficients between brain regions. The group Independent Component Analysis (ICA) had identified five bilateral task-related components comprising the primary auditory cortex, the mid-superior temporal gyrus, the most posterior aspect of the superior temporal gyrus, the hippocampus, the angular gyrus and the medial aspect of the parietal lobule (precuneus/posterior cingulate). Furthermore, a left-lateralized network (sixth component) was also identified comprising the inferior frontal gyrus (including Broca's area), the inferior parietal lobule, and the medial temporal gyrus. The components (brain regions) for the SEM were identified based on the ICA maps and the results are discussed in light of recent neuroimaging studies corroborating the functional segregation of Broca's and Wernicke's areas and the important role played by the right hemisphere in narrative comprehension. The classical Wernicke-Geschwind (WG) model for speech processing is expanded to a two-route model involving a direct route between Broca's and Wernicke's area and an indirect route involving the parietal lobe.

Fine modulation in network activation during motor execution and motor imagery.

Motor imagery, the 'mental rehearsal of motor acts without overt movements', involves either a visual representation (visual imagery, VI) or mental simulation of movement, associated with a kinesthetic feeling (kinetic imagery, KI). Previous brain imaging work suggests that patterns of brain activation differ when comparing execution (E) with either type of imagery but the functional connectivity of the participating networks has not been studied. Using functional magnetic resonance imaging (fMRI) and structural equation modeling, this study elucidates the inter-relationships among the relevant areas for each of the three motor behaviors. Our results suggest that networks underlying these behaviors are not identical, despite the extensive overlap between E and KI. Inputs to M1, which are facilitatory during E, have the opposite effect during KI, suggesting a physiological mechanism whereby the system prevents overt movements. Finally, this study highlights the role of the connection of superior parietal lobule to the supplementary motor area in both types of motor imagery.

Rotation of molecular hydrogen in Si: unambiguous identification of ortho-H(2) and para-D(2).

The 3618.4 and 2642.6 cm(-1) infrared absorption lines of interstitial H(2) and D(2) in silicon have been studied under applied uniaxial stresses. The resulting splittings and their small dependence on isotope establish that H(2) in Si is a nearly free rotor and that these lines arise from vibrational transitions between rovibrational states with rotational quantum number J = 1 (T(2) in T(d) symmetry) for ortho-H(2) and para-D(2).

Key to understanding interstitial H2 in Si.

A new IR absorption line at 3191.1 cm(-1) has been discovered for the interstitial HD molecule in Si. This new line appears for sample temperatures above approximately 20 K and lies 73.9 cm(-1) below the 3265.0 cm(-1) line previously observed for HD. We attribute the 73.9 cm(-1) energy difference to the rotation of the interstitial HD molecule. The selection rules associated with these two lines are consistent with the puzzling absence of an ortho-para splitting in the IR absorption spectra of H2 and D2 in Si.

The interaction of social and emotional processes in the brain.

Social stimuli function as emotional barometers for the immediate environment are the catalysts for many emotional reactions, and have inherent value for relationships and survival independent of their current emotional content. We, therefore, propose that the neural mechanisms underlying social and emotional information processing may be interconnected. In the current study, we examined the independent and interactive effects of social and emotional processes on brain activation. Whole-brain images were acquired while participants viewed and categorized affective pictures that varied on two dimensions: emotional content (i. e., neutral, emotional) and social content (i. e., faces/people, objects/scenes). Patterns of activation were consistent with past findings demonstrating that the amygdala and part of the visual cortex were more active to emotionally evocative pictures than to neutral pictures and that the superior temporal sulcus was more active to social than to nonsocial pictures. Furthermore, activation of the superior temporal sulcus and middle occipito-temporal cortex showed evidence of the interactive processing of emotional and social information, whereas activation of the amygdala showed evidence of additive effects. These results indicate that interactive effects occur early in the stream of processing, suggesting that social and emotional information garner greater attentional resources and that the conjunction of social and emotional cues results in synergistic early processing, whereas the amygdala appears to be primarily implicated in processing biologically or personally relevant stimuli, regardless of the nature of the relevance (i. e., social, emotional, or both).