Hemodynamic and electrophysiological evidence of resting-state network activity in the primate

An expanding body of literature describes the existence of concerted brain activations in the absence of any external stimuli. Resting-state networks have been identified and demonstrated to be modulated during the performance of specific cognitive operations. However, despite mounting evidence the possibility still remains that those correlated signal fluctuations reflect non-neural phenomena. In order to isolate functionally relevant spontaneous coactivations, we utilized a multi-level sampling approach to obtain co-registered brain signals across a range of sampling resolution and sensitivity. Surface and local field potentials, hemodynamic signals (near-infrared spectroscopy, NIRS), and cell spiking were recorded from dorsolateral prefrontal and posterior parietal cortices in four monkeys trained to remain motionless in a primate chair. The use of an optical recording technique (NIRS) allows measurement of a signal that is physiologically equivalent to that obtained using BOLD fMRI, though with millisecond temporal resolution and minimal technical or environmental constraints. The different signal types exhibited correlations between the two regions of interest in both the frequency and time domains. This evidence suggests that the resting-state network activations detected by fMRI do in fact reflect functional coactivations of areas across multiple levels of network communication

Functional differentiation within the monkey cortex as revealed by near-infrared spectroscopy

The role of prefrontal cortex in working memory (WM) is well established. However, questions remain regarding the topography and “domain-specific differentiation” of different types of information processing in the cortex. While it has been theorized that dorsolateral (DPFC) and ventrolateral (VPFC) prefrontal cortex preferentially process spatial and object WM, respectively, both electrophysiological evidence in the monkey and neuroimaging in the human have largely failed to demonstrate such regional differentiation. In this study we use near-infrared spectroscopy (NIRS) to detect functional changes, across relatively large cortical cell populations, simultaneously from prefrontal and posterior parietal cortices. Imaging data were recorded from a Rhesus macaque performing two types of WM tasks: a spatial task in which the animal had to retain the spatial position of a visual stimulus, and a non-spatial task where he had to retain its color (red or green) during a 20s delay. During performance of the spatial WM task, cerebral activation trends were found in which DPFC exhibited stronger activation than did the VPFC, and posterior parietal cortex maintained higher delay activation than did frontal regions. These differences were less pronounced during performance of the non-spatial task. Additionally, incorrect trials generally elicited lower activations during the delay period than did trials ending with a correct response. Furthermore, NIRS data collected during the performance of a haptic WM task also appear to exhibit inter-regional differences in delay activation. The data thus suggest the presence of preferential cognitive processing between and within posterior and frontal cortical regions

Meditation effects within the hippocampal complex revealed by voxel-based morphometry and cytoarchitectonic probabilistic mapping.

Scientific studies addressing anatomical variations in meditators' brains have emerged rapidly over the last few years, where significant links are most frequently reported with respect to gray matter (GM). To advance prior work, this study examined GM characteristics in a large sample of 100 subjects (50 meditators, 50 controls), where meditators have been practicing close to 20 years, on average. A standard, whole-brain voxel-based morphometry approach was applied and revealed significant meditation effects in the vicinity of the hippocampus, showing more GM in meditators than in controls as well as positive correlations with the number of years practiced. However, the hippocampal complex is regionally segregated by architecture, connectivity, and functional relevance. Thus, to establish differential effects within the hippocampal formation (cornu ammonis, fascia dentata, entorhinal cortex, subiculum) as well as the hippocampal-amygdaloid transition area, we utilized refined cytoarchitectonic probabilistic maps of (peri-) hippocampal subsections. Significant meditation effects were observed within the subiculum specifically. Since the subiculum is known to play a key role in stress regulation and meditation is an established form of stress reduction, these GM findings may reflect neuronal preservation in long-term meditators-perhaps due to an attenuated release of stress hormones and decreased neurotoxicity

A High-Resolution Anatomical Framework of the Neonatal Mouse Brain for Managing Gene Expression Data

This study aims to provide a high-resolution atlas and use it as an anatomical framework to localize the gene expression data for mouse brain on postnatal day 0 (P0). A color Nissl-stained volume with a resolution of 13.3 × 50 × 13.3 μ3 was constructed and co-registered to a standard anatomical space defined by an averaged geometry of C57BL/6J P0 mouse brains. A 145 anatomical structures were delineated based on the histological images. Anatomical relationships of delineated structures were established based on the hierarchical relations defined in the atlas of adult mouse brain (MacKenzie-Graham et al., 2004) so the P0 atlas can be related to the database associated with the adult atlas. The co-registered multimodal atlas as well as the original anatomical delineations is available for download at http://www.loni.ucla.edu/Atlases/. The region-specific anatomical framework based on the neonatal atlas allows for the analysis of gene activity within a high-resolution anatomical space at an early developmental stage. We demonstrated the potential application of this framework by incorporating gene expression data generated using in situ hybridization to the atlas space. By normalizing the gene expression patterns revealed by different images, experimental results from separate studies can be compared and summarized in an anatomical context. Co-displaying multiple registered datasets in the atlas space allows for 3D reconstruction of the co-expression patterns of the different genes in the atlas space, hence providing better insight into the relationship between the differentiated distribution pattern of gene products and specific anatomical systems

Digital Atlases as a Framework for Data Sharing

Digital brain atlases are useful as references, analytical tools, and as a data integration framework. As a result, they and their supporting tools are being recognized as potentially useful resources in the movement toward data sharing. Several projects are connecting infrastructure to these tools which facilitate sharing, managing, and retrieving data of different types, scale, and even location. With these in place, we have the ability to combine, analyze, and interpret these data in a manner not previously possible, opening the door to examine issues in new and exciting ways, and potentially leading to speedier discovery of answers as well as new questions about the brain. Here we discuss recent efforts in the use of digital mouse atlases for data sharing

Frontoinsular cortical microstructure is linked to life satisfaction in young adulthood

Life satisfaction is a component of subjective wellbeing that reflects a global judgement of the quality of life according to an individual’s own needs and expectations. As a psychological construct, it has attracted attention due to its relationship to mental health, resilience to stress, and other factors. Neuroimaging studies have identified neurobiological correlates of life satisfaction; however, they are limited to functional connectivity and gray matter morphometry. We explored features of gray matter microstructure obtained through compartmental modeling of multi-shell diffusion MRI data, and we examined cortical microstructure in frontoinsular cortex in a cohort of 807 typical young adults scanned as part of the Human Connectome Project. Our experiments identified the orientation dispersion index (ODI), and analogously fractional anisotropy (FA), of frontoinsular cortex as a robust set of anatomically-specific lateralized diffusion MRI microstructure features that are linked to life satisfaction, independent of other demographic, socioeconomic, and behavioral factors. We further validated our findings in a secondary test-retest dataset and found high reliability of our imaging metrics and reproducibility of outcomes. In our analysis of twin and non-twin siblings, we found basic microstructure in frontoinsular cortex to be strongly genetically determined. We also found a more moderate but still very significant genetic role in determining microstructure as it relates to life satisfaction in frontoinsular cortex. Our findings suggest a potential linkage between well-being and microscopic features of frontoinsular cortex, which may reflect cellular morphology and architecture and may more broadly implicate the integrity of the homeostatic processing performed by frontoinsular cortex as an important component of an individual’s judgements of life satisfaction

THC Exposure is Reflected in the Microstructure of the Cerebral Cortex and Amygdala of Young Adults

The endocannabinoid system serves a critical role in homeostatic regulation through its influence on processes underlying appetite, pain, reward, and stress, and cannabis has long been used for the related modulatory effects it provides through tetrahydrocannabinol (THC). We investigated how THC exposure relates to tissue microstructure of the cerebral cortex and subcortical nuclei using computational modeling of diffusion magnetic resonance imaging data in a large cohort of young adults from the Human Connectome Project. We report strong associations between biospecimen-defined THC exposure and microstructure parameters in discrete gray matter brain areas, including frontoinsular cortex, ventromedial prefrontal cortex, and the lateral amygdala subfields, with independent effects in behavioral measures of memory performance, negative intrusive thinking, and paternal substance abuse. These results shed new light on the relationship between THC exposure and microstructure variation in brain areas related to salience processing, emotion regulation, and decision making. The absence of effects in some other cannabinoid-receptor-rich brain areas prompts the consideration of cellular and molecular mechanisms that we discuss. Further studies are needed to characterize the nature of these effects across the lifespan and to investigate the mechanistic neurobiological factors connecting THC exposure and microstructural parameters

Practical management of heterogeneous neuroimaging metadata by global neuroimaging data repositories

Rapidly evolving neuroimaging techniques are producing unprecedented quantities of digital data at the same time that many research studies are evolving into global, multi-disciplinary collaborations between geographically distributed scientists. While networked computers have made it almost trivial to transmit data across long distances, collecting and analyzing this data requires extensive metadata if the data is to be maximally shared. Though it is typically straightforward to encode text and numerical values into files and send content between different locations, it is often difficult to attach context and implicit assumptions to the content. As the number of and geographic separation between data contributors grows to national and global scales, the heterogeneity of the collected metadata increases and conformance to a single standardization becomes implausible. Neuroimaging data repositories must then not only accumulate data but must also consolidate disparate metadata into an integrated view. In this article, using specific examples from our experiences, we demonstrate how standardization alone cannot achieve full integration of neuroimaging data from multiple heterogeneous sources and why a fundamental change in the architecture of neuroimaging data repositories is needed instead

Interactive Exploration of Neuroanatomical Meta-Spaces

Large-archives of neuroimaging data present many opportunities for re-analysis and mining that can lead to new findings of use in basic research or in the characterization of clinical syndromes. However, interaction with such archives tends to be driven textually, based on subject or image volume meta-data, not the actual neuroanatomical morphology itself, for which the imaging was performed to measure. What is needed is a content-driven approach for examining not only the image content itself but to explore brains that are anatomically similar, and identifying patterns embedded within entire sets of neuroimaging data. With the aim of visual navigation of large- scale neurodatabases, we introduce the concept of brain meta-spaces. The meta-space encodes pair-wise dissimilarities between all individuals in a population and shows the relationships between brains as a navigable framework for exploration. We employ multidimensional scaling (MDS) to implement meta-space processing for a new coordinate system that distributes all data points (brain surfaces) in a common frame-of-reference, with anatomically similar brain data located near each other. To navigate within this derived meta-space, we have developed a fully interactive 3D visualization environment that allows users to examine hundreds of brains simultaneously, visualize clusters of brains with similar characteristics, zoom in on particular instances, and examine the surface topology of an individual brain's surface in detail. The visualization environment not only displays the dissimilarities between brains, but also renders complete surface representations of individual brain structures, allowing an instant 3D view of the anatomies, as well as their differences. The data processing is implemented in a grid-based setting using the LONI Pipeline workflow environment. Additionally users can specify a range of baseline brain atlas spaces as the underlying scale for comparative analyses. The novelty in our approach lies in the user ability to simultaneously view and interact with many brains at once but doing so in a vast meta-space that encodes (dis) similarity in morphometry. We believe that the concept of brain meta-spaces has important implications for the future of how users interact with large-scale archives of primary neuroimaging data