scholarly journals Integrated resource for functional and structural connectivity of the marmoset brain

2021 ◽  
Author(s):  
Xiaoguang Tian ◽  
Yuyuan Chen ◽  
Piotr Majka ◽  
Diego Szczupak ◽  
Yonatan Sanz-Perl ◽  
...  

The comprehensive integration of structural and functional connectivity data is required for the accurate modeling of brain functions. While resources for studying structural connectivity of non-human primate marmoset brains already exist, their integration with functional connectivity data has remained unavailable. Therefore, we present a comprehensive resource for marmoset brain mapping, which integrates the largest awake resting-state fMRI dataset to date (39 marmosets, 709 runs, and 12053 mins), cellular-level neuronal-tracing dataset (52 marmosets and 143 injections), and multi-resolution diffusion MRI dataset. The combination of these data into the same MRI space allowed us to 1). map the fine-detailed functional networks and cortical parcellations; 2). develop a deep-learning-based parcellation generator to preserve the topographical organization of functional connectivity and reflect individual variabilities; 3). investigate the structural basis underlying functional connectivity by computational modeling. Our resource will broadly model the marmoset brain architecture and facilitate future comparative and translational studies of primate brains.

2020 ◽  
Author(s):  
Oren Civier ◽  
Marion Sourty ◽  
Fernando Calamante

AbstractWe introduce a connectomics metric that integrates information on structural connectivity (SC) from diffusion MRI tractography and functional connectivity (FC) from resting-state functional MRI, at individual subject level. The metric is based on the ability of SC to broadly predict FC using a simple linear predictive model; for each connection in the brain, the metric quantifies the deviation from that model. For the metric to capture underlying physiological properties, we minimise systematic measurement errors and processing biases in both SC and FC, and address several challenges with the joint analysis. This also includes a data-driven normalisation approach. The combined metric may provide new information by indirectly assessing white matter structural properties that cannot be inferred from diffusion MRI alone, and/or complex interregional neural interactions that cannot be inferred from functional MRI alone. To demonstrate the utility of the metric, we used young adult data from the Human Connectome Project to examine all bilateral pairs of ipsilateral connections, i.e. each left-hemisphere connection in the brain was paired with its right-hemisphere homologue. We detected a minority of bilateral pairs where the metric value is significantly different across hemispheres, which we suggest reflects cases of ipsilateral connections that have distinct functional specialisation in each hemisphere. The pairs with significant effects spanned all cortical lobes, and also included several cortico-subcortical connections. Our findings highlight the potential in a joint analysis of structural and functional measures of connectivity, both for clinical applications and to help in the interpretation of results from standard functional connectivity analysis.Significance StatementBased on the notion that structure predicts function, the scientific community sought to demonstrate that structural information on fibre bundles that connect brain regions is sufficient to estimate the strength of interregional interactions. However, an accurate prediction using MRI has proved elusive. This paper posits that the failure to predict function from structure originates from limitations in measurement or interpretation of either diffusion MRI (to assess fibre bundles), fMRI (to assess functional interactions), or both. We show that these limitations can be nevertheless beneficial, as the extent of divergence between the two modalities may reflect hard-to-measure properties of interregional connections, such as their functional role in the brain. This provides many insights, including into the division of labour between hemispheres.


2017 ◽  
Author(s):  
David E. Warren ◽  
Matthew J. Sutterer ◽  
Joel Bruss ◽  
Taylor J. Abel ◽  
Andrew Jones ◽  
...  

AbstractFunctional connectivity, as measured by resting-state fMRI, has proven a powerful method for studying brain systems in the context of behavior, development, and disease states. However, the relationship of functional connectivity to structural connectivity remains unclear. If functional connectivity relies on structural connectivity, then anatomical isolation of a brain region should eliminate functional connectivity with other brain regions. We tested this by measuring functional connectivity of the surgically disconnected temporal pole in resection patients (N=5; mean age 37; 2F, 3M). Functional connectivity was evaluated based on coactivation of whole-brain fMRI data with the average low-frequency BOLD signal from disconnected tissue in each patient. In sharp contrast to our prediction, we observed significant functional connectivity between the disconnected temporal pole and remote brain regions in each disconnection case. These findings raise important questions about the neural bases of functional connectivity measures derived from the fMRI BOLD signal.


Author(s):  
Matthew J. Hoptman ◽  
Umit Tural ◽  
Kelvin O. Lim ◽  
Daniel C. Javitt ◽  
Lauren E. Oberlin

Schizophrenia is widely seen as a disorder of dysconnectivity. Neuroimaging studies have examined both structural and functional connectivity in the disorder, but these modalities have rarely been integrated directly. We scanned 29 patients with schizophrenia and 25 healthy control subjects and acquired resting state fMRI and diffusion tensor imaging. The Functional and Tractographic Connectivity Analysis Toolbox (FATCAT) was used to estimate functional and structural connectivity of the default mode network. Correlations between modalities were investigated, and multimodal connectivity scores (MCS) were created using principal components analysis. Nine of 28 possible region pairs showed consistent (>80%) tracts across participants. Correlations between modalities were found among those with schizophrenia for the prefrontal cortex, posterior cingulate, and lateral temporal lobes with frontal and parietal regions, consistent with frontotemporoparietal network involvement in the disorder. In patients, MCS values correlated with several aspects of the Positive and Negative Syndrome Scale, positively with those involving inwardly directed psychopathology, and negatively with those involving external psychopathology. In this preliminary sample, we found FATCAT to be a useful toolbox to directly integrate and examine connectivity between imaging modalities. A consideration of conjoint structural and functional connectivity can provide important information about the network mechanisms of schizophrenia.


Author(s):  
Matthew J. Hoptman ◽  
Umit Tural ◽  
Kelvin O. Lim ◽  
Daniel C. Javitt ◽  
Lauren E. Oberlin

Schizophrenia is widely seen as a disorder of dysconnectivity. Neuroimaging studies have examined both structural and functional connectivity in the disorder, but these modalities have rarely been integrated directly. We scanned 29 patients with schizophrenia and 25 healthy control subjects and acquired resting state fMRI and diffusion tensor imaging. The Functional and Tractographic Connectivity Analysis Toolbox (FATCAT) was used to estimate functional and structural connectivity of the default mode network. Correlations between modalities were investigated, and multimodal connectivity scores (MCS) were created using principal components analysis. Nine of 28 possible region pairs showed consistent (>80%) tracts across participants. Correlations between modalities were found among those with schizophrenia for the prefrontal cortex, posterior cingulate, and lateral temporal lobes with frontal and parietal regions, consistent with frontotemporoparietal network involvement in the disorder. In patients, MCS values correlated with several aspects of the Positive and Negative Syndrome Scale, positively with those involving inwardly directed psychopathology, and negatively with those involving external psychopathology. In this preliminary sample, we found FATCAT to be a useful toolbox to directly integrate and examine connectivity between imaging modalities. A consideration of conjoint structural and functional connectivity can provide important information about the network mechanisms of schizophrenia.


2017 ◽  
Vol 90 (1) ◽  
pp. 62-72 ◽  
Author(s):  
Mehdi Behroozi ◽  
Felix Ströckens ◽  
Martin Stacho ◽  
Onur Güntürkün

In the last two decades, the avian hippocampus has been repeatedly studied with respect to its architecture, neurochemistry, and connectivity pattern. We review these insights and conclude that we unfortunately still lack proper knowledge on the interaction between the different hippocampal subregions. To fill this gap, we need information on the functional connectivity pattern of the hippocampal network. These data could complement our structural connectivity knowledge. To this end, we conducted a resting-state fMRI experiment in awake pigeons in a 7-T MR scanner. A voxel-wise regression analysis of blood oxygenation level-dependent (BOLD) fluctuations was performed in 6 distinct areas, dorsomedial (DM), dorsolateral (DL), triangular shaped (Tr), dorsolateral corticoid (CDL), temporo-parieto-occipital (TPO), and lateral septum regions (SL), to establish a functional connectivity map of the avian hippocampal network. Our study reveals that the system of connectivities between CDL, DL, DM, and Tr is the functional backbone of the pigeon hippocampal system. Within this network, DM is the central hub and is strongly associated with DL and CDL BOLD signal fluctuations. DM is also the only hippocampal region to which large Tr areas are functionally connected. In contrast to published tracing data, TPO and SL are only weakly integrated in this network. In summary, our findings uncovered a structurally otherwise invisible architecture of the avian hippocampal formation by revealing the dynamic blueprints of this network.


2021 ◽  
Author(s):  
Benjamin C. Tendler ◽  
Taylor Hanayik ◽  
Olaf Ansorge ◽  
Sarah Bangerter-Christensen ◽  
Gregory S. Berns ◽  
...  

Post-mortem MRI provides the opportunity to acquire high-resolution datasets to investigate neuroanatomy, and validate the origins of image contrast through microscopy comparisons. We introduce the Digital Brain Bank (open.win.ox.ac.uk/DigitalBrainBank), an interactive data discovery and release platform providing open access to curated, multimodal post-mortem neuroimaging datasets. Datasets span three themes - Digital Neuroanatomist: data for neuroanatomical investigations; Digital Brain Zoo: data for comparative neuroanatomy; Digital Pathologist: data for neuropathology investigations. The first Digital Brain Bank release includes fourteen distinctive whole-brain diffusion MRI datasets for structural connectivity investigations, alongside microscopy and complementary MRI modalities. This includes one of the highest-resolution whole-brain human diffusion MRI datasets ever acquired, whole-brain diffusion MRI in seven non-human primate species, and one of the largest post-mortem whole-brain cohort imaging studies in neurodegeneration. Taken together, the Digital Brain Bank provides a cross-scale, cross-species investigation framework facilitating the incorporation of post-mortem data into neuroimaging studies.


2018 ◽  
Author(s):  
Elliot A. Layden ◽  
Kathryn E. Schertz ◽  
Sarah E. London ◽  
Marc G. Berman

AbstractFunctional homotopy, or synchronous spontaneous activity between symmetric, contralateral brain regions, is a fundamental characteristic of the mammalian brain’s functional architecture(1–6). In mammals, functional homotopy may be predominantly mediated by the corpus callosum (CC), a white matter structure thought to balance the interhemispheric coordination and hemispheric specialization critical for many complex brain functions, including lateralized human language abilities(7, 8). The CC first emerged with the Eutherian (placental) mammals ~160 MYA and is not found in other vertebrates(9, 10). Despite this, other vertebrates also exhibit complex brain functions requiring bilateral integration and lateralization(11). For example, much as humans acquire speech, the zebra finch (Taeniopygia guttata) songbird learns to sing from tutors and must balance hemispheric specialization(12) with interhemispheric coordination to successfully learn and produce song(13). We therefore tested whether the zebra finch brain also exhibits functional homotopy despite lacking the CC. Implementing custom resting-state fMRI (rs-fMRI) functional connectivity (FC) analyses, we demonstrate widespread functional homotopy between pairs of contralateral brain regions required for learned song but which lack direct anatomical projections (i.e., structural connectivity; SC). We believe this is the first demonstration of functional homotopy in a non-Eutherian vertebrate; however, it is unlikely to be the only instance of it. The remarkable congruence between functional homotopy in the zebra finch and Eutherian brains indicates that alternative mechanisms must exist for balanced interhemispheric coordination in the absence of a CC. This insight may have broad implications for understanding complex, bilateral neural processing across phylogeny and how information is integrated between hemispheres.Significance StatementThe mammalian brain exhibits strongly synchronized hemodynamic activity (i.e., functional connectivity) between symmetric, contralateral (i.e., homotopic) brain regions. This pattern is thought to be largely mediated by the corpus callosum (CC), a large white matter tract unique to mammals, which balances interhemispheric coordination and lateralization. Many complex brain functions, including human language, are thought to critically rely upon this balance. Despite lacking the CC, the zebra finch exhibits a song learning process with striking parallels to human speech acquisition, including lateralization and interhemispheric coordination. Using resting-state fMRI, we show that the zebra finch brain exhibits widespread homotopic functional connectivity within a network critical for learned song, suggesting that this symmetrical activity pattern may phylogenetically precede the evolution of the CC.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Adnan A. S. Alahmadi

Abstract Objectives Traditionally, the superior parietal lobule (SPL) is usually investigated as one region of interest, particularly in functional magnetic resonance imaging (fMRI) studies. However, cytoarchitectonic analysis has shown that the SPL has a complex, heterogeneous topology that comprises more than seven sub-regions. Since previous studies have shown how the SPL is significantly involved in different neurological functions—such as visuomotor, cognitive, sensory, higher order, working memory and attention—this study aims to investigate whether these cytoarchitecturally different sub-regions have different functional connectivity to different functional brain networks. Methods This study examined 198 healthy subjects using resting-state fMRI and investigated the functional connectivity of seven sub-regions of the SPL to eight regional functional networks. Results The findings showed that most of the seven sub-regions were functionally connected to these targeted networks and that there are differences between these sub-regions and their functional connectivity patterns. The most consistent functional connectivity was observed with the visual and attention networks. There were also clear functional differences between Brodmann area (BA) 5 and BA7. BA5, with its three sub-regions, had strong functional connectivity to both the sensorimotor and salience networks. Conclusion These findings have enhanced our understanding of the functional organisations of the complexity of the SPL and its varied topology and also provide clear evidence of the functional patterns and involvements of the SPL in major brain functions.


2021 ◽  
Author(s):  
Gianpaolo Antonio Basile ◽  
Salvatore Bertino ◽  
Victor Nozais ◽  
Alessia Bramanti ◽  
Rosella Ciurleo ◽  
...  

AbstractThe contribution of structural connectivity to functional connectivity dynamics is still far from being fully elucidated. Herein, we applied track-weighted dynamic functional connectivity (tw-dFC), a model integrating structural, functional, and dynamic connectivity, on high quality diffusion weighted imaging and resting-state fMRI data from two independent repositories. The tw-dFC maps were analyzed using independent component analysis, aiming at identifying spatially independent white matter components which support dynamic changes in functional connectivity. Each component consisted of a spatial map of white matter bundles that show consistent fluctuations in functional connectivity at their endpoints, and a time course representative of such functional activity. These components show high intra-subject, inter-subject, and inter-cohort reproducibility. We provided also converging evidence that functional information about white matter activity derived by this method can capture biologically meaningful features of brain connectivity organization, as well as predict higher-order cognitive performance.


2018 ◽  
Author(s):  
Arnaud Messé ◽  
Karl J. Hollensteiner ◽  
Céline Delettre ◽  
Leigh-Anne Dell ◽  
Florian Pieper ◽  
...  

AbstractIntrinsic coupling modes (ICMs) provide a framework for describing the interactions of ongoing brain activity at multiple spatial and temporal scales. Two families of ICMs can be distinguished: phase and envelope ICMs. The principles that shape these ICMs remain partly elusive, in particular their relation to the underlying brain structure. Here we explored structure-function relationships in the ferret brain between ICMs quantified from ongoing brain activity recorded with chronically implanted ECoG arrays and structural connectivity (SC) obtained from high-resolution diffusion MRI tractography. Large-scale computational models as well as simple topological ingredients of SC were used to explore the ability to predict both types of ICMs. Importantly, all investigations were conducted with ICM measures that are sensitive or insensitive to volume conduction effects. The results show that both types of ICMs are strongly related to SC, except when using ICM measures removing zero-lag synchronizations. Computational models are challenged to predict these ICM patterns consistently, and simple predictions from SC topological features can sometimes outperform them. Overall, the results demonstrate that patterns of cortical functional coupling as reflected in both phase and envelope ICMs bear a substantial relation to the underlying structural connectivity of the cerebral cortex.


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