Luca Cocchi

Whole-brain anatomical networks: Does the choice of nodes matter?

Whole-brain anatomical connectivity in living humans can be modeled as a network with diffusion-MRI and tractography. Network nodes are associated with distinct grey-matter regions, while white-matter fiber bundles serve as interconnecting network links. However, the lack of a gold standard for regional parcellation in brain MRI makes the definition of nodes arbitrary, meaning that network nodes are defined using templates employing either random or anatomical parcellation criteria. Consequently, the number of nodes included in networks studied by different authors has varied considerably, from less than 100 up to more than 10(4). Here, we systematically and quantitatively assess the behavior, structure and topological attributes of whole-brain anatomical networks over a wide range of nodal scales, a variety of grey-matter parcellations as well as different diffusion-MRI acquisition protocols. We show that simple binary decisions about network organization, such as whether small-worldness or scale-freeness is evident, are unaffected by spatial scale, and that the estimates of various organizational parameters (e.g. small-worldness, clustering, path length, and efficiency) are consistent across different parcellation scales at the same resolution (i.e. the same number of nodes). However, these parameters vary considerably as a function of spatial scale; for example small-worldness exhibited a difference of 95% between the widely-used automated anatomical labeling (AAL) template (approximately 100 nodes) and a 4000-node random parcellation (sigma(AAL)=1.9 vs. sigma(4000)=53.6+/-2.2). These findings indicate that any comparison of network parameters across studies must be made with reference to the spatial scale of the nodal parcellation.

Disrupted Axonal Fiber Connectivity in Schizophrenia

BACKGROUND Schizophrenia is believed to result from abnormal functional integration of neural processes thought to arise from aberrant brain connectivity. However, evidence for anatomical dysconnectivity has been equivocal, and few studies have examined axonal fiber connectivity in schizophrenia at the level of whole-brain networks. METHODS Cortico-cortical anatomical connectivity at the scale of axonal fiber bundles was modeled as a network. Eighty-two network nodes demarcated functionally specific cortical regions. Sixty-four direction diffusion tensor-imaging coupled with whole-brain tractography was performed to map the architecture via which network nodes were interconnected in each of 74 patients with schizophrenia and 32 age- and gender-matched control subjects. Testing was performed to identify pairs of nodes between which connectivity was impaired in the patient group. The connectional architecture of patients was tested for changes in five network attributes: nodal degree, small-worldness, efficiency, path length, and clustering. RESULTS Impaired connectivity in the patient group was found to involve a distributed network of nodes comprising medial frontal, parietal/occipital, and the left temporal lobe. Although small-world attributes were conserved in schizophrenia, the cortex was interconnected more sparsely and up to 20% less efficiently in patients. Intellectual performance was found to be associated with brain efficiency in control subjects but not in patients. CONCLUSIONS This study presents evidence of widespread dysconnectivity in white-matter connectional architecture in a large sample of patients with schizophrenia. When considered from the perspective of recent evidence for impaired synaptic plasticity, this study points to a multifaceted pathophysiology in schizophrenia encompassing axonal as well as putative synaptic mechanisms.

Time-resolved resting-state brain networks

Significance Large-scale organizational properties of brain networks mapped with functional magnetic resonance imaging have been studied in a time-averaged sense. This is an oversimplification. We demonstrate that brain activity between multiple pairs of spatially distributed regions spontaneously fluctuates in and out of correlation over time in a globally coordinated manner, giving rise to sporadic intervals during which information can be efficiently exchanged between neuronal populations. We argue that dynamic fluctuations in the brain’s organizational properties may minimize metabolic requirements while maintaining the brain in a responsive state. Neuronal dynamics display a complex spatiotemporal structure involving the precise, context-dependent coordination of activation patterns across a large number of spatially distributed regions. Functional magnetic resonance imaging (fMRI) has played a central role in demonstrating the nontrivial spatial and topological structure of these interactions, but thus far has been limited in its capacity to study their temporal evolution. Here, using high-resolution resting-state fMRI data obtained from the Human Connectome Project, we mapped time-resolved functional connectivity across the entire brain at a subsecond resolution with the aim of understanding how nonstationary fluctuations in pairwise interactions between regions relate to large-scale topological properties of the human brain. We report evidence for a consistent set of functional connections that show pronounced fluctuations in their strength over time. The most dynamic connections are intermodular, linking elements from topologically separable subsystems, and localize to known hubs of default mode and fronto-parietal systems. We found that spatially distributed regions spontaneously increased, for brief intervals, the efficiency with which they can transfer information, producing temporary, globally efficient network states. Our findings suggest that brain dynamics give rise to variations in complex network properties over time, possibly achieving a balance between efficient information-processing and metabolic expenditure.

Dynamic cooperation and competition between brain systems during cognitive control

The human brain is characterized by a remarkable ability to adapt its information processing based on current goals. This ability, which is encompassed by the psychological construct of cognitive control, involves activity throughout large-scale, specialized brain systems that support segregated functions at rest and during active task performance. Based on recent research, we propose an account in which control functions rely on transitory changes in patterns of cooperation and competition between neural systems. This account challenges current conceptualizations of control as relying on segregated or antagonistic activity of specialized brain systems. Accordingly, we argue that the study of transitory task-based interactions between brain systems is critical to understanding the flexibility of normal cognitive control and its disruption in pathological conditions.

Decreased Functional Brain Connectivity in Adolescents with Internet Addiction

Background Internet addiction has become increasingly recognized as a mental disorder, though its neurobiological basis is unknown. This study used functional neuroimaging to investigate whole-brain functional connectivity in adolescents diagnosed with internet addiction. Based on neurobiological changes seen in other addiction related disorders, it was predicted that connectivity disruptions in adolescents with internet addiction would be most prominent in cortico-striatal circuitry. Methods Participants were 12 adolescents diagnosed with internet addiction and 11 healthy comparison subjects. Resting-state functional magnetic resonance images were acquired, and group differences in brain functional connectivity were analyzed using the network-based statistic. We also analyzed network topology, testing for between-group differences in key graph-based network measures. Results Adolescents with internet addiction showed reduced functional connectivity spanning a distributed network. The majority of impaired connections involved cortico-subcortical circuits (∼24% with prefrontal and ∼27% with parietal cortex). Bilateral putamen was the most extensively involved subcortical brain region. No between-group difference was observed in network topological measures, including the clustering coefficient, characteristic path length, or the small-worldness ratio. Conclusions Internet addiction is associated with a widespread and significant decrease of functional connectivity in cortico-striatal circuits, in the absence of global changes in brain functional network topology.

Altered Functional Brain Connectivity in a Non-Clinical Sample of Young Adults with Attention-Deficit/Hyperactivity Disorder

Attention-deficit/hyperactivity disorder (ADHD) is characterized by symptoms of inattention and hyperactivity/impulsivity that often persist in adulthood. There is a growing consensus that ADHD is associated with abnormal function of diffuse brain networks, but such alterations remain poorly characterized. Using resting-state functional magnetic resonance imaging, we characterized multivariate (complex network measures), bivariate (network-based statistic), and univariate (regional homogeneity) properties of brain networks in a non-clinical, drug-naive sample of high-functioning young men and women with ADHD (nine males, seven females) and a group of matched healthy controls. Data from our sample allowed the isolation of intrinsic functional connectivity alterations specific to ADHD diagnosis and symptoms that are not related to developmental delays, general cognitive dysfunction, or history of medication use. Multivariate results suggested that frontal, temporal, and occipital cortices were abnormally connected locally as well as with the rest of the brain in individuals with ADHD. Results from the network-based statistic support and extend multivariate results by isolating two brain networks comprising regions between which inter-regional connectivity was significantly altered in the ADHD group; namely, a frontal amygdala-occipital network and a frontal temporal-occipital network. Brain behavior correlations further highlighted the key role of altered orbitofrontal-temporal and frontal-amygdala connectivity for symptoms of inattention and hyperactivity/impulsivity. All univariate properties were similar between groups. Taken together, results from this study show that the diagnosis and the two main symptom dimensions of ADHD are related to altered intrinsic connectivity in orbitofrontal-temporal-occipital and fronto-amygdala-occipital networks. Accordingly, our findings highlight the importance of extending the conceptualization of ADHD beyond segregated fronto-striatal alterations.

White matter microstructure in opiate addiction.

Heroin addiction has been associated with impaired neuronal connectivity and cognitive deficits. One mechanism that potentially explains these findings is alterations in white matter connectivity secondary to chronic opiate use. However, few studies have quantitavely examined white matter deficits in opiate addiction (OA). Here, we investigated white matter microstructure in OA using diffusion tensor imaging (DTI). We performed voxel‐wise analysis of fractional anisotropy (FA) in 24 participants with OA and 29 healthy controls. The OA group showed reduced FA in multiple pathways including the corpus callosum, thalamic radiation and inferior longitudinal fasciculus. This FA reduction was mainly the result of increased radial diffusivity (λ⊥), indicative of myelin pathology. Longer duration of OA was also associated with axonal diffusivity (λ1), most robustly in superior longitudinal fasciculi and right frontal white matter suggesting axonal injury in long‐term users. Together, the findings indicate that chronic OA use has widespread and diverse effects on neuronal connectivity and function.

Connectome sensitivity or specificity: which is more important?

Connectomes with high sensitivity and high specificity are unattainable with current axonal fiber reconstruction methods, particularly at the macro-scale afforded by magnetic resonance imaging. Tensor-guided deterministic tractography yields sparse connectomes that are incomplete and contain false negatives (FNs), whereas probabilistic methods steered by crossing-fiber models yield dense connectomes, often with low specificity due to false positives (FPs). Densely reconstructed probabilistic connectomes are typically thresholded to improve specificity at the cost of a reduction in sensitivity. What is the optimal tradeoff between connectome sensitivity and specificity? We show empirically and theoretically that specificity is paramount. Our evaluations of the impact of FPs and FNs on empirical connectomes indicate that specificity is at least twice as important as sensitivity when estimating key properties of brain networks, including topological measures of network clustering, network efficiency and network modularity. Our asymptotic analysis of small-world networks with idealized modular structure reveals that as the number of nodes grows, specificity becomes exactly twice as important as sensitivity to the estimation of the clustering coefficient. For the estimation of network efficiency, the relative importance of specificity grows linearly with the number of nodes. The greater importance of specificity is due to FPs occurring more prevalently between network modules rather than within them. These spurious inter-modular connections have a dramatic impact on network topology. We argue that efforts to maximize the sensitivity of connectome reconstruction should be realigned with the need to map brain networks with high specificity.

Disruption of structure–function coupling in the schizophrenia connectome

Neuroimaging studies have demonstrated that the phenomenology of schizophrenia maps onto diffuse alterations in large-scale functional and structural brain networks. However, the relationship between structural and functional deficits remains unclear. To answer this question, patients with established schizophrenia and matched healthy controls underwent resting-state functional and diffusion weighted imaging. The network-based statistic was used to characterize between-group differences in whole-brain functional connectivity. Indices of white matter integrity were then estimated to assess the structural correlates of the functional alterations observed in patients. Finally, group differences in the relationship between indices of functional and structural brain connectivity were determined. Compared to controls, patients with schizophrenia showed decreased functional connectivity and impaired white matter integrity in a distributed network encompassing frontal, temporal, thalamic, and striatal regions. In controls, strong interregional coupling in neural activity was associated with well-myelinated white matter pathways in this network. This correspondence between structure and function appeared to be absent in patients with schizophrenia. In two additional disrupted functional networks, encompassing parietal, occipital, and temporal cortices, the relationship between function and structure was not affected. Overall, results from this study highlight the importance of considering not only the separable impact of functional and structural connectivity deficits on the pathoaetiology of schizophrenia, but also the implications of the complex nature of their interaction. More specifically, our findings support the core nature of fronto-striatal, fronto-thalamic, and fronto-temporal abnormalities in the schizophrenia connectome.

White matter microstructure in patients with obsessive-compulsive disorder.

BACKGROUND Previous diffusion tensor imaging (DTI) studies in patients with obsessive-compulsive disorder (OCD) have reported inconsistent findings, and it is not known whether observed findings are related to abnormalities in axonal structure or myelination. METHODS In this DTI study, we investigated fractional anisotropy, as well as axial and radial diffusivity, in 21 patients with OCD and 29 healthy controls. RESULTS We found decreased fractional anisotropy in the body of the corpus callosum in the OCD group, which was underpinned by increased radial diffusivity. LIMITATIONS The cross-sectional design was the main limitation. CONCLUSION Our findings of increased radial diffusivity provide preliminary evidence for abnormal myelination in patients with OCD.