A method of linking functional and structural connectivity analysis in urban green infrastructure network construction

Accelerated urbanization and population growth lead to the fragmentation of urban green space and loss of biodiversity. There are few studies on the integration of structural and functional connectivity to solve this problem. Our study aims to draw up a methodology to synthesize two methods of connectivity evaluation, accordingly, to construct an urban green infrastructure (UGI) network which is of great significance to maintain the stability of the urban ecosystem. Taking Beijing as a study area, we first used Morphological Spatial Pattern Analysis (MSPA) to identify the source patches, then combined with the graph theory-based landscape metrics to discuss the effect of different diffusion distances on the regional landscape connectivity and classify the importance level of the source patches. Finally, we used both least-cost path (LCP) and circuit theory to construct network and identify pinch areas in corridors for network optimization. The results show that (1) the landscape connectivity of the study area is obviously polarized. Source patches in mountain and hilly areas have good ecological bases and large areas, and the density of corridors is relatively high, which makes a large contribution to the overall landscape connectivity; Source patches in plain areas are severely fragmented, and there are only a small number of potential corridors connecting urban areas and suburban areas. (2) The UGI network is composed of 70 source patches and 148 potential corridors. The diffusion distance that is most beneficial to improve landscape connectivity is 20–25 km. (3) 6 pinch areas that are of great significance for improving the connectivity of the landscape present the coexistence of high migration resistance and large optimization potential, and urgently need to be restored first. This study provides a method to combine the structural and the functional analysis to construct a UGI network and formulate more scientifical protection strategies for planning departments.

Mapping neurotransmitter systems to the structural and functional organization of the human neocortex

Neurotransmitter receptors support the propagation of signals in the human brain. How receptor systems are situated within macroscale neuroanatomy and how they shape emergent function remains poorly understood, and there exists no comprehensive atlas of receptors. Here we collate positron emission tomography scans in >1,200 healthy individuals to construct a whole-brain 3-D normative atlas of 18 receptors and transporters across 9 different neurotransmitter systems. We find that receptor profiles align with structural connectivity and mediate function, including neurophysiological oscillatory dynamics and resting state hemodynamic functional connectivity. Using the Neurosynth cognitive atlas, we uncover a topographic gradient of overlapping receptor distributions that separates extrinsic and intrinsic psychological processes. Finally, we find both expected and novel associations between receptor distributions and cortical thinning patterns across 13 disorders. We replicate all findings in an independently collected autoradiography dataset. This work demonstrates how chemoarchitecture shapes brain structure and function, providing a new direction for studying multi-scale brain organization.

Network Constraints on Longitudinal Grey Matter Changes in First Episode Psychosis

Background: Different regions of the brain's grey matter are connected by a complex structural network of white matter fibres which are responsible for the propagation of action potentials and the transport of trophic and other molecules. In neurodegenerative disease, these connections constrain the way in which grey matter volume loss progresses. Here, we investigated whether connectome architecture also shapes the spatial pattern of longitudinal grey matter volume changes attributable to illness and antipsychotic medication in first episode psychosis (FEP). Methods: We conducted a triple-blind randomised placebo-control MRI study where 62 young adults with first episode psychosis received either an atypical antipsychotic or placebo over 6-months. A healthy control group was also recruited. Anatomical MRI scans were acquired at baseline, 3-months and 12-months. Deformation-based morphometry was used to estimate illness-related and antipsychotic-related grey matter volume changes over time. Representative functional and structural brain connectivity patterns were derived from an independent healthy control group using resting-state functional MRI and diffusion-weighted imaging. We used neighbourhood deformation models to predict the extent of brain change in a given area by the changes observed in areas to which it is either structurally connected or functionally coupled. Results: At baseline, we found that empirical illness-related regional volume differences were strongly correlated with predicted differences using a model constrained by structural connectivity weights (ρ = .541; p < .001). At 3-months and 12-months, we also found a strong correlation between longitudinal regional illness-related (ρ > .516; p < .001) and antipsychotic-related volume change (ρ > .591; p < .001) with volumetric changes in structurally connected areas. These correlations were significantly greater than those observed across various null models accounting for lower-order spatial and network properties of the data. Associations between empirical and predicted volume change estimates were much lower for models that only considered binary structural connectivity (all ρ < .376), or which were constrained by inter-regional functional coupling (all ρ < .436). Finally, we found that potential epicentres of volume change emerged posteriorly early in the illness and shifted to the prefrontal cortex by later illness stages. Conclusion: Psychosis- and antipsychotic-related grey matter volume changes are strongly shaped by anatomical brain connectivity. This result is consistent with findings in other neurological disorders and implies that such connections may constrain pathological processes causing brain dysfunction in FEP.

Microstructural Impairments in a Topologically Distinct Prefrontal-Habenular Connection in Cocaine Addiction

Drug addiction is characterized by neuroadaptations in mesocorticolimbic networks regulating reward and inhibitory control. The habenula (Hb) is central to adaptive reward and aversion-driven behaviors, serving as a hub connecting emotion/cognitive processing regions including the prefrontal cortex (PFC). However, its role in human drug addiction has not been fully explored. Using diffusion tractography, we detailed PFC structural connectivity with three regions, namely the Hb, ventral tegmental area (VTA), and anterior thalamus (AT), and quantified the tract-specific microstructural integrity using diffusion tensor imaging within the anterior limb of the internal capsule (ALIC) in healthy and cocaine-addicted individuals. White matter microstructure in cocaine-addicted individuals was uniquely impaired in PFC-Hb projections in the ALIC, distinguishable from adjacent PFC-VTA and PFC-AT projections, with more pronounced abnormalities in short-term abstinence. These findings extend preclinical evidence of PFC-Hb circuit impairments in addiction and contextualize the plausible existence of a similar PFC-Hb connection in the human brain.

Age-associated network controllability changes in first episode drug-naïve schizophrenia

Background Recent neuroimaging studies revealed dysregulated neurodevelopmental, or/and neurodegenerative trajectories of both structural and functional connections in schizophrenia. However, how the alterations in the brain’s structural connectivity lead to dynamic function changes in schizophrenia with age remains poorly understood. Methods Combining structural magnetic resonance imaging and a network control theory approach, the white matter network controllability metric (average controllability) was mapped from age 16 to 60 years in 175 drug-naïve schizophrenia patients and 155 matched healthy controls. Results Compared with controls, the schizophrenia patients demonstrated the lack of age-related decrease on average controllability of default mode network (DMN), as well as the right precuneus (a hub region of DMN), suggesting abnormal maturational development process in schizophrenia. Interestingly, the schizophrenia patients demonstrated an accelerated age-related decline of average controllability in the subcortical network, supporting the neurodegenerative model. In addition, compared with controls, the lack of age-related increase on average controllability of the left inferior parietal gyrus in schizophrenia patients also suggested a different pathway of brain development. Conclusions By applying the control theory approach, the present study revealed age-related changes in the ability of white matter pathways to control functional activity states in schizophrenia. The findings supported both the developmental and degenerative hypotheses of schizophrenia, and suggested a particularly high vulnerability of the DMN and subcortical network possibly reflecting an illness-related early marker for the disorder.

Changes in Bihemispheric Structural Connectivity Following Middle Cerebral Artery Infarction

This study investigated the changes in the structural connectivity of the bilateral hemispheres over time following a middle cerebral artery infarction. Eighteen patients in the subacute group and nine patients in the chronic group with mild upper extremity motor impairment (Fugl-Meyer motor assessment score for the upper limb > 43) following middle cerebral artery infarction were retrospectively evaluated in this study. All the patients underwent T1-weighted and diffusion tensor imaging. Tract-based statistical analyses of fractional anisotropy were used to compare the changes in the bilateral structural connectivity with those of age-matched normal controls. The corticospinal tract pathway of the affected hemisphere, corpus callosum, and corona radiata of the unaffected hemisphere had decreased structural connectivity in the subacute group, while the motor association area and anterior corpus callosum in the bilateral frontal lobes had increased structural connectivity in the chronic group. The bilateral hemispheres were influenced even in patients with mild motor impairment following middle cerebral artery infarction, and the structural connectivity of the bilateral hemispheres changed according to the time following the stroke.

Altered Structural and Functional MRI Connectivity in Type 2 Diabetes Mellitus Related Cognitive Impairment: A Review

Type 2 diabetes mellitus (T2DM) is associated with cognitive impairment in many domains. There are several pieces of evidence that changes in neuronal neuropathies and metabolism have been observed in T2DM. Structural and functional MRI shows that abnormal connections and synchronization occur in T2DM brain circuits and related networks. Neuroplasticity and energy metabolism appear to be principal effector systems, which may be related to amyloid beta (Aβ) deposition, although there is no unified explanation that includes the complex etiology of T2DM with cognitive impairment. Herein, we assume that cognitive impairment in diabetes may lead to abnormalities in neuroplasticity and energy metabolism in the brain, and those reflected to MRI structural connectivity and functional connectivity, respectively.

Concurrent fMRI demonstrates propagation of TMS effects across task-related networks

Transcranial magnetic stimulation (TMS) has become an important technique in both scientific and clinical practices, and yet our understanding of how the brain responds to TMS is still limited. Concurrent neuroimaging during TMS may bridge this gap, and emerging evidence suggests widespread that modulatory effects of TMS may be best captured through changes in functional connectivity between distributed networks, rather than local changes in cortical activity. However, the relationship between TMS stimulation parameters and evoked changes in functional connectivity is unknown. In this study, 24 healthy volunteers received concurrent TMS-fMRI while performing a dot-motion direction discrimination task. An MR-compatible coil was used to apply trains of three pulses at 10 Hz rTMS over the primary visual cortex (V1) at the onset of the dot stimuli with four levels of stimulation intensity (20%, 40%, 80%, and 120% of resting motor threshold, RMT). Behavioral results demonstrated impairment of motion discrimination at 80% RMT. FMRI results yielded three findings. First, functional connectivity between visual and non-visual areas increased as a function of rTMS intensity. Second, connectivity within the visual network was positively associated with motion accuracy, while the connectivity between visual and non-visual regions was negatively associated with motion accuracy. Lastly, we found that reductions in the similarity between functional and structural connectivity associated with increasing TMS intensity were constrained to the visual network. These findings demonstrate spatially dependent nonlinear effects of TMS intensity on brain functional connectivity that proceed beyond the site of stimulation and influence associated behavior.

Relationships between Diffusion Tensor Imaging and Resting State Functional Connectivity in Patients with Schizophrenia and Healthy Controls: A Preliminary Study

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 (&gt;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.

Neonatal brain injury influences structural connectivity and childhood functional outcomes

Neonatal brain injury may impact brain development and lead to lifelong functional impairments. Hypoxic-ischemic encephalopathy (HIE) and congenital heart disease (CHD) are two common causes of neonatal brain injury differing in timing and mechanism. Maturation of whole-brain neural networks can be quantified during development using diffusion magnetic resonance imaging (dMRI) in combination with graph theory metrics. DMRI of 35 subjects with CHD and 62 subjects with HIE were compared to understand differences in the effects of HIE and CHD on the development of network topological parameters and functional outcomes. CHD newborns had worse 12–18 month language (P<0.01) and 30 month cognitive (P<0.01), language (P = 0.05), motor outcomes (P = 0.01). Global efficiency, a metric of brain integration, was lower in CHD (P = 0.03) than in HIE, but transitivity, modularity and small-worldness were similar. After controlling for clinical factors known to affect neurodevelopmental outcomes, we observed that global efficiency was highly associated with 30 month motor outcomes (P = 0.02) in both groups. To explore neural correlates of adverse language outcomes in CHD, we used hypothesis-based and data-driven approaches to identify pathways with altered structural connectivity. We found that connectivity strength in the superior longitudinal fasciculus (SLF) tract 2 was inversely associated with expressive language. After false discovery rate correction, a whole connectome edge analysis identified 18 pathways that were hypoconnected in the CHD cohort as compared to HIE. In sum, our study shows that neonatal structural connectivity predicts early motor development after HIE or in subjects with CHD, and regional SLF connectivity is associated with language outcomes. Further research is needed to determine if and how brain networks change over time and whether those changes represent recovery or ongoing dysfunction. This knowledge will directly inform strategies to optimize neurologic functional outcomes after neonatal brain injury.