Most recent paper

Brain Sci. 2022 Jul 28;12(8):998. doi: 10.3390/brainsci12080998.

ABSTRACT

BACKGROUND: Obsessive-compulsive disorder (OCD) is a psychiatric disorder with high clinical heterogeneity manifested by the presence of obsessions and/or compulsions. The classification of the symptom dimensional subtypes is helpful for further exploration of the pathophysiological mechanisms underlying the clinical heterogeneity of OCD. Washing and checking symptoms are the two major symptom subtypes in OCD, but the neural mechanisms of the different types of symptoms are not yet clearly understood. The purpose of this study was to compare regional and network functional alterations between washing and checking OCD based on resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS: In total, 90 subjects were included, including 15 patients in the washing group, 30 patients in the checking group, and 45 healthy controls (HCs). Regional homogeneity (ReHo) was used to compare the differences in regional spontaneous neural activity among the three groups, and local indicators were analyzed by receiver operating characteristic (ROC) curves as imaging markers for the prediction of the clinical subtypes of OCD. Furthermore, differently activated local brain areas, as regions of interest (ROIs), were used to explore differences in altered brain functioning between washing and checking OCD symptoms based on a functional connectivity (FC) analysis.

RESULTS: Extensive abnormalities in spontaneous brain activity involving frontal, temporal, and occipital regions were observed in the patients compared to the HCs. The differences in local brain functioning between checking and washing OCD were mainly concentrated in the bilateral middle frontal gyrus, right supramarginal gyrus, right angular gyrus, and right inferior occipital gyrus. The ROC curve analysis revealed that the hyperactivation right middle frontal gyrus had a better discriminatory value for checking and washing OCD. Furthermore, the seed-based FC analysis revealed higher FC between the left medial superior frontal gyrus and right caudate nucleus compared to that in the healthy controls.

CONCLUSIONS: These findings suggest that extensive local differences exist in intrinsic spontaneous activity among the checking group, washing group, and HCs. The neural basis of checking OCD may be related to dysfunction in the frontal-striatal network, which distinguishes OCD from washing OCD.

PMID:36009061 | DOI:10.3390/brainsci12080998

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2022 Aug 25;39(4):759-766. doi: 10.7507/1001-5515.202203072.

ABSTRACT

Amblyopia is a visual development deficit caused by abnormal visual experience in early life, mainly manifesting as defected visual acuity and binocular visual impairment, which is considered to reflect abnormal development of the brain rather than organic lesions of the eye. Previous studies have reported abnormal spontaneous brain activity in patients with amblyopia. However, the location of abnormal spontaneous activity in patients with amblyopia and the association between abnormal brain function activity and clinical deficits remain unclear. The purpose of this study is to analyze spontaneous brain functional activity abnormalities in patients with amblyopia and their associations with clinical defects using resting-state functional magnetic resonance imaging (fMRI) data. In this study, 31 patients with amblyopia and 31 healthy controls were enrolled for resting-state fMRI scanning. The results showed that spontaneous activity in the right angular gyrus, left posterior cerebellum, and left cingulate gyrus were significantly lower in patients with amblyopia than in controls, and spontaneous activity in the right middle temporal gyrus was significantly higher in patients with amblyopia. In addition, the spontaneous activity of the left cerebellum in patients with amblyopia was negatively associated with the best-corrected visual acuity of the amblyopic eye, and the spontaneous activity of the right middle temporal gyrus was positively associated with the stereoacuity. This study found that adult patients with amblyopia showed abnormal spontaneous activity in the angular gyrus, cerebellum, middle temporal gyrus, and cingulate gyrus. Furthermore, the functional abnormalities in the cerebellum and middle temporal gyrus may be associated with visual acuity defects and stereopsis deficiency in patients with amblyopia. These findings help explain the neural mechanism of amblyopia, thus promoting the improvement of the treatment strategy for amblyopia.

PMID:36008340 | DOI:10.7507/1001-5515.202203072

Brain Connect. 2022 Aug 25. doi: 10.1089/brain.2022.0007. Online ahead of print.

ABSTRACT

Despite the explosive growth of neuroimaging studies aimed at analyzing the brain as a complex system, critical methodological gaps remain to be addressed. Most tools currently used for analyzing network data of the brain are univariate in nature and are based on assumptions borne out of previous techniques not directly related to the big and complex data of the brain. Although graph-based methods have shown great promise, development of principled multivariate models to address inherent limitations of graph-based methods, such as their dependence on network size and degree distributions, and to allow assessing the effects of multiple phenotypes on the brain and simulating brain networks has largely lagged behind. Although some studies have been made in developing multivariate frameworks to fill this gap, in the absence of a "gold-standard" method or guidelines, choosing the most appropriate method for each study can be another critical challenge for investigators in this multidisciplinary field. Here, we briefly introduce important multivariate methods for brain network analyses in two main categories: data-driven and model-based methods. We discuss whether/how such methods are suited for examining connectivity (edge-level), topology (system-level), or both. This review will aid in choosing an appropriate multivariate method with respect to variables such as network type, number of subjects and brain regions included, and the interest in connectivity, topology, or both. This review is aimed to be accessible to investigators from different backgrounds, with a focus on applications in brain network studies, though the methods may be applicable in other areas too.

PMID:36006366 | DOI:10.1089/brain.2022.0007

Brain Connect. 2022 Aug 25. doi: 10.1089/brain.2021.0182. Online ahead of print.

ABSTRACT

BACKGROUND: Multivoxel pattern analysis (MVPA) has emerged as a powerful unbiased approach for generating seed regions of interest (ROIs) in resting-state functional connectivity (RSFC) analysis in a data-driven manner. Studies exploring RSFC in multiple sclerosis have produced diverse and often incongruent results.

OBJECTIVES: The aim of the present study was to investigate RSFC differences between persons with relapsing-remitting multiple sclerosis (RRMS) and healthy controls (HC).

METHODS: We performed a whole-brain connectome-wide MVPA in 50 RRMS patients with expanded disability status scale ≤4 and 50 age and gender-matched HC.

RESULTS: Significant group differences were noted in RSFC in three clusters distributed in the following regions; anterior cingulate gyrus, right middle frontal gyrus and frontal medial cortex. Whole-brain seed-to-voxel RSFC characterization of these clusters as seed ROIs revealed network specific abnormalities, specifically in the anterior cingulate cortex and the default mode network.

CONCLUSIONS: The network-wide RSFC abnormalities we report study agree with previous findings in RRMS. The cognitive and clinical implications of these are discussed herein.

PMID:36006365 | DOI:10.1089/brain.2021.0182

Cereb Cortex. 2022 Aug 25:bhac295. doi: 10.1093/cercor/bhac295. Online ahead of print.

ABSTRACT

The effects of oxytocin (OT) on the social brain can be tracked upon assessing the neural activity in resting and task states, and developing a system-level framework for characterizing the state-based functional relationships of its distinct effect. Here, we contribute to this framework by examining how OT modulates social brain network correlations during resting and task states, using fMRI. First, we investigated network activation, followed by an analysis of the relationships between networks and individual differences. Subsequently, we evaluated the functional connectivity in both states. Finally, the relationship between networks across states was represented by the predictive power of networks in the resting state for task-evoked activities. The differences in the predicted accuracy between the subjects displayed individual variations in this relationship. Our results showed that the activity of the dorsal default mode network in the resting state had the largest predictive power for task-evoked activation of the precuneus network (PN) only in the OT group. The results also demonstrated that OT reduced the individual variation in PN in the prediction process. These findings suggest a distributed but modulatory effect of OT on the association between resting and task-dependent brain networks.

PMID:36005833 | DOI:10.1093/cercor/bhac295

Biosensors (Basel). 2022 Aug 8;12(8):616. doi: 10.3390/bios12080616.

ABSTRACT

Anesthesia is often used in preclinical imaging studies that incorporate mouse or rat models. However, multiple reports indicate that anesthesia has significant physiological impacts. Thus, there has been great interest in performing imaging studies in awake, unanesthetized animals to obtain accurate results without the confounding physiological effects of anesthesia. Here, we describe a newly designed mouse holder that is interfaceable with existing MRI systems and enables awake in vivo mouse imaging. This holder significantly reduces head movement of the awake animal compared to previously designed holders and allows for the acquisition of improved anatomical images. In addition to applications in anatomical T2-weighted magnetic resonance imaging (MRI), we also describe applications in acquiring 31P spectra, manganese-enhanced magnetic resonance imaging (MEMRI) transport rates and resting-state functional magnetic resonance imaging (rs-fMRI) in awake animals and describe a successful conditioning paradigm for awake imaging. These data demonstrate significant differences in 31P spectra, MEMRI transport rates, and rs-fMRI connectivity between anesthetized and awake animals, emphasizing the importance of performing functional studies in unanesthetized animals. Furthermore, these studies demonstrate that the mouse holder presented here is easy to construct and use, compatible with standard Bruker systems for mouse imaging, and provides rigorous results in awake mice.

PMID:36005011 | DOI:10.3390/bios12080616

Psychol Med. 2022 Aug 25:1-10. doi: 10.1017/S0033291722002665. Online ahead of print.

ABSTRACT

BACKGROUND: Studies have shown that people with internet gaming disorder (IGD) exhibit impaired executive control of gaming cravings; however, the neural mechanisms underlying this process remain unknown. In addition, these conclusions were based on the hypothesis that brain networks are temporally static, neglecting dynamic changes in cognitive processes.

METHODS: Resting-state fMRI data were collected from 402 subjects [162 subjects with IGD and 240 recreational game users (RGUs)]. The community structure (recruitment and integration) of the executive control network (ECN) and the basal ganglia network (BGN), which represents the reward network, of patients with IGD and RGUs were compared. Mediation effects among the different networks were analyzed.

RESULTS: Compared to RGUs, subjects with IGD had a lower recruitment coefficient within the right ECN. Further analysis showed that only male subjects had a lower recruitment coefficient. Mediation analysis showed that the integration coefficient of the right ECN mediated the relationship between the recruitment coefficients of both the right ECN and the BGN in RGUs.

CONCLUSIONS: Male subjects with IGD had a lower recruitment coefficient than RGUs, which impairing their impulse control. The mediation results suggest that top-down executive control of the ECN is absent in subjects with IGD. Together, these findings could explain why subjects with IGD exhibit impaired executive control of gaming cravings; these results have important therapeutic implications for developing effective interventions for IGD.

PMID:36004801 | DOI:10.1017/S0033291722002665

Front Aging Neurosci. 2022 Aug 8;14:893297. doi: 10.3389/fnagi.2022.893297. eCollection 2022.

ABSTRACT

BACKGROUND: Neural reorganization occurs after a stroke, and dynamic functional network connectivity (dFNC) pattern is associated with cognition. We hypothesized that dFNC alterations resulted from neural reorganization in post-stroke cognitive impairment (PSCI) patients, and specific dFNC patterns characterized different pathological types of PSCI.

METHODS: Resting-state fMRI data were collected from 16 PSCI patients with hemorrhagic stroke (hPSCI group), 21 PSCI patients with ischemic stroke (iPSCI group), and 21 healthy controls (HC). We performed the dFNC analysis for the dynamic connectivity states, together with their topological and temporal features.

RESULTS: We identified 10 resting-state networks (RSNs), and the dFNCs could be clustered into four reoccurring states (modular, regional, sparse, and strong). Compared with HC, the hPSCI and iPSCI patients showed lower standard deviation (SD) and coefficient of variation (CV) in the regional and modular states, respectively (p < 0.05). Reduced connectivities within the primary network (visual, auditory, and sensorimotor networks) and between the primary and high-order cognitive control domains were observed (p < 0.01).

CONCLUSION: The transition trend to suboptimal states may play a compensatory role in patients with PSCI through redundancy networks. The reduced exploratory capacity (SD and CV) in different suboptimal states characterized cognitive impairment and pathological types of PSCI. The functional disconnection between the primary and high-order cognitive control network and the frontoparietal network centered (FPN-centered) incomplete compensation may be the pathological mechanism of PSCI. These results emphasize the flexibility of neural reorganization during self-repair.

PMID:36003999 | PMC:PMC9393744 | DOI:10.3389/fnagi.2022.893297

Front Psychiatry. 2022 Aug 8;13:992669. doi: 10.3389/fpsyt.2022.992669. eCollection 2022.

NO ABSTRACT

PMID:36003976 | PMC:PMC9393692 | DOI:10.3389/fpsyt.2022.992669

Front Neurosci. 2022 Aug 8;16:970245. doi: 10.3389/fnins.2022.970245. eCollection 2022.

ABSTRACT

BACKGROUND: Textural features of the hippocampus in structural magnetic resonance imaging (sMRI) images can serve as potential diagnostic biomarkers for Alzheimer's disease (AD), while exhibiting a relatively poor discriminant performance in detecting early AD, such as amnestic mild cognitive impairment (aMCI). In contrast to sMRI, functional magnetic resonance imaging (fMRI) can identify brain functional abnormalities in the early stages of cerebral disorders. However, whether the textural features reflecting local functional activity in the hippocampus can improve the diagnostic performance for AD and aMCI remains unclear. In this study, we combined the textural features of the amplitude of low frequency fluctuation (ALFF) in the slow-5 frequency band and structural images in the hippocampus to investigate their diagnostic performance for AD and aMCI using multimodal radiomics technique.

METHODS: Totally, 84 AD, 50 aMCI, and 44 normal controls (NCs) were included in the current study. After feature extraction and feature selection, the radiomics models incorporating sMRI images, ALFF values and their combinations in the bilateral hippocampus were established for the diagnosis of AD and aMCI. The effectiveness of these models was evaluated by receiver operating characteristic (ROC) analysis. The radiomics models were further validated using the external data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database.

RESULTS: The results of ROC analysis showed that the radiomics models based on structural images in the hippocampus had a better diagnostic performance for AD compared with the models using ALFF, while the ALFF-based model exhibited better discriminant performance for aMCI than the models with structural images. The radiomics models based on the combinations of structural images and ALFF were found to exhibit the highest accuracy for distinguishing AD from NCs and aMCI from NCs.

CONCLUSION: In this study, we found that the textural features reflecting local functional activity could improve the diagnostic performance of traditional structural models for both AD and aMCI. These findings may deepen our understanding of the pathogenesis of AD, contributing to the early diagnosis of AD.

PMID:36003964 | PMC:PMC9393721 | DOI:10.3389/fnins.2022.970245

Front Neurosci. 2022 Aug 8;16:909999. doi: 10.3389/fnins.2022.909999. eCollection 2022.

ABSTRACT

A number of studies point to slow (0.1-2 Hz) brain rhythms as the basis for the resting-state functional magnetic resonance imaging (rsfMRI) signal. Slow waves exist in the absence of stimulation, propagate across the cortex, and are strongly modulated by vigilance similar to large portions of the rsfMRI signal. However, it is not clear if slow rhythms serve as the basis of all neural activity reflected in rsfMRI signals, or just the vigilance-dependent components. The rsfMRI data exhibit quasi-periodic patterns (QPPs) that appear to increase in strength with decreasing vigilance and propagate across the brain similar to slow rhythms. These QPPs can complicate the estimation of functional connectivity (FC) via rsfMRI, either by existing as unmodeled signal or by inducing additional wide-spread correlation between voxel-time courses of functionally connected brain regions. In this study, we examined the relationship between cortical slow rhythms and the rsfMRI signal, using a well-established pharmacological model of slow wave suppression. Suppression of cortical slow rhythms led to significant reduction in the amplitude of QPPs but increased rsfMRI measures of intrinsic FC in rats. The results suggest that cortical slow rhythms serve as the basis of only the vigilance-dependent components (e.g., QPPs) of rsfMRI signals. Further attenuation of these non-specific signals enhances delineation of brain functional networks.

PMID:36003960 | PMC:PMC9393715 | DOI:10.3389/fnins.2022.909999

Neuroimage Clin. 2022;35:103139. doi: 10.1016/j.nicl.2022.103139. Epub 2022 Aug 1.

ABSTRACT

Children with auditory processing disorder (APD) experience hearing difficulties, particularly in the presence of competing sounds, despite having normal audiograms. There is considerable debate on whether APD symptoms originate from bottom-up (e.g., auditory sensory processing) and/or top-down processing (e.g., cognitive, language, memory). A related issue is that little is known about whether functional brain network topology is altered in APD. Therefore, we used resting-state functional magnetic resonance imaging data to investigate the functional brain network organization of 57 children from 8 to 14 years old, diagnosed with APD (n = 28) and without hearing difficulties (healthy control, HC; n = 29). We applied complex network analysis using graph theory to assess the whole-brain integration and segregation of functional networks and brain hub architecture. Our results showed children with APD and HC have similar global network properties -i.e., an average of all brain regions- and modular organization. Still, the APD group showed different hub architecture in default mode-ventral attention, somatomotor and frontoparietal-dorsal attention modules. At the nodal level -i.e., single-brain regions-, we observed decreased participation coefficient (PC - a measure quantifying the diversity of between-network connectivity) in auditory cortical regions in APD, including bilateral superior temporal gyrus and left middle temporal gyrus. Beyond auditory regions, PC was also decreased in APD in bilateral posterior temporo-occipital cortices, left intraparietal sulcus, and right posterior insular cortex. Correlation analysis suggested a positive association between PC in the left parahippocampal gyrus and the listening-in-spatialized-noise -sentences task where APD children were engaged in auditory perception. In conclusion, our findings provide evidence of altered brain network organization in children with APD, specific to auditory networks, and shed new light on the neural systems underlying children's listening difficulties.

PMID:36002970 | DOI:10.1016/j.nicl.2022.103139

Neuroimage Clin. 2022;35:103110. doi: 10.1016/j.nicl.2022.103110. Epub 2022 Jul 16.

ABSTRACT

OBJECTIVES: Previous studies with adults suggest that aberrant communication between neural networks underpins functional neurological disorder (FND). The current study adopts a data-driven approach to investigate the extent that functional resting-state networks are disrupted in a pediatric mixed-FND cohort.

METHODS: 31 children with mixed FND and 33 age- and sex-matched healthy controls completed resting-state fMRI scans. Whole-brain independent component analysis (pFWE < 0.05) was then used to identify group differences in resting-state connectivity. Self-report measures included the Depression, Anxiety and Stress Scale (DASS-21) and Early Life Stress Questionnaire (ELSQ). Resting-state heart rate (HR) and cortisol-awakening response (CAR) were available in a subset.

RESULTS: Children with FND showed wide-ranging connectivity changes in eight independent components corresponding to eight resting-state neural networks: language networks (IC6 and IC1), visual network, frontoparietal network, salience network, dorsal attention network, cerebellar network, and sensorimotor network. Children whose clinical presentation included functional seizures (vs children with other FND symptoms) showed greater connectivity decreases in the frontoparietal and dorsal attentional networks. Subjective distress (total DASS score), autonomic arousal (indexed by HR), and HPA dysregulation (attenuated/reversed CAR) contributed to changes in neural network connectivity. Children with FND (vs controls) reported more subjective distress (total DASS score) and more adverse childhood experiences (ACEs) across their lifespan.

CONCLUSIONS: Children with FND demonstrate changes in resting-state connectivity. Identified network alterations underpin a broad range of functions typically disrupted in children with FND. This study complements the adult literature by suggesting that FND in children and adolescents emerges in the context of their lived experience and that it reflects aberrant communication across neural networks.

PMID:36002964 | DOI:10.1016/j.nicl.2022.103110

Neuroimage Clin. 2022;35:103145. doi: 10.1016/j.nicl.2022.103145. Epub 2022 Aug 5.

ABSTRACT

In the present study, we aimed to investigate the resting-state functional connectivity (RS-FC) of the globus pallidus (GP) in patients with amyotrophic lateral sclerosis (ALS) compared to healthy controls, and the relationship between RS-FC changes and disgust recognition. Twenty-six pure-motor ALS patients and 52 healthy controls underwent RS functional MRI and a neuropsychological assessment including the Comprehensive Affect Testing System. A seed-based RS-FC analysis was performed between the left and right GP and the rest of the brain and compared between groups. Correlations between RS-FC significant changes and subjects' performance in recognizing disgust were tested. Compared to controls, patients were significantly less able to recognize disgust. In ALS compared to controls, the seed-based analysis showed: reduced RS-FC between bilateral GP and bilateral middle and superior frontal and middle cingulate gyri, and increased RS-FC between bilateral GP and bilateral postcentral, supramarginal and superior temporal gyri and Rolandic operculum. Decreased RS-FC was further observed between left GP and left middle and inferior temporal gyri and bilateral caudate; and increased RS-FC was also shown between right GP and left lingual and fusiform gyri. In patients and controls, lower performance in recognizing disgust correlated with reduced RS-FC between left GP and left middle and inferior temporal gyri. In pure-motor ALS patients, we demonstrated altered RS-FC between GP and the rest of the brain. The reduced left pallidum-temporo-striatal RS-FC may have a role in the lower ability of patients in recognizing disgust.

PMID:36002963 | DOI:10.1016/j.nicl.2022.103145

Sci Rep. 2022 Aug 24;12(1):14407. doi: 10.1038/s41598-022-18495-z.

ABSTRACT

Machine learning analyses were performed on graph theory (GT) metrics extracted from brain functional and morphological data from temporal lobe epilepsy (TLE) patients in order to identify intrinsic network phenotypes and characterize their clinical significance. Participants were 97 TLE and 36 healthy controls from the Epilepsy Connectome Project. Each imaging modality (i.e., Resting-state functional Magnetic Resonance Imaging (RS-fMRI), and structural MRI) rendered 2 clusters: one comparable to controls and one deviating from controls. Participants were minimally overlapping across the identified clusters, suggesting that an abnormal functional GT phenotype did not necessarily mean an abnormal morphological GT phenotype for the same subject. Morphological clusters were associated with a significant difference in the estimated lifetime number of generalized tonic-clonic seizures and functional cluster membership was associated with age. Furthermore, controls exhibited significant correlations between functional GT metrics and cognition, while for TLE participants morphological GT metrics were linked to cognition, suggesting a dissociation between higher cognitive abilities and GT-derived network measures. Overall, these findings demonstrate the existence of clinically meaningful minimally overlapping phenotypes of morphological and functional GT networks. Functional network properties may underlie variance in cognition in healthy brains, but in the pathological state of epilepsy the cognitive limits might be primarily related to structural cerebral network properties.

PMID:36002603 | DOI:10.1038/s41598-022-18495-z

J Neurosci. 2022 Aug 22:JN-RM-0269-22. doi: 10.1523/JNEUROSCI.0269-22.2022. Online ahead of print.

ABSTRACT

A particularly elusive puzzle concerning the hippocampus is how the structural differences along its long, anteroposterior axis might beget meaningful functional differences, particularly in terms of the granularity of information processing. One measure posits to quantify this granularity by calculating the average statistical independence of the BOLD signal across neighboring voxels, or inter-voxel similarity (IVS), and has shown the anterior hippocampus to process coarser-grained information than the posterior hippocampus. This measure, however, has yielded opposing results in studies of developmental and healthy aging samples, which also varied in fMRI acquisition parameters and hippocampal parcellation methods. In order to reconcile these findings, we measured IVS across two separate resting-state fMRI acquisitions and compared the results across many of the most widely used parcellation methods in a large young-adult sample of male and female humans (Acquisition 1, N = 233; Acquisition 2, N = 176). Finding conflicting results across acquisitions and parcellations, we reasoned that a data-driven approach to hippocampal parcellation is necessary. To this end, we implemented a group masked independent components analysis (mICA) to identify functional subunits of the hippocampus, most notably separating the anterior hippocampus into separate anterior-medial, anterior-lateral, and posteroanterior-lateral components. Measuring IVS across these components revealed a decrease in IVS along the medial-lateral axis of the anterior hippocampus but an increase from anterior to posterior. We conclude that inter-voxel similarity is deeply affected by parcellation, and that grounding one's parcellation in a functionally informed approach might allow for a more complex and reliable characterization of the hippocampus.SIGNIFICANCE STATEMENT:Processing information along hierarchical scales of granularity is critical for many of the feats of cognition considered most human. Recently, the changes in structure, cortical connectivity, and apparent functional properties across parcels of the hippocampal long axis have been hypothesized to underlie this hierarchical gradient in information processing. We show here, however, that the choice of parcellation method itself drastically affects one particular measure of granularity across the hippocampus, and that a functionally informed approach to parcellation reveals gradients both within the anterior hippocampus and in non-linear form across the long axis. These results point to the issue of parcellation as a critical one in the study of the hippocampus and reorient interpretation of existing results.

PMID:36002264 | DOI:10.1523/JNEUROSCI.0269-22.2022

Addict Biol. 2022 Sep;27(5):e13210. doi: 10.1111/adb.13210.

ABSTRACT

Self-control is important for long-term success and could be a protective factor against maladaptive behaviours such as excessive gaming activity or Internet gaming disorder (IGD). However, the neurobiological basis of self-control and its relationship to IGD remain elusive. Using resting-state fMRI data from 89 participants aged from 18 to 26, we found that self-control and the number of IGD symptoms (IGD-S) were positively and negatively correlated with functional connectivity between right ventral striatum (rVS) and dorsal anterior cingulate cortex (dACC), respectively. A mediation analysis indicated that self-control influenced IGD-S partially through the rVS-dACC connectivity. In addition, step-wise regression analyses revealed that the rVS connectivity in a reward-anticipation limbic pathway contributed to IGD-S but not self-control, independent of the dACC pathway. These results suggest that the cingulate-ventral striatal functional connectivity may serve as an important neurobiological underpinning of self-control to regulate maladaptive behaviours such as these manifesting IGD through striatal circuitry balance.

PMID:36001435 | DOI:10.1111/adb.13210

Addict Biol. 2022 Sep;27(5):e13221. doi: 10.1111/adb.13221.

ABSTRACT

BACKGROUND: Tobacco addiction is a chronic, relapsing mental disorder characterized by compulsive tobacco seeking and smoking. Current evidence shows that tobacco addiction exerts their initial reinforcing effects by activating reward circuits in the brain, but the causal connectivity among reward circuits is still unclear. Therefore, it is vital to understand how the reward network works to lead to the compulsive smoking behaviour.

METHOD: We applied dynamic causal modelling (DCM) to resting-state functional magnetic resonance (rs-fMRI) to characterize changes in effective connectivity (EC) among eight major hubs from reward network between 76 long-term male smokers and 55 nonsmoking volunteers (matched with age, gender and education).

RESULTS: Relative to the healthy controls, long-term smokers had stronger ECs from the right anterior insula to left ventral striatum, posterior cingulate cortex (PCC) to ventral tegmental area (VTA), PCC to left anterior insula, left anterior insula to VTA, and ventromedial prefrontal cortex (vmPFC) to PCC and weaker ECs from the VTA to left ventral striatum, right anterior insula to right ventral striatum, and anterior cingulate cortex (ACC) to right anterior insula.

CONCLUSIONS: Overall, our findings revealed disrupted neural causal interactions among parts of the reward network associated with tobacco addiction, expanding the growing evidence for the potential neurobiological mechanisms of tobacco addiction. We found abnormalities within the mesocorticolimbic system and a top-down regulation disorder in the dopamine-dependent process of response inhibition and salience attribution among long-term smokers, which may facilitate the development of effective therapies in tobacco addiction.

PMID:36001421 | DOI:10.1111/adb.13221

JAMA Psychiatry. 2022 Aug 24. doi: 10.1001/jamapsychiatry.2022.2464. Online ahead of print.

ABSTRACT

IMPORTANCE: Major depressive disorder (MDD) is characterized by a substantial burden on health, including changes in appetite and body weight. Heterogeneity of depressive symptoms has hampered the identification of biomarkers that robustly generalize to most patients, thus calling for symptom-based mapping.

OBJECTIVE: To define the functional architecture of the reward circuit subserving increases vs decreases in appetite and body weight in patients with MDD by specifying their contributions and influence on disease biomarkers using resting-state functional connectivity (FC).

DESIGN, SETTING, AND PARTICIPANTS: In this case-control study, functional magnetic resonance imaging (fMRI) data were taken from the Marburg-Münster FOR 2107 Affective Disorder Cohort Study (MACS), collected between September 2014 and November 2016. Cross-sectional data of patients with MDD (n = 407) and healthy control participants (n = 400) were analyzed from March 2018 to June 2022.

MAIN OUTCOMES AND MEASURES: Changes in appetite during the depressive episode and their association with FC were examined using fMRI. By taking the nucleus accumbens (NAcc) as seed of the reward circuit, associations with opposing changes in appetite were mapped, and a sparse symptom-specific elastic-net model was built with 10-fold cross-validation.

RESULTS: Among 407 patients with MDD, 249 (61.2%) were women, and the mean (SD) age was 36.79 (13.4) years. Reduced NAcc-based FC to the ventromedial prefrontal cortex (vmPFC) and the hippocampus was associated with reduced appetite (vmPFC: bootstrap r = 0.13; 95% CI, 0.02-0.23; hippocampus: bootstrap r = 0.15; 95% CI, 0.05-0.26). In contrast, reduced NAcc-based FC to the insular ingestive cortex was associated with increased appetite (bootstrap r = -0.14; 95% CI, -0.24 to -0.04). Critically, the cross-validated elastic-net model reflected changes in appetite based on NAcc FC and explained variance increased with increasing symptom severity (all patients: bootstrap r = 0.24; 95% CI, 0.16-0.31; patients with Beck Depression Inventory score of 28 or greater: bootstrap r = 0.42; 95% CI, 0.25-0.58). In contrast, NAcc FC did not classify diagnosis (MDD vs healthy control).

CONCLUSIONS AND RELEVANCE: In this study, NAcc-based FC reflected important individual differences in appetite and body weight in patients with depression that can be leveraged for personalized prediction. However, classification of diagnosis using NAcc-based FC did not exceed chance levels. Such symptom-specific associations emphasize the need to map biomarkers onto more confined facets of psychopathology to improve the classification and treatment of MDD.

PMID:36001327 | DOI:10.1001/jamapsychiatry.2022.2464

J Anal Tech Res. 2022;4(2):89-101. Epub 2022 May 19.

ABSTRACT

Cognitive reserve (CR) is the ability to preserve cognitive functions in the presence of brain pathology. In the context of Alzheimer's disease (AD), patients with higher CR show better cognitive performance relative to brain damage therefore higher CR reduces the risk of dementia. There is a strong need to develop a neurophysiological biomarker of CR given the growing interest in understanding protective brain mechanisms in AD. FMRI studies indicate that frontoparietal network plays an important role in cognitive reserve. We calculated intraregional functional connectivity of lateral prefrontal cortex (FC LPFC) using functional near infrared spectroscopy (fNIRS) in the resting state of 13 healthy individuals who were also assessed for IQ and motoric skills (the Purdue Pegboard test, PPT). FC LPFC was found to positively correlate with IQ (a proxy measure of cognitive reserve) while showing a lack of or negative correlation with the PPT scores. The results demonstrate that the cost-effective, noninvasive and widely applicable fNIRS technology can be used to evaluate cognitive reserve in individuals at risk for and patients with AD with possible numerous applications in the context of healthy aging and other age-related cognitive disorders.

PMID:35999855 | PMC:PMC9394433