Neuroimage-Clinical最新文献

Parkinson’s disease (PD) is a neurodegenerative disease with cognitive as well as motor impairments. While much is known about the brain networks leading to motor impairments in PD, less is known about the brain networks contributing to cognitive impairments. Here, we leveraged resting-state functional magnetic resonance imaging (rs-fMRI) data from the Parkinson’s Progression Marker Initiative (PPMI) to examine network dysfunction in PD patients with cognitive impairment. We focus on canonical cortical networks linked to cognition, including the salience network (SAL), frontoparietal network (FPN), and default mode network (DMN), as well as a subcortical basal ganglia network (BGN). We used the Montreal Cognitive Assessment (MoCA) as a continuous index of coarse cognitive function in PD. In 82 PD patients, we found that lower MoCA scores were linked with lower intra-network connectivity of the FPN. We also found that lower MoCA scores were linked with lower inter-network connectivity between the SAL and the BGN, the SAL and the DMN, as well as the FPN and the DMN. These data elucidate the relationship of cortical and subcortical functional connectivity with cognitive impairments in PD.

Background and purpose

While mechanical thrombectomy (MT) achieves restoration of cerebral blood flow to the area at risk in patients with acute ischemic stroke (AIS), the influx of blood flow may exacerbate the blood–brain barrier (BBB) disruption and extravasation across the BBB, and it therefore remains unclear how reperfusion impacts the blood–brain barrier integrity. In this study, we use diffusion-prepared pseudocontinuous ASL (DP-pCASL) and Neurite Orientation Dispersion and Density Imaging (NODDI) sequence to measure the water exchange rate (k_w) in patients who underwent either MT or medical management and determine its impact on the brain tissue microstructure in order to elucidate the impact of MT on BBB complex integrity.

Materials and methods

We prospectively enrolled 21 patients with AIS treated at our institution from 10/2021 to 6/2023 who underwent MR imaging at a 3.0-Tesla scanner. Patients underwent DP-pCASl and NODDI imaging in addition to the standard stroke protocol which generated cerebral blood flow (CBF), arterial transit time (ATT), water exchange rate (k_w), orientation dispersion index (ODI), intracellular volume fraction (ICVF), and free water fraction (FWF) parametric maps.

Results

Of the 21 patients, 11 underwent MT and 10 were treated non-operatively. The average age and NIHSS for the MT cohort and non-MT cohorts were 69.3 ± 16.6 years old and 15.0 (12.0–20.0), and 70.2 ± 10.7 (p = 0.882) and 6.0 (3.8–9.0, p = 0.003) respectively. The average CBF, ATT, and k_w in the infarcted territory of the MT cohort were 38.2 (18.4–59.6), 1347.6 (1182.5–1842.3), and 107.8 (79.2–140.1) respectively. The average CBF, ATT, and k_w in the stroke ROI were 16.0 (8.8–36.6, p = 0.036), 1090.8 (937.1–1258.9, p = 0.013), 89.7 (68.0–122.7, p = 0.314) respectively. Linear regression analysis showed increasing CBF (p = 0.008) and undergoing mechanical thrombectomy (p = 0.048) were significant predictors of increased k_w.

Conclusion

Using our multimodal non-contrast MRI protocol, we demonstrate that increased CBF and mechanical thrombectomy increased k_w, suggesting a better functioning BBB complex. Higher k_w suggests less disruption of the BBB complex in the MT cohort.

Background

Nigrostriatal microstructural integrity has been suggested as a biomarker for levodopa response in Parkinson’s disease (PD), which is a strong predictor for motor response to deep brain stimulation (DBS) of the subthalamic nucleus (STN). This study aimed to explore the impact of microstructural integrity of the substantia nigra (SN), STN, and putamen on motor response to STN-DBS using diffusion microstructure imaging.

Methods

Data was collected from 23 PD patients (mean age 63 ± 7, 6 females) who underwent STN-DBS, had preoperative 3 T diffusion magnetic resonance imaging including multishell diffusion-weighted MRI with b-values of 1000 and 2000 s/mm² and records of motor improvement available.

Results

The association between a poorer DBS-response and increased free interstitial fluid showed notable effect sizes (rho > |0.4|) in SN and STN, but not in putamen. However, this did not reach significance after Bonferroni correction and controlling for sex and age.

Conclusion

Microstructural integrity of SN and STN are potential biomarkers for the prediction of therapy efficacy following STN-DBS, but further studies are required to confirm these associations.

In stimulant use and addiction, conflict control processes are crucial for regulating substance use and sustaining abstinence, which can be particularly challenging in social-affective situations. Users of methamphetamine (METH, “Ice”) and 3,4-methylenedioxymethamphetamine (MDMA, “Ecstasy”) both experience impulse control deficits, but display different social-affective and addictive profiles. We thus aimed to compare the effects of chronic use of the substituted amphetamines METH and MDMA on conflict control processes in different social-affective contexts (i.e., anger and happiness) and investigate their underlying neurophysiological mechanisms. For this purpose, chronic but recently abstinent users of METH (n = 38) and MDMA (n = 42), as well as amphetamine-naïve healthy controls (n = 83) performed an emotional face-word Stroop paradigm, while event-related potentials (ERPs) were recorded. Instead of substance-specific differences, both MDMA and METH users showed smaller behavioral effects of cognitive-emotional conflict processing (independently of emotional valence) and selective deficits in emotional processing of anger content. Both effects were underpinned by stronger P3 ERP modulations suggesting that users of substituted amphetamines employ altered stimulus–response mapping and decision-making. Given that these processes are modulated by noradrenaline and that both MDMA and METH use may be associated with noradrenergic dysfunctions, the noradrenaline system may underlie the observed substance-related similarities. Better understanding the functional relevance of this currently still under-researched neurotransmitter and its functional changes in chronic users of substituted amphetamines is thus an important avenue for future research.

Reward-based learning and decision-making are prime candidates to understand symptoms of attention deficit hyperactivity disorder (ADHD). However, only limited evidence is available regarding the neurocomputational underpinnings of the alterations seen in ADHD. This concerns flexible behavioral adaption in dynamically changing environments, which is challenging for individuals with ADHD. One previous study points to elevated choice switching in adolescent ADHD, which was accompanied by disrupted learning signals in medial prefrontal cortex.

Here, we investigated young adults with ADHD (n = 17) as compared to age- and sex-matched controls (n = 17) using a probabilistic reversal learning experiment during functional magnetic resonance imaging (fMRI). The task requires continuous learning to guide flexible behavioral adaptation to changing reward contingencies. To disentangle the neurocomputational underpinnings of the behavioral data, we used reinforcement learning (RL) models, which informed the analysis of fMRI data.

ADHD patients performed worse than controls particularly in trials before reversals, i.e., when reward contingencies were stable. This pattern resulted from ‘noisy’ choice switching regardless of previous feedback. RL modelling showed decreased reinforcement sensitivity and enhanced learning rates for negative feedback in ADHD patients. At the neural level, this was reflected in a diminished representation of choice probability in the left posterior parietal cortex in ADHD. Moreover, modelling showed a marginal reduction of learning about the unchosen option, which was paralleled by a marginal reduction in learning signals incorporating the unchosen option in the left ventral striatum.

Taken together, we show that impaired flexible behavior in ADHD is due to excessive choice switching (‘hyper-flexibility’), which can be detrimental or beneficial depending on the learning environment. Computationally, this resulted from blunted sensitivity to reinforcement of which we detected neural correlates in the attention-control network, specifically in the parietal cortex. These neurocomputational findings remain preliminary due to the relatively small sample size.

Background

Subcortical stroke may significantly alter the cerebral cortical structure and affect attention function, but the details of this process remain unclear. The study aimed to investigate the neural substrates underlying attention impairment in patients with subcortical stroke.

Materials and Methods

In this prospective observational study, two distinct datasets were acquired to identify imaging biomarkers underlying attention deficit. The first dataset consisted of 86 patients with subcortical stroke, providing a cross-sectional perspective, whereas the second comprised 108 patients with stroke, offering longitudinal insights. All statistical analyses were subjected to false discovery rate correction upon P < 0.05.

Results

In the chronic-stage data, the stroke group exhibited significantly poorer attention function compared with that of the control group. The cortical structure analysis showed that patients with stroke exhibited decreased cortical thickness of the precentral gyrus and surface area of the cuneus, along with an increase in various frontal, occipital, and parietal cortices regions. The declined attention function positively correlated with the superior frontal gyrus cortical thickness and supramarginal gyrus surface area. In the longitudinal dataset, patients with stroke showed gradually increasing cortical thickness and surface area within regions of obvious structural reorganization. Furthermore, deficient attention positively correlated with supramarginal gyrus surface area both at the subacute and chronic stages post-stroke.

Conclusions

Subcortical stroke can elicit dynamic reorganization of cortical areas associated with attention impairment. Moreover, the altered surface area of the supramarginal gyrus is a potential neuroimaging biomarker for attention deficits.

Objective

Intracranial volume (ICV) represents the maximal brain volume for an individual, attained prior to late adolescence and remaining constant throughout life after. Thus, ICV serves as a surrogate marker for brain growth integrity. To assess the potential impact of adult-onset multiple sclerosis (MS) and its preceding prodromal subclinical changes on ICV in a large cohort of monozygotic twins clinically discordant for MS.

Methods

FSL software was used to derive ICV estimates from 3D-T1-weighted-3 T-MRI images by using an atlas scaling factor method. ICV were compared between clinically affected and healthy co-twins. All twins were compared to a large healthy reference cohort using standardized ICV z-scores. Mixed models assessed the impact of age at MS diagnosis on ICV.

Results

54 twin-pairs (108 individuals/80female/42.45 ± 11.98 years), 731 individuals (375 non-twins, 109/69 monozygotic/dizygotic twin-pairs; 398female/29.18 ± 0.13 years) and 35 healthy local individuals (20male/31.34 ± 1.53 years). In 45/54 (83 %) twin-pairs, both clinically affected and healthy co-twins showed negative ICV z-scores, i.e., ICVs lower than the average of the healthy reference cohort (M = -1.53 ± 0.11, P<10⁻⁵). Younger age at MS diagnosis was strongly associated with lower ICVs (t = 3.76, P = 0.0003). Stratification of twin-pairs by age at MS diagnosis of the affected co-twin (≤30 versus > 30 years) yielded lower ICVs in those twin pairs with younger age at diagnosis (P = 0.01). Comparison within individual twin-pairs identified lower ICVs in the MS-affected co-twins with younger age at diagnosis compared to their corresponding healthy co-twins (P = 0.003).

Conclusion

We offer for the first-time evidence for strong associations between adult-onset MS and lower ICV, which is more pronounced with younger age at diagnosis. This suggests pre-clinical alterations in early neurodevelopment associated with susceptibility to MS both in individuals with and without clinical manifestation of the disease.

Discourse is a fundamentally important aspect of communication, and discourse production provides a wealth of information about linguistic ability. Aphasia commonly affects, in multiple ways, the ability to produce discourse. Comprehensive aphasia assessments such as the Western Aphasia Battery-Revised (WAB-R) are time- and resource-intensive. We examined whether discourse measures can be used to estimate WAB-R Aphasia Quotient (AQ), and whether this can serve as an ecologically valid, less resource-intensive measure. We used features extracted from discourse tasks using three AphasiaBank prompts involving expositional (picture description), story narrative, and procedural discourse. These features were used to train a machine learning model to predict the WAB-R AQ. We also compared and supplemented the model with lesion location information from structural neuroimaging. We found that discourse-based models could estimate AQ well, and that they outperformed models based on lesion features. Addition of lesion features to the discourse features did not improve the performance of the discourse model substantially. Inspection of the most informative discourse features revealed that different prompt types taxed different aspects of language. These findings suggest that discourse can be used to estimate aphasia severity, and provide insight into the linguistic content elicited by different types of discourse prompts.

Antipsychotic drug treatment for schizophrenia (SZ) can alter brain structure and function, but it is unclear if specific regional changes are associated with treatment outcome. Therefore, we examined the effects of antipsychotic drug treatment on regional grey matter (GM) density, white matter (WM) density, and functional connectivity (FC) as well as associations between regional changes and treatment efficacy. SZ patients (n = 163) and health controls (HCs) (n = 131) were examined by structural magnetic resonance imaging (sMRI) at baseline, and a subset of SZ patients (n = 77) were re-examined after 8 weeks of second-generation antipsychotic treatment to assess changes in regional GM and WM density. In addition, 88 SZ patients and 81 HCs were examined by resting-state functional MRI (rs-fMRI) at baseline and the patients were re-examined post-treatment to examine FC changes. The Positive and Negative Syndrome Scale (PANSS) and MATRICS Consensus Cognitive Battery (MCCB) were applied to measure psychiatric symptoms and cognitive impairments in SZ. SZ patients were then stratified into response and non-response groups according to PANSS score change (≥50 % decrease or <50 % decrease, respectively). The GM density of the right cingulate gyrus, WM density of the right superior frontal gyrus (SFG) plus 5 other WM tracts were reduced in the response group compared to the non-response group. The FC values between the right anterior cingulate and paracingulate gyrus and left thalamus were reduced in the entire SZ group (n = 88) after treatment, while FC between the right inferior temporal gyrus (ITG) and right medial superior frontal gyrus (SFGmed) was increased in the response group. There were no significant changes in regional FC among the non-response group after treatment and no correlations with symptom or cognition test scores. These findings suggest that the right SFG is a critical target of antipsychotic drugs and that WM density and FC alterations within this region could be used as potential indicators in predicting the treatment outcome of antipsychotics of SZ.

Understanding why some patients with depression remain resistant to antidepressant medication could be elucidated by investigating their associated neural features. Although research has consistently demonstrated abnormalities in the anterior cingulate cortex (ACC) – a region that is part of the default mode network (DMN) − in treatment-resistant depression (TRD), a considerable research gap exists in discerning how these neural networks distinguish TRD from treatment-sensitive depression (TSD). We aimed to evaluate the resting-state functional connectivity (rsFC) of the ACC with other regions of the DMN to better understand the role of this structure in the pathophysiology of TRD. 35 TRD patients, 35 TSD patients, and 38 healthy controls (HC) underwent a resting-state functional MRI protocol. Seed-based functional connectivity analyses were performed, comparing the three groups for the connectivity between two subregions of the ACC (the subgenual ACC (sgACC) and the rostral ACC (rACC)) and the DMN (p < 0.05 FWE corrected). Furthermore, inter-network connectivity of the DMN with other neural networks was explored by independent component (ICA) analyses (p < 0.01, FDR corrected). The results demonstrated hyperconnectivity between the rACC and the posterior cingulate cortex in TRD relative to TSD and HC (F(2,105) = 5.335, p < 0.05). ICA found DMN connectivity to regions of the visual network (TRD<TSD) and a parietal region of the DMN (TRD>TSD), differentiating the two clinical groups. These results provide confirmatory evidence of DMN hyperconnectivity and preliminary evidence for its interactions with other neural networks as key neural mechanisms underlying treatment non-responsiveness.