Family-wise Error Research Articles

Large-Scale Exploration of Whole-Brain Structural Connectivity in Anorexia Nervosa: Alterations in the Connectivity of Frontal and Subcortical Networks

BackgroundAnorexia nervosa (AN) is characterized by disturbances in cognition and behavior surrounding eating and weight. The severity of AN combined with the absence of localized brain abnormalities suggests distributed, systemic underpinnings that may be identified using diffusion-weighted magnetic resonance imaging and tractography to reconstruct white matter pathways. MethodsDiffusion-weighted magnetic resonance imaging data acquired from female patients with AN (n= 147) and female healthy control (HC) participants (n = 119), ages 12 to 40 years, were combined across 5 studies. Probabilistic tractography was completed, and full-cortex connectomes describing streamline counts between 84 brain regions were generated and harmonized. Graph theory methods were used to describe alterations in network organization in AN. The network-based statistic tested between-group differences in brain subnetwork connectivity. The metrics strength and efficiency indexed the connectivity of brain regions (network nodes) and were compared between groups using multiple linear regression. ResultsIndividuals with AN, relative to HC peers, had reduced connectivity in a network comprising subcortical regions and greater connectivity between frontal cortical regions (p < .05, familywise error corrected). Node-based analyses indicated reduced connectivity of the left hippocampus in patients relative to HC peers (p < .05, permutation corrected). Severity of illness, assessed by body mass index, was associated with subcortical connectivity (p < .05, uncorrected). ConclusionsAnalyses identified reduced structural connectivity of subcortical networks and regions, and stronger cortical network connectivity, among individuals with AN relative to HC peers. These findings are consistent with alterations in feeding, emotion, and executive control circuits in AN, and may direct hypothesis-driven research into mechanisms of persistent restrictive eating behavior.

Striatal Dopaminergic Depletion Pattern Reflects Pathological Brain Perfusion Changes in Lewy Body Diseases

PurposeIn Lewy body diseases (LBD), various symptoms occur depending on the distribution of Lewy body in the brain, and the findings of brain perfusion and dopamine transporter single-photon emission computed tomography (DAT-SPECT) also change accordingly. We aimed to evaluate the correlation between brain perfusion SPECT and quantitative indices calculated from DAT-SPECT in patients with LBD.ProceduresWe retrospectively enrolled 35 patients with LBD who underwent brain perfusion SPECT with N-isopropyl-p-[123I] iodoamphetamine and DAT-SPECT with 123I-ioflupane. Mini-mental state examination (MMSE) data were also collected from 19 patients. Quantitative indices (specific binding ratio [SBR], putamen-to-caudate ratio [PCR], and caudate-to-putamen ratio [CPR]) were calculated using DAT-SPECT. These data were analysed by the statistical parametric mapping procedure.ResultsIn patients with LBD, decreased PCR index correlated with hypoperfusion in the brainstem (medulla oblongata and midbrain) (uncorrected p < 0.001, k > 100), while decreased CPR index correlated with hypoperfusion in the right temporoparietal cortex (family-wise error corrected p < 0.05), right precuneus (uncorrected p < 0.001, k > 100), and bilateral temporal cortex (uncorrected p < 0.001, k > 100). However, there was no significant correlation between decreased SBR index and brain perfusion. Additionally, the MMSE score was correlated with hypoperfusion in the left temporoparietal cortex (uncorrected p < 0.001).ConclusionsThis study suggests that regional changes in striatal 123I-ioflupane accumulation on DAT-SPECT are related to brain perfusion changes in patients with LBD.

An Extended GFfit Statistic Defined on Orthogonal Components of Pearson's Chi-Square.

The Pearson and likelihood ratio statistics are commonly used to test goodness of fit for models applied to data from a multinomial distribution. The goodness-of-fit test based on Pearson's Chi-squared statistic is sometimes considered to be a global test that gives little guidance to the source of poor fit when the null hypothesis is rejected, and it has also been recognized that the global test can often be outperformed in terms of power by focused or directional tests. For the cross-classification of a large number of manifest variables, the GFfit statistic focused on second-order marginals for variable pairs i,j has been proposed as a diagnostic to aid in finding the source of lack of fit after the model has been rejected based on a more global test. When data are from a table formed by the cross-classification of a large number of variables, the common global statistics may also have low power and inaccurate Type I error level due to sparseness in the cells of the table. The sparseness problem is rarely encountered with the GFfit statistic because it is focused on the lower-order marginals. In this paper, a new and extended version of the GFfit statistic is proposed by decomposing the Pearson statistic from the full table into orthogonal components defined on marginal distributions and then defining the new version, [Formula: see text], as a partial sum of these orthogonal components. While the emphasis is on lower-order marginals, the new version of [Formula: see text] is also extended to higher-order tables so that the [Formula: see text] statistics sum to the Pearson statistic. As orthogonal components of the Pearson [Formula: see text] statistic, [Formula: see text] statistics have advantages over other lack-of-fit diagnostics that are currently available for cross-classified tables: the [Formula: see text] generally have higher power to detect lack of fit while maintaining good Type I error control even if the joint frequencies are very sparse, as will be shown in simulation results; theoretical results will establish that [Formula: see text] statistics have known degrees of freedom and are asymptotically independent with known joint distribution, a property which facilitates less conservative control of false discovery rate (FDR) or familywise error rate (FWER) in a high-dimensional table which would produce a large number of bivariate lack-of-fit diagnostics. Computation of [Formula: see text] statistics is also computationally stable. The extended [Formula: see text] statistic can be applied to a variety of models for cross-classified tables. An application of the new GFfit statistic as a diagnostic for a latent variable model is presented.

Robust Behrens–Fisher Statistic Based on Trimmed Means and Its Usefulness in Analyzing High-Throughput Data

In the context of high-throughput data, the differences in continuous markers between two groups are usually assessed by ordering the p-values obtained from the two-sample pooled t-test or Wilcoxon–Mann–Whitney test and choosing a stringent cutoff such as 10–8 to control the family-wise error rate (FWER) or false discovery rate (FDR). All markers with p-values below the cutoff are declared to be significantly associated with the phenotype. This inherently assumes that the test procedure provides valid type I error estimates in extreme tails of the null distribution. The aforementioned tests assume homoscedasticity in the two groups, and the t-test further assumes underlying distributions to be normally distributed. Cao et al. (Biometrika, 2013, 100, 495–502) have shown that in the context of multiple hypotheses testing the approach based on FDR may not be valid under non-normality and/or heteroscedasticity. Therefore, having a test statistic that is robust to these violations is needed. In this study, we propose a robust analog of Behrens–Fisher statistic based on trimmed means, conduct an extensive simulation study to compare its performance with other competing approaches, and demonstrate its usefulness by applying it to DNA methylation data used by Teschendorff et al. (Genome Res., 2010, 20, 440–446). An R program to implement the proposed method is provided in the Supplementary Material.

Concurrent brain structural and functional alterations in patients with chronic unilateral vestibulopathy.

Chronic unilateral vestibulopathy (CUVP) is a common chronic vestibular syndrome which may be caused by incomplete vestibular dynamic compensation. Neuroimaging technology provides important clues to explore the mechanism of complicated by vestibular dynamic compensation in patients with CUVP. However, previous studies mostly used positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) to investigate the changes of brain function in these patients during the task state, few studies have investigated the alterations during the resting state, Therefore, the study aimed to investigate the possible brain structural and functional alterations in patients with CUVP and explore the dynamic compensation state in patients with CUVP. We recruited 18 patients with right CUVP and 18 age-, gender-, and education level-matched healthy controls (HCs). Vestibular evaluations, such as videonystagmography and caloric tests, were performed. All participants underwent Dizziness Handicap Inventory (DHI) assessment. All participants underwent multimodal magnetic resonance imaging of the brain, including fMRI and three-dimensional T1-weighted MRI. We analyzed the amplitude of low frequency fluctuations (ALFF), regional homogeneity (ReHo), seed based functional connectivity, and voxel-based morphometry (VBM). Compared with HCs, CUVP patients showed significantly increased ALFF values in the right supplementary motor area, significantly decreased ALFF values in the right middle occipital gyrus, significantly decreased ReHo values in the bilateral superior parietal lobule, and significantly enhanced ReHo values in the bilateral cerebellar hemisphere [both P<0.05, family-wise error (FWE) corrected]. Compared with HCs, patients with CUVP showed increased gray matter volumes in the left medial superior frontal gyrus and left middle cingulate gyrus [P<0.001, false discovery rate (FDR) corrected]. Compared with HCs, in patients with CUVP, functional connectivity was enhanced between the left medial superior frontal gyrus and the left orbital inferior frontal gyrus and left angular gyrus and was significantly decreased between the left medial superior frontal gyrus and the right dorsolateral superior frontal gyrus (both P<0.01, FWE corrected). Pearson correlation analysis showed that there was a positive correlation between DHI score and VBM value of the left medial superior frontal gyrus in patients with CUVP (r=-0.430, P=0.003). This study identified abnormalities of neuronal activity intensity and overall activity synchronization in multiple brain regions in patients with CUVP, suggesting that patients with CUVP have extensive brain functional abnormalities, which in turn affects their spatial perception and motor perception. Increased gray matter volume and functional connectivity of the default mode network may be used as potential imaging biomarkers of chronic symptoms in patients with CUVP.

Impact of emotional intelligence on work performance: The mediating role of occupational stress among nurses.

An occupational stress was reported as an inhibitor of optimal performance among nurses. Emotional intelligence (EI) has emerged as a successful behavioral buffer against occupational stress and as a facilitator for better performance. This study aimed to investigate the potential relationship between nurses' EI and their work performance; and to examine the mediating role of occupational stress. A predictive correlational design was adopted. Self-reported questionnaires were administered to 391 full-time bedside nurses recruited from one of the big hospitals in Saudi Arabia, between April and June 2021. Data were coded and analyzed using IBM SPSS version 25.0. Simple and multiple linear regression analyses were used to test the hypotheses. The significance level for all tests was set at p≤ 0.05. Bonferroni correction method was used to control the family-wise error rate. The findings revealed an affirmative association between nurses' EI and work performance (β= 0.69, p< 0.001; r2 = 0.483). Additionally, an inverse association was established between nurses' EI and their perception of occupational stress (β= -0.54, p< 0.001; r2 = 0.286), and between nurses' perception of occupational stress and work performance (β= -0.52; p< 0.001; r2 = 0.226). Additionally, our results showed that occupational stress played a mediating role in the relationship between nurses' EI and work performance. This study presented a novel framework that includes two factors affecting work performance among nurses in Saudi Arabia. Our results suggest that EI is vital for effective work performance among nurses. Additionally, EI was found to be a useful coping strategy against occupational stress. EI has been described as a valuable asset for better performance and effective group cohesiveness among nurses. Optimal nurses᾽ performance leads to meeting patients᾽ needs and organizational goals.

Detecting heterogeneous treatment effects with instrumental variables and application to the Oregon health insurance experiment

There is an increasing interest in estimating heterogeneity in causal effects in randomized and observational studies. However, little research has been conducted to understand effect heterogeneity in an instrumental variables study. In this work we present a method to estimate heterogeneous causal effects using an instrumental variable with matching. The method has two parts. The first part uses subject-matter knowledge and interpretable machine-learning techniques, such as classification and regression trees, to discover potential effect modifiers. The second part uses closed testing to test for statistical significance of each effect modifier while strongly controlling the familywise error rate. We apply this method on the Oregon Health Insurance Experiment, estimating the effect of Medicaid on the number of days an individual’s health does not impede their usual activities by using a randomized lottery as an instrument. Our method revealed Medicaid’s effect was most impactful among older, English-speaking, non-Asian males and younger, English-speaking individuals with, at most, a high school diploma or General Educational Development.

Reward Processing in Alcohol-Dependent Patients and First-Degree Relatives: Functional Brain Activity During Anticipation of Monetary Gains and Losses

BackgroundAccording to the reward deficiency syndrome and allostatic hypotheses, hyposensitivity of mesocorticolimbic regions to non–alcohol-related stimuli predisposes to dependence or is long-lastingly enhanced by chronic substance use. To date, no study has directly compared mesocorticolimbic brain activity during non–drug reward anticipation between alcohol-dependent, at risk, and healthy subjects. MethodsSeventy-five abstinent alcohol-dependent human subjects (mean abstinence duration 957.66 days), 62 healthy first-degree relatives of alcohol-dependent individuals, and 76 healthy control subjects without family history of alcohol dependence performed a monetary incentive delay task. Functional magnetic resonance imaging data of the anticipation phase were analyzed, during which visual cues predicted that fast response to a target would result in monetary gain, avoidance of monetary loss, or a neutral outcome. ResultsDuring gain anticipation, there were no significant group differences. During loss anticipation, abstinent alcohol-dependent subjects showed lower activity in the left anterior insula compared with healthy control subjects without family history of alcohol dependence only (Montreal Neurological Institute [MNI] −25 19 –5; t206 = 4.17, familywise error corrected p = .009). However, this effect was no longer significant when age was included as a covariate. There were no group differences between abstinent alcohol-dependent subjects and healthy first-degree relatives or between healthy first-degree relatives and healthy control subjects during loss anticipation, respectively. ConclusionsNeither the neural reward deficiency syndrome nor the allostatic hypotheses are supported by the results. Future studies should investigate whether the incentive salience hypothesis allows for more accurate predictions regarding mesocorticolimbic brain activity of subjects with alcohol dependence and healthy individuals during reward and loss anticipation and further examine the neural substrates underlying a predisposition to dependence.

Brain Function and Upper Limb Deficit in Stroke With Motor Execution and Imagery: A Cross-Sectional Functional Magnetic Resonance Imaging Study

BackgroundMotor imagery training might be helpful in stroke rehabilitation. This study explored if a specific modulation of movement-related regions is related to motor imagery (MI) ability.MethodsTwenty-three patients with subcortical stroke and 21 age-matched controls were recruited. They were subjectively screened using the Kinesthetic and Visual Imagery Questionnaire (KVIQ). They then underwent functional magnetic resonance imaging (fMRI) while performing three repetitions of different motor tasks (motor execution and MI). Two separate runs were acquired [motor execution tasks (ME and rest) and motor imagery (MI and rest)] in a block design. For the different tasks, analyses of cerebral activation and the correlation of motor/imagery task-related activity and KVIQ scores were performed.ResultsDuring unaffected hand (UH) active grasp movement, we observed decreased activations in the contralateral precentral gyrus (PreCG), contralateral postcentral gyrus (PoCG) [p < 0.05, family wise error (FWE) corrected] and a positive correlation with the ability of FMA-UE (PreCG: r = 0.46, p = 0.028; PoCG: r = 0.44, p = 0.040). During active grasp of the affected hand (AH), decreased activation in the contralateral PoCG was observed (p < 0.05, FWE corrected). MI of the UH induced significant activations of the contralateral superior frontal gyrus, opercular region of the inferior frontal gyrus, and ipsilateral ACC and deactivation in the ipsilateral supplementary motor area (p < 0.05, AlphaSim correction). Ipsilateral anterior cingulate cortex (ACC) activity negatively correlated with MI ability (r = =–0.49, p = 0.022). Moreover, we found significant activation of the contralesional middle frontal gyrus (MFG) during MI of the AH.ConclusionOur results proved the dominant effects of MI dysfunction that exist in stroke during the processing of motor execution. In the motor execution task, the enhancement of the contralateral PreCG and PoCG contributed to reversing the motor dysfunction, while in the MI task, inhibition of the contralateral ACC can increase the impaired KVIQ ability. The bimodal balance recovery model can explain our results well. Recognizing neural mechanisms is critical to helping us formulate precise strategies when intervening with electrical or magnetic stimulation.

Neuroanatomical foundations of delayed reward discounting decision making II: Evaluation of sulcal morphology and fractal dimensionality

Delayed reward discounting (DRD) is a form of decision-making reflecting valuation of smaller immediate rewards versus larger delayed rewards, and high DRD has been linked to several health behaviors, including substance use disorders, attention-deficit/hyperactivity disorder, and obesity. Elucidating the underlying neuroanatomical factors may offer important insights into the etiology of these conditions. We used structural MRI scans of 1038 Human Connectome Project participants (Mage = 28.86, 54.7% female) to explore two novel measures of neuroanatomy related to DRD: 1) sulcal morphology (SM; depth and width) and 2) fractal dimensionality (FD), or cortical morphometric complexity, of parcellated cortical and subcortical regions. To ascertain unique contributions to DRD preferences, indicators that displayed significant partial correlations with DRD after family-wise error correction were entered into iterative mixed-effect models guided by the association magnitude. When considering only SM indicators, the depth of the right inferior and width of the left central sulci were uniquely associated with DRD preferences. When considering only FD indicators, the FD of the left middle temporal gyrus, right lateral orbitofrontal cortex, and left lateral occipital and entorhinal cortices uniquely contributed DRD. When considering SM and FD indicators simultaneously, the right inferior frontal sulcus depth and left central sulcus width; and the FD of the left middle temporal gyrus, lateral occipital cortex and entorhinal cortex were uniquely associated with DRD. These results implicate SM and FD as features of the brain that underlie variation in the DRD decision-making phenotype and as promising candidates for understanding DRD as a biobehavioral disease process.

Brain Structural Changes During Juvenile Fibromyalgia: Relationships With Pain, Fatigue, and Functional Disability.

ObjectiveJuvenile fibromyalgia (FM) is a prevalent chronic pain condition affecting children and adolescents worldwide during a critical period of brain development. To date, no published studies have addressed the pathophysiology of juvenile FM. This study was undertaken to characterize gray matter volume (GMV) alterations in juvenile FM patients for the first time, and to investigate their functional and clinical relevance.MethodsThirty‐four female adolescents with juvenile FM and 38 healthy adolescents underwent a structural magnetic resonance imaging examination and completed questionnaires assessing core juvenile FM symptoms. Using voxel‐based morphometry, we assessed between‐group GMV differences and associations between GMV and functional disability, fatigue, and pain interference in juvenile FM. We also studied whether validated brain patterns predicting pain, cognitive control, or negative emotion were amplified/attenuated in juvenile FM patients and whether structural alterations reported in adult FM were replicated in adolescents with juvenile FM.ResultsCompared to controls, juvenile FM patients showed GMV reductions in the anterior midcingulate cortex (aMCC) region (family‐wise error corrected P [P FWE‐corr] = 0.04; estimated with threshold‐free cluster enhancement [TFCE]; n = 72) associated with pain. Within the juvenile FM group, patients reporting higher functional disability had larger GMV in inferior frontal regions (P FWE‐corr = 0.006; TFCE estimated; n = 34) linked to affective, self‐referential, and language‐related processes. Last, GMV reductions in juvenile FM showed partial overlap with findings in adult FM, specifically for the anterior/posterior cingulate cortices (P = 0.02 and P = 0.03, respectively; n = 72).ConclusionPain‐related aMCC reductions may be a structural hallmark of juvenile FM, whereas alterations in regions involved in emotional, self‐referential, and language‐related processes may predict disease impact on patients’ well‐being. The partial overlap between juvenile and adult FM findings strengthens the importance of early symptom identification and intervention to prevent the transition to adult forms of the disease.

Closed testing with Globaltest, with application in metabolomics.

The Globaltest is a powerful test for the global null hypothesis that there is no association between a group of features and a response of interest, which is popular in pathway testing in metabolomics. Evaluating multiple feature sets, however, requires multiple testing correction. In this paper, we propose a multiple testing method, based on closed testing, specifically designed for the Globaltest. The proposed method controls the familywise error rate simultaneously over all possible feature sets, and therefore allows post hoc inference, that is, the researcher may choose feature sets of interest after seeing the data without jeopardizing error control. To circumvent the exponential computation time of closed testing, we derive a novel shortcut that allows exact closed testing to be performed on the scale of metabolomics data. An R package ctgt is available on comprehensive R archive network for the implementation of the shortcut procedure, with applications on several real metabolomics dataexamples.

Structural imaging studies of patients with chronic pain: an anatomical likelihood estimate meta-analysis.

Neuroimaging is a powerful tool to investigate potential associations between chronic pain and brain structure. However, the proliferation of studies across diverse chronic pain syndromes and heterogeneous results challenges data integration and interpretation. We conducted a preregistered anatomical likelihood estimate meta-analysis on structural magnetic imaging studies comparing patients with chronic pain and healthy controls. Specifically, we investigated a broad range of measures of brain structure as well as specific alterations in gray matter and cortical thickness. A total of 7849 abstracts of experiments published between January 1, 1990, and April 26, 2021, were identified from 8 databases and evaluated by 2 independent reviewers. Overall, 103 experiments with a total of 5075 participants met the preregistered inclusion criteria. After correction for multiple comparisons using the gold-standard family-wise error correction ( P < 0.05), no significant differences associated with chronic pain were found. However, exploratory analyses using threshold-free cluster enhancement revealed several spatially distributed clusters showing structural alterations in chronic pain. Most of the clusters coincided with regions implicated in nociceptive processing including the amygdala, thalamus, hippocampus, insula, anterior cingulate cortex, and inferior frontal gyrus. Taken together, these results suggest that chronic pain is associated with subtle, spatially distributed alterations of brain structure.

Evaluation of thresholding methods for activation likelihood estimation meta-analysis via large-scale simulations.

In recent neuroimaging studies, threshold‐free cluster enhancement (TFCE) gained popularity as a sophisticated thresholding method for statistical inference. It was shown to feature higher sensitivity than the frequently used approach of controlling the cluster‐level family‐wise error (cFWE) and it does not require setting a cluster‐forming threshold at voxel level. Here, we examined the applicability of TFCE to a widely used method for coordinate‐based neuroimaging meta‐analysis, Activation Likelihood Estimation (ALE), by means of large‐scale simulations. We created over 200,000 artificial meta‐analysis datasets by independently varying the total number of experiments included and the amount of spatial convergence across experiments. Next, we applied ALE to all datasets and compared the performance of TFCE to both voxel‐level and cluster‐level FWE correction approaches. All three multiple‐comparison correction methods yielded valid results, with only about 5% of the significant clusters being based on spurious convergence, which corresponds to the nominal level the methods were controlling for. On average, TFCE's sensitivity was comparable to that of cFWE correction, but it was slightly worse for a subset of parameter combinations, even after TFCE parameter optimization. cFWE yielded the largest significant clusters, closely followed by TFCE, while voxel‐level FWE correction yielded substantially smaller clusters, showcasing its high spatial specificity. Given that TFCE does not outperform the standard cFWE correction but is computationally much more expensive, we conclude that employing TFCE for ALE cannot be recommended to the general user.

Magnetization transfer imaging alterations and its diagnostic value in antipsychotic-naïve first-episode schizophrenia.

Magnetization transfer imaging (MTI) may provide more sensitivity and mechanistic understanding of neuropathological changes associated with schizophrenia than volumetric MRI. This study aims to identify brain magnetization transfer ratio (MTR) changes in antipsychotic-naïve first-episode schizophrenia (FES), and to correlate MTR findings with clinical symptom severity. A total of 143 individuals with antipsychotic-naïve FES and 147 healthy controls (HCs) were included and underwent 3.0 T brain MTI between August 2005 and July 2014. Voxelwise analysis was performed to test for MTR differences with family-wise error corrections. Relationships of these differences to symptom severity were assessed using partial correlations. Exploratory analyses using a support vector machine (SVM) classifier were conducted to discriminate FES from HCs using MTR maps. Model performance was examined using a 10-fold stratified cross-validation. Compared with HCs, individuals with FES exhibited higher MTR values in left thalamus, precuneus, cuneus, and paracentral lobule, that were positively correlated with schizophrenia symptom severity [precuneus (r = 0.34, P = 0.0004), cuneus (r = 0.33, P = 0.0006) and paracentral lobule (r = 0.37, P = 0.001)]. Whole-brain MTR maps identified individuals with FES with overall accuracy 75.5% (219 of 290 individuals) based on SVM approach. In antipsychotic-naïve FES, clinically relevant biophysical abnormalities detected by MTI mainly in the left parieto-occipital regions are informative about local brain pathology, and have potential as diagnostic markers.

A hierarchical testing procedure for three arm non-inferiority trials

Non-inferiority trials are becoming very popular for comparative effectiveness research. Non-inferiority trials establish that the effect of an experimental treatment is not worse than that of a reference treatment by more than a specified margin. A three-arm non-inferiority trial that includes the placebo, experimental treatment, and a reference treatment is considered. It has been criticized that the conventional approach for three-arm non-inferiority trials loses power for the non-inferiority hypothesis test unless the power of the assay sensitivity test is close to one. In order to overcome this situation, a novel hierarchical testing procedure with two stages for three-arm non-inferiority trials is developed. The family-wise error rate (FWER) is investigated analytically and numerically of the proposed test procedure. Numerical studies indicate that the suggested method controls FWER and has more power than the traditional approach particularly when the power of that assay sensitivity test is not close to one. Through these empirical studies, it is shown that the proposed method can be successfully applied in practice.

R‐(‐)2,5‐dimethoxy‐4‐iodoamphetamine (DOI) Blunts the Discriminative Stimulus Properties of Oxycodone

AimsA record ~100,000 fatalities due to drug overdoses was reported in the U.S. for the twelve months preceding April 2021. Opioids account for most deaths, and recurrent opioid use may lead to the development of opioid use disorder (OUD), a debilitating chronic disorder. Current medication‐assisted OUD treatment (e.g., buprenorphine) mitigates withdrawal, reduces mortality, and reduces intake of abused opioids. Still, the opioid epidemic crystalized the need to identify novel non‐opioid therapeutics to improve the odds of successful OUD recovery. In the last decade, there has been a resurgence of interest in serotonergic psychedelics for the treatment of psychiatric disorders, including substance use disorders. Psychedelic compounds act through agonist actions at the serotonin (5‐HT) 5‐HT2A receptor (5‐HT2AR) and there is some literature to suggest functional interactions between 5‐HT2AR and opioids. We tested the hypothesis that the psychedelic 5‐HT2AR agonist R‐(‐)2,5‐dimethoxy‐4‐iodoamphetamine (DOI) will disrupt the discriminative stimulus properties of the commonly misused prescription opioid oxycodone. The drug discrimination paradigm is a rigorous laboratory procedure for modeling the interoceptive effects of drugs and is widely recognized as useful in establishing ligand potency and effectiveness in vivo, as well as interrogating abuse liability.MethodsMale, Sprague‐Dawley rats (n = 13) were trained to discriminate an injection (s.c.) of oxycodone (1 mg/kg) from saline (1 ml/kg) in a two‐lever, water‐reinforced paradigm. Pharmacological testing began upon establishment of the stable oxycodone vs. saline discrimination. Substitution tests with DOI (0‐0.2 mg/kg; s.c.) and combination tests with DOI plus oxycodone were conducted interspersed with maintenance sessions. Percent oxycodone‐lever responding, response rates and latency to the first response were analyzed with an experimentwise error rate of α=0.05.ResultsAll rats acquired the oxycodone vs. saline discrimination to stability. Substitution tests indicated that all DOI doses resulted in percent oxycodone‐lever responding significantly different from the training dose of oxycodone (p&lt; 0.05). Pretreatment with DOI (0.1, 0.2 mg/kg) significantly reduced the percent oxycodone‐lever responding (0.5 mg/kg), relative to pretreatment with vehicle (p &lt; 0.05). The selective 5‐HT2AR antagonist M100907 prevented DOI‐induced suppression of oxycodone‐lever responding (p &lt; 0.05).ConclusionsThe current studies reveal that the psychedelic DOI does not substitute for oxycodone, but does suppress the stimulus effects of oxycodone, an effect which is reversed by the 5‐HT2AR antagonist M100907. Taken together, these studies provide support for expanded interrogation of the efficacy of 5‐HT2AR agonists in counteracting the behavioral effects of opioids.

Unbalanced fronto-pallidal neurocircuit underlying set shifting in obsessive-compulsive disorder.

Maladaptive habitual behaviours of obsessive-compulsive disorder are characterized by cognitive inflexibility, which hypothetically arises from dysfunctions of a certain cortico-basal ganglia-thalamo-cortical circuit including the ventrolateral prefrontal region. Inside this neurocircuit, an imbalance between distinct striatal projections to basal ganglia output nuclei, either directly or indirectly via the external globus pallidus, is suggested to be relevant for impaired arbitration between facilitation and inhibition of cortically initiated activity. However, current evidence of individually altered cortico-striatal or thalamo-cortical connectivities is insufficient to understand how cortical dysconnections are linked to the imbalanced basal ganglia system in patients. In this study, we aimed to identify aberrant ventrolateral prefronto-basal ganglia-thalamic subnetworks representing direct-indirect imbalance and its association with cognitive inflexibility in patients. To increase network detection sensitivity, we constructed a cortico-basal ganglia-thalamo-cortical network model incorporating striatal, pallidal and thalamic subregions defined by unsupervised clustering in 105 medication-free patients with obsessive-compulsive disorder (age = 25.05 ± 6.55 years, male/female = 70/35) and 99 healthy controls (age = 23.93 ± 5.80 years, male/female = 64/35). By using the network-based statistic method, we analysed group differences in subnetworks formed by suprathreshold dysconnectivities. Using linear regression models, we tested subnetwork dysconnectivity effects on symptom severity and set-shifting performance assessed by well-validated clinical and cognitive tests. Compared with the healthy controls, patients were slower to track the Part B sequence of the Trail Making Test when the effects of psychomotor and visuospatial functions were adjusted (t = 3.89, P < 0.001) and made more extradimensional shift errors (t = 4.09, P < 0.001). In addition to reduced fronto-striatal and striato-external pallidal connectivities and hypoconnected striato-thalamic subnetwork [P = 0.001, family-wise error rate (FWER) corrected], patients had hyperconnected fronto-external pallidal (P = 0.012, FWER corrected) and intra-thalamic (P = 0.015, FWER corrected) subnetworks compared with the healthy controls. Among the patients, the fronto-pallidal subnetwork alteration, especially ventrolateral prefronto-external globus pallidal hyperconnectivity, was associated with relatively fewer extradimensional shifting errors (β = -0.30, P = 0.001). Our findings suggest that the hyperconnected fronto-external pallidal subnetwork may have an opposite effect to the imbalance caused by the reduced indirect pathway (fronto-striato-external pallidal) connectivities in patients. This ventrolateral prefrontal hyperconnectivity may help the external globus pallidus disinhibit basal ganglia output nuclei, which results in behavioural inhibition, so as to compensate for the impaired set shifting. We suggest the ventrolateral prefrontal and external globus pallidus as neuromodulatory targets for inflexible habitual behaviours in obsessive-compulsive disorder.

Opening the Black Box: Bootstrapping Sensitivity Measures in Neural Networks for Interpretable Machine Learning

Artificial neural networks are powerful tools for data analysis, particularly in the context of highly nonlinear regression models. However, their utility is critically limited due to the lack of interpretation of the model given its black-box nature. To partially address the problem, the paper focuses on the important problem of feature selection. It proposes and discusses a statistical test procedure for selecting a set of input variables that are relevant to the model while taking into account the multiple testing nature of the problem. The approach is within the general framework of sensitivity analysis and uses the conditional expectation of functions of the partial derivatives of the output with respect to the inputs as a sensitivity measure. The proposed procedure extensively uses the bootstrap to approximate the test statistic distribution under the null while controlling the familywise error rate to correct for data snooping arising from multiple testing. In particular, a pair bootstrap scheme was implemented in order to obtain consistent results when using misspecified statistical models, a typical characteristic of neural networks. Numerical examples and a Monte Carlo simulation were carried out to verify the ability of the proposed test procedure to correctly identify the set of relevant features.

Identification of Maximum Safe Dose Based on Ratio of Normally Distributed Data under Heteroscedasticity

In most of the various stepwise confidence interval procedures formulated for identifying maximum safe dose (MSD), homogeneity of variances among different dose levels were required. But in practice, homogeneity of variance is often in doubt. This paper proposes a stepwise confidence set procedure for identifying MSD of drugs based on ratio of population means for normally distributed data under heteroscedasticity without the need for multiplicity adjustment. The procedure employed Fieller&amp;#39;s method and obtained individual (1-&amp;alpha;)100% confidence intervals for identification of the MSD. We illustrate the procedure with a real life example. In addition, we show that power of the procedure increases with increasing ratio of means, and sample size. Power however decreases with increase in clinical relevance margins. We also illustrate that the new procedure can properly control familywise error rate (FWER).