Group-level Differences Research Articles

Thalamic Volumes and Functional Networks Linked With Self-Regulation Dysfunction in Major Depressive Disorder.

Self-regulation (SR) dysfunction is a crucial risk factor for major depressive disorder (MDD). However, neural substrates of SR linking MDD remain unclear. Sixty-eight healthy controls and 75 MDD patients were recruited to complete regulatory orientation assessments with the Regulatory Focus Questionnaire (RFQ) and Regulatory Mode Questionnaire (RMQ). Nodal intra and inter-network functional connectivity (FC) was defined as FC sum within networks of 46 thalamic subnuclei (TS) or 88 AAL brain regions, and between the two networks separately. Group-level volumetric and functional difference were compared by two sample t-tests. Pearson's correlation analysis and mediation analysis were utilized to investigate the relationship among imaging parameters and the two behaviors. Canonical correlation analysis (CCA) was conducted to explore the inter-network FC mode of TS related to behavioral subscales. Network-based Statistics with machine learning combining powerful brain imaging features was applied to predict individual behavioral subscales. MDD patients showed no group-level volumetric difference in 46 TS but represented significant correlation of TS volume and nodal FC with behavioral subscales. Specially, inter-network FC of the orbital part of the right superior frontal gyrus and the left supplementary motor area mediated the correlation between RFQ/RMQ subscales and depressive severity. Furthermore, CCA identified how the two behaviors are linked via the inter-network FC mode of TS. More crucially, thalamic functional subnetworks could predict RFQ/RMQ subscales and psychomotor retardation for MDD individuals. These findings provided neurological evidence for SR affecting depressive severity in the MDD patients and proposed potential biomarkers to identify the SR-based risk phenotype of MDD individuals.

Conceptualizing meaningful between-group difference in change over time: a demonstration of possible viewpoints.

Determining if group-level differences in health outcomes are meaningful has recently been neglected in favour of determining if individuals have experienced a meaningful change. We explore interpretation of a meaningful between-group difference (MBGD) in clinical outcome assessment scores, primarily in the context of randomized clinical trials. We constructed a series of possible 'viewpoints' on how to conceptualize MBGD thresholds. Each viewpoint is discussed critically in terms of potential advantages and disadvantages, with simulated data to facilitate their consideration. Five viewpoints are presented and discussed. The first considers whether thresholds for meaningful within-individual change over time can be equally applied at the group-level, which is shown to be untenable. Viewpoints 2-4 consider what would have to be observed in treatment groups to conclude a meaningful between-group difference has occurred, framed in terms of the proportion of patients perceiving that they had meaningfully improved. The final viewpoint considers an alternative framework where stakeholders are directly questioned on the meaningfulness of varying magnitudes of between-group differences. The choice of a single threshold versus general interpretative guidelines is discussed. There does not appear to be a single method with clear face validity for determining MBGD thresholds. Additionally, the notion that such thresholds can be purely data-driven is challenged, where a degree of subjective stakeholder judgement is likely required. Areas for future research are proposed, to move towards robust method development.

Neural correlates of systemic lidocaine administration in healthy adults measured by functional MRI: a single arm open label study.

Intravenous lidocaine is increasingly used as a nonopioid analgesic, but how it acts in the brain is incompletely understood. We conducted a functional MRI study of pain response, resting connectivity, and cognitive task performance in volunteers to elucidate the effects of lidocaine at the brain-systems level. We enrolled 27 adults (age 22-55 yr) in this single-arm, open-label study. Pain response task and resting-state functional MRI scans at 3 T were obtained at baseline and then with a constant effect-site concentration of lidocaine. Electric nerve stimulation, titrated in advance to 7/10 intensity, was used for the pain task (five times every 10 s). Group-level differences in pain task-evoked responses (primary outcome, focused on the insula) and in resting connectivity were compared between baseline and lidocaine conditions, using adjusted P<0.05 to account for multiple comparisons. Pain ratings and performance on a brief battery of computer-based tasks were also recorded. Lidocaine infusion was associated with decreased pain-evoked responses in the insula (left: Z=3.6, P<0.001, right: Z=3.6, P=0.004) and other brain areas including the cingulate gyrus, thalamus, and primary sensory cortex. Resting-state connectivity showed significant diffuse reductions in both region-to-region and global connectivity measures with lidocaine. Small decreases in pain intensity and unpleasantness and worse memory performance were also seen with lidocaine. Lidocaine was associated with broad reductions in functional MRI response to acute pain and modulated whole-brain functional connectivity, predominantly decreasing long-range connectivity. This was accompanied by small but significant decreases in pain perception and memory performance. NCT05501600.

Individual-specific metabolic network based on 18F-FDG PET revealing multi-level aberrant metabolisms in Parkinson's disease.

Metabolic network analysis in Parkinson's disease (PD) based on 18F-FDG PET has revealed PD-related metabolic patterns. However, alterations at the systemic metabolic network level and at the connection level between different brain regions still remain unknown. This study aimed to explore metabolic network alterations at multiple network levels among PD patients using an individual-specific metabolic network (ISMN) approach. 18F-FDG-PET images of patients with PD (n = 34) and healthy subjects (n = 47) were collected. Healthy subjects were further separated into reference group (n = 28) and control group (n = 19) randomly. Standardized uptake value normalized by lean body mass ratio (SULr) maps was calculated from the PET images. ISMNs were constructed based on SULr maps for PD patients and controls with reference to the reference group. Comparisons of nodal and edge features were performed between PD and control groups. Correlation analysis was conducted between multilevel network properties and clinical scales in PD group. A linear classifier was trained based on nodal or edge features to distinguish PD from controls. The distance from each patient's ISMN to the group-level difference network showed a negative correlation with Hoehn and Yahr stage (r = -0.390, p = .023). Eight nodes from ISMN were identified which exhibited significantly increased nodal degree in PD patients compared to controls (p < .05). Eleven edges were observed which demonstrated significant distinctions in Z-score values in comparisons to the control group (p < .05). Furthermore, the nodal and edge features showed comparable performances in PD diagnosis compared to the traditional SULr values, with area under the receiver operating characteristic curve larger than 0.91. The proposed ISMN approach revealed systemic metabolic deviations, as well as nodal and edge distinctions in PD, which might be supplementary to the existing findings on PD-related metabolic patterns.

Characterization of Patient Activation among Childhood Cancer Survivors in the St. Jude Lifetime Cohort Study (SJLIFE).

Patient activation describes a willingness to take action to manage health and is associated with health outcomes. The purpose of this study was to characterize patient activation and its association with psychological outcomes and health behaviors in childhood cancer survivors. Participants were from the St. Jude Lifetime Cohort Study (SJLIFE). Activation levels (1-4, 4 = highest activation) were measured with the Patient Activation Measure (PAM). Psychological outcomes and health behaviors were obtained via self-report. Cognitive function was assessed by trained examiners. ANOVA or chi-squared tests were utilized to assess group-level differences in activation. Multivariable regression models were used to assess associations between PAM scores and outcomes of interest. Among 2708 survivors and 303 controls, more survivors endorsed lower activation levels than the controls (11.3 vs. 4.7% in level 1) and fewer survivors endorsed the highest level of activation than the controls (45.3 vs. 61.5% in level 4). Not endorsing depression (OR: 2.37, 95% CI 1.87-2.99), anxiety (OR: 2.21, 95% CI 1.73-2.83), and somatization symptoms (OR: 1.99, 95% CI 1.59-2.50), general fear (OR: 1.45, 95% CI 1.23-1.71) and body-focused (OR: 2.21, 95% CI 1.83-2.66), cancer-related worry, and physical (OR: 2.57, 95% CI 2.06-3.20) and mental (OR: 2.08, 95% CI 1.72-2.52) HRQOL was associated with higher levels of activation. Lower activation was associated with not meeting physical activity guidelines (OR: 2.07, 95% CI 1.53-2.80). Survivors endorsed lower activation levels than peers. Interventions to improve physical and psychological health outcomes could leverage these results to identify survivors who benefit from support in patient activation.

A spectrum of altered non-rapid eye movement sleep in schizophrenia.

Multiple facets of sleep neurophysiology, including electroencephalography (EEG) metrics such as non-rapid eye movement (NREM) spindles and slow oscillations, are altered in individuals with schizophrenia (SCZ). However, beyond group-level analyses, the extent to which NREM deficits vary among patients is unclear, as are their relationships to other sources of heterogeneity including clinical factors, ageing, cognitive profiles and medication regimens. Using newly collected high-density sleep EEG data on 103 individuals with SCZ and 68 controls, we first sought to replicate our previously reported group-level differences between patients and controls (original N=130) during N2 stage. Then in the combined sample (N=301 including 175 patients), we characterized patient-to-patient variability. We replicated all group-level mean differences and confirmed the high accuracy of our predictive model (AUC=0.93 for diagnosis). Compared to controls, patients showed significantly increased between-individual variability across many (26%) sleep metrics. Although multiple clinical and cognitive factors were associated with NREM metrics, collectively they did not account for much of the general increase in patient-to-patient variability. Medication regimen was a greater contributor to variability. Some sleep metrics including fast spindle density showed exaggerated age-related effects in SCZ, and patients exhibited older predicted biological ages based on the sleep EEG; further, among patients, certain medications exacerbated these effects, in particular olanzapine. Collectively, our results point to a spectrum of N2 sleep deficits among SCZ patients that can be measured objectively and at scale, with relevance to both the etiological heterogeneity of SCZ as well as potential iatrogenic effects of antipsychotic medication.

Role of pause duration in primary progressive aphasia

ABSTRACT Aims To detect differences in speech fluency in separate primary progressive aphasia syndromes (PPA) using automated analysis techniques. The resulting linguistic features are evaluated for their use in a predictive model to identify common patterns in speakers with PPA. As fluency is observable in audio recordings, its quantification may provide a low-cost instrument that augments spontaneous speech analyses in clinical practice. Methods and Procedures Speech was recorded in 14 controls, 7 nonfluent variant (nfvPPA) and 8 semantic variant (svPPA) speakers. The recordings were annotated for speech and non-speech with Kaldi, a common toolkit for speech processing software. Variables relating to fluency (pause rate, number of pauses, length of pauses) were analyzed. Outcomes and Results The best fitting distribution of pause duration was a combination of two Gaussian distributions, corresponding with pause categories short vs. long. Group level differences were found in the rate of pauses and proportion of silence: nfvPPA speakers use more short pauses relative to long pauses than control speakers, and the duration of short and long pauses is longer; svPPA speakers use more longer pauses relative to short pauses. Their short pauses are significantly shorter than those from control speakers. Participants in both PPA groups pause more frequently. SvPPA speakers are typically perceived as fluent. However, our analysis shows their fluency patterns to be distinct from control speakers, if the long-short distinction is observed. Conclusions Automatic measurements of pause duration show meaningful distinctions across the groups and might provide future aid in clinical assessment.

Task-based functional neural correlates of social cognition across autism and schizophrenia spectrum disorders

BackgroundAutism and schizophrenia spectrum disorders (SSDs) both feature atypical social cognition. Despite evidence for comparable group-level performance in lower-level emotion processing and higher-level mentalizing, limited research has examined the neural basis of social cognition across these conditions. Our goal was to compare the neural correlates of social cognition in autism, SSDs, and typically developing controls (TDCs).MethodsData came from two harmonized studies in individuals diagnosed with autism or SSDs and TDCs (aged 16–35 years), including behavioral social cognitive metrics and two functional magnetic resonance imaging (fMRI) tasks: a social mirroring Imitate/Observe (ImObs) task and the Empathic Accuracy (EA) task. Group-level comparisons, and transdiagnostic analyses incorporating social cognitive performance, were run using FSL’s PALM for each task, covarying for age and sex (1000 permutations, thresholded at p < 0.05 FWE-corrected). Exploratory region of interest (ROI)-based analyses were also conducted.ResultsImObs and EA analyses included 164 and 174 participants, respectively (autism N = 56/59, SSD N = 50/56, TDC N = 58/59). EA and both lower- and higher-level social cognition scores differed across groups. While canonical social cognitive networks were activated, no significant whole-brain or ROI-based group-level differences in neural correlates for either task were detected. Transdiagnostically, neural activity during the EA task, but not the ImObs task, was associated with lower- and higher-level social cognitive performance.LimitationsDespite attempting to match our groups on age, sex, and race, significant group differences remained. Power to detect regional brain differences is also influenced by sample size and multiple comparisons in whole-brain analyses. Our findings may not generalize to autism and SSD individuals with co-occurring intellectual disabilities.ConclusionsThe lack of whole-brain and ROI-based group-level differences identified and the dimensional EA brain-behavior relationship observed across our sample suggest that the EA task may be well-suited to target engagement in novel intervention testing. Our results also emphasize the potential utility of cross-condition approaches to better understand social cognition across autism and SSDs.

Kappa opioid receptor availability predicts severity of anhedonia in schizophrenia.

The kappa opioid receptor (KOR) and its endogenous agonist dynorphin have been implicated in multiple psychiatric conditions including psychotic disorders. We tested the hypotheses that kappa expression is elevated and associated with psychotic symptoms in schizophrenia. We measured kappa expression in unmedicated patients with schizophrenia (7 female, 6 male) and matched controls (7 female, 6 male) with positron emission tomography (PET). We also acquired a measurement of cumulative dopamine activity over the life span in the same subjects using neuromelanin sensitive MRI. We hypothesized that neuromelanin accumulation would be higher in patients than controls and that in patients there would be a positive association between KOR availability and neuromelanin accumulation. Fourteen patients and thirteen controls were enrolled. Whole brain dynamic PET imaging data using the KOR selective tracer [18F]LY245998 were acquired. Distribution volume (VT) was measured with region of interest analysis in 14 brain regions. Neuromelanin accumulation in midbrain dopaminergic nuclei was assessed in the same subjects. Positive and negative symptoms were measured by a clinical psychologist. We did not observe group level differences in KOR expression, neuromelanin accumulation or relationships of these to positive symptoms. Unexpectedly, we did observe strong positive associations between KOR expression and symptoms of anhedonia in the patients (Pearson r > 0.7, uncorrected p < 0.01 in 8 cortical brain regions). We also observed moderate associations between KOR expression and neuromelanin levels in patients. In conclusion, we did not observe a relationship between kappa and symptoms of psychosis but the observed relationship to the negative symptom of anhedonia is in line with recent work testing kappa antagonism as a therapy for anhedonia in depression.

Natural Language Processing Applied to Spontaneous Recall of Famous Faces Reveals Memory Dysfunction in Temporal Lobe Epilepsy Patients.

Epilepsy patients rank memory problems as their most significant cognitive comorbidity. Current clinical assessments are laborious to administer and score and may not always detect subtle memory decline. The Famous Faces Task (FF) has robustly demonstrated that left temporal lobe epilepsy (LTLE) patients remember fewer names and biographical details compared to right TLE (RTLE) patients and healthy controls (HCs). We adapted the FF task to capture subjects' entire spontaneous spoken recall, then scored responses using manual and natural language processing (NLP) methods. We expected to replicate previous group level differences using spontaneous speech and semi-automated analysis. Seventy-three (N=73) adults (28 LTLE, 18 RTLE, and 27 HCs) were included in a case-control prospective study design. Twenty FF in politics, sports, and entertainment (active 2008-2017) were shown to subjects, who were asked if they could recognize and spontaneously recall as much biographical detail as possible. We created human-generated and automatically-generated keyword dictionaries for each celebrity, based on a randomly selected training set of half of the HC transcripts. To control for speech output, we measured the speech duration, total word count and content word count for the FF task and a Cookie Theft Control Task (CTT), in which subjects were merely asked to describe a visual scene. Subjects' responses to FF and CTT tasks were recorded, transcribed, and analyzed in a blinded manner with a combination of manual and automated NLP approaches. Famous face recognition accuracy was similar between groups. LTLE patients recalled fewer biographical details compared to HCs and RTLEs using both the gold-standard human-generated dictionary (24%±12% vs. 31%±12% and 30%±12%, p=0.007) and the automated dictionary (24%±12% vs. 31%±12% and 32%±13%, p=0.007). There were no group level differences in speech duration, total word count, or content word count for either the FF and CTT to explain difference in recall performance. There was a positive, statistically significant relationship between MOCA score and FF recall performance as scored by the human-generated (ρ= .327, p= .029) and automatically-generated dictionaries (ρ= .422, p= .004) for TLE subjects, but not HCs, an effect that was driven by LTLE subjects. LTLE patients remember fewer details of famous people than HCs or RTLE patients, as discovered by NLP analysis of spontaneous recall. Decreased biographical memory was not due to decreased speech output and correlated with lower MOCA scores. NLP analysis of spontaneous recall can detect memory dysfunction in clinical populations in a semi-automated, objective, and sensitive manner.

Chronic cannabis use alters the spontaneous and oscillatory gamma dynamics serving cognitive control.

Regular cannabis use is associated with cortex-wide changes in spontaneous and oscillatory activity, although the functional significance of such changes remains unclear. We hypothesized that regular cannabis use would suppress spontaneous gamma activity in regions serving cognitive control and scale with task performance. Participants (34 cannabis users, 33 nonusers) underwent an interview regarding their substance use history and completed the Eriksen flanker task during magnetoencephalography (MEG). MEG data were imaged in the time-frequency domain and virtual sensors were extracted from the peak voxels of the grand-averaged oscillatory interference maps to quantify spontaneous gamma activity during the pre-stimulus baseline period. We then assessed group-level differences in spontaneous and oscillatory gamma activity, and their relationship with task performance and cannabis use metrics. Both groups exhibited a significant behavioral flanker interference effect, with slower responses during incongruent relative to congruent trials. Mixed-model ANOVAs indicated significant gamma-frequency neural interference effects in the left frontal eye fields (FEF) and left temporoparietal junction (TPJ). Further, a group-by-condition interaction was detected in the left FEF, with nonusers exhibiting stronger gamma oscillations during incongruent relative to congruent trials and cannabis users showing no difference. In addition, spontaneous gamma activity was sharply suppressed in cannabis users relative to nonusers in the left FEF and TPJ. Finally, spontaneous gamma activity in the left FEF and TPJ was associated with task performance across all participants, and greater cannabis use was associated with weaker spontaneous gamma activity in the left TPJ of the cannabis users. Regular cannabis use was associated with weaker spontaneous gamma in the TPJ and FEF. Further, the degree of use may be proportionally related to the degree of suppression in spontaneous activity in the left TPJ.

Machine learning classification of functional neurological disorder using structural brain MRI features

BackgroundBrain imaging studies investigating grey matter in functional neurological disorder (FND) have used univariate approaches to report group-level differences compared with healthy controls (HCs). However, these findings have limited translatability...

Classifying Inflammation on Intestinal Ultrasound Images and Cineloops - A Learning Curve Study.

Intestinal ultrasound has become a crucial tool for assessing inflammation in patients with inflammatory bowel disease, prompting a surge in demand for trained sonographers. While educational programs exist, the length of training needed to reach proficiency in correctly classifying inflammation remains unclear. Our study addresses this gap partly by exploring the learning curves associated with the deliberate practice of sonographic disease assessment, focusing on the key disease activity parameters of bowel wall thickness, bowel wall stratification, color Doppler signal, and inflammatory fat. Twenty-one novices and six certified intestinal ultrasound practitioners engaged in an 80-case deliberate practice online training program. A panel of three experts independently graded ultrasound images representing various degrees of disease activity and agreed upon a consensus score. We used statistical analyses, including mixed-effects regression models, to evaluate learning trajectories. Pass/fail thresholds distinguishing novices from certified practitioners were determined through contrasting-groups analyses. Novices showed significant improvement in interpreting bowel wall thickness, surpassing the pass/fail threshold, and reached mastery level by case 80. For color Doppler signal and inflammatory fat, novices surpassed the pass/fail threshold but did not achieve mastery. Novices did not improve in assessing bowel wall stratification. We found considerable individual and group-level differences in learning curves supporting the concept of competency-based training for assessing bowel wall thickness, color Doppler signal and inflammatory fat. However, despite practice over 80 cases, novices did not improve in their interpretation of bowel wall stratification, suggesting that a different approach is needed for this parameter.

The ‘Carrot Test’: An approach to characterize individual differences in oral processing behaviour and eating rate

BackgroundEating rate is a modifiable risk factor for obesity and efficient methods to objectively characterise an individual’s oral processing behaviours could help better identify people at risk of increased energy consumption. Many previous approaches to characterise oral processing and eating rate have relied on specialised equipment or wearable devices that are time consuming, expensive or require expertise to administer. The current trial used video-coding of the consumption of a standardised test food (the ‘carrot test’) to measure oral processing. ObjectiveWe sought (i) to test whether self-reported eating rate (SRER) is predictive of food oral processing derived from coded eating behaviours captured in the laboratory with a standardised test food, and (ii) to test whether differences in SRER are predictive of oral processing behaviours, eating rate and intake of a test meal. MethodsTwo hundred and fifty-three volunteers (86 male and 167 female, mean age 39.5 ± 13.6 years, mean BMI 22.2 ± 3.4 kg/m2) provided their SRER and anthropometric measurements of height, weight and dual-energy X-ray absorptiometry (DEXA) percentage fat mass. Participants were also video recorded eating a fixed 50 g portion of carrot and an ad libitum lunch meal of fried rice. Average eating rate (g/min), bite size (g) and number of chews per bite for the carrot and lunch were derived through behavioural coding of the videos. Energy intake (kcal) was recorded at lunch and a later afternoon snack. ResultsFaster SRER significantly predicted faster eating rate, larger bite size and more chews per bite observed during intake of the carrot (ß = −0.26–0.21, p ≤ 0.001) and the lunch (ß = −0.26–0.35, p ≤ 0.014). SRER did not significantly predict intake at lunch or during the afternoon snack (ß = 0.05–0.07, p ≥ 0.265). Participants’ oral processing of the carrot significantly predicted oral processing of the lunch (ß = −0.25–0.40, p ≤ 0.047) and faster eating rate of the carrot significantly predicted increased lunch intake (ß = 0.119, p = 0.045). None of the oral processing behaviours predicted afternoon snack intake (ß = −0.01–0.05, p ≥ 0.496). None of these associations were moderated by BMI or body composition. ConclusionWe confirm that SRER is a valid measure of group level differences in individual oral processing behaviours, but did not predict an individual’s energy intake at a lunch-time meal. With this approach, it is possible to characterise differences in eating rate by coding eating behaviours for a standardized test food (in this case, a fixed portion of raw carrot). This approach could be used to provide an objective measure of a person’s habitual oral processing behaviour, and was shown to be a significant predictor of eating rate and energy intake for a later test meal.

Assessment of resting cerebral perfusion between methamphetamine-associated psychosis and schizophrenia through arterial spin labeling MRI.

The clinical manifestations of methamphetamine (METH)-associated psychosis (MAP) and acute paranoid schizophrenia (SCZ) are similar. This study aims to assess regional cerebral blood flow (rCBF) in individuals who use METH and in those with SCZ using the MRI arterial spin labeling (ASL) technique. We prospectively recruited 68 participants and divided them into four groups: MAP (N = 15), SCZ (N = 13), METH users with no psychosis (MNP; N = 22), and normal healthy controls (CRL; N = 18). We measured rCBF using an MRI three-dimensional pseudo-continuous ASL sequence. Clinical variables were assessed using the Positive and Negative Syndrome Scale (PANSS) and Brief Assessment of Cognition in Schizophrenia (BACS). Group-level rCBF differences were analyzed using a two-sample t-test. Decreased rCBF was found in the precuneus, premotor cortex, caudate nucleus, dorsolateral prefrontal cortex, and thalamus in the MNP group compared with the CRL group. The MAP group had significantly decreased rCBF in the precuneus, hippocampus, anterior insula, inferior temporal gyrus, inferior orbitofrontal gyrus, and superior occipital gyrus compared with the MNP group. Increased rCBF in the precuneus and premotor cortex was seen in the MAP group compared with the SCZ group. rCBF in the precuneus and premotor cortex significantly correlated negatively with the PANSS but correlated positively with BACS scores in the MAP and SCZ groups. METH exposure was associated with decreased rCBF in the precuneus and premotor cortex. Patients with MAP exhibited higher rCBF than those with SCZ, implying preserved insight and favorable outcomes. rCBF can therefore potentially serve as a diagnostic approach to differentiate patients with MAP from those with SCZ.

Biomarker identification by interpretable maximum mean discrepancy.

In many biomedical applications, we are confronted with paired groups of samples, such as treated versus control. The aim is to detect discriminating features, i.e. biomarkers, based on high-dimensional (omics-) data. This problem can be phrased more generally as a two-sample problem requiring statistical significance testing to establish differences, and interpretations to identify distinguishing features. The multivariate maximum mean discrepancy (MMD) test quantifies group-level differences, whereas statistically significantly associated features are usually found by univariate feature selection. Currently, few general-purpose methods simultaneously perform multivariate feature selection and two-sample testing. We introduce a sparse, interpretable, and optimized MMD test (SpInOpt-MMD) that enables two-sample testing and feature selection in the same experiment. SpInOpt-MMD is a versatile method and we demonstrate its application to a variety of synthetic and real-world data types including images, gene expression measurements, and text data. SpInOpt-MMD is effective in identifying relevant features in small sample sizes and outperforms other feature selection methods such as SHapley Additive exPlanations and univariate association analysis in several experiments. The code and links to our public data are available at https://github.com/BorgwardtLab/spinoptmmd.

Cerebral glucose metabolic correlates of cognitive and behavioural impairments in amyotrophic lateral sclerosis

ObjectiveHalf of ALS patients are cognitively and/or behaviourally impaired. As cognition/behaviour and cerebral glucose metabolism can be correlated by means of 18F-Fluorodeoxyglucose positron emission tomography (FDG-PET), we aimed to utilise FDG-PET, first, to replicate group-level differences in glucose metabolism between non-demented ALS patients separated into non-impaired (ALSni), cognitively impaired (ALSci), behaviourally impaired (ALSbi), and cognitively and behaviourally impaired (ALScbi) groups; second, to investigate glucose metabolism and performance in various cognitive domains; and third, to examine the impact of partial volume effects correction (PVEC) of the FDG-PET data on the results.MethodsWe analysed neuropsychological, clinical, and imaging data from 67 ALS patients (30 ALSni, 21 ALSci, 5 ALSbi, and 11 ALScbi). Cognition was assessed with the Edinburgh Cognitive and Behavioural ALS Screen, and two social cognition tests. FDG-PET and structural MRI scans were acquired for each patient. Voxel-based statistical analyses were undertaken on grey matter volume (GMV) and non-corrected vs. PVE-corrected FDG-PET scans.ResultsALSci and ALScbi had lower cognitive scores than ALSni. In contrast to both ALSni and ALSci, ALScbi showed widespread hypometabolism in the superior- and middle-frontal gyri in addition to the right temporal pole. Correlations were observed between the GMV, the FDG-PET signal, and various cognitive scores. The FDG-PET results were largely unaffected by PVEC.InterpretationOur study identified widespread differences in hypometabolism in the ALScbi-ni but not in the ALSci-ni group comparison, raising the possibility that cerebral metabolism may be more closely related to the presence of behavioural changes than to mild cognitive deficits.

Neural correlates of response to joint attention in 2-to-5-year-olds in relation to ASD and social-communicative abilities: An fNIRS and behavioral study.

Autism spectrum disorder (ASD) is associated with life-long challenges with social cognition, and one of its earliest and most common manifestations is atypical joint attention, which is a pivotal skill in social-cognitive and linguistic development. Early interventions for ASD children often focus on training initiation of joint attention (IJA) and response to joint attention bids (RJA), which are important for social communication and cognition. Here, we used functional near-infrared spectroscopy and behavioral measures to test typically developing (TD, n = 17) and ASD children (n = 18), to address the relationship between the neural correlates of RJA and social-communicative behavior. Group-level differences were present for RJA-specific activation over right temporal sites, where TD children showed higher levels of activation during RJA than ASD children, whereas the two groups did not differ in the control condition. Correlations between neural activation and behavioral traits suggest that, in ASD children, neural activation during RJA is related to the frequency of RJA behavior when the former is measured over left temporal sites, and to social affect symptoms when considered for right temporal sites. Possible implications of the evidenced correlations are discussed.

Racial Appraisals by White, Black, Hispanic, and Multiracial Americans

Racial appraisals, defined as people’s judgments of other people’s race, influence racial inequality and discrimination, anti-discrimination efforts, and collective identity. I conduct a survey of 1,102 American adults of all races that builds on recent scholarship about how Americans assess others’ race, in two ways. First, I examine a wider range of cues for race than prior studies. I uncover novel evidence that self-identification and small group (family and intra-cultural) judgments shape appraisals, especially for Hispanic and Native American targets. I also find support for prior work showing that cues like appearance and ancestry are important signals. Second, I move beyond prior studies’ focus on White Americans’ appraisals; I examine how several different racial groups appraise race. I find some similarities but also striking differences, particularly in the wider range of experiential and small group cues that Black and Hispanic Americans use when assessing Whiteness, Blackness, and Latinidad, compared with Whites. I argue that four group-level differences in appraisal patterns uncovered here are rooted in specific aspects of America’s history of racial domination, and consider implications.

The effect of positive emotion on foreign language teacher engagement and well-being: A cross-cultural comparison

Foreign language teaching enjoyment (FLTE) has recently been introduced as a broad positive emotion experienced by foreign language (FL) teachers, despite obstacles embedded in FL teaching. However, identifying its psychological outcomes – and the cultural specificity of these outcomes – has received scant research attention across different contexts. The present cross-cultural study aims to investigate whether teachers’ FLTE can predict and influence engagement and well-being in the English as a foreign language (EFL) context of Iran and China. A series of structural equation models (SEMs) indicated that EFL teachers’ FLTE affected their work engagement and well-being in both Iranian and Chinese samples, with structural invariance tests confirming the group-level differences between Iranian and Chinese EFL teachers in the light of FLTE outcomes. The study provides insight into the positive outcomes of positive emotions in FL teaching as framed by the lens of positive psychology. In addition, a rare non-Western cross-cultural comparison contributes to the ongoing discussions in literature regarding the influence of cultural contexts on the experience and outcome manifestation of positive emotions.