Patients with posttraumatic stress disorder (PTSD) exhibit smaller regional brain volumes in commonly reported regions including the amygdala and hippocampus, regions associated with fear and memory processing. In the current study, we have conducted a voxel-based morphometry (VBM) meta-analysis using whole-brain statistical maps with neuroimaging data from the ENIGMA-PGC PTSD working group.

T1-weighted structural neuroimaging scans from 36 cohorts (PTSD n = 1309; controls n = 2198) were processed using a standardized VBM pipeline (ENIGMA-VBM tool). We meta-analyzed the resulting statistical maps for voxel-wise differences in gray matter (GM) and white matter (WM) volumes between PTSD patients and controls, performed subgroup analyses considering the trauma exposure of the controls, and examined associations between regional brain volumes and clinical variables including PTSD (CAPS-4/5, PCL-5) and depression severity (BDI-II, PHQ-9).

PTSD patients exhibited smaller GM volumes across the frontal and temporal lobes, and cerebellum, with the most significant effect in the left cerebellum (Hedges’ g = 0.22, pcorrected = .001), and smaller cerebellar WM volume (peak Hedges’ g = 0.14, pcorrected = .008). We observed similar regional differences when comparing patients to trauma-exposed controls, suggesting these structural abnormalities may be specific to PTSD. Regression analyses revealed PTSD severity was negatively associated with GM volumes within the cerebellum (pcorrected = .003), while depression severity was negatively associated with GM volumes within the cerebellum and superior frontal gyrus in patients (pcorrected = .001).

PTSD patients exhibited widespread, regional differences in brain volumes where greater regional deficits appeared to reflect more severe symptoms. Our findings add to the growing literature implicating the cerebellum in PTSD psychopathology.

Diagnostic criteria for major depressive disorder allow for heterogeneous symptom profiles but genetic analysis of major depressive symptoms has the potential to identify clinical and etiological subtypes. There are several challenges to integrating symptom data from genetically informative cohorts, such as sample size differences between clinical and community cohorts and various patterns of missing data.

We conducted genome-wide association studies of major depressive symptoms in three cohorts that were enriched for participants with a diagnosis of depression (Psychiatric Genomics Consortium, Australian Genetics of Depression Study, Generation Scotland) and three community cohorts who were not recruited on the basis of diagnosis (Avon Longitudinal Study of Parents and Children, Estonian Biobank, and UK Biobank). We fit a series of confirmatory factor models with factors that accounted for how symptom data was sampled and then compared alternative models with different symptom factors.

The best fitting model had a distinct factor for Appetite/Weight symptoms and an additional measurement factor that accounted for the skip-structure in community cohorts (use of Depression and Anhedonia as gating symptoms).

The results show the importance of assessing the directionality of symptoms (such as hypersomnia versus insomnia) and of accounting for study and measurement design when meta-analyzing genetic association data.

The COVID-19 pandemic significantly disrupted schools and learning formats. Children with epilepsy are at-risk for generalized academic difficulties. We investigated the potential impact of COVID-19 on learning in those with epilepsy by comparing achievement on well-established academic measures among school-age children with epilepsy referred prior to the COVID-19 pandemic and those referred during the COVID-19 pandemic.

This study included 466 children [52% male, predominately White (76%), MAge=10.75 years] enrolled in the Pediatric Epilepsy Research Consortium Epilepsy (PERC) Surgery database project who were referred for surgery and seen for neuropsychological testing. Patients were divided into two groups based on a proxy measure of pandemic timing completed by PERC research staff at each site (i.e., “were there any changes to typical in-person administration [of the evaluation] due to COVID?”). 31% of the sample (N = 144) were identified as having testing during the pandemic (i.e., “yes” response), while 69% were identified as having testing done pre-pandemic (i.e., “no” response). Of the 31% who answered yes, 99% of administration changes pertained to in-person testing or other changes, with 1% indicating remote testing. Academic achievement was assessed by performance measures (i.e., word reading, reading comprehension, spelling, math calculations, and math word problems) across several different tests. T-tests compared the two groups on each academic domain. Subsequent analyses examined potential differences in academic achievement among age cohorts that approximately matched grade level [i.e., grade school (ages 5-10), middle school (ages 11-14), and high school (ages 15-18)].

No significant differences were found between children who underwent an evaluation before the pandemic compared to those assessed during the pandemic based on age norms across academic achievement subtests (all p’s > .34). Similarly, there were no significant differences among age cohorts. The average performance for each age cohort generally fell in the low average range across academic skills. Performance inconsistently varied between age cohorts. The youngest cohort (ages 5-10) scored lower than the other cohorts for sight-word reading, whereas this cohort scored higher than the middle cohort (ages 11-14) for math word problems and reading comprehension. There were no significant differences between the two pandemic groups on demographic variables, intellectual functioning, or epilepsy variables (i.e., age of onset, number of seizure medications, seizure frequency).

Academic functioning was generally equivalent between children with epilepsy who underwent academic testing as part of a pre-surgical evaluation prior to the pandemic compared to those who received testing during the pandemic. Additionally, academic functioning did not significantly differ between age cohorts. Children with epilepsy may have entered the pandemic with effective academic supports and/or were accustomed to school disruptions given their seizure history. Replication is needed as findings are based on a proxy measure of pandemic timing and the extent to which children experienced in-person, remote, and hybrid learning is unknown. Children tested a year into the pandemic, after receiving instruction through varying educational methods, may score differently than those tested earlier. Future research can address these gaps. Although it is encouraging that academic functioning was not disproportionately impacted during the pandemic in this sample, children with epilepsy are at-risk for generalized academic difficulties and continued monitoring of academic functioning is necessary.

The Pediatric Epilepsy Research Consortium (PERC) Epilepsy Surgery Database Project is a multisite collaborative that includes neuropsychological evaluations of children presenting for epilepsy surgery. There is some evidence for specific neuropsychological phenotypes within epilepsy (Hermann et al, 2016); however, this is less clear in pediatric patients. As a first step, we applied an empirically-based subtyping approach to determine if there were specific profiles using indices from the Wechsler scales [Verbal IQ (VIQ), Nonverbal IQ (NVIQ), Processing Speed Index (PSI), Working Memory Index (WMI)]. We hypothesized that there would be at least four profiles that are distinguished by slow processing speed and poor working memory as well as profiles with significant differences between verbal and nonverbal reasoning abilities.

Our study included 372 children (M=12.1 years SD=4.1; 77.4% White; 48% male) who completed an age-appropriate Wechsler measure, enough to render at least two index scores. Epilepsy characteristics included 84.4% with focal epilepsy (evenly distributed between left and right focus) and 13.5% with generalized or mixed seizure types; mean age of onset = 6.7 years, SD = 4.5; seizure frequency ranged from daily to less than monthly; 53% had structural etiology; 71% had an abnormal MRI; and mean number of antiseizure medications was two. Latent profile analysis was used to identify discrete underlying cognitive profiles based on intellectual functioning. Demographic and epilepsy characteristics were compared among profiles.

Based on class enumeration procedures, a 3-cluster solution provided the best fit for the data, with profiles characterized by generally Average, Low Average, or Below Average functioning. 32.8% were in the Average profile with mean index scores ranging from 91.7-103.2; 47.6% were in the Low Average profile with mean index ranging from 80.7 to 84.5; and 19.6% were in the Below Average profile with mean index scores ranging from 55.0-63.1. Across all profiles, the lowest mean score was the PSI, followed by WMI. VIQ and NVIQ represented relatively higher scores for all three profiles. Mean discrepancy between indices within a profile was as large as 11.5 IQ points. No demographics or epilepsy characteristics were significantly different across cognitive phenotypes.

Latent cognitive phenotypes in a pediatric presurgical cohort were differentiated by general level of functioning; however, across profiles, processing speed was consistently the lowest index followed by working memory. These findings across phenotypes suggest a common relative weakness which may result from a global effect of antiseizure medications and/or the widespread impact of seizures on neural networks even in a largely focal epilepsy cohort; similar to adult studies with temporal lobe epilepsy (Hermann et al, 2007). Future work will use latent profile analysis to examine phenotypes across other domains relevant to pediatric epilepsy including attention, naming, motor, and memory functioning. These findings are in line with collaborative efforts towards cognitive phenotyping which is the aim of our PERC Epilepsy Surgery Database Project that has already established one of the largest pediatric epilepsy surgery cohorts.

Children with epilepsy are at greater risk of lower academic achievement than their typically developing peers (Reilly and Neville, 2015). Demographic, social, and neuropsychological factors, such as executive functioning (EF), mediate this relation. While research emphasizes the importance of EF skills for academic achievement among typically developing children (e.g., Best et al., 2011; Spiegel et al., 2021) less is known among children with epilepsy (Ng et al., 2020). The purpose of this study is to examine the influence of EF skills on academic achievement in a nationwide sample of children with epilepsy.

Participants included 427 children with epilepsy (52% male; MAge= 10.71), enrolled in the Pediatric Epilepsy Research Consortium (PERC) Epilepsy Surgery Database who had been referred for surgery and underwent neuropsychological testing. Academic achievement was assessed by performance measures (word reading, reading comprehension, spelling, and calculation and word-based mathematics) and parent-rating measures (Adaptive Behavior Assessment System (ABAS) Functional Academics and Child Behavior Checklist (CBCL) School Performance). EF was assessed by verbal fluency measures, sequencing, and planning measures from the Delis Kaplan Executive Function System (DKEFS), NEPSY, and Tower of London test. Rating-based measures of EF included the 'Attention Problems’ subscale from the CBCL and 'Cognitive Regulation’ index from the Behavior Rating Inventory of Executive Function (BRIEF-2). Partial correlations assessed associations between EF predictors and academic achievement, controlling for fullscale IQ (FSIQ; A composite across intelligence tests). Significant predictors of each academic skill or rating were entered into a two-step regression that included FSIQ, demographics, and seizure variables (age of onset, current medications) in the first step with EF predictors in the second step.

Although zero-order correlations were significant between EF predictors and academic achievement (.29 < r’s < .63 for performance; -.63 < r’s < -.50 for rating measures), partial correlations controlling for FSIQ showed fewer significant relations. For performance-based EF, only letter fluency (DKEFS Letter Fluency) and cognitive flexibility (DKEFS Trails Condition 4) demonstrated significant associations with performance-based academic achievement (r’s > .29). Regression models for performance-based academic achievement indicated that letter fluency (ß = .22, p = .017) and CBCL attention problems (ß = -.21, p =.002) were significant predictors of sight-word reading. Only letter fluency (ß = .23, p =.006) was significant for math calculation. CBCL Attention Problems were a significant predictor of spelling performance (ß = -.21, p = .009) and reading comprehension (ß = -.18, p =.039). CBCL Attention Problems (ß = -.38, p <.001 for ABAS; ß = -.34, p =.002 for CBCL School) and BRIEF-2 Cognitive Regulation difficulties (ß = -.46, p < .001 for ABAS; ß = -.46, p =.013 for CBCL School) were significant predictors of parent-rated ABAS Functional Academics and CBCL School Performance.

Among a national pediatric epilepsy dataset, performance-based and ratings-based measures of EF predicted performance academic achievement, whereas only ratings-based EF predicted parent-rated academic achievement, due at least in part to shared method variance. These findings suggest that interventions that increase cognitive regulation, reduce symptoms of attention dysfunction, and promote self-generative, flexible thinking, may promote academic achievement among children with epilepsy.

Pediatric patients with frontal lobe epilepsy (FLE) have higher rates of attention deficit hyperactivity disorder (ADHD), as well as executive functioning (EF) and fine motor (FM) challenges. Relations between these constructs have been established in youth with ADHD and are supported by FM and EF skill involvement in frontal-subcortical systems. Still, they are not well understood in pediatric FLE. We hypothesized that poorer FM performance would be related to greater executive dysfunction and ADHD symptomatology in this group.

47 children and adolescents with FLE (AgeM=12.47, SD=5.18; IQM=84.07; SD=17.56; Age of Seizure OnsetM=6.85, SD=4.64; right-handed: n=34; left-handed: n=10; Unclear: n=3) were enrolled in the Pediatric Epilepsy Research Consortium dataset as part of their phase I epilepsy surgical evaluation. Participants were selected if they had unifocal FLE and completed the Lafayette Grooved Pegboard (GP). Seizure lateralization (left-sided: n=19; right-sided: n=26; bilateral: n=2) and localization were established via data (e.g., EEG, MRI) presented at a multidisciplinary team case conference. Patients completed neuropsychological measures of FM, attention, and EF. Parents also completed questionnaires inquiring about their child’s everyday EF and ADHD symptomatology. Correlational analyses were conducted to examine FM, EF, and ADHD relations.

Dominant hand (DH) manual dexterity (GP) was related to parent-reported EF (Behavior Rating Inventory of Executive Function, Second Edition [BRIEF-2]-Global Executive Composite [GEC]: r(15) =-.70, p<.01, d=1.96). While not statistically significant, medium to large effect sizes were found for GP DH and parent-reported inattention (Behavior Assessment System for Children, Third Edition [BASC-3]-Attention Problems: r(12)=-.39, p=.17, d=.85) and hyperactivity/impulsivity (BASC-3-Hyperactivity: r(11)= -.44, p=.13, d=.98), as well as performance-based attention (Conners Continuous Performance Test, Third Edition -Omission Errors: r(12)=-.35, p=.22, d=.41), working memory (Wechsler Intelligence Scale for Children - Fifth Edition [WISC-V]-Digit Span [DS]: r(19)=.38, p=.09, d=.82) and cognitive flexibility (Delis-Kaplan Executive Function System (D-KEFS) Verbal Fluency Category Switching: r(13)=.46, p=.08, d=1.04); this suggests that these relations may exist but that our study was underpowered to detect them. Non-dominant hand (NDH) manual dexterity was related to performance-based working memory (WISC-V-DS: r(19)=.50, p<.01, d=1.12) and cognitive flexibility (D-KEFS-Trails Making Test Number-Letter Switching: r(17)=.64, p<.01, d=1.67). Again, while underpowered, medium to large effect sizes were found for GP NDH and parent-reported EF (BRIEF-2 GEC: r(15) =-.45, p=.07, d=1.01) and performance-based phonemic fluency (D-KEFS-Letter Fluency: r(13)=.31, p=.20, d=.65).

Our findings suggest that FM, EF, and ADHD are related in youth with FLE; however, these relations appear to vary by skill and hand. We posit that our findings are due in part to the frontal-cerebellar networks given their anatomic proximity between frontal motor areas and the dorsolateral prefrontal cortex - as well as their shared functional involvement in these networks. Future studies should evaluate the predictive validity of initial FM skills for later executive dysfunction and ADHD symptomatology in FLE. If such relations emerge, contributions of early FM interventions on EF development should be examined. Further replication of these findings with a larger sample is warranted.

People with serious mental illness (SMI) have high rates of smoking and need better access to cessation treatment. Mobile behavioral interventions for cessation have been effective for the general population, but are not usable by many with SMI due to cognitive impairments or severe symptoms. We developed a tailored mobile cessation treatment intervention with features to reduce cognitive load.

We enrolled 20 smokers with SMI and showed them how to use the program on a device of their choice. They were assessed at 8 weeks for intervention use, usability, satisfaction, smoking characteristics, and biologically verified abstinence.

Participants accessed an average of 23.6 intervention sessions (SD = 17.05; range 1–48; median = 17.5) for an average total of 231.64 minutes (SD = 227.13; range 4.89–955.21; median = 158.18). For 87% of the sessions, average satisfaction scores were 3 or greater on a scale of 1–4. Regarding smoking, 25% of participants had reduced their smoking and 10% had biologically verified abstinence from smoking at 8 weeks.

Home and community use of this mobile cessation intervention was feasible among smokers with SMI. Further research is needed to evaluate such scalable approaches to increase access to behavioral treatment for this group.

People with severe persistent mental illness (SPMI) experience a greater burden and severity of chronic disease, late diagnosis, and premature death compared with the general population. Those with SPMI also receive fewer medical treatments, poor quality of care, and are less likely to receive palliative care. A systematic scoping review was undertaken to determine the extent, range, and nature of research activity about people with SPMI requiring palliative care, and to identify gaps and opportunities for future research.

A systematic scoping review was undertaken in September 2017 and updated in May 2018 to map literature on this topic, determine the extent and range of what has been published, and report the findings. This five-stage framework was conducted by (1) identifying the research question; (2) identifying relevant studies; (3) determining study selection; (4) charting the data; and 5) collating, summarizing, and reporting the results. A narrative approach to analysis was used to synthesize and interpret findings. A search of multidisciplinary healthcare databases resulted in 46 included articles.

Four major themes were identified from the included studies: complexity of care; limited access to care (both through systems and healthcare providers); competence and autonomy; and the potential for relationships between mental health and palliative care.

This review reveals a highly vulnerable population with complex needs that are not reliably being met by the healthcare system and providers. Research in this area must continue to develop using rigorous qualitative and quantitative study designs, and interventions should be developed and tested based on existing knowledge to inform care. The voices of people with SPMI in need of palliative care must be represented in future studies to address gaps. To expand a body of literature addressing mainly individuals, system perspectives and sociocultural analysis can bring much to contextualizing the experience of living with SPMI in the palliative phase of care. Adoption of a palliative approach, which promotes the principles of palliative care across nonspecialized care settings provided by nonspecialist palliative providers, has the potential to increase access to high-quality palliative treatment for people with SPMI.

Research shows that cognitive rehabilitation (CR) has the potential to improve goal performance and enhance well-being for people with early stage Alzheimer’s disease (AD). This single subject, multiple baseline design (MBD) research investigated the clinical efficacy of an 8-week individualised CR intervention for individuals with early stage AD.

Three participants with early stage AD were recruited to take part in the study. The intervention consisted of eight sessions of 60–90 minutes of CR. Outcomes included goal performance and satisfaction, quality of life, cognitive and everyday functioning, mood, and memory self-efficacy for participants with AD; and carer burden, general mental health, quality of life, and mood of carers.

Visual analysis of MBD data demonstrated a functional relationship between CR and improvements in participants’ goal performance. Subjective ratings of goal performance and satisfaction increased from baseline to post-test for three participants and were maintained at follow-up for two. Baseline to post-test quality of life scores improved for three participants, whereas cognitive function and memory self-efficacy scores improved for two.

Our findings demonstrate that CR can improve goal performance, and is a socially acceptable intervention that can be implemented by practitioners with assistance from carers between sessions. This study represents one of the promising first step towards filling a practice gap in this area. Further research and randomised-controlled trials are required.

Our understanding of the complex relationship between schizophrenia symptomatology and etiological factors can be improved by studying brain-based correlates of schizophrenia. Research showed that impairments in value processing and executive functioning, which have been associated with prefrontal brain areas [particularly the medial orbitofrontal cortex (MOFC)], are linked to negative symptoms. Here we tested the hypothesis that MOFC thickness is associated with negative symptom severity.

This study included 1985 individuals with schizophrenia from 17 research groups around the world contributing to the ENIGMA Schizophrenia Working Group. Cortical thickness values were obtained from T1-weighted structural brain scans using FreeSurfer. A meta-analysis across sites was conducted over effect sizes from a model predicting cortical thickness by negative symptom score (harmonized Scale for the Assessment of Negative Symptoms or Positive and Negative Syndrome Scale scores).

Meta-analytical results showed that left, but not right, MOFC thickness was significantly associated with negative symptom severity (βstd = −0.075; p = 0.019) after accounting for age, gender, and site. This effect remained significant (p = 0.036) in a model including overall illness severity. Covarying for duration of illness, age of onset, antipsychotic medication or handedness weakened the association of negative symptoms with left MOFC thickness. As part of a secondary analysis including 10 other prefrontal regions further associations in the left lateral orbitofrontal gyrus and pars opercularis emerged.

Using an unusually large cohort and a meta-analytical approach, our findings point towards a link between prefrontal thinning and negative symptom severity in schizophrenia. This finding provides further insight into the relationship between structural brain abnormalities and negative symptoms in schizophrenia.