151 results
Unleashing collective intelligence for public decision-making: the Data for Policy community
- Zeynep Engin, Emily Gardner, Andrew Hyde, Stefaan Verhulst, Jon Crowcroft
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- Data & Policy / Volume 6 / 2024
- Published online by Cambridge University Press:
- 15 April 2024, e23
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Since its establishment in 2014, Data for Policy (https://dataforpolicy.org) has emerged as a prominent global community promoting interdisciplinary research and cross-sector collaborations in the realm of data-driven innovation for governance and policymaking. This report presents an overview of the community’s evolution from 2014 to 2023 and introduces its six-area framework, which provides a comprehensive mapping of the data for policy research landscape. The framework is based on extensive consultations with key stakeholders involved in the international committees of the annual Data for Policy conference series and the open-access journal Data & Policy (https://www.cambridge.org/core/journals/data-and-policy), published by Cambridge University Press. By presenting this inclusive framework, along with the guiding principles and future outlook for the community, this report serves as a vital foundation for continued research and innovation in the field of data for policy.
Annual risk of hepatitis E virus infection and seroreversion: Insights from a serological cohort in Sitakunda, Bangladesh
- Amy Dighe, Ashraful Islam Khan, Taufiqur Rahman Bhuiyan, Md Taufiqul Islam, Zahid Hasan Khan, Ishtiakul Islam Khan, Juan Dent Hulse, Shakeel Ahmed, Mamunur Rashid, Md Zakir Hossain, Rumana Rashid, Sonia T. Hegde, Emily S. Gurley, Firdausi Qadri, Andrew S. Azman
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- Epidemiology & Infection / Volume 152 / 2024
- Published online by Cambridge University Press:
- 18 March 2024, e52
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Hepatitis E virus (HEV) is a major cause of acute jaundice in South Asia. Gaps in our understanding of transmission are driven by non-specific symptoms and scarcity of diagnostics, impeding rational control strategies. In this context, serological data can provide important proxy measures of infection. We enrolled a population-representative serological cohort of 2,337 individuals in Sitakunda, Bangladesh. We estimated the annual risks of HEV infection and seroreversion both using serostatus changes between paired serum samples collected 9 months apart, and by fitting catalytic models to the age-stratified cross-sectional seroprevalence. At baseline, 15% (95 CI: 14–17%) of people were seropositive, with seroprevalence highest in the relatively urban south. During the study, 27 individuals seroreverted (annual seroreversion risk: 15%, 95 CI: 10–21%), and 38 seroconverted (annual infection risk: 3%, 95CI: 2–5%). Relying on cross-sectional seroprevalence data alone, and ignoring seroreversion, underestimated the annual infection risk five-fold (0.6%, 95 CrI: 0.5–0.6%). When we accounted for the observed seroreversion in a reversible catalytic model, infection risk was more consistent with measured seroincidence. Our results quantify HEV infection risk in Sitakunda and highlight the importance of accounting for seroreversion when estimating infection incidence from cross-sectional seroprevalence data.
Identifying incarceration status in the electronic health record using large language models in emergency department settings
- Thomas Huang, Vimig Socrates, Aidan Gilson, Conrad Safranek, Ling Chi, Emily A. Wang, Lisa B. Puglisi, Cynthia Brandt, R. Andrew Taylor, Karen Wang
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- Journal:
- Journal of Clinical and Translational Science / Volume 8 / Issue 1 / 2024
- Published online by Cambridge University Press:
- 11 March 2024, e53
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Background:
Incarceration is a significant social determinant of health, contributing to high morbidity, mortality, and racialized health inequities. However, incarceration status is largely invisible to health services research due to inadequate clinical electronic health record (EHR) capture. This study aims to develop, train, and validate natural language processing (NLP) techniques to more effectively identify incarceration status in the EHR.
Methods:The study population consisted of adult patients (≥ 18 y.o.) who presented to the emergency department between June 2013 and August 2021. The EHR database was filtered for notes for specific incarceration-related terms, and then a random selection of 1,000 notes was annotated for incarceration and further stratified into specific statuses of prior history, recent, and current incarceration. For NLP model development, 80% of the notes were used to train the Longformer-based and RoBERTa algorithms. The remaining 20% of the notes underwent analysis with GPT-4.
Results:There were 849 unique patients across 989 visits in the 1000 annotated notes. Manual annotation revealed that 559 of 1000 notes (55.9%) contained evidence of incarceration history. ICD-10 code (sensitivity: 4.8%, specificity: 99.1%, F1-score: 0.09) demonstrated inferior performance to RoBERTa NLP (sensitivity: 78.6%, specificity: 73.3%, F1-score: 0.79), Longformer NLP (sensitivity: 94.6%, specificity: 87.5%, F1-score: 0.93), and GPT-4 (sensitivity: 100%, specificity: 61.1%, F1-score: 0.86).
Conclusions:Our advanced NLP models demonstrate a high degree of accuracy in identifying incarceration status from clinical notes. Further research is needed to explore their scaled implementation in population health initiatives and assess their potential to mitigate health disparities through tailored system interventions.
Participation, autonomy and control are shared concepts within older people's interpretations of independence: a qualitative interview study
- Emily Taylor, Julia Frost, Susan Ball, Andrew Clegg, Lesley Brown, Victoria A. Goodwin
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- Ageing & Society , First View
- Published online by Cambridge University Press:
- 06 March 2024, pp. 1-24
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To date, support for independence in older people has been largely focused on achieving practice- and policy-orientated goals such as maintenance of function, remaining in one's own home and reducing the impact of receiving care. Uncertainty about what independence means to older people means that these goals may not align with what matters and should be considered for a more person-centred approach to independence. This study aimed to improve understanding of the meaning and facilitators of independence from older people's perspectives. Semi-structured interviews were conducted with 14 community-dwelling people aged 75+, purposively sampled for maximum variance in demographic characteristics. Interviews, conducted by phone or online, were recorded and transcribed. Analysis was conducted using a framework approach to organise, and facilitate comparison of, inductively and deductively generated codes. Patterns were identified and interpreted into themes. Transcripts and themes were reviewed with the research team. Disagreements in interpretations were resolved through discussion. Two themes were identified. The first theme, ‘Older people draw on personal values and experiences to develop unique interpretations of independence’, was underpinned by three concepts: participation, autonomy and control. The concepts reflected patterns identified within participants’ meanings of independence. The second theme, ‘It's not what you have, but how you think about it that creates independence’, represented participants’ shared prioritisation of psychological attributes over physical or environmental resources for maintaining independence. Participation, autonomy and control are shared concepts within older people's diverse interpretations of independence. This paper addresses uncertainty around what independence means to older people and contributes three key concepts that should be considered when operationalising person-centred support for independence.
Anxiety in late-life depression: Associations with brain volume, amyloid beta, white matter lesions, cognition, and functional ability
- Maria Kryza-Lacombe, Michelle T. Kassel, Philip S. Insel, Emma Rhodes, David Bickford, Emily Burns, Meryl A. Butters, Duygu Tosun, Paul Aisen, Rema Raman, Susan Landau, Andrew J. Saykin, Arthur W. Toga, Clifford R. Jack, Jr, Robert Koeppe, Michael W. Weiner, Craig Nelson, R. Scott Mackin
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- International Psychogeriatrics , First View
- Published online by Cambridge University Press:
- 25 January 2024, pp. 1-12
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Objectives:
Late-life depression (LLD) is common and frequently co-occurs with neurodegenerative diseases of aging. Little is known about how heterogeneity within LLD relates to factors typically associated with neurodegeneration. Varying levels of anxiety are one source of heterogeneity in LLD. We examined associations between anxiety symptom severity and factors associated with neurodegeneration, including regional brain volumes, amyloid beta (Aβ) deposition, white matter disease, cognitive dysfunction, and functional ability in LLD.
Participants and Measurements:Older adults with major depression (N = 121, Ages 65–91) were evaluated for anxiety severity and the following: brain volume (orbitofrontal cortex [OFC], insula), cortical Aβ standardized uptake value ratio (SUVR), white matter hyperintensity (WMH) volume, global cognition, and functional ability. Separate linear regression analyses adjusting for age, sex, and concurrent depression severity were conducted to examine associations between anxiety and each of these factors. A global regression analysis was then conducted to examine the relative associations of these variables with anxiety severity.
Results:Greater anxiety severity was associated with lower OFC volume (β = −68.25, t = −2.18, p = .031) and greater cognitive dysfunction (β = 0.23, t = 2.46, p = .016). Anxiety severity was not associated with insula volume, Aβ SUVR, WMH, or functional ability. When examining the relative associations of cognitive functioning and OFC volume with anxiety in a global model, cognitive dysfunction (β = 0.24, t = 2.62, p = .010), but not OFC volume, remained significantly associated with anxiety.
Conclusions:Among multiple factors typically associated with neurodegeneration, cognitive dysfunction stands out as a key factor associated with anxiety severity in LLD which has implications for cognitive and psychiatric interventions.
Impact of primary care triage using the Head and Neck Cancer Risk Calculator version 2 on tertiary head and neck services in the post-coronavirus disease 2019 period
- Jiak-Ying Tan, Christopher John Callaghan, Alexander William Lewthwaite, Claudia Ching Hei Chan, Colette Teng Wee, Emily Yeg Hei To, Isabel Summers, James William Nelson, Mathew Benjamin Smith, Lucy Qian Li, Catriona Morton, Lorna Porteous, Andrew Stewart Evans, Iain James Nixon
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- The Journal of Laryngology & Otology , First View
- Published online by Cambridge University Press:
- 22 January 2024, pp. 1-6
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Objective
This study investigates the impact of primary care utilisation of a symptom-based head and neck cancer risk calculator (Head and Neck Cancer Risk Calculator version 2) in the post-coronavirus disease 2019 period on the number of primary care referrals and cancer diagnoses.
MethodsThe number of referrals from April 2019 to August 2019 and from April 2020 to July 2020 (pre-calculator) was compared with the number from the period January 2021 to August 2022 (post-calculator) using the chi-square test. The patients’ characteristics, referral urgency, triage outcome, Head and Neck Cancer Risk Calculator version 2 score and cancer diagnosis were recorded.
ResultsIn total, 1110 referrals from the pre-calculator period were compared with 1559 from the post-calculator period. Patient characteristics were comparable for both cohorts. More patients were referred on the cancer pathway in the post-calculator cohort (pre-calculator patients 51.1 per cent vs post-calculator 64.0 per cent). The cancer diagnosis rate increased from 2.7 per cent in the pre-calculator cohort to 3.3 per cent in the post-calculator cohort. A lower rate of cancer diagnosis in the non-cancer pathway occurred in the cohort managed using the Head and Neck Cancer Risk Calculator version 2 (10 per cent vs 23 per cent, p = 0.10).
ConclusionHead and Neck Cancer Risk Calculator version 2 demonstrated high sensitivity in cancer diagnosis. Further studies are required to improve the predictive strength of the calculator.
27 Assessing Differences in Academic Achievement Among a National Sample of Children with Epilepsy Before and During the COVID-19 Pandemic
- Brandon Almy, Lauren Scimeca, David Marshall, Brittany L. Nordhaus, Erin Fedak Romanowski, Nancy McNamara, Elise Hodges, Madison M. Berl, Alyssa Ailion, Donald J. Bearden, Katrina Boyer, Crystal M. Cooper, Amanda M. Decrow, Priscilla H. Duong, Patricia Espe-Pfeifer, Marsha Gabriel, Jennifer I. Koop, Kelly A. McNally, Andrew Molnar, Emily Olsen, Kim E. Ono, Kristina E. Patrick, Brianna Paul, Jonathan Romain, Leigh N. Sepeta, Rebecca L.H. Stilp, Greta N. Wilkening, Mike Zaccariello, Frank Zelko
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 28-29
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Objective:
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.
Participants and Methods: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)].
Results: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).
Conclusions: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.
53 2-Back Performance Does Not Differ Between Cognitive Training Groups in Older Adults Without Dementia
- Nicole D Evangelista, Jessica N Kraft, Hanna K Hausman, Andrew O’Shea, Alejandro Albizu, Emanuel M Boutzoukas, Cheshire Hardcastle, Emily J Van Etten, Pradyumna K Bharadwaj, Hyun Song, Samantha G Smith, Steven DeKosky, Georg A Hishaw, Samuel Wu, Michael Marsiske, Ronald Cohen, Gene E Alexander, Eric Porges, Adam J Woods
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 360-361
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Objective:
Cognitive training is a non-pharmacological intervention aimed at improving cognitive function across a single or multiple domains. Although the underlying mechanisms of cognitive training and transfer effects are not well-characterized, cognitive training has been thought to facilitate neural plasticity to enhance cognitive performance. Indeed, the Scaffolding Theory of Aging and Cognition (STAC) proposes that cognitive training may enhance the ability to engage in compensatory scaffolding to meet task demands and maintain cognitive performance. We therefore evaluated the effects of cognitive training on working memory performance in older adults without dementia. This study will help begin to elucidate non-pharmacological intervention effects on compensatory scaffolding in older adults.
Participants and Methods:48 participants were recruited for a Phase III randomized clinical trial (Augmenting Cognitive Training in Older Adults [ACT]; NIH R01AG054077) conducted at the University of Florida and University of Arizona. Participants across sites were randomly assigned to complete cognitive training (n=25) or an education training control condition (n=23). Cognitive training and the education training control condition were each completed during 60 sessions over 12 weeks for 40 hours total. The education training control condition involved viewing educational videos produced by the National Geographic Channel. Cognitive training was completed using the Posit Science Brain HQ training program, which included 8 cognitive training paradigms targeting attention/processing speed and working memory. All participants also completed demographic questionnaires, cognitive testing, and an fMRI 2-back task at baseline and at 12-weeks following cognitive training.
Results:Repeated measures analysis of covariance (ANCOVA), adjusted for training adherence, transcranial direct current stimulation (tDCS) condition, age, sex, years of education, and Wechsler Test of Adult Reading (WTAR) raw score, revealed a significant 2-back by training group interaction (F[1,40]=6.201, p=.017, η2=.134). Examination of simple main effects revealed baseline differences in 2-back performance (F[1,40]=.568, p=.455, η2=.014). After controlling for baseline performance, training group differences in 2-back performance was no longer statistically significant (F[1,40]=1.382, p=.247, η2=.034).
Conclusions:After adjusting for baseline performance differences, there were no significant training group differences in 2-back performance, suggesting that the randomization was not sufficient to ensure adequate distribution of participants across groups. Results may indicate that cognitive training alone is not sufficient for significant improvement in working memory performance on a near transfer task. Additional improvement may occur with the next phase of this clinical trial, such that tDCS augments the effects of cognitive training and results in enhanced compensatory scaffolding even within this high performing cohort. Limitations of the study include a highly educated sample with higher literacy levels and the small sample size was not powered for transfer effects analysis. Future analyses will include evaluation of the combined intervention effects of a cognitive training and tDCS on nback performance in a larger sample of older adults without dementia.
1 Quantity or quality? Comparing objective and subjective participation measures to predict quality of life in aging msTBI.
- Andrew P Cwiek, Samantha Vervoordt, Emily E Carter, Frank G Hillary
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- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 113-114
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Objective:
Community reintegration and participation have been shown to be significantly correlated to improved Quality of Life (QoL) following moderate to severe traumatic brain injury (msTBI), yet these models often come with significant levels of unaccounted variability (Pierce and Hanks, 2006). Measures for community participation frequently employ objective measures of participation, such as number of outings in a week or current employment status (Migliorini et al., 2016), which may not adequately account for lifestyle differences, especially in aging populations. Less often integrated are subjective measures of an individual’s own belongingness and autonomy within the community (Heineman et al., 2011), also referred to as their participation enfranchisement (PE). The present study examines three questions pertinent to the potential clinical value of PE. First, do measures of objective participation significantly predict an individual’s PE ratings? Second, are both types of measures equally successful predictors of QoL for aging individuals with chronic-stage msTBI. Finally, would controlling for either objective or subjective integration ratings enable neurocognitive assessments to better predict QoL post injury?
Participants and Methods:41 older-adults (M= 65.32; SD= 7.51) with a history of msTBI were included (M= 12.59 years post-injury;SD= 8.29) for analysis. Subjective community integration was measured through the Participation Enfranchisement Survey. The Participation Assessment with Recombined Tools-Objective (PART-O) provided the objective measurement of participation. Quality of life was assessed through the Quality of Life after Brain Injury (QOLIBRI). An estimate of neurocognitive performance was created through the Brief Test of Adult Cognition by Telephone (BTACT), which includes six domains including: verbal-learning and memory (immediate and delayed recall), working memory (digit-span backwards), reasoning (number sequencing), semantic fluency (category fluency), and processing speed (backwards counting). Performance on the BTACT, PE ratings, and PART-O scores were included as the dependent variables in stepwise, linear regression models predicting QoL ratings to assess the differential contribution of the dependent variables and potential interaction effects.
Results:While both the PART-O (f(1,39)=5.52;p=.024,n2=.124) and the PE survey (f(1,39)=14.31 ;p<.001,n2=.268) significantly predicted QoL, the addition of PE in the PART-O model resulted in significant (20.9%) reduction in unaccounted variance. Further in the model controlling for PE, PART-O no longer provides a significant (p=.15) contribution to the model estimating QoL (f(2,38)=8.41; p=.001). Performance on the BTACT correlated with PART-O (p<.0001), but not PE (p=.13) ratings. Finally, across two models controlling for BTACT performance, PE (p=.002,partial n2=.23), but not PART-O (p=.28,partial n2=.031) contributed significantly to QoL predictions. No significant interactions between PART-O, PE, and/or BTACT were observed when added to any model.
Conclusions:MsTBI impacts nearly every facet of an individual’s life, and as such, improving QoL post-injury requires a broad, yet well-considered approach. The objective ratings of participation, subjective PE, BTACT performance, all independently predicted quality of life in this sample. However, after controlling for neurocognitive assessment performance, PE was shown to independently contribute to quality of life, while the PART-O ratings no longer provided significant contribution. While community integration is a vital factor to consider for long-term rehabilitation, tailoring what “integration” means to the patient may hold significant potential to improve long-term quality of life.
2 Higher White Matter Hyperintensity Load Adversely Affects Pre-Post Proximal Cognitive Training Performance in Healthy Older Adults
- Emanuel M Boutzoukas, Andrew O’Shea, Jessica N Kraft, Cheshire Hardcastle, Nicole D Evangelista, Hanna K Hausman, Alejandro Albizu, Emily J Van Etten, Pradyumna K Bharadwaj, Samantha G Smith, Hyun Song, Eric C Porges, Alex Hishaw, Steven T DeKosky, Samuel S Wu, Michael Marsiske, Gene E Alexander, Ronald Cohen, Adam J Woods
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- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 671-672
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Objective:
Cognitive training has shown promise for improving cognition in older adults. Aging involves a variety of neuroanatomical changes that may affect response to cognitive training. White matter hyperintensities (WMH) are one common age-related brain change, as evidenced by T2-weighted and Fluid Attenuated Inversion Recovery (FLAIR) MRI. WMH are associated with older age, suggestive of cerebral small vessel disease, and reflect decreased white matter integrity. Higher WMH load associates with reduced threshold for clinical expression of cognitive impairment and dementia. The effects of WMH on response to cognitive training interventions are relatively unknown. The current study assessed (a) proximal cognitive training performance following a 3-month randomized control trial and (b) the contribution of baseline whole-brain WMH load, defined as total lesion volume (TLV), on pre-post proximal training change.
Participants and Methods:Sixty-two healthy older adults ages 65-84 completed either adaptive cognitive training (CT; n=31) or educational training control (ET; n=31) interventions. Participants assigned to CT completed 20 hours of attention/processing speed training and 20 hours of working memory training delivered through commercially-available Posit Science BrainHQ. ET participants completed 40 hours of educational videos. All participants also underwent sham or active transcranial direct current stimulation (tDCS) as an adjunctive intervention, although not a variable of interest in the current study. Multimodal MRI scans were acquired during the baseline visit. T1- and T2-weighted FLAIR images were processed using the Lesion Segmentation Tool (LST) for SPM12. The Lesion Prediction Algorithm of LST automatically segmented brain tissue and calculated lesion maps. A lesion threshold of 0.30 was applied to calculate TLV. A log transformation was applied to TLV to normalize the distribution of WMH. Repeated-measures analysis of covariance (RM-ANCOVA) assessed pre/post change in proximal composite (Total Training Composite) and sub-composite (Processing Speed Training Composite, Working Memory Training Composite) measures in the CT group compared to their ET counterparts, controlling for age, sex, years of education and tDCS group. Linear regression assessed the effect of TLV on post-intervention proximal composite and sub-composite, controlling for baseline performance, intervention assignment, age, sex, years of education, multisite scanner differences, estimated total intracranial volume, and binarized cardiovascular disease risk.
Results:RM-ANCOVA revealed two-way group*time interactions such that those assigned cognitive training demonstrated greater improvement on proximal composite (Total Training Composite) and sub-composite (Processing Speed Training Composite, Working Memory Training Composite) measures compared to their ET counterparts. Multiple linear regression showed higher baseline TLV associated with lower pre-post change on Processing Speed Training sub-composite (ß = -0.19, p = 0.04) but not other composite measures.
Conclusions:These findings demonstrate the utility of cognitive training for improving postintervention proximal performance in older adults. Additionally, pre-post proximal processing speed training change appear to be particularly sensitive to white matter hyperintensity load versus working memory training change. These data suggest that TLV may serve as an important factor for consideration when planning processing speed-based cognitive training interventions for remediation of cognitive decline in older adults.
1 Task-Based Functional Connectivity and Network Segregation of the Useful Field of View (UFOV) fMRI task
- Jessica N Kraft, Hanna K Hausman, Cheshire Hardcastle, Alejandro Albizu, Andrew O’Shea, Nicole D Evangelista, Emanuel M Boutzoukas, Emily J Van Etten, Pradyumna K Bharadwaj, Hyun Song, Samantha G Smith, Steven T DeKosky, Georg A Hishaw, Samuel Wu, Michael Marsiske, Ronald Cohen, Eric Porges, Adam J Woods
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- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 606-607
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Objective:
Interventions using a cognitive training paradigm called the Useful Field of View (UFOV) task have shown to be efficacious in slowing cognitive decline. However, no studies have looked at the engagement of functional networks during UFOV task completion. The current study aimed to (a) assess if regions activated during the UFOV fMRI task were functionally connected and related to task performance (henceforth called the UFOV network), (b) compare connectivity of the UFOV network to 7 resting-state functional connectivity networks in predicting proximal (UFOV) and near-transfer (Double Decision) performance, and (c) explore the impact of network segregation between higher-order networks and UFOV performance.
Participants and Methods:336 healthy older adults (mean age=71.6) completed the UFOV fMRI task in a Siemens 3T scanner. UFOV fMRI accuracy was calculated as the number of correct responses divided by 56 total trials. Double Decision performance was calculated as the average presentation time of correct responses in log ms, with lower scores equating to better processing speed. Structural and functional MRI images were processed using the default pre-processing pipeline within the CONN toolbox. The Artifact Rejection Toolbox was set at a motion threshold of 0.9mm and participants were excluded if more than 50% of volumes were flagged as outliers. To assess connectivity of regions associated with the UFOV task, we created 10 spherical regions of interest (ROIs) a priori using the WFU PickAtlas in SPM12. These include the bilateral pars triangularis, supplementary motor area, and inferior temporal gyri, as well as the left pars opercularis, left middle occipital gyrus, right precentral gyrus and right superior parietal lobule. We used a weighted ROI-to-ROI connectivity analysis to model task-based within-network functional connectivity of the UFOV network, and its relationship to UFOV accuracy. We then used weighted ROI-to-ROI connectivity analysis to compare the efficacy of the UFOV network versus 7 resting-state networks in predicting UFOV fMRI task performance and Double Decision performance. Finally, we calculated network segregation among higher order resting state networks to assess its relationship with UFOV accuracy. All functional connectivity analyses were corrected at a false discovery threshold (FDR) at p<0.05.
Results:ROI-to-ROI analysis showed significant within-network functional connectivity among the 10 a priori ROIs (UFOV network) during task completion (all pFDR<.05). After controlling for covariates, greater within-network connectivity of the UFOV network associated with better UFOV fMRI performance (pFDR=.008). Regarding the 7 resting-state networks, greater within-network connectivity of the CON (pFDR<.001) and FPCN (pFDR=. 014) were associated with higher accuracy on the UFOV fMRI task. Furthermore, greater within-network connectivity of only the UFOV network associated with performance on the Double Decision task (pFDR=.034). Finally, we assessed the relationship between higher-order network segregation and UFOV accuracy. After controlling for covariates, no significant relationships between network segregation and UFOV performance remained (all p-uncorrected>0.05).
Conclusions:To date, this is the first study to assess task-based functional connectivity during completion of the UFOV task. We observed that coherence within 10 a priori ROIs significantly predicted UFOV performance. Additionally, enhanced within-network connectivity of the UFOV network predicted better performance on the Double Decision task, while conventional resting-state networks did not. These findings provide potential targets to optimize efficacy of UFOV interventions.
78 BVMT-R Learning Ratio Moderates Cognitive Training Gains in Useful Field of View Task in Healthy Older Adults
- Cheshire Hardcastle, Jessica N. Kraft, Hanna K. Hausman, Andrew O’Shea, Alejandro Albizu, Nicole D. Evangelista, Emanuel Boutzoukas, Emily J. Van Etten, Pradyumna K. Bharadwaj, Hyun Song, Samantha G. Smith, Eric Porges, Steven DeKosky, Georg A. Hishaw, Samuel Wu, Michael Marsiske, Ronald Cohen, Gene E. Alexander, Adam J. Woods
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- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 180-181
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Objective:
Cognitive training using a visual speed-of-processing task, called the Useful Field of View (UFOV) task, reduced dementia risk and reduced decline in activities of daily living at a 10-year follow-up in older adults. However, there is variability in the level of cognitive gains after cognitive training across studies. One potential explanation for this variability could be moderating factors. Prior studies suggest variables moderating cognitive training gains share features of the training task. Learning trials of the Hopkins Verbal Learning Test-Revised (HVLT-R) and Brief Visuospatial Memory Test-Revised (BVMT-R) recruit similar cognitive abilities and have overlapping neural correlates with the UFOV task and speed-ofprocessing/working memory tasks and therefore could serve as potential moderators. Exploring moderating factors of cognitive training gains may boost the efficacy of interventions, improve rigor in the cognitive training literature, and eventually help provide tailored treatment recommendations. This study explored the association between the HVLT-R and BVMT-R learning and the UFOV task, and assessed the moderation of HVLT-R and BVMT-R learning on UFOV improvement after a 3-month speed-ofprocessing/attention and working memory cognitive training intervention in cognitively healthy older adults.
Participants and Methods:75 healthy older adults (M age = 71.11, SD = 4.61) were recruited as part of a larger clinical trial through the Universities of Florida and Arizona. Participants were randomized into a cognitive training (n=36) or education control (n=39) group and underwent a 40-hour, 12-week intervention. Cognitive training intervention consisted of practicing 4 attention/speed-of-processing (including the UFOV task) and 4 working memory tasks. Education control intervention consisted of watching 40-minute educational videos. The HVLT-R and BVMT-R were administered at the pre-intervention timepoint as part of a larger neurocognitive battery. The learning ratio was calculated as: trial 3 total - trial 1 total/12 - trial 1 total. UFOV performance was measured at pre- and post-intervention time points via the POSIT Brain HQ Double Decision Assessment. Multiple linear regressions predicted baseline Double Decision performance from HVLT-R and BVMT-R learning ratios controlling for study site, age, sex, and education. A repeated measures moderation analysis assessed the moderation of HVLT-R and BVMT-R learning ratio on Double Decision change from pre- to post-intervention for cognitive training and education control groups.
Results:Baseline Double Decision performance significantly associated with BVMT-R learning ratio (β=-.303, p=.008), but not HVLT-R learning ratio (β=-.142, p=.238). BVMT-R learning ratio moderated gains in Double Decision performance (p<.01); for each unit increase in BVMT-R learning ratio, there was a .6173 unit decrease in training gains. The HVLT-R learning ratio did not moderate gains in Double Decision performance (p>.05). There were no significant moderations in the education control group.
Conclusions:Better visuospatial learning was associated with faster Double Decision performance at baseline. Those with poorer visuospatial learning improved most on the Double Decision task after training, suggesting that healthy older adults who perform below expectations may show the greatest training gains. Future cognitive training research studying visual speed-of-processing interventions should account for differing levels of visuospatial learning at baseline, as this could impact the magnitude of training outcomes.
6 Adjunctive Transcranial Direct Current Stimulation and Cognitive Training Alters Default Mode and Frontoparietal Control Network Connectivity in Older Adults
- Hanna K Hausman, Jessica N Kraft, Cheshire Hardcastle, Nicole D Evangelista, Emanuel M Boutzoukas, Andrew O’Shea, Alejandro Albizu, Emily J Van Etten, Pradyumna K Bharadwaj, Hyun Song, Samantha G Smith, Eric S Porges, Georg A Hishaw, Samuel Wu, Steven DeKosky, Gene E Alexander, Michael Marsiske, Ronald A Cohen, Adam J Woods
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 675-676
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Objective:
Aging is associated with disruptions in functional connectivity within the default mode (DMN), frontoparietal control (FPCN), and cingulo-opercular (CON) resting-state networks. Greater within-network connectivity predicts better cognitive performance in older adults. Therefore, strengthening network connectivity, through targeted intervention strategies, may help prevent age-related cognitive decline or progression to dementia. Small studies have demonstrated synergistic effects of combining transcranial direct current stimulation (tDCS) and cognitive training (CT) on strengthening network connectivity; however, this association has yet to be rigorously tested on a large scale. The current study leverages longitudinal data from the first-ever Phase III clinical trial for tDCS to examine the efficacy of an adjunctive tDCS and CT intervention on modulating network connectivity in older adults.
Participants and Methods:This sample included 209 older adults (mean age = 71.6) from the Augmenting Cognitive Training in Older Adults multisite trial. Participants completed 40 hours of CT over 12 weeks, which included 8 attention, processing speed, and working memory tasks. Participants were randomized into active or sham stimulation groups, and tDCS was administered during CT daily for two weeks then weekly for 10 weeks. For both stimulation groups, two electrodes in saline-soaked 5x7 cm2 sponges were placed at F3 (cathode) and F4 (anode) using the 10-20 measurement system. The active group received 2mA of current for 20 minutes. The sham group received 2mA for 30 seconds, then no current for the remaining 20 minutes.
Participants underwent resting-state fMRI at baseline and post-intervention. CONN toolbox was used to preprocess imaging data and conduct region of interest (ROI-ROI) connectivity analyses. The Artifact Detection Toolbox, using intermediate settings, identified outlier volumes. Two participants were excluded for having greater than 50% of volumes flagged as outliers. ROI-ROI analyses modeled the interaction between tDCS group (active versus sham) and occasion (baseline connectivity versus postintervention connectivity) for the DMN, FPCN, and CON controlling for age, sex, education, site, and adherence.
Results:Compared to sham, the active group demonstrated ROI-ROI increases in functional connectivity within the DMN following intervention (left temporal to right temporal [T(202) = 2.78, pFDR < 0.05] and left temporal to right dorsal medial prefrontal cortex [T(202) = 2.74, pFDR < 0.05]. In contrast, compared to sham, the active group demonstrated ROI-ROI decreases in functional connectivity within the FPCN following intervention (left dorsal prefrontal cortex to left temporal [T(202) = -2.96, pFDR < 0.05] and left dorsal prefrontal cortex to left lateral prefrontal cortex [T(202) = -2.77, pFDR < 0.05]). There were no significant interactions detected for CON regions.
Conclusions:These findings (a) demonstrate the feasibility of modulating network connectivity using tDCS and CT and (b) provide important information regarding the pattern of connectivity changes occurring at these intervention parameters in older adults. Importantly, the active stimulation group showed increases in connectivity within the DMN (a network particularly vulnerable to aging and implicated in Alzheimer’s disease) but decreases in connectivity between left frontal and temporal FPCN regions. Future analyses from this trial will evaluate the association between these changes in connectivity and cognitive performance post-intervention and at a one-year timepoint.
28 Factor Structure of Conventional Neuropsychological Tests and NIH-Toolbox in Healthy Older Adults
- Kailey Langer, Cheshire Hardcastle, Hanna Hausman, Jessica Kraft, Alejandro Albizu, Nicole Evangelista, Emanuel Boutzoukas, Andrew O’Shea, Emily Van Etten, Samantha Smith, Hyun Song, Pradyumna Bharadwaj, Georg Hishaw, Samuel Wu, Steven DeKosky, Gene Alexander, Eric Porges, Michael Marsiske, Ronald Cohen, Adam Woods
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, p. 710
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The National Institutes of Health-Toolbox cognition battery (NIH-TCB) is widely used in cognitive aging studies and includes measures in cognitive domains evaluated for dimensional structure and psychometric properties in prior research. The present study addresses a current literature gap by demonstrating how NIH-TCB integrates into a battery of traditional clinical neuropsychological measures. The dimensional structure of NIH-TCB measures along with conventional neuropsychological tests is assessed in healthy older adults.
Participants and Methods:Baseline cognitive data were obtained from 327 older adults. The following measures were collected: NIH-Toolbox cognitive battery, Controlled Oral Word Association (COWA) letter and animals tests, Wechsler Test of Adult Reading (WTAR), Stroop Color-Word Interference Test, Paced Auditory Serial Addition Test (PASAT), Brief Visuospatial Memory Test (BVMT), Letter-Number Sequencing (LNS), Hopkins Verbal Learning Test (HVLT), Trail Making Test A&B, Digit Span. Hmisc, psych, and GPARotation packages for R were used to conduct exploratory factor analyses (EFA). A 5-factor solution was conducted followed by a 6-factor solution. Promax rotation was used for both EFA models.
Results:The 6-factor EFA solution is reported here. Results indicated the following 6 factors: working memory (Digit Span forward, backward, and sequencing, PASAT trials 1 and 2, NIH-Toolbox List Sorting, LNS), speed/executive function (Stroop color naming, word reading, and color-word interference, NIH-Toolbox Flanker, Dimensional Change, and Pattern Comparison, Trail Making Test A&B), verbal fluency (COWA letters F-A-S), crystallized intelligence (WTAR, NIH-Toolbox Oral Recognition and Picture Vocabulary), visual memory (BVMT immediate and delayed), and verbal memory (HVLT immediate and delayed. COWA animals and NIH-Toolbox Picture Sequencing did not adequately load onto any EFA factor and were excluded from the subsequent CFA.
Conclusions:Findings indicate that in a sample of healthy older adults, these collected measures and those obtained through the NIH-Toolbox battery represent 6 domains of cognitive function. Results suggest that in this sample, picture sequencing and COWA animals did not load adequately onto the factors created from the rest of the measures collected. These findings should assist in interpreting future research using combined NIH-TCB and neuropsychological batteries to assess cognition in healthy older adults.
9 Connecting memory and functional brain networks in older adults: a resting state fMRI study
- Jori L Waner, Hanna K Hausman, Jessica N Kraft, Cheshire Hardcastle, Nicole D Evangelista, Andrew O’Shea, Alejandro Albizu, Emanuel M Boutzoukas, Emily J Van Etten, Pradyumna K Bharadwaj, Hyun Song, Samantha G Smith, Steven T DeKosky, Georg A Hishaw, Samuel S Wu, Michael Marsiske, Ronald Cohen, Gene E Alexander, Eric C Porges, Adam J Woods
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 527-528
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Nonpathological aging has been linked to decline in both verbal and visuospatial memory abilities in older adults. Disruptions in resting-state functional connectivity within well-characterized, higherorder cognitive brain networks have also been coupled with poorer memory functioning in healthy older adults and in older adults with dementia. However, there is a paucity of research on the association between higherorder functional connectivity and verbal and visuospatial memory performance in the older adult population. The current study examines the association between resting-state functional connectivity within the cingulo-opercular network (CON), frontoparietal control network (FPCN), and default mode network (DMN) and verbal and visuospatial learning and memory in a large sample of healthy older adults. We hypothesized that greater within-network CON and FPCN functional connectivity would be associated with better immediate verbal and visuospatial memory recall. Additionally, we predicted that within-network DMN functional connectivity would be associated with improvements in delayed verbal and visuospatial memory recall. This study helps to glean insight into whether within-network CON, FPCN, or DMN functional connectivity is associated with verbal and visuospatial memory abilities in later life.
Participants and Methods:330 healthy older adults between 65 and 89 years old (mean age = 71.6 ± 5.2) were recruited at the University of Florida (n = 222) and the University of Arizona (n = 108). Participants underwent resting-state fMRI and completed verbal memory (Hopkins Verbal Learning Test - Revised [HVLT-R]) and visuospatial memory (Brief Visuospatial Memory Test - Revised [BVMT-R]) measures. Immediate (total) and delayed recall scores on the HVLT-R and BVMT-R were calculated using each test manual’s scoring criteria. Learning ratios on the HVLT-R and BVMT-R were quantified by dividing the number of stimuli (verbal or visuospatial) learned between the first and third trials by the number of stimuli not recalled after the first learning trial. CONN Toolbox was used to extract average within-network connectivity values for CON, FPCN, and DMN. Hierarchical regressions were conducted, controlling for sex, race, ethnicity, years of education, number of invalid scans, and scanner site.
Results:Greater CON connectivity was significantly associated with better HVLT-R immediate (total) recall (ß = 0.16, p = 0.01), HVLT-R learning ratio (ß = 0.16, p = 0.01), BVMT-R immediate (total) recall (ß = 0.14, p = 0.02), and BVMT-R delayed recall performance (ß = 0.15, p = 0.01). Greater FPCN connectivity was associated with better BVMT-R learning ratio (ß = 0.13, p = 0.04). HVLT-R delayed recall performance was not associated with connectivity in any network, and DMN connectivity was not significantly related to any measure.
Conclusions:Connectivity within CON demonstrated a robust relationship with different components of memory function as well across verbal and visuospatial domains. In contrast, FPCN only evidenced a relationship with visuospatial learning, and DMN was not significantly associated with memory measures. These data suggest that CON may be a valuable target in longitudinal studies of age-related memory changes, but also a possible target in future non-invasive interventions to attenuate memory decline in older adults.
3 Latent Wechsler Profiles in Presurgical Pediatric Epilepsy
- Madison M Berl, Erin T Kaseda, Jennifer I Koop, Brandon Almy, Alyssa Ailion, Donald J Bearden, Katrina Boyer, Crystal M Cooper, Amanda M DeCrow, Priscilla H Duong, Patricia Espe-Pfeifer, Marsha Gabriel, Elise Hodges, David Marshall, Kelly A McNally, Andrew Molnar, Emily Olsen, Kim E Ono, Kristina E Patrick, Brianna Paul, Jonathan Romain, Leigh N Sepeta, Rebecca LH Stilp, Greta Wilkening, Michael Zaccariello, Frank Zelko, PERC Epilepsy Surgery Database Project
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- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 308-310
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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.
Participants and Methods: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.
Results: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.
Conclusions: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.
26 The Importance of Executive Functioning for Academic Achievement Among a National Sample of Children with Epilepsy
- Brandon Almy, David Marshall, Brittany L. Nordhaus, Erin Fedak Romanowski, Nancy McNamara, Elise Hodges, Madison M. Berl, Alyssa Ailion, Donald J. Bearden, Katrina Boyer, Crystal M. Cooper, Amanda M. Decrow, Priscilla H. Duong, Patricia Espe-Pfeifer, Marsha Gabriel, Jennifer I. Koop, Kelly A. McNally, Andrew Molnar, Emily Olsen, Kim E. Ono, Kristina E. Patrick, Brianna Paul, Jonathan Romain, Leigh N. Sepeta, Rebecca L.H. Stilp, Greta N. Wilkening, Mike Zaccariello, Frank Zelko
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- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 26-27
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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 and Methods: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.
Results: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.
Conclusions: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.
18 Regional patterns of mitochondrial function using phosphorus magnetic resonance spectroscopy in older adults at-risk for Alzheimer’s disease.
- Francesca V Lopez, Andrew O’Shea, Stacey Alvarez-Alvarado, Adrianna Ratajska, Lauren Kenney, Rachel Schade, Katie Rodriguez, Alyssa Ray, Rebecca O’Connell, Lauren Santos, Emily Van Etten, Hyun Song, Emma Armstrong, Tiffany Gin, Zhiguang Huo, Gene Alexander, Adam J Woods, Dawn Bowers
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- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 331-332
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The brain is reliant on mitochondria to carry out a host of vital cellular functions (e.g., energy metabolism, respiration, apoptosis) to maintain neuronal integrity. Clinically relevant, dysfunctional mitochondria have been implicated as central to the pathogenesis of Alzheimer’s disease (AD). Phosphorous magnetic resonance spectroscopy (31p MRS) is a non-invasive and powerful method for examining in vivo mitochondrial function via high energy phosphates and phospholipid metabolism ratios. At least one prior 31p MRS study found temporal-frontal differences for high energy phosphates in persons with mild AD. The goal of the current study was to examine regional (i.e., frontal, temporal) 31p MRS ratios of mitochondrial function in a sample of older adults at-risk for AD. Given the high energy consumption in temporal lobes (i.e., hippocampus) and preferential age-related changes in frontal structure-function, we predicted 31p MRS ratios of mitochondrial function would be greater in temporal as compared to frontal regions.
Participants and Methods:The current study leveraged baseline neuroimaging data from an ongoing multisite study at the University of Florida and University of Arizona. Participants were older adults with memory complaints and a first-degree family history of AD [N = 70; mean [M] age [years] = 70.9, standard deviation [SD] =5.1; M education [years] = 16.2, SD = 2.2; M MoCA = 26.5, SD = 2.4; 61.4% female; 91.5% non-latinx white]. To achieve optimal sensitivity, we used a single voxel method to examine 31p MRS ratios (bilateral prefrontal and left temporal). Mitochondrial function was estimated by computing 5 ratios for each voxel: summed adenosine triphosphate to total pooled phosphorous (ATP/TP; momentary energy), ATP to inorganic phosphate (ATP/Pi; energy consumption), phosphocreatine to ATP (PCr/ATP; energy reserve), phosphocreatine to inorganic phosphate (PCr/Pi; oxidative phosphorylation), and phosphomonoesters to phosphodiesters (PME/PDE; cellular membrane turnover rate). All ratios were corrected for voxel size and cerebrospinal fluid fraction. Separate repeated measures analyses of variance controlling for scanner site differences (RM ANCOVAs) were performed.
Results:31p MRS ratios were unrelated to demographic characteristics and were not included as additional covariates in analyses. Results of separate RM ANCOVAs revealed all 31p MRS ratios of mitochondrial function were greater in left temporal relative to bilateral prefrontal voxel: ATP/TP (p < .001), ATP/Pi (p = .001), PCr/ATP (p = .004), PCr/Pi (p = .004), and PME/PDE (p = .017). Effect sizes (partial eta squared) ranged from 0.6-.20.
Conclusions:Consistent and extending one prior study, all 31p MRS ratios of mitochondrial function were greater in temporal as compared to frontal regions in older adults at-risk for AD. This may in part be related to the intrinsically high metabolic rate of the temporal region and preferential age-related changes in frontal structure-function. Alternatively, findings may reflect the influence of unaccounted factors (e.g., hemodynamics, auditory stimulation). Longitudinal study designs may inform whether patterns of mitochondrial function across different brain regions are present early in development, occur across the lifespan, or some combination. In turn, this may inform future studies examining differences in mitochondrial function (as measured using 31p MRS) in AD.
34 Machine Learning Predicts Time to Dementia Conversion in Cognitively Normal Subjects
- Emily E Brickell, Andrew Whitford, Anneliese Boettcher
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- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, p. 909
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Identification of pre-clinical Alzheimer’s disease (AD) is necessary for the development of future disease-modifying treatments, which would ideally target pre-clinical stages to mitigate functional loss. Despite advanced in biomarker development, clinical trials are still without a non-invasive and cost-effective means of identifying pre-symptomatic subjects who are at high risk for eventual conversion to AD. In previous work, we developed a machine learning algorithm using neuropsychological test scores and health history to identify subjects at high risk for eventual conversion. Here, we examine the performance of a similar algorithm in predicting the timing of that conversion in years.
Participants and Methods:Data were obtained from the National Alzheimer’s Coordination Center (NACC) Uniform Data Set (UDS) version 3.0. Subjects with normal cognition at baseline were used to train a multi-class Random Forest classifier to predict conversion to AD. Each subject could be classified as a short-, mid-, or long-term converter (0-3 years, 4 to 6 years, and 7 to 9 years, respectively) or as a non-converter, if no dementia diagnosis was given within ten years of baseline. Predictors included baseline demographics, basic medical history, and neuropsychological test results. Algorithms were evaluated using standard, cross-validated performance metrics.
Results:Multi-class Matthews correlation coefficient between predicted time to diagnosis and the ground truth averaged 0.26 +/- 0.06 across 100 cross validation splits. Prediction accuracy exceeded 0.67 in all cases, when computed for each class individually, and was greatest for the short-term (0.75) and nonconverter (0.78) classes.
Conclusions:Machine-learning algorithms applied to neuropsychological, demographic, and medical history information were able to predict the eventual timing of conversion to dementia in cognitively healthy adults significantly better than chance. Results were most accurate when predicting shorter time to conversion. Results illustrate the potential of this data analytic approach for targeted recruitment in clinical trials.
38 Fine Motor Skills in Pediatric Frontal Lobe Epilepsy are Associated with Executive Dysfunction and ADHD Symptomatology
- Moshe Maiman, Madison Berl, Jennifer I Koop, Donald J Bearden, Katrina Boyer, Crystal M Cooper, Amanda M Decrow, Priscilla H. Duong, Patricia Espe-Pfeifer, Marsha Gabriel, Elise Hodges, Kelly A McNally, Andrew Molnar, Emily Olsen, Kim E Ono, Kristina E Patrick, Brianna Paul, Jonathan Romain, Leigh N Sepeta, Rebecca LH Stilp, Greta N Wilkening, Mike Zaccariello, Frank Zelko, Clemente Vega, Trey Moore, Szimonetta Mulati, Phillip Pearl, Jeffrey Bolton, Alyssa Ailion
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- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 37-38
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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.
Participants and Methods: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.
Results: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).
Conclusions: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.