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Shepard E, Sweeney C, Thompson L, Jacobs S, Grimm J, Weyandt LL. Effectiveness of executive functioning training among heterogeneous adolescent samples: A systematic review. APPLIED NEUROPSYCHOLOGY. CHILD 2023; 12:327-343. [PMID: 35914534 DOI: 10.1080/21622965.2022.2106436] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The aim of the present systematic review was to discuss the reported efficacy of executive functioning training techniques among adolescents. A systematic review of the literature was conducted to retrieve and consolidate findings from articles evaluating executive functioning training techniques among adolescents. A total of 26 articles were located that examined the role of executive functioning training techniques among adolescents (age 10-19 years). Articles retrieved enabled comparison across psychiatric and medical diagnoses including attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), as well as adolescents with physical health concerns. Results revealed that among typically developing adolescents, executive functioning training was non-significant or yielded small effect size improvements in executive functioning as measured by behavioral and neuroimaging tasks among 62.5% of studies reviewed. In contrast, in those with medical conditions, ASD, ADHD, and conduct disorder, all but two studies reviewed yielded a medium to large effect size, supporting the effectiveness of EF training. Future research is needed to identify the long-term efficacy of these treatments, as well as their generalizability to real-world conditions.
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Affiliation(s)
- Emily Shepard
- Department of Psychology, University of Rhode Island, Kingston, Rhode Island, USA
| | - Caroline Sweeney
- Department of Psychology, University of Rhode Island, Kingston, Rhode Island, USA
| | - Lauren Thompson
- Interdisciplinary Neuroscience Program, University of Rhode Island, Kingston, Rhode Island, USA
| | - Sophie Jacobs
- Department of Psychology, University of Rhode Island, Kingston, Rhode Island, USA
| | - Jessica Grimm
- Department of Psychology, University of Rhode Island, Kingston, Rhode Island, USA
| | - Lisa L Weyandt
- Department of Psychology, Interdisciplinary Neuroscience Program, University of Rhode Island, Kingston, Rhode Island, USA
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Chai WJ, Abd Hamid AI, Omar H, Abdul Rahman MR, Fitzrol DN, Idris Z, Ghani ARI, Wan Mohamad WNA, Mustafar F, Hanafi MH, Kandasamy R, Abdullah MZ, Amaruchkul K, Valdes-Sosa PA, Bringas-Vega ML, Biswal B, Songsiri J, Yaacob H, Ibrahim H, Sumari P, Noh NA, Musa KI, Ahmad AH, Azman A, Jamir Singh PS, Othman A, Abdullah JM. Neural alterations in working memory of mild-moderate TBI: An fMRI study in Malaysia. J Neurosci Res 2022; 100:915-932. [PMID: 35194817 DOI: 10.1002/jnr.25023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 10/10/2021] [Accepted: 12/31/2021] [Indexed: 02/05/2023]
Abstract
Working memory (WM) encompasses crucial cognitive processes or abilities to retain and manipulate temporary information for immediate execution of complex cognitive tasks in daily functioning such as reasoning and decision-making. The WM of individuals sustaining traumatic brain injury (TBI) was commonly compromised, especially in the domain of WM. The current study investigated the brain responses of WM in a group of participants with mild-moderate TBI compared to their healthy counterparts employing functional magnetic resonance imaging. All consented participants (healthy: n = 26 and TBI: n = 15) performed two variations of the n-back WM task with four load conditions (0-, 1-, 2-, and 3-back). The respective within-group effects showed a right hemisphere-dominance activation and slower reaction in performance for the TBI group. Random-effects analysis revealed activation difference between the two groups in the right occipital lobe in the guided n-back with cues, and in the bilateral occipital lobe, superior parietal region, and cingulate cortices in the n-back without cues. The left middle frontal gyrus was implicated in the load-dependent processing of WM in both groups. Further group analysis identified that the notable activation changes in the frontal gyri and anterior cingulate cortex are according to low and high loads. Though relatively smaller in scale, this study was eminent as it clarified the neural alterations in WM in the mild-moderate TBI group compared to healthy controls. It confirmed the robustness of the phenomenon in TBI with the reproducibility of the results in a heterogeneous non-Western sample.
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Affiliation(s)
- Wen Jia Chai
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia.,Brain and Behaviour Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Aini Ismafairus Abd Hamid
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia.,Brain and Behaviour Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia.,Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Hazim Omar
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia.,Brain and Behaviour Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia.,Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Muhammad Riddha Abdul Rahman
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia.,Brain and Behaviour Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia.,School of Medical Imaging, Faculty of Health Sciences, Universiti Sultan Zainal Abidin, Kuala Nerus, Malaysia
| | - Diana Noma Fitzrol
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia.,Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Zamzuri Idris
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia.,Brain and Behaviour Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia.,Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Abdul Rahman Izaini Ghani
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia.,Brain and Behaviour Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia.,Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Wan Nor Azlen Wan Mohamad
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia.,Brain and Behaviour Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia.,Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Faiz Mustafar
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia.,Brain and Behaviour Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia.,Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Muhammad Hafiz Hanafi
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia.,Brain and Behaviour Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia.,Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | | | - Mohd Zaid Abdullah
- School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Nibong Tebal, Malaysia
| | - Kannapha Amaruchkul
- Graduate School of Applied Statistics, National Institute of Development Administration (NIDA), Bangkok, Thailand
| | - Pedro A Valdes-Sosa
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,The Cuban Neurosciences Center, La Habana, Cuba
| | - Maria L Bringas-Vega
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,The Cuban Neurosciences Center, La Habana, Cuba
| | - Bharat Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, New Jersey, USA
| | - Jitkomut Songsiri
- EE410 Control Systems Laboratory, Department of Electrical Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand
| | - Hamwira Yaacob
- Department of Computer Science, Kulliyyah of Information and Communication Technology, Kuala Lumpur, International Islamic University Malaysia, Kuala Lumpur, Malaysia
| | - Haidi Ibrahim
- Brain and Behaviour Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia.,School of Electrical and Electronic Engineering, Universiti Sains Malaysia, Nibong Tebal, Malaysia
| | - Putra Sumari
- School of Computer Sciences, Universiti Sains Malaysia, Pulau Pinang, Malaysia
| | - Nor Azila Noh
- Department of Medical Science 1, Faculty of Medicine and Health Sciences, Universiti Sains Islam Malaysia, Nilai, Malaysia
| | - Kamarul Imran Musa
- Department of Community Medicine, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Asma Hayati Ahmad
- Department of Physiology, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Azlinda Azman
- School of Medical Imaging, Faculty of Health Sciences, Universiti Sultan Zainal Abidin, Kuala Nerus, Malaysia.,School of Social Sciences, Universiti Sains Malaysia, Pulau Pinang, Malaysia
| | | | - Azizah Othman
- Department of Psychiatry, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia
| | - Jafri Malin Abdullah
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia.,Brain and Behaviour Cluster, School of Medical Sciences, Universiti Sains Malaysia, Kota Bharu, Malaysia.,Hospital Universiti Sains Malaysia, Universiti Sains Malaysia, Kota Bharu, Malaysia
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Moore AL, Carpenter DM, James RL, Miller TM, Moore JJ, Disbrow EA, Ledbetter CR. Neuroimaging and Neuropsychological Outcomes Following Clinician-Delivered Cognitive Training for Six Patients With Mild Brain Injury: A Multiple Case Study. Front Hum Neurosci 2020; 14:229. [PMID: 32670040 PMCID: PMC7326946 DOI: 10.3389/fnhum.2020.00229] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Accepted: 05/25/2020] [Indexed: 12/12/2022] Open
Abstract
Nearly half of all mild brain injury sufferers experience long-term cognitive impairment, so an important goal in rehabilitation is to address their multiple cognitive deficits to help them return to prior levels of functioning. Cognitive training, or the use of repeated mental exercises to enhance cognition, is one remediation method for brain injury. The primary purpose of this hypothesis-generating pilot study was to explore the statistical and clinical significance of cognitive changes and transfer of training to real-life functioning following 60 h of Brain Booster, a clinician-delivered cognitive training program, for six patients with mild traumatic brain injury (TBI) or non-traumatic acquired brain injury (ABI). The secondary purpose was to explore changes in functional connectivity and neural correlates of cognitive test gains following the training. We used a multiple case study design to document significant changes in cognitive test scores, overall IQ score, and symptom ratings; and we used magnetic resonance imaging (MRI) to explore trends in functional network connectivity and neural correlates of cognitive change. All cognitive test scores showed improvement with statistically significant changes on five of the seven measures (long-term memory, processing speed, reasoning, auditory processing, and overall IQ score). The mean change in IQ score was 20 points, from a mean of 108 to a mean of 128. Five themes emerged from the qualitative data analysis including improvements in cognition, mood, social identity, performance, and Instrumental Activities of Daily Living (IADLs). With MRI, we documented significant region-to-region changes in connectivity following cognitive training including those involving the cerebellum and cerebellar networks. We also found significant correlations between changes in IQ score and change in white matter integrity of bilateral corticospinal tracts (CST) and the left uncinate fasciculus. This study adds to the growing body of literature examining the effects of cognitive training for mild TBI and ABI, and to the collection of research on the benefits of cognitive training in general. Clinical Trial Registration: www.ClinicalTrials.gov, identifier NCT02918994.
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Affiliation(s)
- Amy Lawson Moore
- Department of Psychology, Gibson Institute of Cognitive Research, Colorado Springs, CO, United States
| | - Dick M. Carpenter
- College of Education, University of Colorado Colorado Springs, Colorado Springs, CO, United States
| | | | - Terissa Michele Miller
- Department of Psychology, Gibson Institute of Cognitive Research, Colorado Springs, CO, United States
| | - Jeffrey J. Moore
- School of Nursing, Colorado State University-Pueblo, Pueblo, CO, United States
| | - Elizabeth A. Disbrow
- Department of Neurology, Louisiana State University Health Sciences Center, Shreveport, LA, United States
- Louisiana State University Health Sciences Center, Center for Brain Health, Shreveport, LA, United States
| | - Christina R. Ledbetter
- Louisiana State University Health Sciences Center, Center for Brain Health, Shreveport, LA, United States
- Department of Neurosurgery, Louisiana State University Health Sciences Center, Shreveport, LA, United States
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Poudel GR, Dominguez D JF, Verhelst H, Vander Linden C, Deblaere K, Jones DK, Cerin E, Vingerhoets G, Caeyenberghs K. Network diffusion modeling predicts neurodegeneration in traumatic brain injury. Ann Clin Transl Neurol 2020; 7:270-279. [PMID: 32105414 PMCID: PMC7086000 DOI: 10.1002/acn3.50984] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Accepted: 12/10/2019] [Indexed: 02/03/2023] Open
Abstract
Objective Traumatic brain injury (TBI) is a heterogeneous disease with multiple neurological deficits that evolve over time. It is also associated with an increased incidence of neurodegenerative diseases. Accordingly, clinicians need better tools to predict a patient’s long‐term prognosis. Methods Diffusion‐weighted and anatomical MRI data were collected from 17 adolescents (mean age = 15y8mo) with moderate‐to‐severe TBI and 19 healthy controls. Using a network diffusion model (NDM), we examined the effect of progressive deafferentation and gray matter thinning in young TBI patients. Moreover, using a novel automated inference method, we identified several injury epicenters in order to determine the neural degenerative patterns in each TBI patient. Results We were able to identify the subject‐specific patterns of degeneration in each patient. In particular, the hippocampus, temporal cortices, and striatum were frequently found to be the epicenters of degeneration across the TBI patients. Orthogonal transformation of the predicted degeneration, using principal component analysis, identified distinct spatial components in the temporal–hippocampal network and the cortico‐striatal network, confirming the vulnerability of these networks to injury. The NDM model, best predictive of the degeneration, was significantly correlated with time since injury, indicating that NDM can potentially capture the pathological progression in the chronic phase of TBI. Interpretation These findings suggest that network spread may help explain patterns of distant gray matter thinning, which would be consistent with Wallerian degeneration of the white matter connections (i.e., “diaschisis”) from diffuse axonal injuries and multifocal contusive injuries, and the neurodegenerative patterns of abnormal protein aggregation and transmission, which are hallmarks of brain changes in TBI. NDM approaches could provide highly subject‐specific biomarkers relevant for disease monitoring and personalized therapies in TBI.
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Affiliation(s)
- Govinda R Poudel
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC, Australia
| | - Juan F Dominguez D
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Burwood, VIC, Australia
| | - Helena Verhelst
- Department of Experimental Psychology, Faculty of Psychology and Educational Sciences, Ghent University, Ghent, Oost-Vlaanderen, Belgium
| | | | - Karel Deblaere
- Department of Neuroradiology, Ghent University Hospital, Ghent, Oost-Vlaanderen, Belgium
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, Wales, United Kingdom
| | - Ester Cerin
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC, Australia
| | - Guy Vingerhoets
- Department of Experimental Psychology, Faculty of Psychology and Educational Sciences, Ghent University, Ghent, Oost-Vlaanderen, Belgium
| | - Karen Caeyenberghs
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Burwood, VIC, Australia
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