Neurophysiological Evidence for a Compensatory Activity during a Simple Oddball Task in Adolescents with Type 1 Diabetes Mellitus
Language English Country United States Media electronic-ecollection
Document type Journal Article
PubMed
30116745
PubMed Central
PMC6079416
DOI
10.1155/2018/8105407
Knihovny.cz E-resources
- MeSH
- Diabetes Mellitus, Type 1 physiopathology therapy MeSH
- Diabetic Retinopathy metabolism MeSH
- Evoked Potentials MeSH
- Glycated Hemoglobin analysis MeSH
- Hyperglycemia physiopathology MeSH
- Cognition MeSH
- Blood Glucose MeSH
- Humans MeSH
- Adolescent MeSH
- Brain physiopathology MeSH
- Neuropsychological Tests MeSH
- Motion MeSH
- Reaction Time * MeSH
- Case-Control Studies MeSH
- Evoked Potentials, Visual * MeSH
- Check Tag
- Humans MeSH
- Adolescent MeSH
- Male MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Glycated Hemoglobin A MeSH
- hemoglobin A1c protein, human MeSH Browser
- Blood Glucose MeSH
OBJECTIVE: The poor metabolic control in type 1 diabetes mellitus (T1D) has a negative impact on the developing brain. Hyperglycemia and glycemic fluctuations disrupt mainly executive functions. To assess a hypothesized deficit of the executive functions, we evaluated visual processing and reaction time in an oddball task. METHODS: Oddball visual event-related potentials (ERPs), reaction time, and pattern-reversal visual evoked potentials (VEPs) were examined in a cohort of twenty-two 12- to 18-year-old T1D patients without diabetic retinopathy at normal glycemia and in nineteen 10- to 21-year-old healthy controls. RESULTS: The P100 peak time of the VEPs was significantly prolonged in T1D patients compared with the control group (p < 0.017). In contrast to the deteriorated sensory response, the area under the curve of the P3b component of the ERPs was significantly larger (p = 0.035) in patients, while reaction time in the same task did not differ between groups (p = 0.713). CONCLUSIONS: The deterioration on a sensory level, enhanced activity during cognitive processing, and balanced behavioral response support the view that neuroplasticity counterbalances the neural impairment by enhanced cognitive processing to achieve normal behavioral performance in T1D adolescents.
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Diamond A. Executive functions. Annual Review of Psychology. 2013;64(1):135–168. doi: 10.1146/annurev-psych-113011-143750. PubMed DOI PMC
Duke D. C., Harris M. A. Executive function, adherence, and glycemic control in adolescents with type 1 diabetes: a literature review. Current Diabetes Reports. 2014;14(10):p. 532. doi: 10.1007/s11892-014-0532-y. PubMed DOI
Hood K. K., Peterson C. M., Rohan J. M., Drotar D. Association between adherence and glycemic control in pediatric type 1 diabetes: a meta-analysis. Pediatrics. 2009;124(6):e1171–e1179. doi: 10.1542/peds.2009-0207. PubMed DOI
Perez K. M., Patel N. J., Lord J. H., et al. Executive function in adolescents with type 1 diabetes: relationship to adherence, glycemic control, and psychosocial outcomes. Journal of Pediatric Psychology. 2017;42:636–646. doi: 10.1093/jpepsy/jsw093. PubMed DOI PMC
Nylander C., Toivonen H., Nasic S., Söderström U., Tindberg Y., Fernell E. Children and adolescents with type 1 diabetes and high HbA1c—a neurodevelopmental perspective. Acta Paediatrica. 2013;102(4):410–415. doi: 10.1111/apa.12128. PubMed DOI
Shehata G., Eltayeb A. Cognitive function and event-related potentials in children with type 1 diabetes mellitus. Journal of Child Neurology. 2010;25(4):469–474. doi: 10.1177/0883073809341667. PubMed DOI
Smith L. B., Kugler B. B., Lewin A. B., Duke D. C., Storch E. A., Geffken G. R. Executive functioning, parenting stress, and family factors as predictors of diabetes management in pediatric patients with type 1 diabetes using intensive regimens. Children's Health Care. 2014;43(3):234–252. doi: 10.1080/02739615.2013.839383. DOI
West R., Schwarb H., Johnson B. N. The influence of age and individual differences in executive function on stimulus processing in the oddball task. Cortex. 2010;46(4):550–563. doi: 10.1016/j.cortex.2009.08.001. PubMed DOI
Duncan C. C., Barry R. J., Connolly J. F., et al. Event-related potentials in clinical research: guidelines for eliciting, recording, and quantifying mismatch negativity, P300, and N400. Clinical Neurophysiology. 2009;120(11):1883–1908. doi: 10.1016/j.clinph.2009.07.045. PubMed DOI
Polich J., Herbst K. L. P300 as a clinical assay: rationale, evaluation, and findings. International Journal of Psychophysiology. 2000;38(1):3–19. doi: 10.1016/S0167-8760(00)00127-6. PubMed DOI
Polich J. Updating P300: an integrative theory of P3a and P3b. Clinical Neurophysiology. 2007;118(10):2128–2148. doi: 10.1016/j.clinph.2007.04.019. PubMed DOI PMC
World Medical Association. World Medical Association Declaration of Helsinki. Ethical principles for medical research involving human subjects. JAMA. 2013;310(20):2191–2194. doi: 10.1001/jama.2013.281053. PubMed DOI
Gorst C., Kwok C. S., Aslam S., et al. Long-term glycemic variability and risk of adverse outcomes: a systematic review and meta-analysis. Diabetes Care. 2015;38(12):2354–2369. doi: 10.2337/dc15-1188. PubMed DOI
Perantie D. C., Lim A., Wu J., et al. Effects of prior hypoglycemia and hyperglycemia on cognition in children with type 1 diabetes mellitus. Pediatric Diabetes. 2008;9(2):87–95. doi: 10.1111/j.1399-5448.2007.00274.x. PubMed DOI
Di Russo F., Pitzalis S., Spitoni G., et al. Identification of the neural sources of the pattern-reversal VEP. NeuroImage. 2005;24(3):874–886. doi: 10.1016/j.neuroimage.2004.09.029. PubMed DOI
Brainard D. H. The psychophysics toolbox. Spatial Vision. 1997;10(4):433–436. doi: 10.1163/156856897X00357. PubMed DOI
Odom J. V., Bach M., Brigell M., et al. ISCEV standard for clinical visual evoked potentials: (2016 update) Documenta Ophthalmologica. 2016;133(1):1–9. doi: 10.1007/s10633-016-9553-y. PubMed DOI
R Development Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing; 2017.
Broe R. Early risk stratification in pediatric type 1 diabetes. Acta Ophthalmologica. 2015;93(5):p. 490. doi: 10.1111/aos.12761. PubMed DOI
Robin X., Turck N., Hainard A., et al. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics. 2011;12(1):p. 77. doi: 10.1186/1471-2105-12-77. PubMed DOI PMC
Youden W. J. Index for rating diagnostic tests. Cancer. 1950;3(1):32–35. doi: 10.1002/1097-0142(1950)3:1<32::AID-CNCR2820030106>3.0.CO;2-3. PubMed DOI
Ryan C. M., van Duinkerken E., Rosano C. Neurocognitive consequences of diabetes. The American Psychologist. 2016;71(7):563–576. doi: 10.1037/a0040455. PubMed DOI
Cato A., Hershey T. Cognition and type 1 diabetes in children and adolescents. Diabetes Spectrum. 2016;29(4):197–202. doi: 10.2337/ds16-0036. PubMed DOI PMC
Überall M., Renner C., Edl S., Parzinger E., Wenzel D. VEP and ERP abnormalities in children and adolescents with prepubertal onset of insulin-dependent diabetes mellitus. Neuropediatrics. 1996;27(2):88–93. doi: 10.1055/s-2007-973755. PubMed DOI
Cameron F. J., Scratch S. E., Nadebaum C., et al. Neurological consequences of diabetic ketoacidosis at initial presentation of type 1 diabetes in a prospective cohort study of children. Diabetes Care. 2014;37(6):1554–1562. doi: 10.2337/dc13-1904. PubMed DOI PMC
Gallardo-Moreno G. B., Gonzalez-Garrido A. A., Gudayol-Ferre E., Guardia-Olmos J. Type 1 diabetes modifies brain activation in young patients while performing visuospatial working memory tasks. Journal of Diabetes Research. 2015;2015:9. doi: 10.1155/2015/703512.703512 PubMed DOI PMC
Wessels A. M., Rombouts S. A. R. B., Simsek S., et al. Microvascular disease in type 1 diabetes alters brain activation: a functional magnetic resonance imaging study. Diabetes. 2006;55(2):334–340. doi: 10.2337/diabetes.55.02.06.db05-0680. PubMed DOI
Audoin B., Ibarrola D., Ranjeva J. P., et al. Compensatory cortical activation observed by fMRI during a cognitive task at the earliest stage of multiple sclerosis. Human Brain Mapping. 2003;20(2):51–58. doi: 10.1002/hbm.10128. PubMed DOI PMC
Sciberras-Lim E. T., Lambert A. J. Attentional orienting and dorsal visual stream decline: review of behavioral and EEG studies. Frontiers in Aging Neuroscience. 2017;9:p. 246. doi: 10.3389/fnagi.2017.00246. PubMed DOI PMC
Di Russo F., Berchicci M., Bozzacchi C., Perri R. L., Pitzalis S., Spinelli D. Beyond the “Bereitschaftspotential”: action preparation behind cognitive functions. Neuroscience & Biobehavioral Reviews. 2017;78:57–81. doi: 10.1016/j.neubiorev.2017.04.019. PubMed DOI
Goethals E. R., de Wit M., van Broeck N., et al. Child and parental executive functioning in type 1 diabetes: their unique and interactive role toward treatment adherence and glycemic control. Pediatric Diabetes. 2018;19(3):520–526. doi: 10.1111/pedi.12552. PubMed DOI
Wasserman R. M., Hilliard M. E., Schwartz D. D., Anderson B. J. Practical strategies to enhance executive functioning and strengthen diabetes management across the lifespan. Current Diabetes Reports. 2015;15(8):p. 52. doi: 10.1007/s11892-015-0622-5. PubMed DOI PMC
Toplak M. E., West R. F., Stanovich K. E. Practitioner review: do performance-based measures and ratings of executive function assess the same construct? Journal of Child Psychology and Psychiatry. 2013;54(2):131–143. doi: 10.1111/jcpp.12001. PubMed DOI