How Is Temporal Processing Affected in Children with Attention-deficit/hyperactivity Disorder?

Suarez, Isabel; Aragón, Carlos De Los Reyes; Diaz, Elisa; Iglesias, Tania; Barceló, Ernesto; Vélez, Jorge Íván Bonilla; Casini, Laurence

doi:10.1080/87565641.2020.1764566

Cited by 10 publications

(5 citation statements)

References 64 publications

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“…According to a review by Toplak et al (2006), most of the studies suggested timeprocessing alterations in ADHD in the form of higher discrimination thresholds or more discrepant reproductions (typically underestimations). Consistent with these findings, a recent study reported greater difficulties in discrimination between short and long time stimuli as well as under-reproduced time intervals in children with ADHD ( Suarez et al, 2020 ). According to Carelli and Wiberg ( 2012 ), such impairments are found in studies with duration discrimination or duration reproduction but not in verbal time estimation.…”

Section: Introductionsupporting

confidence: 63%

Prospective and Retrospective Verbal Time Estimation in Children with ADHD

Walg¹,

Prior²

2021

AdvCognPsychol

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There is increasing evidence that timing deficits represent a primary cause of key symptoms in ADHD. However, results in experiments on timing may vary with different methods of assessing timing competencies. The present study directly compared two central paradigms, namely, prospective and retrospective time estimation in children with ( n = 30) and without ( n = 29) ADHD. In both conditions, durations were estimated considerably longer by children with ADHD. Children with ADHD significantly overestimated the real duration of the task compared to children without ADHD in the retrospective but not in the prospective condition. In general, prospective estimates were more accurate than retrospective ones. The findings corroborate the essential role that timing deficits and a faster internal clock play in ADHD. Furthermore, the results demonstrate the importance of careful differentiation between prospective and retrospective time estimation.

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Section: Introductionsupporting

confidence: 63%

Prospective and Retrospective Verbal Time Estimation in Children with ADHD

Walg¹,

Prior²

2021

AdvCognPsychol

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“…Currently, our research group studies the differential expression of ncRNA in subjects with Alzheimer's disease compared to healthy subjects. We also plan to study the exosomal load in patients with attention deficit-hyperactivity disorder [359][360][361][362][363][364] and HIV and Huntington's disease [365,366]. Funding: This study was financed by MINCIENCIAS, project "Nuevos ARN no codificantes exosomales y su papel en la patogénesis de la Enfermedad de Alzheimer", code 121584468097, grant 844/2019, contract 416-2020, awarded to Grupo en Genética y Medicina Molecular and Grupo de Productividad y Competitividad, Universidad del Norte, Barranquilla, Colombia.…”

Section: Discussionmentioning

confidence: 99%

Exosomes: Potential Disease Biomarkers and New Therapeutic Targets

et al. 2021

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Exosomes are extracellular vesicles released by cells, both constitutively and after cell activation, and are present in different types of biological fluid. Exosomes are involved in the pathogenesis of diseases, such as cancer, neurodegenerative diseases, pregnancy disorders and cardiovascular diseases, and have emerged as potential non-invasive biomarkers for the detection, prognosis and therapeutics of a myriad of diseases. In this review, we describe recent advances related to the regulatory mechanisms of exosome biogenesis, release and molecular composition, as well as their role in health and disease, and their potential use as disease biomarkers and therapeutic targets. In addition, the advantages and disadvantages of their main isolation methods, characterization and cargo analysis, as well as the experimental methods used for exosome-mediated drug delivery, are discussed. Finally, we present potential perspectives for the use of exosomes in future clinical practice.

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“…We argue that future genetic studies of ADHD may greatly benefit from our findings. In fact, such studies could use the severity of symptoms to elucidate how individuals with symptoms in different domains-inattention, hyperactivity, impulsivity-perform neuropsychological tasks (i.e., measures of working memory, cognitive function, and executive function) (Jimenez-Figueroa et al, 2017;Pineda-Alhucema et al, 2018;Suarez et al, 2020), and to determine the contribution to ADHD severity of genetic variants that confer susceptibility in Caucasian populations (Demontis et al, 2019). Although these candidate variants have not been replicated in genome-wide analyzes, their utility as risk variants for ADHD needs further investigation.…”

Section: Discussionmentioning

confidence: 99%

Machine Learning Prediction of ADHD Severity: Association and Linkage to ADGRL3, DRD4, and SNAP25

et al. 2021

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Objective: To investigate whether single nucleotide polymorphisms (SNPs) in the ADGRL3, DRD4, and SNAP25 genes are associated with and predict ADHD severity in families from a Caribbean community. Method: ADHD severity was derived using latent class cluster analysis of DSM-IV symptomatology. Family-based association tests were conducted to detect associations between SNPs and ADHD severity latent phenotypes. Machine learning algorithms were used to build predictive models of ADHD severity based on demographic and genetic data. Results: Individuals with ADHD exhibited two seemingly independent latent class severity configurations. SNPs harbored in DRD4, SNAP25, and ADGRL3 showed evidence of linkage and association to symptoms severity and a potential pleiotropic effect on distinct domains of ADHD severity. Predictive models discriminate severe from non-severe ADHD in specific symptom domains. Conclusion: This study supports the role of DRD4, SNAP25, and ADGRL3 genes in outlining ADHD severity, and a new prediction framework with potential clinical use.

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How Is Temporal Processing Affected in Children with Attention-deficit/hyperactivity Disorder?

Cited by 10 publications

References 64 publications

Prospective and Retrospective Verbal Time Estimation in Children with ADHD

Prospective and Retrospective Verbal Time Estimation in Children with ADHD

Exosomes: Potential Disease Biomarkers and New Therapeutic Targets

Machine Learning Prediction of ADHD Severity: Association and Linkage to ADGRL3, DRD4, and SNAP25

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