Displaying all 8 publications

Abstract:
Sort:
  1. Manan HA, Franz EA, Yahya N
    Neuroradiology, 2020 Mar;62(3):353-367.
    PMID: 31802156 DOI: 10.1007/s00234-019-02322-w
    PURPOSE: Functional MRI (fMRI) can be employed to non-invasively localize brain regions involved in functional areas of language in patients with brain tumour, for applications including pre-operative mapping. The present systematic review was conducted to explore prevalence of different language paradigms utilised in conjunction with fMRI approaches for pre-operative mapping, with the aim of assessing their effectiveness and suitability.

    METHODS: A systematic literature search of brain tumours in the context of fMRI methods applied to pre-operative mapping for language functional areas was conducted using PubMed/MEDLINE and Scopus electronic database following PRISMA guidelines. The article search was conducted between the earliest record and March 1, 2019. References and citations were checked in Google Scholar database.

    RESULTS: Twenty-nine independent studies were identified, comprising 1031 adult participants with 976 patients characterised with different types and sizes of brain tumours, and the remaining 55 being healthy controls. These studies evaluated functional language areas in patients with brain tumours prior to surgical interventions using language-based fMRI. Results demonstrated that 86% of the studies used a Word Generation Task (WGT) to evoke functional language areas during pre-operative mapping. Fifty-seven percent of the studies that used language-based paradigms in conjunction with fMRI as a pre-operative mapping tool were in agreement with intra-operative results of language localization.

    CONCLUSIONS: WGT was most commonly utilised and is proposed as a suitable and useful technique for a language-based paradigm fMRI for pre-operative mapping. However, based on available evidence, WGT alone is not sufficient. We propose a combination and convergence paradigms for a more sensitive and specific map of language function for pre-operative mapping. A standard guideline for clinical applications should be established.

    Matched MeSH terms: Verbal Behavior*
  2. Hunt EA, Cruz-Eng H, Bradshaw JH, Hodge M, Bortner T, Mulvey CL, et al.
    Resuscitation, 2015 Jan;86:1-5.
    PMID: 25457379 DOI: 10.1016/j.resuscitation.2014.10.007
    Observations of cardiopulmonary arrests (CPAs) reveal concerning patterns when clinicians identify a problem, (e.g. loss of pulse) but do not immediately initiate appropriate therapy (e.g. compressions) resulting in delays in life saving therapy.
    Matched MeSH terms: Verbal Behavior
  3. Simons RC
    J. Nerv. Ment. Dis., 1980 Apr;168(4):195-206.
    PMID: 7365478
    Latah is a culture-bound syndrome from Malaysia and Indonesia. Persons exhibiting the Latah syndrome respond to minimal stimuli with exaggerated startles, often exclaimning normally inhibited sexually denotative words. Sometimes Latahs after being startled obey the commands or imitate the actions of persons about them. Most episodes of Latah are intentionally provoked for the amusement of onlookers. Similar sets of interactive behaviors have been reported from genetically and culturally unrelated populations (e.g., Bantu, Ainu, and French Canadians). Since competent anthropological investigators have shown Latah to be intimately tied to specific factors in the cultural systems of the Southeast Asian societies in which it is found, its occurrence elswhere has been considered paradoxical. New data, including films and videotapes of hyperstartling persons from Malaysia, the Philippines, Japan, and the United States, suggest a model capable of resolving the apparent paradox by showing how the various forms of latah are culture-specific exploitations of a neurophysiological potential shared by humans and other mammals. Latah provides an especially revealing example of the complex ways in which neurophysiological, experiential, and cultural variables interact to produce a strongly marked and phenomenon.
    Matched MeSH terms: Verbal Behavior
  4. Rahman MM, Usman OL, Muniyandi RC, Sahran S, Mohamed S, Razak RA
    Brain Sci, 2020 Dec 07;10(12).
    PMID: 33297436 DOI: 10.3390/brainsci10120949
    Autism Spectrum Disorder (ASD), according to DSM-5 in the American Psychiatric Association, is a neurodevelopmental disorder that includes deficits of social communication and social interaction with the presence of restricted and repetitive behaviors. Children with ASD have difficulties in joint attention and social reciprocity, using non-verbal and verbal behavior for communication. Due to these deficits, children with autism are often socially isolated. Researchers have emphasized the importance of early identification and early intervention to improve the level of functioning in language, communication, and well-being of children with autism. However, due to limited local assessment tools to diagnose these children, limited speech-language therapy services in rural areas, etc., these children do not get the rehabilitation they need until they get into compulsory schooling at the age of seven years old. Hence, efficient approaches towards early identification and intervention through speedy diagnostic procedures for ASD are required. In recent years, advanced technologies like machine learning have been used to analyze and investigate ASD to improve diagnostic accuracy, time, and quality without complexity. These machine learning methods include artificial neural networks, support vector machines, a priori algorithms, and decision trees, most of which have been applied to datasets connected with autism to construct predictive models. Meanwhile, the selection of features remains an essential task before developing a predictive model for ASD classification. This review mainly investigates and analyzes up-to-date studies on machine learning methods for feature selection and classification of ASD. We recommend methods to enhance machine learning's speedy execution for processing complex data for conceptualization and implementation in ASD diagnostic research. This study can significantly benefit future research in autism using a machine learning approach for feature selection, classification, and processing imbalanced data.
    Matched MeSH terms: Verbal Behavior
  5. Shadli RM, Pieter MS, Yaacob MJ, Rashid FA
    Brain Inj, 2011;25(6):596-603.
    PMID: 21534737 DOI: 10.3109/02699052.2011.572947
    The influence of apolipoprotein (APOE) on neuropsychological outcome was investigated in 19 patients (25.79 ± 7.22 years) with mild-to-moderate traumatic brain injury and 14 matched healthy control subjects (27.43 ± 6.65 years).
    Matched MeSH terms: Verbal Behavior/physiology
  6. Smith TO, Neal SR, Peryer G, Sheehan KJ, Tan MP, Myint PK
    Int Psychogeriatr, 2019 10;31(10):1491-1498.
    PMID: 30522546 DOI: 10.1017/S1041610218002065
    OBJECTIVES: To determine the relationship between falls and deficits in specific cognitive domains in older adults.

    DESIGN: An analysis of the English Longitudinal Study of Ageing (ELSA) cohort.

    SETTING: United Kingdom community-based.

    PARTICIPANTS: 5197 community-dwelling older adults recruited to a prospective longitudinal cohort study.

    MEASUREMENTS: Data on the occurrence of falls and number of falls, which occurred during a 12-month follow-up period, were assessed against the specific cognitive domains of memory, numeracy skills, and executive function. Binomial logistic regression was performed to evaluate the association between each cognitive domain and the dichotomous outcome of falls in the preceding 12 months using unadjusted and adjusted models.

    RESULTS: Of the 5197 participants included in the analysis, 1308 (25%) reported a fall in the preceding 12 months. There was no significant association between the occurrence of a fall and specific forms of cognitive dysfunction after adjusting for self-reported hearing, self-reported eyesight, and functional performance. After adjustment, only orientation (odds ratio [OR]: 0.80; 95% confidence intervals [CI]: 0.65-0.98, p = 0.03) and verbal fluency (adjusted OR: 0.98; 95% CI: 0.96-1.00; p = 0.05) remained significant for predicting recurrent falls.

    CONCLUSIONS: The cognitive phenotype rather than cognitive impairment per se may predict future falls in those presenting with more than one fall.

    Matched MeSH terms: Verbal Behavior*
  7. Normala I, Abdul HA, Azlin B, Nik Ruzyanei NJ, Hazli Z, Shah SA
    Med J Malaysia, 2010 Sep;65(3):199-203.
    PMID: 21939168
    This is a cross sectional comparison study to assess executive function and attention span in euthymic patients with bipolar 1 disorder. It compares the performance of these two cognitive domains in 40 patients with bipolar 1 disorder to that of 40 healthy normal subjects using Trail Making (TMT), Digit Span (Forward and Backward) and Verbal Fluency (VF) tests. The association between demographic, clinical characteristics and performance in all tests were examined. Patients with bipolar illness showed significant impairment with moderate to large effect sizes (VF = 0.67, TMT A = 0.52, TMT B = 0.81, Digit Forward = 0.97, Digit backward = 1.10) in all tasks of executive and attention functioning. These impairments are observed in the absence of active mood symptoms while duration and severity of illness are not found to have an effect on both cognitive domains. Medications received by patients with bipolar disorder have significant association with performance on executive tasks. The results of this study add on to the existing global evidence of cognitive impairment in bipolar illness despite its cross cultural differences. Its presence in the absence of mania, depression or mixed episode indicates that cognitive impairment is stable even after symptoms recovery.
    Matched MeSH terms: Verbal Behavior
  8. Hartog J
    Ment Hyg, 1971 Jan;55(1):35-44.
    PMID: 5549644
    Matched MeSH terms: Verbal Behavior
Related Terms
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links