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1.
Iran J Child Neurol ; 16(1): 39-50, 2022.
Article in English | MEDLINE | ID: mdl-35222656

ABSTRACT

OBJECTIVES: The profile of mental disorders has been changing over time. The aim of this study was to investigate the prevalence of mental disorders in children and adolescents in the Lorestan province of Iran. MATERIALS & METHODS: This community-based cross-sectional study was done on 1001 children and adolescents aged 6-18 years from Lorestan province randomly selected by multistage cluster sampling method. Children and their parents were interviewed using the Kiddie-Sads-Present and Lifetime Version (K-SADS-PL). Also, the comorbidities of psychiatric disorders were evaluated. RESULTS: According to obtained results, 25.1% of participants were diagnosed to have at least one psychiatric disorder. The prevalence of psychiatric disorders was not significantly different between the two sexes (OR=0.876, P=0.378) and three age groups (P>0.05). this prevalence was significantly higher in rural areas than in urban areas (OR= 1.997, P=0) and was significantly lower in children of fathers with a high school diploma or higher education compared to children of less-educated fathers (P<0.05). On contrary, it was significantly more prevalent in children of mothers with high school and bachelor's degrees compared to illiterate mothers. (p<0.05). The most prevalent psychiatric disorders were oppositional defiant disorder (ODD) (5.9%), separation anxiety disorder (5.3%), and depressive disorders (5%). The most prevalent groups of psychiatric disorders included anxiety disorders (11.2%), behavioral disorders (9.4%), and mood disorders (5%). Behavioral disorders were highly comorbid with anxiety disorders (20.7%). CONCLUSION: Mental disorders affect a high proportion of children and adolescents in Lorestan province. There is a need for psychiatric facilities to provide for the needs of families to child mental health services.

2.
J Neurophysiol ; 111(10): 1986-2000, 2014 May.
Article in English | MEDLINE | ID: mdl-24572093

ABSTRACT

Electrophysiology in primates has implicated long-range neural coherence as a potential mechanism for enhancing sensory detection. To test whether local synchronization and long-range neural coherence support detection performance in rats, we recorded local field potentials (LFPs) in frontal and parietal cortex while rats performed an auditory detection task. We observed significantly elevated power at multiple low frequencies (<15 Hz) preceding the target beep when the animal failed to respond to the signal (misses), in both frontal and parietal cortex. In terms of long-range coherence, we observed significantly more frontal-parietal coherence in the beta band (15-30 Hz) before the signal on misses compared with hits. This effect persisted after regressing away linear trends in the coherence values during a session, showing that the excess frontal-parietal beta coherence prior to misses cannot be explained by slow motivational changes during a session. In addition, a trend toward higher low-frequency (<15 Hz) coherence prior to miss trials compared with hits became highly significant when we rereferenced the LFPs to the mean voltage on each recording array, suggesting that the results are specific to our frontal and parietal areas. These results do not support a role for long-range frontal-parietal coherence or local synchronization in facilitating the detection of external stimuli. Rather, they extend to long-range frontal-parietal coherence previous findings that correlate local synchronization of low-frequency (<15 Hz) oscillations with inattention to external stimuli and synchronization of beta rhythms (15-30 Hz) with voluntary or involuntary prolongation of the current cognitive or motor state.


Subject(s)
Auditory Perception/physiology , Frontal Lobe/physiology , Parietal Lobe/physiology , Signal Detection, Psychological/physiology , Acoustic Stimulation , Animals , Beta Rhythm , Cortical Synchronization , Electrodes, Implanted , Male , Motivation , Neuropsychological Tests , Rats, Long-Evans , Signal Processing, Computer-Assisted , Task Performance and Analysis , Time Factors
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