Whole Brain Child Epub 11 [Extra Quality]

Whole Brain Child Epub 11 [Extra Quality]

Whole Brain Child Epub 11 >>> https://ssurll.com/2sYz4n

Obesity, as compared to normal weight, is associated with detectable structural differences in the brain. To the best of our knowledge, no previous study has examined the association of physical fitness with gray matter volume in overweight/obese children using whole brain analyses. Thus, the aim of this study was to examine the association between the key components of physical fitness (i.e. cardiorespiratory fitness, speed-agility and muscular fitness) and brain structural volume, and to assess whether fitness-related changes in brain volumes are related to academic performance in overweight/obese children. A total of 101 overweight/obese children aged 8-11 years were recruited from Granada, Spain. The physical fitness components were assessed following the ALPHA health-related fitness test battery. T1-weighted images were acquired with a 3.0 T S Magnetom Tim Trio system. Gray matter tissue was calculated using Diffeomorphic Anatomical Registration Through Exponentiated Lie algebra (DARTEL). Academic performance was assessed by the Batería III Woodcock-Muñoz Tests of Achievement. All analyses were controlled for sex, peak high velocity offset, parent education, body mass index and total brain volume. The statistical threshold was calculated with AlphaSim and further Hayasaka adjusted to account for the non-isotropic smoothness of structural images. The main results showed that higher cardiorespiratory fitness was related to greater gray matter volumes (P < 0.001, k = 64) in 7 clusters with β ranging from 0.493 to 0.575; specifically in frontal regions (i.e. premotor cortex and supplementary motor cortex), subcortical regions (i.e. hippocampus and caudate), temporal regions (i.e. inferior temporal gyrus and parahippocampal gyrus) and calcarine cortex. Three of these regions (i.e. premotor cortex, supplementary motor cortex and hippocampus) were related to better academic performance (β ranging from 0.211 to 0.352; all P < 0.05). Higher speed-agility was associated with greater gray matter volumes (P < 0.001, k = 57) in 2 clusters (i.e. the inferior frontal gyrus and the superior temporal gyrus) with β ranging from 0.564 to 0.611. Both clusters were related to better academic performance (β ranging from 0.217 to 0.296; both P < 0.05). Muscular fitness was not independently associated with greater gray matter volume in any brain region. Furthermore, there were no statistically significant negative association between any component of physical fitness and gray matter volume in any region of the brain. In conclusion, cardiorespiratory fitness and speed-agility, but not muscular fitness, may independently be associated with greater volume of numerous cortical and subcortical brain structures; besides, some of these brain structures may be related to better academic performance. Importantly, the identified associations of fitness and gray matter volume were different for each fitness component. These findings suggest that increases in cardiorespiratory fitness and speed-agility may positively influence the development of distinctive brain regions and academic indicators, and thus counteract the harmful effect of overweight and obesity on brain structure during childhood.

Background: Functional connectivity analyses of functional magnetic resonance imaging data are a powerful tool for characterizing brain networks and how they are disrupted in neural disorders. However, many such analyses examine only one or a small number of a priori seed regions. Studies that consider the whole brain frequently rely on anatomic atlases to define network nodes, which might result in mixing distinct activation time-courses within a single node. Here, we improve upon previous methods by using a data-driven brain parcellation to compare connectivity profiles of dyslexic (DYS) versus non-impaired (NI) readers in the first whole-brain functional connectivity analysis of dyslexia.

Cerebral visual impairment, also known as cortical visual impairment, has become the most common cause of visual impairment in children in the United States and the developed world. Expert contributors from many countries illuminate the complexities of vision loss related to brain injury and neurological causes and provide readers with approaches toassessment and intervention. Vision and the Brain provides current research and thinking on CVI including: the role of the brain in vision; effects of brain damage on vision; impact of CVI on child development; donsideration in behavioral diagnosis; CVI, autism spectrum disorders, and ADHD; eye movement disorders in children with CVI; and refractive errors and impaired focusing.

Autistic individuals showed different atypical regional gray matter volumetric changes in childhood, adolescence, and adulthood compared to their TD peers, indicating that it is essential to consider developmental stages of the brain when exploring brain structural atypicalities in autism.

The results of the regional specificity of structural brain abnormalities in ASD in childhood, adolescence, and early adulthood were also inconsistent [5, 11, 12]. Previous studies have suggested that the increase of total brain volume after birth in ASD individuals may involve the increase in the volume of almost all brain regions [11], including the frontal lobe [18, 19], temporal lobe [9], occipital lobe [20], cerebellum [21], amygdala [22], or the increased volume of some brain regions and decreased volume of other brain regions [23]. A previous research demonstrated that brain overgrowth in early ASD mainly involves cortical thickening [20]. The results of the regional specificity of structural brain abnormalities in autistic children, adolescents, and adults were widely reported, including frontal lobe [24, 25], temporal lobe [26], parietal lobe [27], occipital lobe [27], amygdala [28], caudate nucleus [29], hippocampus [24], thalamus [5], and cerebellum [30].

For the statistical analysis of whole-brain volume, single variable covariance analysis was employed, with inclusion of whole-brain volume, whole-WM volume, and whole-GM volume as dependent variables, as well as gender, age, and IQ as covariates.

Regarding the comparison of whole-brain WM volume, Radua Via et al. [38] conducted a meta-analysis of the articles that were recorded in the PubMed database from 2002 to 2010 and concentrated on WM volume of autistic individuals, and they found no significant difference in the whole-brain WM volume between ASD and TD groups.

The cingulate cortex involves various functions, including motor control [77], cognitive control [77], conflict monitoring [78], and social cognition [79]. These functions are partly neuronal functions of cingulate cortex itself and partly functional connections with other brain regions. The cingulate cortex was considered as one of the atypical brain areas that was closely related to the pathology of ASD. Posterior cingulate cortex is a part of the human facial expression processing neural network [80] and an important area of marginal-cortical network that is responsible for social emotional behavior, and is closely associated with social deficits in ASD. A meta-analysis of fMRI studies on ASD found that the activation of cingulate gyrus in autistic adults was significantly weaker than that in TD adults [81]. These findings fully demonstrated the functional atypicalities of the left posterior cingulate gyrus in ASD, which could be due to the local atypical structure of the left posterior cingulate gyrus or the typical connection of neural network in ASD. Another study found that in non-social tasks, the left cingulate gyrus of autistic adults was weaker than that in autistic children [48]. In TD individuals, the functional connectivity between posterior cingulate gyrus and medial prefrontal cortex increased with age, while it decreased with age in ASD group [82]. It is suggested that the left cingulate gyrus and the posterior cingulate gyrus of autistic individuals had different functional levels at different ages, which could be related to the changes of GM volume in the left posterior cingulate gyrus of autistic individuals at different ages.

Notes: Brain maturation is influenced by heredity and environment, prenatal and postnatal insult, nutritional status, sleep patterns, pharmacotherapy, and surgical interventions during early childhood. Furthermore, physical, mental, economical, and psychological stress; drug abuse (caffeine, nicotine, and ethanol); and sex hormones, including estrogen, progesterone, and testosterone influence the development and maturation of the adolescent brain. MRI studies have suggested that neurocircuitry and myelinogenesis remain under construction during adolescence because these events in the CNS depend on sex hormones that are specifically increased during puberty.

Question Is screen-based media use associated with differences in the structural integrity of brain white matter tracts that support language and literacy skills in preschool-aged children?

Findings In this cross-sectional study of 47 healthy prekindergarten children, screen use greater than that recommended by the American Academy of Pediatrics guidelines was associated with (1) lower measures of microstructural organization and myelination of brain white matter tracts that support language and emergent literacy skills and (2) corresponding cognitive assessments.

Importance The American Academy of Pediatrics (AAP) recommends limits on screen-based media use, citing its cognitive-behavioral risks. Screen use by young children is prevalent and increasing, although its implications for brain development are unknown.

Main Outcomes and Measures ScreenQ is a 15-item measure of screen-based media use reflecting the domains in the AAP recommendations: access to screens, frequency of use, content viewed, and coviewing. Higher scores reflect greater use. ScreenQ scores were applied as the independent variable in 3 multiple linear regression models, with scores in 3 standardized assessments as the dependent variable, controlling for child age and household income: Comprehensive Test of Phonological Processing, Second Edition (CTOPP-2; Rapid Object Naming subtest); Expressive Vocabulary Test, Second Edition (EVT-2; expressive language); and Get Ready to Read! (GRTR; emergent literacy skills). The DTI measures included fractional anisotropy (FA) and radial diffusivity (RD), which estimated microstructural organization and myelination of white matter tracts. ScreenQ was applied as a factor associated with FA and RD in whole-brain regression analyses, which were then narrowed to 3 left-sided tracts supporting language and emergent literacy abilities. 2b1af7f3a8