Article
Underconnected, but how? A survey of functional connectivity MRI studies in autism spectrum disorders.
Brain Development Imaging Laboratory, Department of Psychology, San Diego State University, San Diego, CA 92120, USA.
Cerebral Cortex (impact factor:
6.54).
03/2011;
21(10):2233-43.
DOI:10.1093/cercor/bhq296
pp.2233-43
Source: PubMed
-
Article: Salivary cotinine, doctor-diagnosed asthma and respiratory symptoms in primary schoolchildren.
[show abstract] [hide abstract]
ABSTRACT: Due to impaired airway function, children are at risk for adverse respiratory symptoms if exposed to environmental tobacco smoke (ETS). A community-based, cross-sectional study of 425 children (5-11 years) attending 15 primary schools in a low socio-economic area of Merseyside/UK was undertaken to investigate the association of adverse respiratory symptoms and ETS exposure using a parent-completed questionnaire and children's salivary cotinine measurements. Overall, 28.9% of children had doctor-diagnosed asthma (DDA) and 11.3% a history of hospital admission for respiratory illnesses. The symptom triad of cough, wheeze and breathlessness (C+W+B+) occurred in 12.6% of children. The geometric mean cotinine level was 0.37 ng/ml (95% CI, 0.33-0.42 ng/ml) and it was estimated that 45.6% of children were ETS exposed. A history of asthma in the family was reported for 9.2% of fathers and 7.2% of mothers. Salivary cotinine level was significantly increased in children with DDA compared to those without (P = 0.002). Cotinine-validated levels [adjusted odds ratio (AOR), 1.8; 95% CI, 1.4-2.5), low socio-economic (disadvantaged) status (AOR, 1.4; 1.1-2.9), child's male gender (AOR, 1.6; 1.1-2.5) and maternal smoking (AOR, 2.2; 1.4-3.1) were significantly associated with DDA. The cotinine-validated level (AOR, 1.4; 1.1-2.9) as well as maternal smoking (AOR, 1.8; 1.1-2.5), were also independently associated with C+W+B+. The use of salivary cotinine as an indicator of ETS exposure could be used to inform parents of exposure risk to their asthmatic children and may help re-enforce deterrent efforts to reduce childhood parental smoking exposure.Maternal and Child Health Journal 04/2008; 12(2):188-93. · 2.24 Impact Factor -
Article: Functional connectivity in the resting brain: a network analysis of the default mode hypothesis.
[show abstract] [hide abstract]
ABSTRACT: Functional imaging studies have shown that certain brain regions, including posterior cingulate cortex (PCC) and ventral anterior cingulate cortex (vACC), consistently show greater activity during resting states than during cognitive tasks. This finding led to the hypothesis that these regions constitute a network supporting a default mode of brain function. In this study, we investigate three questions pertaining to this hypothesis: Does such a resting-state network exist in the human brain? Is it modulated during simple sensory processing? How is it modulated during cognitive processing? To address these questions, we defined PCC and vACC regions that showed decreased activity during a cognitive (working memory) task, then examined their functional connectivity during rest. PCC was strongly coupled with vACC and several other brain regions implicated in the default mode network. Next, we examined the functional connectivity of PCC and vACC during a visual processing task and show that the resultant connectivity maps are virtually identical to those obtained during rest. Last, we defined three lateral prefrontal regions showing increased activity during the cognitive task and examined their resting-state connectivity. We report significant inverse correlations among all three lateral prefrontal regions and PCC, suggesting a mechanism for attenuation of default mode network activity during cognitive processing. This study constitutes, to our knowledge, the first resting-state connectivity analysis of the default mode and provides the most compelling evidence to date for the existence of a cohesive default mode network. Our findings also provide insight into how this network is modulated by task demands and what functions it might subserve.Proceedings of the National Academy of Sciences 02/2003; 100(1):253-8. · 9.68 Impact Factor -
Article: Principles of diffusion tensor imaging and its applications to basic neuroscience research.
[show abstract] [hide abstract]
ABSTRACT: The brain contains more than 100 billion neurons that communicate with each other via axons for the formation of complex neural networks. The structural mapping of such networks during health and disease states is essential for understanding brain function. However, our understanding of brain structural connectivity is surprisingly limited, due in part to the lack of noninvasive methodologies to study axonal anatomy. Diffusion tensor imaging (DTI) is a recently developed MRI technique that can measure macroscopic axonal organization in nervous system tissues. In this article, the principles of DTI methodologies are explained, and several applications introduced, including visualization of axonal tracts in myelin and axonal injuries as well as human brain and mouse embryonic development. The strengths and limitations of DTI and key areas for future research and development are also discussed.Neuron 10/2006; 51(5):527-39. · 14.74 Impact Factor
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed.
The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual
current impact factor.
Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence
agreement may be applicable.
Keywords
atypical brain networks
autism spectrum disorders
data analysis choices
distinguish studies
Distinguishing patterns
functional connectivity
functional connectivity studies
general underconnectivity
network dysfunction
NGU
NGU findings
NGU studies
numerous methodological variables
sensorimotor impairments
study types
task-driven time series
underconnectivity
underconnectivity findings
whole brain
whole-brain field