Functional MRI-guided probabilistic tractography of cortico-cortical and cortico-subcortical language networks in children

Broser, Philip J.; Groeschel, Samuel; Hauser, Till‐Karsten; Lidzba, Karen; Wilke, Marko

doi:10.1016/j.neuroimage.2012.07.060

Cited by 19 publications

(20 citation statements)

References 62 publications

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“…Imaging of structural connectivity has demonstrated that cortico-cortical language connections are already lateralized in children (Broser et al, 2012). Moreover, atypical development of white matter connectivity has been linked to language difficulties in populations of children born very prematurely (i.e.…”

Section: Discussionmentioning

confidence: 99%

Development of Network Synchronization Predicts Language Abilities

Doesburg

Tingling

MacDonald

et al. 2016

Journal of Cognitive Neuroscience

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Synchronization of oscillations among brain areas is understood to mediate network communication supporting cognition, perception and language. How task-dependent synchronization during word production develops throughout childhood and adolescence, as well as how such network coherence is related to the development of language abilities, remains poorly understood. To address this, we recorded magnetoencephalography (MEG) while 73 participants aged 4 -18 years performed a verb generation task. Atlas-guided source reconstruction was performed, and phase synchronization among regions was calculated. Task-dependent increases in synchronization were observed in the theta, alpha and beta frequency ranges, and network synchronization differences were observed between age groups. Task-dependent synchronization was strongest in the theta band, as were differences between age groups. Network topologies were calculated for brain regions associated with verb generation, and were significantly associated with both age and language abilities. These findings establish the maturational trajectory of network synchronization underlying expressive language abilities throughout childhood and adolescence, and provide the first evidence for an association between large-scale neurophysiological network synchronization and individual differences in the development of language abilities.

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Section: Discussionmentioning

confidence: 99%

Development of Network Synchronization Predicts Language Abilities

Doesburg

Tingling

MacDonald

et al. 2016

Journal of Cognitive Neuroscience

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show abstract

“…Currently, a majority of literature works that combined DTI and fMRI reviewed in this paper fall into this category (e.g., Broser et al, 2012; Dougherty et al, 2005; Ethofer et al, 2011; Greicius et al, 2009; Guye et al, 2003; Kim et al, 2006; Kleiser et al, 2010; Lowe et al, 2008; Schonberg et al, 2006; Shimono et al, 2012; Supekar et al, 2010; Upadhyay et al, 2007; van den Heuvel et al, 2008b; Yang et al, 2009). These literature works can be further divided into two sub-streams: the first one uses task-based fMRI to guide DTI tractography or isolate fiber tracts for later analysis; the other one uses fMRI-derived activations map to validate DTI-related results, e.g., cortical parcellation based on structural connectivity.…”

Section: Methods Of Dti/fmri Fusionmentioning

confidence: 99%

“…One study from Ethofer et al (2011) found regions that showed significant effects regarding the gaze shifts by using a series of facial stimuli and made them as seed regions in which the probabilistic fiber tracking was performed. Other recent literatures include Shimono et al (2012) and Broser et al (2012). The former one used a psychophysical task derived ROIs, and the latter one applied two tasks (Wilke et al, 2006, 2005) to generate language-related functional masks to guide the WM structure selection.…”

Section: Methods Of Dti/fmri Fusionmentioning

confidence: 99%

Fusing DTI and fMRI data: A survey of methods and applications

et al. 2014

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The relationship between brain structure and function has been one of the centers of research in neuroimaging for decades. In recent years, diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) techniques have been widely available and popular in cognitive and clinical neurosciences for examining the brain’s white matter (WM) micro-structures and gray matter (GM) functions, respectively. Given the intrinsic integration of WM/GM and the complementary information embedded in DTI/fMRI data, it is natural and well-justified to combine these two neuroimaging modalities together to investigate brain structure and function and their relationships simultaneously. In the past decade, there have been remarkable achievements of DTI/fMRI fusion methods and applications in neuroimaging and human brain mapping community. This survey paper aims to review recent advancements on methodologies and applications in incorporating multimodal DTI and fMRI data, and offer our perspectives on future research directions. We envision that effective fusion of DTI/fMRI techniques will play increasingly important roles in neuroimaging and brain sciences in the years to come.

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“…The first class of approach is a "frequency" approach. Some apply information obtained from a probabilistic tracking algorithm, and use the variance in the number of successfully reconstructed pathways between two nodes to explore covariance with "function" (e.g., Parker et al, 2005;Broser et al, 2012). The "probabilistic tractography score" is often interpreted as a quantitative marker of "connectivity" in this context.…”

Section: Brain Networkmentioning

confidence: 99%