Strengthening of Top-Down Frontal Cognitive Control Networks Underlying the Development of Inhibitory Control: A Functional Magnetic Resonance Imaging Effective Connectivity Study

Hwang, Kai; Velanova, Katerina; Luna, Beatríz

doi:10.1523/jneurosci.2825-10.2010

Cited by 277 publications

(208 citation statements)

References 88 publications

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“…Existing literature suggests that the lateral PFC is a source of top-down biasing signal that influences sensorimotor processes (Hwang et al, 2010;Johnston and Everling, 2011). We found that in response to the heightened control demand in AS trials, beta-band power increased in the right DLPFC during the preparatory period, and causally influenced FEF alphaband activity.…”

Section: Discussionmentioning

confidence: 99%

Cortical Neurodynamics of Inhibitory Control

et al. 2014

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The ability to inhibit prepotent responses is critical for successful goal-directed behaviors. To investigate the neural basis of inhibitory control, we conducted a magnetoencephalography study where human participants performed the antisaccade task. Results indicated that neural oscillations in the prefrontal cortex (PFC) showed significant task modulations in preparation to suppress saccades. Before successfully inhibiting a saccade, beta-band power (18 -38 Hz) in the lateral PFC and alpha-band power (10 -18 Hz) in the frontal eye field (FEF) increased. Trial-by-trial prestimulus FEF alpha-band power predicted successful saccadic inhibition. Further, inhibitory control enhanced cross-frequency amplitude coupling between PFC beta-band (18 -38 Hz) activity and FEF alpha-band activity, and the coupling appeared to be initiated by the PFC. Our results suggest a generalized mechanism for top-down inhibitory control: prefrontal beta-band activity initiates alpha-band activity for functional inhibition of the effector and/or sensory system.

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Section: Discussionmentioning

confidence: 99%

Cortical Neurodynamics of Inhibitory Control

et al. 2014

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“…The reason is that these methods make the same set of assumptions (e.g., stationarity) about the time series. Accumulating evidence demonstrates the effectiveness of using Granger causality to characterize fMRI data (Rypma et Hwang et al, 2010;Jiao et al, 2011). Moreover, recent work shows that both resting-state and task-state fMRI data are well described by autoregressive models, which are the basis for deriving Granger causality (Sridharan et al, 2007;Bressler and Seth, 2011;Hamilton et al, 2011).…”

Section: Methodological Considerationsmentioning

confidence: 99%

Causal Interactions in Attention Networks Predict Behavioral Performance

Wen¹,

Yao²,

Liu³

et al. 2012

J. Neurosci.

144

140

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Lesion and functional brain imaging studies have suggested that there are two anatomically nonoverlapping attention networks. The dorsal frontoparietal network controls goal-oriented top-down deployment of attention; the ventral frontoparietal network mediates stimulus-driven bottom-up attentional reorienting. The interaction between the two networks and its functional significance has been considered in the past but no direct test has been carried out. We addressed this problem by recording fMRI data from human subjects performing a trial-by-trial cued visual spatial attention task in which the subject had to respond to target stimuli in the attended hemifield and ignore all stimuli in the unattended hemifield. Correlating Granger causal influences between regions of interest with behavioral performance, we report two main results. First, stronger Granger causal influences from the dorsal attention network (DAN) to the ventral attention network (VAN), i.e., DAN3 VAN, are generally associated with enhanced performance, with right intraparietal sulcus (IPS), left IPS, and right frontal eye field being the main sources of behavior-enhancing influences. Second, stronger Granger causal influences from VAN to DAN, i.e., VAN3 DAN, are generally associated with degraded performance, with right temporal-parietal junction being the main sources of behavior-degrading influences. These results support the hypothesis that signals from DAN to VAN suppress and filter out unimportant distracter information, whereas signals from VAN to DAN break the attentional set maintained by the dorsal attention network to enable attentional reorienting.

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“…Age-related differences in top-down control are associated with a strengthening of effective connectivity between frontal and posterior brain regions (Hwang et al, 2010). Recent results from resting state functional connectivity MRI (fcMRI) describe changes in functional networks during development as an increase in segregation (thus a decrease in short-range connections) and an increase in integration (largescale connections; Fair et al, 2009Fair et al, , 2007.…”

Section: Maturational Changes In the Structures Functions And Mechamentioning

confidence: 99%

“…Measures of functional connectivity may offer a useful tool for elucidating the relevance of age-graded changes in the interaction of the two components for WM performance. Initial studies of this kind point to profound developmental differences in the configuration and recruitment of brain networks in childhood (e.g., Hwang et al, 2010;Jolles et al, 2011) and adulthood (e.g., Andrews-Hanna et al, 2007;Damoiseaux et al, 2008). Developmental changes in childhood seem to reflect a decrease in short-range connections and an increase in large-scale connections (e.g., Fair et al, 2009Fair et al, , 2007.…”

Section: Questions For Future Researchmentioning

confidence: 99%

Lifespan age differences in working memory: A two-component framework

Sander

Lindenberger

Werkle‐Bergner

2012

Neuroscience & Biobehavioral Reviews

133

101

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a b s t r a c tWe suggest that working memory (WM) performance can be conceptualized as the interplay of low-level feature binding processes and top-down control, relating to posterior and frontal brain regions and their interaction in a distributed neural network. We propose that due to age-differential trajectories of posterior and frontal brain regions top-down control processes are not fully mature until young adulthood and show marked decline with advancing age, whereas binding processes are relatively mature in children, but show senescent decline in older adults. A review of the literature spanning from middle childhood to old age shows that binding and top-down control processes undergo profound changes across the lifespan. We illustrate commonalities and dissimilarities between children, younger adults, and older adults reflecting the change in the two components' relative contribution to visual WM performance across the lifespan using results from our own lab. We conclude that an integrated account of visual WM lifespan changes combining research from behavioral neuroscience and cognitive psychology of child development as well as aging research opens avenues to advance our understanding of cognition in general.

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Strengthening of Top-Down Frontal Cognitive Control Networks Underlying the Development of Inhibitory Control: A Functional Magnetic Resonance Imaging Effective Connectivity Study

Cited by 277 publications

References 88 publications

Cortical Neurodynamics of Inhibitory Control

Cortical Neurodynamics of Inhibitory Control

Causal Interactions in Attention Networks Predict Behavioral Performance

Lifespan age differences in working memory: A two-component framework

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