Quantitative Characterization of Functional Anatomical Contributions to Cognitive Control under Uncertainty

Fan, Jin; Dam, Nicholas T. Van; Gu, Xiaosi; Liu, Xun; Wang, Hongbin; Tang, Cheuk Y.; Hof, Patrick R.

doi:10.1162/jocn_a_00554

Cited by 52 publications

(62 citation statements)

References 118 publications

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“…The alerting cue carries the temporal information about the target onset, triggering the activation of FPN and other subcortical regions for the preparation of response. The AI, in addition to ACC, has a distinct functional role in monitoring baseline uncertainty (Fan et al, 2014). Also, in a recent study we found that TPJ is a necessary region in the interaction between bottom-up and top-down attentional control (Wu et al, 2015).…”

Section: Discussionmentioning

confidence: 99%

“…Here the FPN is defined more broadly than in Petersen and Posner (2012) and includes the ACC, AI, and thalamus of the cingulo-opercular network (Dosenbach et al, 2008). Within the FPN, ACC and AI are involved in baseline uncertainty processing (Fan et al, 2014). The involvement of FPN in the alerting and executive control functions is supported by the identified brain regions of FPN (frontal and parietal regions), as well as occipital regions and putamen and cerebellum, associated with the interaction effect between these attentional functions.…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, the FPN is phasically activated for the general purpose of cognitive control in a task state with increased uncertainty. In our previous studies, we have argued that cognitive control is implemented by attentional functions (Mackie et al, 2013), and demonstrated that the activation of the regions of FPN is a linear function of cognitive control load, estimated in units of information entropy (Fan et al, 2014). …”

Section: Discussionmentioning

confidence: 99%

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The activation of interactive attentional networks

et al. 2016

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Attention can be conceptualized as comprising the functions of alerting, orienting, and executive control. Although the independence of these functions has been demonstrated, the neural mechanisms underlying their interactions remain unclear. Using the revised attention network test and functional magnetic resonance imaging, we examined cortical and subcortical activity related to these attentional functions and their interactions. Results showed that areas in the extended frontoparietal network (FPN), including dorsolateral prefrontal cortex, frontal eye fields (FEF), areas near and along the intraparietal sulcus, anterior cingulate and anterior insular cortices, basal ganglia, and thalamus were activated across multiple attentional functions. Specifically, the alerting function was associated with activation in the locus coeruleus (LC) in addition to regions in the FPN. The orienting functions were associated with activation in the superior colliculus (SC) and the FEF. The executive control function was mainly associated with activation of the FPN and cerebellum. The interaction effect of alerting by executive control was also associated with activation of the FPN, while the interaction effect of validity by executive control was mainly associated with the activation in the pulvinar. The current findings demonstrate that cortical and specific subcortical areas play a pivotal role in the implementation of attentional functions and underlie their dynamic interactions.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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The activation of interactive attentional networks

et al. 2016

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“…Although task paradigms that parametrically manipulate demand for control have been employed in healthy controls (Fan et al, 2014;Forster et al, 2011;Wendt et al, 2014), such paradigms have rarely been employed in addiction research. Prior evidence of interactions between working memory load and smoking state (sated, abstinent) has been observed in smokers, where abstinence leads to increased activation in dorsal lateral prefrontal cortex (dlPFC) at low, but not medium or high, working memory load (Xu et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

Insula Demonstrates a Non-Linear Response to Varying Demand for Cognitive Control and Weaker Resting Connectivity With the Executive Control Network in Smokers

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Salmeron

et al. 2016

Neuropsychopharmacol

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Deficits in cognitive control processes are a primary characteristic of nicotine addiction. However, while network-based connectivity measures of dysfunction have frequently been observed, empirical evidence of task-based dysfunction in these processes has been inconsistent. Here, in a sample of smokers (n = 35) and non-smokers (n = 21), a previously validated parametric flanker task is employed to characterize addiction-related alterations in responses to varying (ie, high, intermediate, and low) demands for cognitive control. This approach yields a demand-response curve that aims to characterize potential non-linear responses to increased demand for control, including insensitivities or lags in fully activating the cognitive control network. We further used task-based differences in activation between groups as seeds for resting-state analysis of network dysfunction in an effort to more closely link prior inconsistencies in task-related activation with evidence of impaired network connectivity in smokers. For both smokers and non-smokers, neuroimaging results showed similar increases in activation in brain areas associated with cognitive control. However, reduced activation in right insula was seen only in smokers and only when processing intermediate demand for cognitive control. Further, in smokers, this task-modulated right insula showed weaker functional connectivity with the superior frontal gyrus, a component of the task-positive executive control network. These results demonstrate that the neural instantiation of salience attribution in smokers is both more effortful to fully activate and has more difficulty communicating with the exogenous, task-positive, executive control network. Together, these findings further articulate the cognitive control dysfunction associated with smoking and illustrate a specific brain circuit potentially responsible.

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“…Frontoparietal activity has been found to scale with the amount of cognitive control required by tasks and, in particular, the amount of uncertainty within a decision (Fan, 2014;Fan et al, 2014). The common recruitment of this network during free decisions is thought to result from the greater demand on selection processes required when choosing between multiple options, compared to simple goal maintenance for instructed choices (Bunge et al, 2002;Duncan, 2013;Frith, 1991;Hadland et al, 2001;Thimm et al, 2012).…”

Section: Discussionmentioning

confidence: 99%

Neural dynamics of voluntary decision-making

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As we navigate the world, we prepare to make voluntary decisions in relation to the opportunities afforded by the environment. An essential aspect of these decisions is that they are experienced with a sense of free will. In both philosophical and layperson accounts of free will, the "ability to choose otherwise" serves a central role and, further, there is evidence that individuals preferentially choose options that maximise the availability of choice. The underlying reason for this widespread emphasis on choice has been difficult to reconcile with traditional views of free will and decision-making.Embodied theories of decision-making propose that individuals are driven to be in states where a greater number of options are available because this maximises their perceived ability to influence the environment in future states. This view places critical emphasis on the period of time that precedes a decision, during which individuals proactively prepare for the upcoming decision. On this basis, a decision may be experienced as free if the individual believes himself to have multiple potential options available. Studies have shown the ability to predict free choices but little is known about the role potential options plays during the voluntary decision-making process.In my thesis, I investigated the proactive neural processes of voluntary decisionmaking in dynamic environments. In particular, I aimed to test the hypothesis that free decisions are associated with a proactive state in which multiple potential choices are considered. To do so, I carried out a set of three studies where I examined behavioural and functional magnetic resonance imaging (fMRI) data of participants while they performed free decisions in virtual environments.In Chapter 2, I designed an fMRI study to investigate the neural patterns of activity preceding a free decision. I found that frontoparietal and salience networks were more active for free decisions than instructed decisions during an initial period of proactive choice selection. Using multi-voxel pattern analysis (MVPA), I showed that upcoming choices could be predicted from both the motor and visual cortices once participants were able to match their planned colour choice to its spatial location. Notably, the decoding accuracy for free decisions was lower than instructed decisions, indicating less reliable choice representation.This corresponded to eye fixation results showing greater visual attention to the alternative options in the case of free decisions, together indicating that choice consideration may be an ongoing process when individuals freely prepare decisions. iiiIn Chapter 3, I tested whether the state of having alternative options was reflected in neural representations of upcoming choices and, further, if this translated to differences in the subjective experience of free choice. In this fMRI study, I found that the availability of an alternative option could be decoded from patterns of activity in the dorsolateral prefrontal cortex. Moreover, decoding accuracy ...

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Quantitative Characterization of Functional Anatomical Contributions to Cognitive Control under Uncertainty

Cited by 52 publications

References 118 publications

The activation of interactive attentional networks

The activation of interactive attentional networks

Insula Demonstrates a Non-Linear Response to Varying Demand for Cognitive Control and Weaker Resting Connectivity With the Executive Control Network in Smokers

Neural dynamics of voluntary decision-making

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