Neural networks related to pro-saccades and anti-saccades revealed by independent component analysis

Domagalik, Aleksandra; Beldzik, Ewa; Fąfrowicz, Magdalena; Ogińska, Halszka; Marek, Tadeusz

doi:10.1016/j.neuroimage.2012.06.006

Cited by 47 publications

(47 citation statements)

References 85 publications

(138 reference statements)

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“…Less commonly observed is the temporo-parietal network involving bilateral inferior temporal gyri and intraparietal sulcus (IPS). The executive control network usually includes the bilateral prefrontal cortex and the core regions (Smith et al 2009;Domagalik et al 2012). Here, the executive control and prefrontal networks were separated.…”

Section: Fmri Resultsmentioning

confidence: 99%

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When three is greater than five: EEG and fMRI signatures of errors in numerical and physical comparisons

et al. 2017

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Unravelling the neural mechanisms, which determine performance accuracy, is one of the key concepts in cognitive neuroscience. When compared to correct responses, shorter reaction times are commonly observed behavioural feature of errors committed in typical conflict tasks. Yet, little is known about the origins of this phenomenon. In this study, EEG and fMRI experiments were conducted using the numerical version of the Stroop paradigm, which yielded unique behavioural outcomes. Particularly, errors in numerical comparison had shorter reaction times than correct trials, whereas physical comparison resulted in the opposite pattern. This criss-crossing interaction effect was used as a marker when exploring time-courses of brain activity. Group independent component analysis was applied to neurophysiological data and event-related analysis was conducted on the components' time-courses. Results revealed one centro-parietal EEG component and one temporo-parietal fMRI neural network, which exhibited significant task and accuracy interactions. Showing linear increase that peaked right after the response onset, the activity of centro-parietal EEG component was linked to the decision variable signal, which reflects a process of accumulating evidence until reaching an actiontriggering threshold. Both amplitude measurements and linear fits to the signal provided evidence for distinctive characteristics between numerical and physical comparisons, thereby explaining the behavioural outcomes: errors are committed due to accumulation of evidence in favour of the other (wrong) task instruction. The architecture of the temporo-parietal network, which comprises bilateral inferior temporal and intraparietal regions, is highly consistent with the recently established core ''number network''. These findings link perceptual decisions with the generalized magnitude system and impart novel insights into the neural determinants of errors in humans.

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Section: Fmri Resultsmentioning

confidence: 99%

“…The left and right frontoparietal and the auditory networks are highly reproducible, as indicated by all the referenced studies. Lastly, the network comprising the precuneus (Domagalik et al 2012) is less often observed. Only the temporo-parietal network achieved the established criteria of significant interaction [ …”

Section: Fmri Resultsmentioning

confidence: 99%

When three is greater than five: EEG and fMRI signatures of errors in numerical and physical comparisons

et al. 2017

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“…Because of its unique capacity of separating signal mixture from each voxel into source signals, investigators have used sICA to de-noise fMRI data by separating artifacts from signals (Aron and Poldrack, 2006; Beckmann, 2012; Brooks et al, 2013; Du et al, 2016; Griffanti et al, 2014; Tohka et al, 2008; Yakunina et al, 2013). Furthermore, some fMRI sICA studies have described spatial overlap of two or more FNs, indicating that sICA can separate BOLD signal mixtures from individual voxels into two or more FNs in the overlapping regions (Calhoun et al, 2008; Domagalik et al, 2012; Kim et al, 2009a; Kim et al, 2009b; Menz et al, 2009; St Jacques et al, 2011; van Wageningen et al, 2009; Wu et al, 2009; Zhang and Li, 2012). Very recently, we and at least three other groups systematically described FN overlap generated by sICA (Beldzik et al, 2013; Braga et al, 2013; Geranmayeh et al, 2014; Leech et al, 2012; Xu et al, 2014a; Xu et al, 2013a; Xu et al, 2013b; Yeo et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…In another study, both GLM and sICA were used to interrogate fMRI data acquired during pro-saccadic (PS) and anti-saccadic (AS) tasks (Beldzik et al, 2013; Domagalik et al, 2012). sICA extracted 11 FNs which showed extensive overlap at multiple brain regions including the intraparietal sulcus, frontal eye field, precuneus and posterior cingulate (PCC).…”

Section: Introductionmentioning

confidence: 99%

Large-scale functional network overlap is a general property of brain functional organization: Reconciling inconsistent fMRI findings from general-linear-model-based analyses

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Calhoun

et al. 2016

Neuroscience & Biobehavioral Reviews

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Functional magnetic resonance imaging (fMRI) studies regularly use univariate general-linear-model-based analyses (GLM). Their findings are often inconsistent across different studies, perhaps because of several fundamental brain properties including functional heterogeneity, balanced excitation and inhibition (E/I), and sparseness of neuronal activities. These properties stipulate heterogeneous neuronal activities in the same voxels and likely limit the sensitivity and specificity of GLM. This paper selectively reviews findings of histological and electrophysiological studies and fMRI spatial independent component analysis (sICA) and reports new findings by applying sICA to two existing datasets. The extant and new findings consistently demonstrate several novel features of brain functional organization not revealed by GLM. They include overlap of large-scale functional networks (FNs) and their concurrent opposite modulations, and no significant modulations in activity of most FNs across the whole brain during any task conditions. These novel features of brain functional organization are highly consistent with the brain’s properties of functional heterogeneity, balanced E/I, and sparseness of neuronal activity, and may help reconcile inconsistent GLM findings.

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“…a saccade directed in opposite direction of the required landing point) occur very infrequently in prosaccade trials (Ettinger et al, 2003(Ettinger et al, , 2005Smyrnis et al, 2002;Tatler and Hutton, 2007). Furthermore, the spatial goal of the saccade is not directly mapped on the sensory stimulus but has to be computed by inverting the initial stimulus vector by 180°, making the required stimulus response mapping spatially more complex than in standard prosaccades (Domagalik et al, 2012;Munoz and Everling, 2004). Due to these sensorimotor and inhibitory demands antisaccades are associated with longer reaction times, decreased spatial accuracy, and a greater recruitment of a dorsal fronto-parietal network including the PPC and the frontal and supplementary eye fields (FEF, SEF) than simple prosaccades (Bedi et al, 2013;Brown et al, 2006;Domagalik et al, 2012;Ettinger et al, 2003Ettinger et al, , 2005Ettinger et al, , 2008Smyrnis et al, 2002;Tatler and Hutton, 2007; for a review see: McDowell et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

Functional magnetic resonance imaging of sensorimotor transformations in saccades and antisaccades

et al. 2014

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Neural networks related to pro-saccades and anti-saccades revealed by independent component analysis

Cited by 47 publications

References 85 publications

When three is greater than five: EEG and fMRI signatures of errors in numerical and physical comparisons

When three is greater than five: EEG and fMRI signatures of errors in numerical and physical comparisons

Large-scale functional network overlap is a general property of brain functional organization: Reconciling inconsistent fMRI findings from general-linear-model-based analyses

Functional magnetic resonance imaging of sensorimotor transformations in saccades and antisaccades

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