Linking inter-individual differences in the conflict adaptation effect to spontaneous brain activity

NeuroImage ◽  
2014 ◽  
Vol 90 ◽  
pp. 146-152 ◽  
Author(s):  
Ting Wang ◽  
Zhencai Chen ◽  
Guang Zhao ◽  
Glenn Hitchman ◽  
Congcong Liu ◽  
...  
2014 ◽  
Vol 112 (8) ◽  
pp. 1838-1848 ◽  
Author(s):  
Kelly Anne Barnes ◽  
Kevin M. Anderson ◽  
Mark Plitt ◽  
Alex Martin

When humans are provided with ample time to make a decision, individual differences in strategy emerge. Using an adaptation of a well-studied decision making paradigm, motion direction discrimination, we probed the neural basis of individual differences in strategy. We tested whether strategies emerged from moment-to-moment reconfiguration of functional brain networks involved in decision making with task-evoked functional MRI (fMRI) and whether intrinsic properties of functional brain networks, measured at rest with functional connectivity MRI (fcMRI), were associated with strategy use. We found that human participants reliably selected one of two strategies across 2 days of task performance, either continuously accumulating evidence or waiting for task difficulty to decrease. Individual differences in decision strategy were predicted both by the degree of task-evoked activation of decision-related brain regions and by the strength of pretask correlated spontaneous brain activity. These results suggest that spontaneous brain activity constrains strategy selection on perceptual decisions.


2013 ◽  
Vol 44 (01) ◽  
Author(s):  
N Rustamov ◽  
R Rodriguez-Raecke ◽  
B Kopp ◽  
L Timm ◽  
R Dengler ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Eric Lacosse ◽  
Klaus Scheffler ◽  
Gabriele Lohmann ◽  
Georg Martius

AbstractCognitive fMRI research primarily relies on task-averaged responses over many subjects to describe general principles of brain function. Nonetheless, there exists a large variability between subjects that is also reflected in spontaneous brain activity as measured by resting state fMRI (rsfMRI). Leveraging this fact, several recent studies have therefore aimed at predicting task activation from rsfMRI using various machine learning methods within a growing literature on ‘connectome fingerprinting’. In reviewing these results, we found lack of an evaluation against robust baselines that reliably supports a novelty of predictions for this task. On closer examination to reported methods, we found most underperform against trivial baseline model performances based on massive group averaging when whole-cortex prediction is considered. Here we present a modification to published methods that remedies this problem to large extent. Our proposed modification is based on a single-vertex approach that replaces commonly used brain parcellations. We further provide a summary of this model evaluation by characterizing empirical properties of where prediction for this task appears possible, explaining why some predictions largely fail for certain targets. Finally, with these empirical observations we investigate whether individual prediction scores explain individual behavioral differences in a task.


2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Yumei Wang ◽  
Xiaochuan Zhao ◽  
Shunjiang Xu ◽  
Lulu Yu ◽  
Lan Wang ◽  
...  

Most patients with mild cognitive impairment (MCI) are thought to be in an early stage of Alzheimer’s disease (AD). Resting-state functional magnetic resonance imaging reflects spontaneous brain activity and/or the endogenous/background neurophysiological process of the human brain. Regional homogeneity (ReHo) rapidly maps regional brain activity across the whole brain. In the present study, we used the ReHo index to explore whole brain spontaneous activity pattern in MCI. Our results showed that MCI subjects displayed an increased ReHo index in the paracentral lobe, precuneus, and postcentral and a decreased ReHo index in the medial temporal gyrus and hippocampus. Impairments in the medial temporal gyrus and hippocampus may serve as important markers distinguishing MCI from healthy aging. Moreover, the increased ReHo index observed in the postcentral and paracentral lobes might indicate compensation for the cognitive function losses in individuals with MCI.


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