Neural representations of the amount and the delay time of reward in intertemporal decision making

Wang, Qiang; Wang, Yajie; Wang, Pinchun; Peng, Maomiao; Zhang, Manman; Zhu, Yuxuan; Wei, Shiyu; Chen, Chuansheng; Chen, Xiongying; Luo, Shan; Bai, Xuejun

doi:10.1002/hbm.25445

Cited by 31 publications

(31 citation statements)

References 82 publications

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“…In contrast, the MVPA approach detected potential brainbehavior associations based on distributed representational patterns on voxels' GMVs, consistent with previous studies that highlighted higher sensitivity in MVPA (Q. Wang et al, , 2021. To date, this method has been widely employed to investigate the neural mechanisms of higher-level cognitive processes and various behavioral indexes (Haxby et al, 2014;Norman et al, 2006; Q.…”

Section: Discussionsupporting

confidence: 83%

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The Medial Temporal Lobe Structure and Function Support Positive Affect

Jin

Feng

Zhu

et al. 2022

Preprint

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Positive affect (PA) is not only associated with individuals’ psychological and physical health, but also their cognitive processes. However, whether medial temporal lobe (MTL) and its subfields’ volume/functional connectivity can explain individual variability in PA remains understudied. We investigated the morphological (i.e., gray matter volume; GMV) and functional characteristics (i.e., resting-state functional connectivity; rsFC) of PA combined with univariate and multivariate pattern analyses (MVPA) using a large sample of participants (n = 321). We simultaneously collected the T1-weighted (n = 321), high-resolution MTL T2-weighted, and resting-state functional imaging data (n = 209). The MTL and its subfields’ volumes, including the CA1, CA2 + 3, DG, and subiculum (SUB), perirhinal cortex (PRC), and parahippcampus (PHC), were extracted by automatic segmentation of hippocampal subfields (ASHS) software. The morphological results revealed that GMVs in the prefrontal-occipital and limbic (i.e., hippocampus, amygdala, and PHC) systems were associated with variability in PA at the whole-brain level using MVPA but not univariate analysis. Linear regression results further revealed a positive association between the MTL subfields’ GMV, especially for the right PRC, and PA after controlling for several covariates. PRC-seed-based rsFC analyses further revealed that its couplings with the fronto-parietal-occipital system predicted PA in both univariate and MVPA. These findings provide novel insights into the neuroanatomical and functional substrates underlying human PA trait. Findings also suggest critical contributions of the MTL and its subfield of the perirhinal cortex, but not hippocampal subfields, as well as its functional coupling with the fronto-parietal control-system on the formation of PA.

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Section: Discussionsupporting

confidence: 83%

“…Based on prior studies (Lv et al, 2020; Q. Wang et al, 2021), we set the ε parameter in the SVR to be 0.01. A three-fold cross-validation analysis was conducted in the present study.…”

Section: Univariate and Multivariate Pattern Analysesmentioning

confidence: 99%

The Medial Temporal Lobe Structure and Function Support Positive Affect

Jin

Feng

Zhu

et al. 2022

Preprint

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“…Notably, different parts of the dPFC are related to different aspects of DD, including the dlPFC, an executive control region, (Hare et al, 2014) and the dMPFC, implicated in processing future rewards and delay time (Wang et al, 2021). Other regions of the DMN, including the vmPFC and PCC, have been implicated in subjective valuation processes critical for decision-making (Pfeifer and Berkman, 2018; Bartra, McGuire, and Kable, 2013; Kable and Glimcher, 2007).…”

Section: Discussionmentioning

confidence: 99%

Individual Differences in Delay Discounting are Associated with Dorsal Prefrontal Cortex Connectivity in Youth

Mehta

Pines

Adebimpe

et al. 2023

Preprint

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Delay discounting is a measure of impulsive choice relevant in adolescence as it predicts many real-life outcomes, including substance use disorders, obesity, and academic achievement. However, the functional networks underlying individual differences in delay discounting during youth remain incompletely described. Here we investigate the association between multivariate patterns of functional connectivity and individual differences in impulsive choice in a large sample of youth. A total of 293 youth (9-23 years) completed a delay discounting task and underwent resting-state fMRI at 3T. A connectome-wide analysis using multivariate distance-based matrix regression was used to examine whole-brain relationships between delay discounting and functional connectivity was then performed. These analyses revealed that individual differences in delay discounting were associated with patterns of connectivity emanating from the left dorsal prefrontal cortex, a hub of the default mode network. Delay discounting was associated with greater functional connectivity between the dorsal prefrontal cortex and other parts of the default mode network, and reduced connectivity with regions in the dorsal and ventral attention networks. These results suggest that delay discounting in youth is associated with individual differences in relationships both within the default mode network and between the default mode and networks involved in attentional and cognitive control.

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“…Although the neural mechanisms between different choices processes in intertemporal decision-making have been explored extensively (Kable and Glimcher, 2007;Hare et al, 2009;Harris et al, 2011;Waegeman et al, 2014;Maier Silvia et al, 2015), relatively less studies have examined such different neural mechanisms from the perspective of neural representation (Wang et al, 2014(Wang et al, , 2021Chen et al, 2019;Piva et al, 2019). By taking full advantage of information from the voxels, multivariate analysis endows us with higher sensitivity and reliability (Lv et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

“…This kind of distributed information can be measured with the help of multivariate approach, which overcomes the limitations of univariate approach by searching for the optimal combination of scattered voxels and evaluating their contributions to decision discriminability (Kriegeskorte et al, 2006;Davis et al, 2014). However, albeit being widely employed in studying individual's perceptual and cognitive status (Haxby, 2012), multivariate analysis has relatively rarely been implemented in the functional imaging of intertemporal choice (Wang et al, 2014(Wang et al, , 2021Chen et al, 2019;Piva et al, 2019), with most studies focusing on the dissociable representations of different intertemporal choices. Meanwhile, individual differences in intertemporal choice task have seldom been probed by this approach, especially with task-based images.…”

Section: Introductionmentioning

confidence: 99%

Multivariate analysis differentiates intertemporal choices in both value and cognitive control network

Wang²

2023

Front. Neurosci.

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Choices between immediate smaller reward and long-term larger reward are referred to as intertemporal choice. Numerous functional magnetic resonance imaging (fMRI) studies have investigated the neural substrates of intertemporal choice via conventional univariate analytical approaches, revealing dissociable activations of decisions involving immediately available rewards and decisions involving delayed rewards in value network. With the help of multivariate analyses, which is more sensitive for evaluating information encoded in spatially distributed patterns, we showed that fMRI activity patterns represent viable signatures of intertemporal choice, as well as individual differences while controlling for age. Notably, in addition to value network, regions from cognitive control network play prominent roles in differentiating between different intertemporal choices as well as individuals with distinct discount rates. These findings provide clear evidence that substantiates the important role of value and cognitive control networks in the neural representation of one’s intertemporal decisions.

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Neural representations of the amount and the delay time of reward in intertemporal decision making

Cited by 31 publications

References 82 publications

The Medial Temporal Lobe Structure and Function Support Positive Affect

The Medial Temporal Lobe Structure and Function Support Positive Affect

Individual Differences in Delay Discounting are Associated with Dorsal Prefrontal Cortex Connectivity in Youth

Multivariate analysis differentiates intertemporal choices in both value and cognitive control network

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