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Performance and Material-Dependent Holistic Representation of Unconscious Thought: A Functional Magnetic Resonance Imaging Study.

ABSTRACT: Psychological research has demonstrated that humans can think unconsciously. Unconscious thought (UT) refers to cognitive or affective decision-related processes that occur beyond conscious awareness. UT processes are considered more effective in complex decision-making than conscious thought (CT). In addition, holistic representation plays a key role in UT and consists of a multimodal, value-related cognitive process. While the neural correlates of UT have recently been investigated, the holistic representation hypothesis of UT has not been confirmed. Therefore, in the present study, we aimed to further evaluate this hypothesis by utilizing two UT tasks (person and consumer-product evaluations) in conjunction with an improved functional magnetic resonance imaging (fMRI) experimental protocol. Participants evaluated four alternatives with 12 attributes each. In the UT condition, once the decision information had been presented, the participants completed a 1-back task for 120 s and evaluated each alternative, as well as an independent 1-back task in the absence of any decision information. We then performed regression analysis of the UT performance in both tasks. Our results revealed a positive correlation between performance in the UT task and the use of the anterior part of the precuneus/paracentral lobule in the person evaluation task and between performance and the posterior part of the precuneus, postcentral gyrus, middle occipital gyrus, and superior parietal lobule in the consumer-product evaluation task. The involvement of the precuneus area in both tasks was indicative of a multimodal, value-related process and is consistent with the features of holistic representation, supporting a central role for holistic representation in UT. Furthermore, the involvement of different precuneus subregions in the two UT tasks may reflect the task dependency of the key representation critical for advantageous UT.

SUBMITTER: Kageyama T

PROVIDER: S-EPMC6908964 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Individuals often form more reasonable judgments from complex information after a period of distraction vs. deliberation. This phenomenon has been attributed to sophisticated unconscious thought during the distraction period that integrates and organizes the information (Unconscious Thought Theory; Dijksterhuis and Nordgren, 2006). Yet, other research suggests that experiential processes are strengthened during the distraction (relative to deliberation) period, accounting for the judgment and decision benefit. We tested between these possibilities, hypothesizing that unconscious thought is distinct from experiential processes, and independently contributes to judgments and decisions during a distraction period. Using an established paradigm, Experiment 1 (N = 319) randomly induced participants into an experiential or rational mindset, after which participants received complex information describing three roommates to then consider consciously (i.e., deliberation) or unconsciously (i.e., distraction). Results revealed superior roommate judgments (but not choices) following distraction vs. deliberation, consistent with Unconscious Thought Theory. Mindset did not have an influence on roommate judgments. However, planned tests revealed a significant advantage of distraction only within the rational-mindset condition, which is contrary to the idea that experiential processing alone facilitates complex decision-making during periods of distraction. In a second experiment (N = 136), we tested whether effects of unconscious thought manifest for a complex analytical reasoning task for which experiential processing would offer no advantage. As predicted, participants in an unconscious thought condition outperformed participants in a control condition, suggesting that unconscious thought can be analytical. In sum, the current results support the existence of unconscious thinking processes that are distinct from experiential processes, and can be rational. Thus, the experiential vs. rational nature of a process might not cleanly delineate conscious and unconscious thought.

Project description:Objective3D cine-magnetic resonance imaging (cine-MRI) can capture images of the human body volume with high spatial and temporal resolutions to study the anatomical dynamics. However, the reconstruction of 3D cine-MRI is challenged by highly undersampled k-space data in each dynamic (cine) frame, due to the slow speed of MR signal acquisition. We proposed a machine learning-based framework, spatial and temporal implicit neural representation learning (STINR-MR), for accurate 3D cine-MRI reconstruction from highly undersampled data.ApproachSTINR-MR used a joint reconstruction and deformable registration approach to achieve a high acceleration factor for cine volumetric imaging. It addressed the ill-posed spatiotemporal reconstruction problem by solving a reference-frame 3D MR image and a corresponding motion model which deforms the reference frame to each cine frame. The reference-frame 3D MR image was reconstructed as a spatial implicit neural representation (INR) network, which learns the mapping from input 3D spatial coordinates to corresponding MR values. The dynamic motion model was constructed via a temporal INR, as well as basis deformation vector fields (DVFs) extracted from prior/onboard 4D-MRIs using principal component analysis (PCA). The learned temporal INR encodes input time points and outputs corresponding weighting factors to combine the basis DVFs into time-resolved motion fields that represent cine-frame-specific dynamics. STINR-MR was evaluated using MR data simulated from the 4D extended cardiac-torso (XCAT) digital phantom, as well as MR data acquired clinically from a healthy human subject. Its reconstruction accuracy was also compared with that of the model-based non-rigid motion estimation method (MR-MOTUS).Main resultsSTINR-MR can reconstruct 3D cine-MR images with high temporal (<100 ms) and spatial (3 mm) resolutions. Compared with MR-MOTUS, STINR-MR consistently reconstructed images with better image quality and fewer artifacts and achieved superior tumor localization accuracy via the solved dynamic DVFs. For the XCAT study, STINR reconstructed the tumors to a mean±S.D. center-of-mass error of 1.0±0.4 mm, compared to 3.4±1.0 mm of the MR-MOTUS method. The high-frame-rate reconstruction capability of STINR-MR allows different irregular motion patterns to be accurately captured.SignificanceSTINR-MR provides a lightweight and efficient framework for accurate 3D cine-MRI reconstruction. It is a 'one-shot' method that does not require external data for pre-training, allowing it to avoid generalizability issues typically encountered in deep learning-based methods.

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Performance and Material-Dependent Holistic Representation of Unconscious Thought: A Functional Magnetic Resonance Imaging Study.

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