iScience
February 2, 2021
Jonathan Smallwood, Adam Turnbull, Hao-ting Wang et al.
130 citations
A core goal in cognitive neuroscience is identifying the physical substrates of the patterns of thought that occupy our daily lives. Contemporary views suggest that the landscape of ongoing experience is heterogeneous and can be influenced by features of both the person and the context. This perspective piece considers recent work that explicitly accounts for both the heterogeneity of the...
Scientific Reports
December 3, 2020
Theodoros Karapanagiotidis, Diego Vidaurre, Andrew J. Quinn et al.
82 citations
When unoccupied by an explicit external task, humans engage in a wide range of different types of self-generated thinking. These are often unrelated to the immediate environment and have unique psychological features. Although contemporary perspectives on ongoing thought recognise the heterogeneity of these self-generated states, we lack both a clear understanding of how to classify the...
Neuroimage
June 22, 2020
Brontë Mckeown, Will Strawson, Hao-ting Wang et al.
102 citations
Contemporary accounts of ongoing thought recognise it as a heterogeneous and multidimensional construct, varying in both form and content. An emerging body of evidence demonstrates that distinct types of experience are associated with unique neurocognitive profiles, that can be described at the whole-brain level as interactions between multiple large-scale networks. The current study sought to...
Nature Communications
August 23, 2019
Adam Turnbull, Hao-ting Wang, Charlotte Murphy et al.
197 citations
When environments lack compelling goals, humans often let their minds wander to thoughts with greater personal relevance; however, we currently do not understand how this context-dependent prioritisation process operates. Dorsolateral prefrontal cortex (DLPFC) maintains goal representations in a context-dependent manner. Here, we show this region is involved in prioritising off-task thought in...
Andrew J. Anderson, Adam Turnbull, Feng V. Lin
preprint
Abstract The human brain’s capacity to imagine visual scenes from memory is thought to rely on the medial temporal subsystem of the default mode network (MT-DMN), yet the neural codes supporting this ability remain poorly understood. We combined functional magnetic resonance imaging (fMRI) with vision and language artificial intelligence models to characterize neural codes during...