Periodic Reporting for period 3 - WANDERINGMINDS (Not all minds that wander are lost: A neurocognitive test of mind-wandering state’s contribution to human cognition.)
Reporting period: 2018-12-01 to 2020-05-31
This project is focused on identifying the neural and experiential processes that contribute to the mind-wandering state. It uses a combination of experience sampling and measures of neural function as assessed using functional magnetic resonance imaging with the aim of developing a component process account of how mental states evolve across time and people. The project will validate these accounts in terms of their capacity to account for functional outcomes linked to the experiences that occur during mind-wandering such as creativity, problems in concentrating and unhappiness. This project is important because although ongoing thought is both common, and can be a marker for problems such as anxiety and depression, we currently lack a mechanistic understanding of how it operates. The main objectives of this project is to combine the tools of cognitive neuroscience with measures of ongoing thought and well established measures of cognition, to develop a theoretical account of how different types of ongoing thought can elicit the types of consequences that it does.
At this point in the project we have completed the individual difference aspect of our study. In a series of analyses that explore the shared variance associated with brain organisation we have demonstrated that the organisation of the so-called default mode network, conveys important information about the style of mind-wandering that a person engages in. These analyses have confirmed the component process account that asserts that the mind-wandering state entails a state when attention is decoupled from memory (Poerio et al., 2017). We have found that these different types of mind-wandering are related to different patterns of functional outcome. We have found that creative experiences are related to a pattern of spontaneous thought that is distinct from those linked to problems in concentration (wang et al., in press). Our work has also identified that individuals who describe their experiences as having a closer link to their intentions, show closer coupling between the default mode network and areas linked to executive control (Golchert et al., 2017). More generally we have developed an empirically ground account of how the topographical organisation of the cortex impacts upon the of spontaneous thought processes (Margulies et al., 2017).
Our project has made important progress in both furthering our understanding of the nature of ongoing thought, as well as understanding the underlying mechanisms. Our study has highlighted that patterns of neural activity in the default mode network can dissociate individuals in terms of their patterns of ongoing thought. Critically, we found that these patterns of individual difference made unique predictions for individuals associated functional outcomes. This observations suggests that the way that neural processing occurs in the default mode network may be important in the ability to discriminate different types of ongoing thought, providing a potential neural mechanism that may underpin the different types of experience. This work is published in Psychological Science.
In a similar vein, our work on the macroscale patterns of neural function has highlighted that the default mode network, rather than being a task negative network, can instead be understood as a set of regions that sit at the top of a cognitive hierarchy. This observation, published in the Proceedings of the National Academy of Sciences, not only provides a mechanistic account for why this system is involved in patterns of ongoing thought, but explains why this system has a complex heterogenous role in many different cognitive states. This observation therefore provides a neurcognitive description that goes beyond the state of the art.
Moving forward, we anticipate that we will make important headway in understanding the pattern of neural activity that explains why ongoing thought can have both costs and benefits, focusing on the hypothesis that problems in attention describe why this state can impact on the performance of complex external tasks, and we will also explore the hypothesis that problems in emotional regulation explain the associations between ongoing thought and affective disturbance. Data collection and analysis for these strands of the project are currently underway. We also expect to make important advances in understanding the dynamics of ongoing thought by applying hidden markov models to understand the temporal dynamics of ongoing thought. This project is at the point of writing up. Finally, we expect to make important headway in understanding how patterns of ongoing thought can discriminate between psychiatric conditions (such as ADHD, ASD and epilepsy). These projects are currently at the point of data collection, but we anticipate that they will be completed within the next 24 months.
In a similar vein, our work on the macroscale patterns of neural function has highlighted that the default mode network, rather than being a task negative network, can instead be understood as a set of regions that sit at the top of a cognitive hierarchy. This observation, published in the Proceedings of the National Academy of Sciences, not only provides a mechanistic account for why this system is involved in patterns of ongoing thought, but explains why this system has a complex heterogenous role in many different cognitive states. This observation therefore provides a neurcognitive description that goes beyond the state of the art.
Moving forward, we anticipate that we will make important headway in understanding the pattern of neural activity that explains why ongoing thought can have both costs and benefits, focusing on the hypothesis that problems in attention describe why this state can impact on the performance of complex external tasks, and we will also explore the hypothesis that problems in emotional regulation explain the associations between ongoing thought and affective disturbance. Data collection and analysis for these strands of the project are currently underway. We also expect to make important advances in understanding the dynamics of ongoing thought by applying hidden markov models to understand the temporal dynamics of ongoing thought. This project is at the point of writing up. Finally, we expect to make important headway in understanding how patterns of ongoing thought can discriminate between psychiatric conditions (such as ADHD, ASD and epilepsy). These projects are currently at the point of data collection, but we anticipate that they will be completed within the next 24 months.