Reduced Semantic Control in Older Adults is Linked to Intrinsic DMN Connectivity

Ageing provides an interesting window into semantic cognition: while younger adults generally outperform older adults on many cognitive tasks, knowledge continues to accumulate over the lifespan and consequently, the semantic store (i.e., vocabulary size) remains stable (or even improves) during healthy ageing. Semantic cognition involves the interaction of at least two components – a semantic store and control processes that interact to ensure efficient and context-relevant use of representations. Given older adults perform less well on tasks measuring executive control, their ability to access the semantic store in a goal driven manner may be compromised. Older adults also consistently show reductions in intrinsic brain connectivity, and we examined how these brain changes relate to age-related changes in semantic performance. We found that while older participants outperformed their younger counterparts on tests of vocabulary size (i.e., NART), younger participants were faster and more accurate in tasks requiring semantic control, and these age differences correlated with measures of intrinsic connectivity between the anterior temporal lobe (ATL) and medial prefrontal cortex (mPFC), within the default mode network. Higher intrinsic connectivity from right ATL to mPFC at rest related to better performance on verbal (but not picture) semantic tasks, and older adults showed an exaggerated version of this pattern, suggesting that this within-DMN connectivity may become more important for conceptual access from words as we age. However, this appeared to be at the expense of control over semantic retrieval – there was little relationship between connectivity and performance for strong associations in either group, but older adults with stronger connectivity showed particularly inefficient retrieval of weak associations. Older adults may struggle to harness the default mode network to support demanding patterns of semantic retrieval, resulting in a performance cost

Robust prediction of individual creative ability from brain functional connectivity

People’s ability to think creatively is a primary means of technological and cultural progress, yet the neural architecture of the highly creative brain remains largely undefined. Here, we employed a recently developed method in functional brain imaging analysis—connectome-based predictive modeling—to identify a brain network associated with high-creative ability, using functional magnetic resonance imaging (fMRI) data acquired from 163 participants engaged in a classic divergent thinking task. At the behavioral level, we found a strong correlation between creative thinking ability and self-reported creative behavior and accomplishment in the arts and sciences (r = 0.54). At the neural level, we found a pattern of functional brain connectivity related to high-creative thinking ability consisting of frontal and parietal regions within default, salience, and executive brain systems. In a leave-one-out cross-validation analysis, we show that this neural model can reliably predict the creative quality of ideas generated by novel participants within the sample. Furthermore, in a series of external validation analyses using data from two independent task fMRI samples and a large task-free resting-state fMRI sample, we demonstrate robust prediction of individual creative thinking ability from the same pattern of brain connectivity. The findings thus reveal a whole-brain network associated with high-creative ability comprised of cortical hubs within default, salience, and executive systems—intrinsic functional networks that tend to work in opposition—suggesting that highly creative people are characterized by the ability to simultaneously engage these large-scale brain networks

Investigating the neural correlates of ongoing experience

Spontaneous thoughts are heterogeneous and inherently dynamic. Despite their time-variant properties, studies exploring spontaneous thoughts have identified thematic patterns that exhibit trait-like characteristics and are stable across time. Concurrently, structural and functional neuroimaging studies have shown unique and stable whole-brain network configurations linked to behaviour either through the static and dynamic intrinsic communication and activity of their core regions or through informational exchange with each other. This thesis aimed to explore how these within and between network interactions at different temporal scales might relate to variations in ongoing experience. We utilised different neuroimaging modalities (diffusion weighted and functional magnetic resonance imaging) and applied both static and dynamic analyses techniques. We found evidence of inter-individual variation in all cases associated with different patterns of spontaneous thoughts. Experiment 1 found that variation in white matter architecture projecting to the hippocampus, as well as the stable functional interaction of the hippocampus with the medial prefrontal cortex were linked to the tendency of experiencing thoughts related to the future or the past. Experiment 2 found that static functional connectivity of the precuneus and a lateral fronto-temporal network was related to visual imagery. Furthermore, we found that coupling of a lateral visual network with regions of the brainstem and cerebellum was associated with ruminative thinking, self-consciousness and attentional problems. Importantly, our results highlighted an interaction among these associations, where the brainstem visual network coupling moderated the relationship between parietal-frontal regions and reports of visual imagery. Finally, Experiment 3 used hidden Markov modelling to identify dynamic neural states linked to thoughts related to problem-solving and less intrusive thinking, as well as better physical and mental health. Collectively, these studies highlight the utility of using both static and dynamic measures of neural function to understand patterns of ongoing experience

The disentanglement of the neural and experiential complexity of self-generated thoughts : A users guide to combining experience sampling with neuroimaging data

Human cognition is not limited to the processing of events in the external environment, and the covert nature of certain aspects of the stream of consciousness (e.g. experiences such as mind-wandering) provides a methodological challenge. Although research has shown that we spend a substantial amount of time focused on thoughts and feelings that are intrinsically generated, evaluating such internal states, purely on psychological grounds can be restrictive. In this review of the different methods used to examine patterns of ongoing thought, we emphasise how the process of triangulation between neuroimaging techniques, with self-reported information, is important for the development of a more empirically grounded account of ongoing thought. Specifically, we show how imaging techniques have provided critical information regarding the presence of covert states and can help in the attempt to identify different aspects of experience

The structural basis of semantic control: Evidence from individual differences in cortical thickness

Semantic control allows us to shape our conceptual retrieval to suit the circumstances in a flexible way. Tasks requiring semantic control activate a large-scale network including left inferior prefrontal gyrus (IFG) and posterior middle temporal gyrus (pMTG) – this network responds when retrieval is focussed on weak as opposed to dominant associations. However, little is known about the biological basis of individual differences in this cognitive capacity: regions that are commonly activated in task-based fMRI may not relate to variation in controlled retrieval. The current study combined analyses of MRI-based cortical thickness with resting-state fMRI connectivity to identify structural markers of individual differences in semantic control. We found that participants who performed relatively well on tests of controlled semantic retrieval showed increased structural covariance between left pMTG and left anterior middle frontal gyrus (aMFG). This pattern of structural covariance was specific to semantic control and did not predict performance when harder non-semantic judgements were contrasted with easier semantic judgements. The intrinsic functional connectivity of these two regions forming a structural covariance network overlapped with previously-described semantic control regions, including bilateral IFG and intraparietal sulcus, and left posterior temporal cortex. These results add to our knowledge of the neural basis of semantic control in three ways: (i) Semantic control performance was predicted by the structural covariance network of left pMTG, a site that is less consistently activated than left IFG across studies. (ii) Our results provide further evidence that semantic control is at least partially separable from domain-general executive control. (iii) More flexible patterns of memory retrieval occurred when pMTG co-varied with distant regions in aMFG, as opposed to nearby visual, temporal or parietal lobe regions, providing further evidence that left prefrontal and posterior temporal areas form a distributed network for semantic control

Distinct individual differences in default mode network connectivity relate to off-task thought and text memory during reading

Often, as we read, we find ourselves thinking about something other than the text; this tendency to mind-wander is linked to poor comprehension and reduced subsequent memory for texts. Contemporary accounts argue that periods of off-task thought are related to the tendency for attention to be decoupled from external input. We used fMRI to understand the neural processes that underpin this phenomenon. First, we found that individuals with poorer text-based memory tend to show reduced recruitment of left middle temporal gyrus in response to orthographic input, within a region located at the intersection of default mode, dorsal attention and frontoparietal networks. Voxels within these networks were taken as seeds in a subsequent resting-state study. The default mode network region (i) had greater connectivity with medial prefrontal cortex, falling within the same network, for individuals with better text-based memory, and (ii) was more decoupled from medial visual regions in participants who mind-wandered more frequently. These findings suggest that stronger intrinsic connectivity within the default mode network is linked to better text processing, while reductions in default mode network coupling to the visual system may underpin individual variation in the tendency for our attention to become disengaged from what we are reading

Distinct patterns of thought mediate the link between brain functional connectomes and well-being

Ongoing thought patterns constitute important aspects of both healthy and abnormal human cognition. However, the neural mechanisms behind these daily experiences and their contribution to well-being remain a matter of debate. Here, using resting-state fMRI and retrospective thought sampling in a large neurotypical cohort (n = 211), we identified two distinct patterns of thought, broadly describing the participants’ current concerns and future plans, that significantly explained variability in the individual functional connectomes. Consistent with the view that ongoing thoughts are an emergent property of multiple neural systems, network-based analysis highlighted the central importance of both unimodal and transmodal cortices in the generation of these experiences. Importantly, while state-dependent current concerns predicted better psychological health, mediating the effect of functional connectomes, trait-level future plans were related to better social health, yet with no mediatory influence. Collectively, we show that ongoing thoughts can influence the link between brain physiology and well-being

The neural dynamics of individual differences in episodic autobiographical memory

The ability to mentally travel to specific events from one’s past, dubbed episodic autobiographical memory (E-AM), contributes to adaptive functioning. Nonetheless, the mechanisms underlying its typical interindividual variation remain poorly understood. To address this issue, we capitalize on existing evidence that successful performance on E-AM tasks draws on the ability to visualize past episodes and reinstate their unique spatiotemporal context. Hence, here, we test whether features of the brain’s functional architecture relevant to perceptual versus conceptual processes shape individual differences in both self-rated E-AM and laboratory-based episodic memory (EM) for random visual scene sequences (visual EM). We propose that superior subjective E-AM and visual EM are associated with greater similarity in static neural organization patterns, potentially indicating greater efficiency in switching, between rest and mental states relevant to encoding perceptual information. Complementarily, we postulate that impoverished subjective E-AM and visual EM are linked to dynamic brain organization patterns implying a predisposition towards semanticizing novel perceptual information. Analyses were conducted on resting state and task-based fMRI data from 329 participants (160 women) in the Human Connectome Project (HCP) who completed visual and verbal EM assessments, and an independent gender diverse sample (N = 59) who self-rated their E-AM. Interindividual differences in subjective E-AM were linked to the same neural mechanisms underlying visual, but not verbal, EM, in general agreement with the hypothesized static and dynamic brain organization patterns. Our results suggest that higher E-AM entails more efficient processing of temporally extended information sequences, whereas lower E-AM entails more efficient semantic or gist-based processing