Biology subjects

Spreng, N.

Publications and source records attributed to Spreng, N..

6 recordsLinked to original sources

bioRxiv2026

Novelty-seeking and directed exploration scale with dissociable social network outcomes and brain systems in older adults

Social isolation and loneliness are major determinants of well-being in older adults. Shrinking social networks and age-related shifts in social behavior and decision-making may increase vulnerability to loneliness. These changes in social decision-making strategies can be conceptualized within an exploration-exploitation tradeoff framework, in which social options with known outcomes are prioritized over uncertain ones. Yet, no study has characterized how complementary decision-making strategies, undirected novelty seeking and goal-directed exploration, relate to social network constructs or are supported by distinct neural systems. These strategies capture distinct forms of decision-making: undirected novelty seeking is driven by the intrinsic salience of novel options independent of expected informational gain, whereas goal-directed exploration involves deliberately sampling uncertain options to reduce uncertainty and optimize future choices. Here, we used fMRI and a novel social bandit reinforcement task to identify dissociable social constructs and brain systems linked to undirected novelty seeking and goal-directed exploration in older adults. Undirected novelty seeking was associated with social network size and with activity of temporoparietal and mid-cingulate brain areas. Goal-directed exploration predicted subjective feelings of social connectedness and was associated with activity of anterior cingulate and prefrontal brain areas. Crucially, choice probabilities from a non-social version of the three-arm bandit task were not associated with social decision-making nor with social constructs. Our findings suggest that, in later life, dissociable social decision-making strategies, when faced with unknown options, rely on distinct neural systems supporting social network size as well as subjective feelings of social connectedness.

neuroscience↗

bioRxiv2025

State dependent shifts in large scale functional topographies

Although functional networks can be consistently identified across cognitive states, they also undergo dynamic reconfigurations across different contexts. For example, naturalistic movie watching paradigms amplify activity in sensory systems compared to resting conditions. However, it remains unclear how these different states affect large-scale brain organization. The current study leveraged high-resolution in vivo 7T fMRI data from the Human Connectome Project (HCP) and the Precision NeuroImaging (PNI) datasets to examine large scale functional connectivity changes between resting and movie-watching conditions. To understand these changes within topographic and geometric principles of brain organization, connectivity shifts were stratified relative to macroscale cortical hierarchy and geodesic distance. Our results revealed that primary sensory areas showed increased local connectivity and reduced long-range interactions during movie watching relative to resting conditions, whereas the default mode network (DMN) exhibited an opposing pattern characterized by reduced within-network long-range connectivity and enhanced connectivity with distant regions outside the DMN. Together, these findings demonstrate that different cognitive states involve geometry-and hierarchy-informed reorganization of large-scale functional networks.

neuroscience↗

bioRxiv2023

Ventromedial Frontoinsular Connectivity is Associated with Long-term Smoking Behavior Change in Aging

A central question in the field of cognitive aging and behavioral neuroscience is what enables some individuals to successfully change their behavior more than others? Smoking is a significant risk factor for cognitive decline, particularly in vulnerable populations, including those who are at an elevated risk for Alzheimers disease (AD). Developing effective smoking reduction strategies is therefore a public health priority. The goal of the current study is to better understand the brain mechanisms underlying long-term smoking behavior change in cognitively normal, but at-risk, older adults. Neuroimaging and human lesional studies have implicated the insula and its functional network in subjective interoceptive awareness of cigarette craving and smoking-cue reactivity. We sought to characterize the extent to which anterior insular resting-state functional connectivity MRI predicted long-term smoking reduction (mean: 2.7 years, range 8 months - 4 years) using a seed-to-voxel approach. Twenty-three (18 women; 26% APOE4 carriers; 61.5 years, SD = 3.7) cognitively unimpaired older individuals who smoked cigarettes at their baseline visit and have a first-degree family history of AD (at least one parent or multiple siblings affected) were included from a prospective longitudinal cohort, PREVENT-AD (Pre-symptomatic Evaluation of Experimental or Novel Treatments for Alzheimer Disease) in the current study. We found that reduced long-term smoking behavior was associated with diminished functional connectivity between bilateral anterior insula and ventromedial prefrontal cortex (vmPFC). In a second pre-registered replication study within a larger, independent sample of one hundred and eighteen cognitively normal older adults who smoked cigarettes at baseline from the UK Biobank (73 women; 27.9 % APOE4 carriers; 60.3 years, SD = 2.7), we found that baseline diminished resting-state functional connectivity between anterior insula and vmPFC predicted long-term smoking reduction (mean 5.2 years; ranging from 3 years to 7 years). To our knowledge, this is the largest study to examine the neural substrates of long-term smoking cessation in human aging. Our results suggest that frontoinsular circuits may be a therapeutic target for smoking reduction and disease prevention in older adults at risk for AD.

neuroscience↗

bioRxiv2022

The neural basis of cost-benefit trade-offs in effort investment: a quantitative activation likelihood estimation meta-analysis

Influential theories of cognitive effort-based decision-making suggest that a cost-benefit trade-off guides mental effort allocation and that this trade-off may be reflected in shared neural activity in circuits tracking potential reward and task demand, supporting the idea that. While the dorsal medial prefrontal cortex (mPFC) - and particularly the anterior cingulate cortex (dACC) - has been proposed as a candidate region implementing this computation, it remains unclear whether mPFC/dACC activity tracks rewards and task demand independently or integrates them to reflect effort intensity. Recent accounts posit that the dACC plays a key role in mediating cost-benefit trade-offs. However, empirical evidence remains inconsistent. We conducted a systematic meta-analysis of neuroimaging studies, using the activation-likelihood estimation method to quantify brain activity across 45 studies (N = 1273 participants) investigating choices and task performance in reward-guided cognitive control. We observed significant recruitment of the mPFC/dACC, putamen, and anterior insula for processing larger rewards and higher task demands. The mPFC/dACC clusters sensitive to task demands and rewards were anatomically distinct: caudal mPFC/dACC activity tracked increasing task demands, while rostral mPFC/dACC activity tracked increasing reward. Interestingly, caudal mPFC/dACC activity tracked the integration of reward and task-demand, compatible with cost-benefit trade-off theories of dACC function. These findings provide evidence for distinct signals for mental demand and reward in the mPFC/dACC, which are integrated to support the decision to invest mental effort.

neuroscience↗

bioRxiv2021

Individual-Specific Areal-Level Parcellations Improve Functional Connectivity Prediction of Behavior

Resting-state functional MRI (rs-fMRI) allows estimation of individual-specific cortical parcellations. We have previously developed a multi-session hierarchical Bayesian model (MS-HBM) for estimating high-quality individual-specific network-level parcellations. Here, we extend the model to estimate individual-specific areal-level parcellations. While network-level parcellations comprise spatially distributed networks spanning the cortex, the consensus is that areal-level parcels should be spatially localized, i.e., should not span multiple lobes. There is disagreement about whether areal-level parcels should be strictly contiguous or comprise multiple non-contiguous components, therefore we considered three areal-level MS-HBM variants spanning these range of possibilities. Individual-specific MS-HBM parcellations estimated using 10min of data generalized better than other approaches using 150min of data to out-of-sample rs-fMRI and task-fMRI from the same individuals. Resting-state functional connectivity (RSFC) derived from MS-HBM parcellations also achieved the best behavioral prediction performance. Among the three MS-HBM variants, the strictly contiguous MS-HBM (cMS-HBM) exhibited the best resting-state homogeneity and most uniform within-parcel task activation. In terms of behavioral prediction, the gradient-infused MS-HBM (gMS-HBM) was numerically the best, but differences among MS-HBM variants were not statistically significant. Overall, these results suggest that areal-level MS-HBMs can capture behaviorally meaningful individual-specific parcellation features beyond group-level parcellations. Multi-resolution trained models and parcellations are publicly available (https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/brain_parcellation/Kong2022_ArealMSHBM).

neuroscience↗

bioRxiv2020

LSD flattens the functional hierarchy of the human brain

LSD and psilocybin are serotonergic psychedelic compounds with potential in the treatment of mental health disorders. Past neuroimaging investigations have revealed that both compounds can elicit significant changes to whole-brain functional organization and dynamics. A recent proposal linked past findings into a unified model and hypothesized reduced whole-brain hierarchical organization as a key mechanism underlying the psychedelic state, but this has yet to be directly tested. We applied a non-linear dimensionality reduction technique previously used to map hierarchical connectivity gradients to pharmacological resting-state fMRI data to assess cortical organization in the LSD and psilocybin state. Results supported our primary hypothesis: The principal gradient of cortical connectivity, describing a hierarchy from unimodal to transmodal cortex, was significantly flattened under both drugs relative to their respective placebo conditions. Between-condition contrasts revealed that this was driven by a reduction of functional differentiation at both hierarchical extremes - default and frontoparietal networks at the upper end, and somatomotor at the lower. Gradient-based connectivity mapping confirmed that this was underpinned by increased unimodal-transmodal crosstalk. In addition, LSD-dependent principal gradient changes tracked changes in self-reported ego-dissolution. Results involving the second and third gradient, which respectively represent axes of sensory and executive differentiation, also showed significant alterations across both drugs. These findings provide support for a recent mechanistic model of the psychedelic state relevant to therapeutic applications of psychedelics. More fundamentally, we provide the first evidence that macroscale connectivity gradients are sensitive to a pharmacological manipulation, specifically highlighting an important relationship between cortical organization and serotonergic modulation.

neuroscience↗