Cortical Microstructural Integrity is Associated with Decision-Making Biases in Older Adulthood

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Abstract Submission 

Patrick Hewan¹, Alfie Wearn², Roel van Dooren³, Lindsay Wyatt¹, Ilana Leppert⁴, Giulia Baracchini⁵, Colleen Hughes², Jennifer Tremblay-Mercier⁶, Elisabeth Sylvain⁶, Judes Poirier⁶, Sylvia Villeneuve⁷, Christine Tardif⁴, R. Nathan Spreng⁸, Gary Turner¹

¹York University, Toronto, Ontario, ²McGill University, Montreal, Québec, ³Institutes of Psychology & Brain and Cognition, Leiden University, The Netherlands, Leiden, South Holland, ⁴McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, Quebec, ⁵Montreal Neurological Institute and Hospital, Montreal, Quebec, ⁶Douglas Mental Health University Institute, Montreal, Québec, ⁷Brain Imaging Centre, Douglas Institute Research Centre, Montreal, Qc, ⁸Montreal Neurological Institute, McGill University, Montreal, Quebec

Patrick Hewan  
York University
Toronto, Ontario

Alfie Wearn  
McGill University
Montreal, Québec

Roel van Dooren  
Institutes of Psychology & Brain and Cognition, Leiden University, The Netherlands
Leiden, South Holland

Lindsay Wyatt  
York University
Toronto, Ontario

Ilana Leppert  
McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital
Montreal, Quebec

Giulia Baracchini  
Montreal Neurological Institute and Hospital
Montreal, Quebec

Colleen Hughes  
McGill University
Montreal, Québec

Jennifer Tremblay-Mercier  
Douglas Mental Health University Institute
Montreal, Québec

Elisabeth Sylvain  
Douglas Mental Health University Institute
Montreal, Québec

Judes Poirier  
Douglas Mental Health University Institute
Montreal, Québec

Sylvia Villeneuve  
Brain Imaging Centre, Douglas Institute Research Centre
Montreal, Qc

Christine Tardif  
McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital
Montreal, Quebec

R. Nathan Spreng  
Montreal Neurological Institute, McGill University
Montreal, Quebec

Gary Turner  
York University
Toronto, Ontario

The exploration-exploitation (EE) trade-off is a decision-making process that relies on cortical regions involved in reward processing and monitoring, and their integration with subcortical nuclei involved in attention and learning¹. In recent work, we used quantitative MRI (qMRI) to examine the microstructural integrity of the locus coeruleus (LC), a core subcortical node in the EE circuit, and showed that this brain measure robustly predicts performance on a foraging-based measure of EE². Here, we investigated whether a similar relationship exists across cortical regions implicated in EE, examining cellular microstructure as related to foraging performance in medial orbitofrontal cortex (mOFC), rostral middle frontal gyrus (rMFG), frontopolar cortex (FPC), and dorsal anterior cingulate cortex (dACC)-core cortical regions identified in a recent meta-analysis from our lab³ and related theoretical models^1,4. We predicted that lower integrity would be associated with sub-optimal decision-making performance, marked by an exploitation-bias in older adulthood⁵.

PARTICIPANTS: 132 cognitively healthy older adults (mean age 70s, 68% female) from the PREVENT-AD cohort⁶.

BEHAVIORAL TASK⁷: A computerized foraging task. Participants control an avatar and forage for points within 5 minutes. NEUROIMAGING PROTOCOL: MRI scans were acquired on a 3T Siemens PrismaFit including: T1w MPRAGE (1mm isotropic, TR/TE/TI=2300/2.96/900ms, FA=9°); Three multi-echo sequences (1mm isotropic, total TA=17:30) with predominant weighting for: T1 (TR=18ms, 6 echoes, TE=2.16-14.81ms, FA 20°), magnetization transfer (MT) (TR=27ms, 6 echoes, TE=2.04-14.89ms, FA 6°, MT pulse FA 540°, 2.2kHz off-resonance, 12.8ms) and proton density (TR=27ms, 8 echoes, TE=2.04-22.20ms, echo-spacing=2.57ms, FA 6°). IMAGE PROCESSING: MTsat maps were calculated using the hMRI toolbox⁸. Cortical ROIs were defined using the Desikan-Killiany atlas⁹.

ANALYSIS: Marginal value theorem determined optimal foraging performance on a group level¹⁰. Partial correlations were conducted between core regions, a cortical control region not predicted to be associated with EE, and foraging performance. Partial correlations controlled for age, gender, education, brain volume, cortical thickness in each ROI, and MTsat in the corpus callosum to control for generalized age-related changes in MTsat.

MTsat values in the mOFC, rMFG, and FPC were significantly correlated with task performance (mOFC: pr(126) = 0.19, p < 0.05; rMFG: pr(126) = 0.25, p < 0.01, FPC: pr(126) = 0.19, p < 0.05 while dACC was not significant (pr(126) = 0.14, p = 0.13). Additionally, there was no correlation between MTsat and foraging performance in the lateral occipital cortex (LO; pr(126) = 0.07, p= 0.4), a region we predicted not to be associated with foraging performance.

We examined whether the integrity of core cortical regions previously implicated in EE decision-making is associated with performance on a foraging task. As predicted, qMRI-derived MTsat values were significantly and positively correlated with EE decision-making in the mOFC, rMFG, and FPC, with a similar trend observed for dACC, all core EE decision-making nodes. In contrast, MTsat in the LO, a cortical control region not previously implicated in EE, was not related to EE performance. Specifically, lower MTsat values in EE regions were associated with increased exploitation, replicating a recent finding in LC². Critically, no behavioural associations were observed with grey matter volume in these EE regions, nor when controlling for volumes in our correlation models with MTsat. MTsat as measured by qMRI is a promising marker of the integrity of this cortico-subcortical circuit, providing a novel lens on the neural mechanisms underlying changes in decision-making performance, and the emergence of a exploitation bias in later life⁵.

Decision Making ¹

Aging ²

Aging

STRUCTURAL MRI

Other - QUANTITATIVE MRI