Biology subjects

Bäckman, L.

Publications and source records attributed to Bäckman, L..

4 recordsLinked to original sources

bioRxiv2024

Brain-Cognitive Gaps in relation to Dopamine and Health-related Factors: Insights from AI-Driven Functional Connectome Predictions

A key question in human neuroscience is to understand how individual differences in brain function relate to cognitive differences. However, the optimal condition of brain function to study between-person differences in cognition remains unclear. While many studies have developed objective biomarkers to accurately predict intelligence and general cognition, consensus on domain-specific markers has not yet emerged. Brain age has been proposed as a potential candidate, but recent research suggests that brain age offers minimal additional information on cognitive decline beyond what chronological age provides, prompting a shift toward approaches focused directly on cognitive prediction. Using a deep learning approach, we evaluated the predictive power of the functional connectome during various states (resting state, movie-watching, and n-back) on episodic memory and working memory performance. Our findings show that while connectomes during task, especially during movie watching, better predict both episodic and working memory, resting state connectomes are equally effective in predicting episodic memory. Furthermore, individuals with a negative brain-cognition gap (where brain predictions underestimate actual performance) exhibited lower physical activity and higher cardiovascular risk compared to those with a positive gap. This shows that knowledge of the brain-cognition gap provides insights into factors contributing to cognitive resilience. Further lower PET-derived measures of dopamine binding were linked to a greater brain-cognition gap, mediated by regional functional variability. Together, our findings highlight the importance of brain state in connectome-based cognitive prediction and introduce the brain cognitive gap as a potentially informative, dopamine-modulated marker of vulnerability to compromise brain function.

neuroscience↗

bioRxiv2023

The iron-dopamine D1 coupling modulates neural signatures of working memory across adulthood

Brain iron overload and decreased integrity of the dopaminergic system have been independently reported as brain substrates of cognitive decline in aging. Dopamine (DA), and iron are co-localized in high concentrations in the striatum and prefrontal cortex (PFC), but follow opposing age-related trajectories across the lifespan. DA contributes to cellular iron homeostasis and the activation of D1-like DA receptors (D1DR) alleviates oxidative stress-induced inflammatory responses, suggesting a mutual interaction between these two fundamental components. Still, a direct in-vivo study testing the iron-D1DR relationship and their interactions on brain function and cognition across the lifespan is rare. Using PET and MRI data from the DyNAMiC study (n=180, age=20-79, %50 female), we showed that elevated iron content was related to lower D1DRs in DLPFC, but not in striatum, suggesting that dopamine-rich regions are less susceptible to elevated iron. Critically, older individuals with elevated iron and lower D1DR exhibited less frontoparietal activations during the most demanding task, which in turn was related to poorer working-memory performance. Together, our findings suggest that the combination of elevated iron load and reduced D1DR contribute to disturbed PFC-related circuits in older age, and thus may be targeted as two modifiable factors for future intervention. HighlightsO_LIFirst study demonstrating the association between regional iron and dopamine D1DR in adult humans. C_LIO_LIThe interplay between age-related elevated iron and diminished D1DR explained lower task-related brain activity, which in turn was related to poorer task performance. C_LIO_LIOur findings iron-DA coupling can help progress the understanding of the mechanisms behind DA-related neurodegeneration. C_LI

neuroscience↗

bioRxiv2022

Bi-phasic patterns of age-related differences in dopamine D1 receptors across the adult lifespan

The dopamine (DA) system, particularly D1-like DA receptors (D1DR), declines across the adult life. The functional consequences of reduced D1DR has been hypothesized to vary across life periods, but the precise timing of these periods is unknown. To examine distinct phases in age-related D1DR reductions, we studied 180 healthy adults (90 females, 20-80 years), who underwent D1DR PET assessment using [11C]SCH23390. A bi-phasic pattern of age-related D1DR differences was revealed, with an inflection point at approximately 40 years of age. Notably, D1DR levels before and after the inflection showed opposing relations to neurocognitive functions, in concordance with distinct consequences of D1DR differences during development and in old age. Furthermore, D1DR reductions in later life were linked to age-related cerebrovascular consequences. These results support a distinction between D1DR reductions in early adulthood from those later in life, and suggest less dramatic and more malleable DA losses in aging than previously suggested.

neuroscience↗

bioRxiv2022

Dynamic regulation of neural variability during working memory reflects dopamine, functional integration, and decision-making

The regulation of moment-to-moment neural variability may permit effective responses to changing cognitive demands. However, the mechanisms that support variability regulation are unknown. In the context of working memory, we leverage the largest available PET and fMRI dataset to jointly consider three lenses through which neural variability regulation could be understood: dopamine capacity, network-level functional integration, and flexible decision processes. We show that with greater working memory load, upregulation of variability was associated with elevated dopamine capacity and heightened functional integration, effects dominantly expressed in the striato-thalamic system rather than cortex. Strikingly, behavioral modeling revealed that working memory load evoked substantial decision biases during evidence accumulation, and those who jointly expressed a more optimal decision bias and higher dopamine capacity were most likely to upregulate striato-thalamic variability under load. We argue that the ability to align striato-thalamic variability to level of demand may be a hallmark of a well-functioning brain.

neuroscience↗