Computational modeling of working memory decline in normal aging

Research project description

PhD will investigate the effects of aging on brain networks that underlie working memory, using a combination of large-scale computational modeling and analysis of experimental data.  

Behavioral studies generally show a cognitive decline across the adult life span in both human and non-human primates, particularly in working memory tasks. Working memory is the brain mechanism for temporarily storing information, making it a critical cognitive ability for the activities of daily living. The cognitive changes that occur during normal aging appear to result from a combination of structural and functional changes in specific brain areas, inter-area connections, and individual neurons (Luebke et al. 2010; Peters and Keper 2012). However, despite a wealth of experimental data, a coherent theoretical framework of how the various age-related changes to neurons and neural pathways interact and lead to declines in working memory is currently lacking. 

The main objective of this project is to develop a large-scale computational neural network model to fill this gap and reveal the functional consequences of age-related neuronal and connectivity changes on cognitive function. We will use new targeted analyses of a large dataset of 40 rhesus monkeys (young, middle-aged and aged), gathered by our collaborators in Boston University, to constrain realistic large-scale computational models of normal brain aging. The driving scientific question of this project is to advance our understanding of how age-related changes in inter-area communication impact neuronal network dynamics of working memory circuits and ultimately lead to disruption of neuronal networks that mediate behavioral function.  

We expect the project will reveal mechanisms that may compensate for age-related changes to restore function at the cellular, circuit and, ultimately, cognitive level. It has thus broad implications for strategies to enhance brain function in normal aging.

Academic background / Skills

Candidates must hold a degree that allows admission to the official doctoral programme at UAB.  

Additional requirements for a stronger application are: 

• We are looking for a graduate student motivated to pursue a PhD thesis in computational neuroscience. As outlined above, the idea is to study the effects of aging on brain networks that underlie working memory and decision making, using a combination of large-scale computational modeling and analysis of experimental data obtained by a collaborating experimental laboratory.  
• The ideal candidate has strong quantitative skills (mathematics, physics and related disciplines) and a keen interest in neurobiology.

Research group/s description

The computational neuroscience unit at the CRM was founded in 2012 and is made up of five Principal Investigators (Alex Roxin, Klaus Wimmer, Alex Hyafil, Toni Guillamon and Gemma Huguet) and their groups. The unit is an active member of a larger, Barcelona-wide Neuroscience community which includes theoretical, experimental, and clinical groups located in a variety of university departments and research centers.  

Research in the computational neuroscience unit is largely focused on systems-level neuroscience. Broadly speaking, this involves investigating how large assemblies of interacting neurons give rise to animal and human behavior. Our approach is generally to combine computational modeling with data analysis. 

We offer a rich scientific environment at the CRM and in the Barcelona computational and systems neuroscience community. A research stay in the experimental lab is possible (and encouraged).