H2020Индивидуална стипендия2018–2020

BrainBehaviourModel · Understanding decision making by linking brain and behaviour

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период: 2018-06-01 → 2020-05-31
Финансиране от ЕС: 165 599 €
Участници: 1
Схема: MSCA-IF-EF-ST

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Накратко на български

Връзката между мозъчната активност и вземането на решения се анализира чрез математически модели, например при избора дали е безопасно да се пресече улицата. Това помага да се разбере как конкретни процеси в мозъка влияят върху когнитивни параметри, свързани с IQ или ADHD.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

Understanding decision making by linking brain and behaviour

Decision-making is an integral part of our daily lives. We regularly face decisions in simple and more complex situations: “Is it safe to cross the road?” or “Should I buy this house?”. Even if an optimal choice might exist objectively, people vary in decision-making behaviour due to differences in the information that they pick up, personal goals and preferences, and traits such as impulsivity or reasoning ability. One of the challenges for researchers in the field of cognitive neuroscience is that we can only observe the outcome of someone’s decision. We cannot directly measure the (unconscious) thought process that led to it. Over the last few decades, insightful mathematical models have been developed that allow us to estimate hidden cognitive parameters that influence our behaviour, such as the rate of evidence accumulation and the decision threshold. Individual values of these parameters may serve as markers for working memory capacity and IQ, as well as for clinical symptoms such as ADHD, high-anxiety and depression. Yet, we are only starting to grasp how cognitive parameters are encoded in terms of brain activity. While we know that individual values of cognitive parameters correlate with metabolic changes (fMRI-BOLD responses) and with the amplitude of electrophysiological signals (EEG) from specific brain regions, we do not understand how brain regions work together to control our decision-making behaviour. The main objective of the research project is to shed light on the neurobiological processes underlying cognitive parameters. It combines mathematical models of decision-making behaviour with computational models of brain activity that can explain how measured EEG activity may arise from synaptic interactions between brain regions. Furthermore, the project places special emphasis on the role of the basal ganglia, a network of nuclei that are located deeply inside the brain that are considered to be pivotal for action selection. Understanding the exchange of information between basal ganglia nuclei and the cortex is important for optimization of deep brain stimulation treatment in neurological and psychiatric disorders such as Parkinson’s disease and obsessive-compulsive disorder, where disturbances in decision-making behaviour may strongly affect the quality of life.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

Why do some people make decisions impulsively while others are more cautious? The answer may lie in individual differences in synaptic connectivity strengths within the underlying brain network. Previous work has found correlations between aspects of the decision making process and BOLD or electrophysiological responses. However, a proper mechanistic and biological explanation is still missing. This is nevertheless crucial for understanding how neurotransmitter systems influence behaviour and lead to impulse control disorders, addiction, or eating disorders. To reach this aim, I propose to combine state-of-the-art cognitive models with likewise state-of-the-art models of neural responses. My ‘BrainBehaviour model’ will link cognitive factors that influence behaviour with synaptic connectivity patterns that give rise to neuroimaging findings.Using this model, I will first analyse high-resolution (7T) fMRI data of subjects performing a stop-signal task. I will then turn to a novel data set comprising local field potential recordings obtained from deep brain stimulation electrodes implanted in the subthalamic nucleus for treatment of Parkinson’s disease, in combination with simultaneous MEG. After model inversion, the estimated parameters will be used to test specific hypotheses on the role of the hyperdirect, indirect, and direct pathways in movement inhibition.The project is not only at the forefront of cognitive and computational neuroscience but it also offers invaluable training experiences, including the opportunity to work with high-tech imaging data (7T fMRI), mastering dynamic causal modelling, learning how to apply advanced cognitive models, and a good number of transferable skills like teaching and student supervision. The latter will result in an official teaching certificate that is compulsory for all university lecturers in the Netherlands. Granting this proposal will be a vital step for progressing my career beyond the current postdoctoral level.

Оригинален текст от CORDIS (на английски).

Участници

UNIVERSITEIT VAN AMSTERDAM · AmsterdamКоординаторНидерландия