Neural and developmental correlates of social influence

  • Amsterdam
  • This position has been filled

connected_mindz Connected Minds Lab

People often rely on others when making decisions, by for example copying other’s decisions or adapting their own decision into the direction of someone else’s. In this project, we will investigate on whom people rely on and when. For example, we hypothesize that people will rely more on friends or confident others.

We will research this from a developmental perspective, asking whether social information use and, importantly, neural patterns change over the course of adolescence.

An internship in our lab offers students the possibility to become acquainted with fMRI techniques and developmental research. The student will experience academic research by combining individual and team work.

Relevant papers:

·        Hofmans L, van den Bos W. (2022). Social learning across adolescence: A Bayesian neurocognitive perspective. Dev Cogn Neurosci. 58:101151. doi: 10.1016/j.dcn.2022.101151.

·        Gradassi, A., Slagter, S K, da Silva Pinho, A., van den Bos, W. (2022). Network distance and centrality shape social learning in the classroom. School Psychology. Advance online publication.

Your work will consist of:

·        Recruitment and fMRI testing: The student will recruit adolescents from high schools (12-18 yo) and will assist/be responsible for fMRI scanning.

·        Analysis: Because the testing of adolescents will still be ongoing, the analysis will be performed on data from adults, for which data collection has finished already. This will entail analysis of behavioral data, using R. Depending on the time available and the skills/experience of the student, this might be extended to fMRI analysis.

·        Critically reviewing the existing literature

·        Participating in lab meetings


·        Dutch

·        A background in neuroscience, psychology or a related field;

·        Strong affinity with doing research (e.g. research focused bachelor or master program);

·        Experience with statistical analyses;

·        Ability to work efficiently and structured in a team-setting.

·        Willingness and ability to quickly learn R (previous experience is appreciated)

·        The internship will be technically and logistically quite demanding. Because the research population can only be scanned outside secondary school hours, data collection will partly take place outside regular office hours. We expect applications from highly motivated students.


To apply or ask more information, email Lieke Hofmans with a short description of your motivation and relevant previous experience.