Cognitive Dynamics Lab

Investigating the brain, behavior, and societal processes as interconnected temporal phenomena.

Our work focuses on complex connected systems—ranging from brains to societies—and how these processes evolve. We operate at the intersection of multiple disciplines, including cognitive neuroscience, network neuroscience, metascience, network theory, cognitive science, and social psychology. Our primary focus is on developing innovative and robust methods to analyze complex cognitive functions and behaviors in an interconnected world.

Research Areas

1. Cognitive Neuroscience & Brain Connectivity: We investigate cognitive functions in both healthy individuals and clinical populations, applying advanced neuroimaging and behavioral data analysis techniques. A key focus is on developing and implementing temporal network theory approaches to understand how brain connectivity changes over time. Clinical applications of our work include studies on chronic pain, bipolar disorder, and fatigue. Example Publications:

   • Thompson et al., 2017: Discusses the shift from static to temporal network theory and its applications in functional brain connectivity.

   • Klahn et al., 2024: Investigates brain network hubs in the somatosensory cortex and their role in bipolar disorder.

2. Behavior in a Connected Society: We extend network science beyond the brain, studying how social, psychological, and biological networks interact to shape behavior and health outcomes. This includes a range of phenomena, from the media's role in shaping expectations on scientific topics, understanding how biopsychosocial factors influence long-term health trajectories, to exploring online behavior and digital interactions. Example Publications:

   • Gedin et al., 2022: Explores the relationship between media coverage and placebo responses in clinical trials of cannabis-based therapies. (With the Pain Neuroimaging Lab at Karolinska Institutet)

   • Thompson et al., 2025: Examines biopsychosocial networks derived from conscription data to predict chronic pain development. (With the Pain Neuroimaging Lab at Karolinska Institutet)

   • Clarke & Thompson (upcoming): Investigates incivility dynamics in online comment sections.

3. Metascience & Scientific Practices: Our research seeks to improve the clarity and reliability of scientific communication and methodology. We analyze trends in the readability of scientific texts, explore dataset reuse issues, and develop frameworks for hypothesis generation and media engagement in science. This work contributes to improving the transparency and efficiency of research dissemination.
   Example Publications:

   • Plavén-Sigray et al., 2017: Demonstrates that scientific texts have become less readable over time, impacting accessibility.

   • Thompson et al., 2020: Discusses dataset decay and the challenges of repeated analyses on open datasets.

   • Thompson & Skau, 2023: Explores the scope and formulation of scientific hypotheses.

4. Network Theory & Neuroimaging Methods: We develop and test novel computational tools for analyzing network structure and dynamics in neuroscience. This includes leading the development of software such as teneto (for temporal network analysis) and netplotbrain (for brain network visualization).
   Example Publications:

   • Thompson et al., 2017: Introduces methods for applying temporal network theory to functional brain connectivity.

   • Fanton & Thompson, 2023: Presents NetPlotBrain, a Python package for visualizing networks in neuroscience.

5. Cognitive Network Profiles: Our ongoing work focuses on developing methodologies for quantifying cognitive network profiles through dense behavioral sampling over time. This research aims to refine how individual cognitive functions are embedded within dynamic network structures.