Assessing implicit learning: Calibration, measurement, and psychophysiological modelling

Pavlovian threat conditioning is widely used to investigate potential therapies for anxiety disorders, but the assessment of implicit learning in this paradigm is highly heterogeneous. In the first part of my talk, I take a general psychometric perspective on how to evaluate the measurement of volatile cognitive attributes in experimental settings. I propose to evaluate measurement methods by their 'retrodictive validity' in independent calibration experiments, i.e. the correlation between intended and measured attribute values in an established manipulation. In the second part, I focus on implicit learning as a specific example of an attribute that is commonly inferred from continuous data time series. I will discuss different measurement models for this inference, among which a formal psychophysiological modelling framework yields high retrodictive validity.

Speaker: Dominik Back (MPC UCL)

Thursday 9^th January, 14:00

Max Planck UCL Centre for Computational Psychiatry and Ageing Research

Russell Square House, 10-12 Russell Square, second floor