TEX2022: Bringing together Predictive Processes and Statistical Learning

Session

Processing of Sequences

S2

Jul 19, 2022, 4:00 PM

Aula Magna (SISSA - International School for Advanced Studies)

15. Learning and Memorization of a Multi-modality and Multi-cue Sequence

Ms Nicole Sin Hang Law (The University of Oxford)

7/19/22, 4:00 PM

Predictive Processes and Statistical Learning

Talk

Statistical learning allows us to detect and acquire different types of regularities from the environment but how multiple regularities could be integrated and learnt across time remain uncertain. This study set out to examine the multidimensional capacity and learning phases of statistical learning. We exposed 40 healthy adults to an audio-visual sequence with both conditional and...

23. Humans parsimoniously represent auditory sequences by pruning and completing the underlying network structure

Lucas Benjamin

7/19/22, 4:20 PM

Predictive Processes and Statistical Learning

Talk

Successive auditory inputs are rarely independent, their relationships ranging from local transitions between elements to hierarchical and nested representations. In many situations, humans retrieve these dependencies even from limited datasets. However, this learning at multiple scale levels is poorly understood. Here We used the formalism proposed by network science to study the behavioral...

28. Direct brain recordings reveal continuous encoding of structure in random stimuli

Julian Fuhrer (University of Oslo)

7/19/22, 4:40 PM

Predictive Processes and Statistical Learning

Talk

How does the brain process randomness? Mounting evidence suggests it tries to make sense of any given sequence, generating sophisticated internal models that continuously draw on statistical structures in the unfolding sensory input to maintain a detailed representation of its environment. However, it is unknown how specifically this modelling applies to random sensory signals. Here, we...