An Oscillator Ensemble Model of Sequence Learning

Autor: Peng Wang, Andreas K. Engel, Xiaolin Hu, Alexander Maye, Jonathan Daume
Rok vydání: 2019
Předmět:
Computer science
Brain activity and meditation
phase-locked loops
Cognitive Neuroscience
Speech recognition
Memorization
lcsh:RC346-429
050105 experimental psychology
lcsh:RC321-571
03 medical and health sciences
Cellular and Molecular Neuroscience
0302 clinical medicine
Stimulus modality
Synchronization (computer science)
phase reset
0501 psychology and cognitive sciences
lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry
lcsh:Neurology. Diseases of the nervous system
Original Research
Sequence
Basis (linear algebra)
Ensemble forecasting
Crossmodal
business.industry
multisensory integration
Fingerprint (computing)
05 social sciences
Multisensory integration
Pattern recognition
crossmodal
prediction
Sensory Systems
Artificial intelligence
Sequence learning
business
030217 neurology & neurosurgery
Neuroscience
frequency tuning
Zdroj: Frontiers in Integrative Neuroscience, Vol 13 (2019)
Frontiers in Integrative Neuroscience
ISSN: 1662-5145
DOI: 10.3389/fnint.2019.00043
Popis: Learning and memorizing sequences of events is an important function of the human brain and the basis for forming expectations and making predictions. Learning is facilitated by repeating a sequence several times, causing rhythmic appearance of the individual sequence elements. This observation invites to consider the resulting multitude of rhythms as a spectral ‘fingerprint’ which characterizes the respective sequence. Here we explore the implications of this perspective by developing a neurobiologically plausible computational model which captures this ‘fingerprint’ by attuning an ensemble of neural oscillators. In our model, this attuning process is based on a number of oscillatory phenomena that have been observed in electrophysiological recordings of brain activity like synchronization, phase locking and reset as well as cross-frequency coupling. We compare the learning properties of the model with behavioral results from a study in human participants and observe good agreement of the errors for different levels of complexity of the sequence to be memorized. Finally, we suggest an extension of the model for processing sequences that extend over several sensory modalities.
Databáze: OpenAIRE
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