291 research outputs found

    Reconsidering the Imaging Evidence Used to Implicate Prediction Error as the Driving Force behind Learning.

    Get PDF
    In this paper, we review the evidence that learning is driven by signaling of Prediction Error [PE] by some neurons. We model associative learning in artificial neural networks using Hebbian (non-PE) learning algorithms to investigate whether the data used to implicate PE in learning can arise without actual PE computation. We conclude that the metabolic demands of synaptic change during Hebbian learning would produce a PE-correlated component in functional magnetic resonance imaging (fMRI), which suggests that the research used to imply PE in learning is currently inconclusive

    Recent advances in functional neuroimaging analysis for cognitive neuroscience

    Get PDF
    Functional magnetic resonance imaging and electro-/magneto-encephalography are some of the main neuroimaging technologies used by cognitive neuroscientists to study how the brain works. However, the methods for analysing the rich spatial and temporal data they provide are constantly evolving, and these new methods in turn allow new scientific questions to be asked about the brain. In this brief review, we highlight a handful of recent analysis developments that promise to further advance our knowledge about the working of the brain. These include (1) multivariate approaches to decoding the content of brain activity, (2) time-varying approaches to characterising states of brain connectivity, (3) neurobiological modelling of neuroimaging data, and (4) standardisation and big data initiatives.Peer reviewe

    Assumptions behind scoring source and item memory impact on conclusions about memory: A reply to Kellen and Singmann's comment (2017).

    Get PDF
    In our recent article in the journal Cortex (Cooper, Greve, & Henson, 2017), we examined memory for source and item information using data from two different source monitoring paradigms and six different groups of participants. When comparing standard accuracy analysis and various Multinomial Processing Tree (MPT) models, we found that the type of analysis determined the extent to which item and/or source memory differences were found across groups (healthy young and older groups, an older group with mild memory problems, and individuals with hippocampal lesions). Our main point was methodological: that one could draw different conclusions (e.g., whether ageing or hippocampal lesions affect only source memory, or both source and item memory) depending on the analysis used

    Neural Differentiation of Incorrectly Predicted Memories.

    Get PDF
    Frequently experiencing an item in a specific context leads to the prediction that this item will occur when we encounter the same context in future. However, this prediction sometimes turns out to be incorrect, and recent behavioural research suggests that such “prediction errors” improve encoding of new information (Greve et al. 2017)
    corecore