Model-based analyses: Promises, pitfalls, and example applications to the study of cognitive control

We discuss a recent approach to investigating cognitive control, which has the potential to deal with some of the challenges inherent in this endeavour. In a model-based approach, the researcher defines a formal, computational model that performs the task at hand and whose performance matches that of a research participant. The internal variables in such a model might then be taken as proxies for latent variables computed in the brain. We discuss the potential advantages of such an approach for the study of the neural underpinnings of cognitive control and its pitfalls, and we make explicit the assumptions underlying the interpretation of data obtained using this approach

A neurocognitive approach to music reading

Music reading offers a unique perspective on the acquisition of a notational system. Many people cannot read music, but a large proportion are motivated to learn. Musical literacy is therefore amenable to studies of acquisition in a way that language literacy is not. The studies reviewed here investigate how musical symbols on the page are decoded into a musical response. The studies address the nature of the mental representations used in music reading, as well as their instantiation within the brain. The results of a musical Stroop paradigm are described, in which musical notation was present but irrelevant for task performance. The presence of musical notation produced systematic effects on reaction time, demonstrating that reading of the written note, like the written word, is obligatory for those who are musically literate. Spatial interference tasks are also described that suggest that music reading, at least for the pianist, can be characterized as a set of vertical to horizontal mappings. These behavioral findings are mirrored by the results of an fMRI training study in which musically untrained adults were taught to read music and play piano keyboard over a period of three months. Specific learning-related changes were seen in the superior parietal cortex and fusiform gyrus, for melody reading and rhythm reading, respectively. These changes are suggested to correspond to the acquisition of processes that deal with the extraction of spatial and featural properties of notation, respectively

Your mistake is my mistake ... or is it? Behavioural adjustments following own and observed actions in cooperative and competitive contexts

Item does not contain fulltextA social speeded choice-reaction-time task was used to study adaptive behaviours following own and observed actions (errors and correct responses) in cooperative and competitive contexts. After making an erroneous response, the appropriate remedial action to avoid future errors in speeded reaction tasks is to slow down. Consistent with previous results, people indeed slow down following their own errors. Importantly, people who slow down most following own errors also slow down following observed errors in a cooperative situation. In a competitive context, a different pattern was found. People accelerated after errors from their opponent. The current findings demonstrate that the social context determines the way people respond to the errors of others, indicating that the neural systems that control remedial actions are highly flexible. These systems may underlie social adaptive behaviour, enabling people to respond flexibly to other people's actions in a wide variety of social contexts.9 p

Reassessing associations between white matter and behaviour with multimodal microstructural imaging

Several studies have established specific relationships between White Matter (WM) and behaviour. However, these studies have typically focussed on fractional anisotropy (FA), a neuroimaging metric that is sensitive to multiple tissue properties, making it difficult to identify what biological aspects of WM may drive such relationships. Here, we carry out a pre-registered assessment of WM-behaviour relationships in 50 healthy individuals across multiple behavioural and anatomical domains, and complementing FA with myelin sensitive quantitative MR modalities (MT, R1, R2*). Surprisingly, we only find support for predicted relationships between FA and behaviour in one of three pre-registered tests. For one behavioural domain, where we failed to detect an FA-behaviour correlation, we instead find evidence for a correlation between behaviour and R1. This hints that multimodal approaches are able to identify a wider range of WM-behaviour relationships than focusing on FA alone. To test whether a common biological substrate such as myelin underlies WM-behaviour relationships, we then ran joint multimodal analyses, combining across all MRI parameters considered. No significant multimodal signatures were found and power analyses suggested that sample sizes of 40-200 may be required to detect such joint multimodal effects, depending on the task being considered. These results demonstrate that FA-behaviour relationships from the literature can be replicated, but may not be easily generalisable across domains. Instead, multimodal microstructural imaging may be best placed to detect a wider range of WM-behaviour relationships, as different MRI modalities provide distinct biological sensitivities. Our findings highlight a broad heterogeneity in WM's relationship with behaviour, suggesting that variable biological effects may be shaping their interaction. (c) 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)