Future trends in Neuroimaging: Neural processes as expressed within real-life contexts

Researchers have recently begun to examine the neural basis of musical improvisation, one of the most complex forms of creative behavior. The emerging field of improvisation neuroscience has implications not only for the study of artistic expertise, but also for understanding the neural underpinnings of domain-general processes such as motor control and language production. This review synthesizes functional magnetic resonance imagining (fMRI) studies of musical improvisation, including vocal and instrumental improvisation, with samples of jazz pianists, classical musicians, freestyle rap artists, and non-musicians. A network of prefrontal brain regions commonly linked to improvisatory behavior is highlighted, including the pre-supplementary motor area, medial prefrontal cortex, inferior frontal gyrus, dorsolateral prefrontal cortex, and dorsal premotor cortex. Activation of premotor and lateral prefrontal regions suggests that a seemingly unconstrained behavior may actually benefit from motor planning and cognitive control. Yet activation of cortical midline regions points to a role of spontaneous cognition characteristic of the default network. Together, such results may reflect cooperation between large-scale brain networks associated with cognitive control and spontaneous thought. The improvisation literature is integrated with Pressing's theoretical model, and discussed within the broader context of research on the brain basis of creative cognition.

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“…Future researchers should continue to strike a balance between ecological validity and experimental control (cf. Hasson and Honey, 2012).…”

Section: Future Directionsmentioning

confidence: 99%

The neuroscience of musical improvisation

Beaty

2015

Neuroscience & Biobehavioral Reviews

178

163

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“…Until very recently, however, the links between the phenomena studied using fMRI and the real-world behavior to which such research aims to apply have rarely been assessed directly Hasson & Honey, 2012). As a result, the real-world relevance of laboratory-based fMRI research has often been unclear (see Mitchell, 2012, for more general discussion of this issue).…”

Section: Combining Ema and Fmri To Study Tobacco Dependencementioning

confidence: 99%

Integrating Ecological Momentary Assessment and Functional Brain Imaging Methods: New Avenues for Studying and Treating Tobacco Dependence

Wilson

Smyth

MacLean

2013

Nicotine & Tobacco Research

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introduction: Ecological momentary assessment (EMA) and related methods typically entail repeatedly and intensively sampling behavior as it occurs over time and under naturalistic conditions. Although the methodological features of EMA make it a highly valuable research technique in its own right, EMA can also be a potent counterpart to other approaches. One methodological partnership with substantial yet largely untapped potential for the study of tobacco dependence is the pairing of EMA with functional brain imaging.

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“…Even though the study of language in its ecological setting has in certain cognitive traditions been regarded as an ill-advised enterprise on principled and practical grounds (Chomsky, 1959(Chomsky, , 1995, it was highlighted as a necessary empirical step to study the brain from the systems level (see Hasson and Honey, 2012;Small and Nusbaum, 2004).…”

Section: Naturalistic Stimuli and Data Reusementioning

confidence: 99%

Probabilistic language models in cognitive neuroscience: Promises and pitfalls

Armeni

Willems

Frank

2017

Neuroscience & Biobehavioral Reviews

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A R T I C L E I N F O A B S T R A C TCognitive neuroscientists of language comprehension study how neural computations relate to cognitive computations during comprehension. On the cognitive part of the equation, it is important that the computations and processing complexity are explicitly defined. Probabilistic language models can be used to give a computationally explicit account of language complexity during comprehension. Whereas such models have so far predominantly been evaluated against behavioral data, only recently have the models been used to explain neurobiological signals. Measures obtained from these models emphasize the probabilistic, information-processing view of language understanding and provide a set of tools that can be used for testing neural hypotheses about language comprehension. Here, we provide a cursory review of the theoretical foundations and example neuroimaging studies employing probabilistic language models. We highlight the advantages and potential pitfalls of this approach and indicate avenues for future research.

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Future trends in Neuroimaging: Neural processes as expressed within real-life contexts

Cited by 159 publications

References 113 publications

The neuroscience of musical improvisation

The neuroscience of musical improvisation

Integrating Ecological Momentary Assessment and Functional Brain Imaging Methods: New Avenues for Studying and Treating Tobacco Dependence

Probabilistic language models in cognitive neuroscience: Promises and pitfalls

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