Rolf Degen summarizing... Unlike a machine, in which dedicated components are entrusted with fixed functions, the brain operates more like a complex dynamic system in which changing coalitions of neurons can perform varying tasks depending on the context

Improving the study of brain-behavior relationships by revisiting basic assumptions. Christiana Westlin et al. Trends in Cognitive Sciences, February 2 2023. https://doi.org/10.1016/j.tics.2022.12.015

Highlights

The study of brain-behavior relationships has been guided by several foundational assumptions that are called into question by empirical evidence from human brain imaging and neuroscience research on non-human animals.

Neural ensembles distributed across the whole brain may give rise to mental events rather than localized neural populations. A variety of neural ensembles may contribute to one mental event rather than one-to-one mappings. Mental events may emerge as a complex ensemble of interdependent signals from the brain, body, and world rather than from neural ensembles that are context-independent.

A more robust science of brain-behavior relationships awaits if research efforts are grounded in alternative assumptions that are supported by empirical evidence and which provide new opportunities for discovery.

Abstract: Neuroimaging research has been at the forefront of concerns regarding the failure of experimental findings to replicate. In the study of brain-behavior relationships, past failures to find replicable and robust effects have been attributed to methodological shortcomings. Methodological rigor is important, but there are other overlooked possibilities: most published studies share three foundational assumptions, often implicitly, that may be faulty. In this paper, we consider the empirical evidence from human brain imaging and the study of non-human animals that calls each foundational assumption into question. We then consider the opportunities for a robust science of brain-behavior relationships that await if scientists ground their research efforts in revised assumptions supported by current empirical evidence.

Keywords: brain-behavior relationshipswhole-brain modelingdegeneracycomplexityvariation

Concluding remarks

Scientific communities tacitly agree on assumptions about what exists (called ontological commitments), what questions to ask, and what methods to use. All assumptions are firmly rooted in a philosophy of science that need not be acknowledged or discussed but is practiced nonetheless. In this article, we questioned the ontological commitments of a philosophy of science that undergirds much of modern neuroscience research and psychological science in particular. We demonstrated that three common commitments should be reconsidered, along with a corresponding course correction in methods (see Outstanding questions). Our suggestions require more than merely improved methodological rigor for traditional experimental design (Box 1). Such improvements are important, but may aid robustness and replicability only when the ontological assumptions behind those methods are valid. Accordingly, a productive way forward may be to fundamentally rethink what a mind is and how a brain works. We have suggested that mental events arise from a complex ensemble of signals across the entire brain, as well as the from the sensory surfaces of the body that inform on the states of the inner body and outside world, such that more than one signal ensemble maps to a single instance of a single psychological category (maybe even in the same context [51,56]). To this end, scientists might find inspiration by mining insights from adjacent fields, such as evolution, anatomy, development, and ecology (e.g., [123,124]), as well as cybernetics and systems theory (e.g., [125,126]). At stake is nothing less than a viable science of how a brain creates a mind through its constant interactions with its body, its physical environment, and with the other brains-in-bodies that occupy its social world.

Outstanding questions

Well-powered brain-wide analyses imply that meaningful signals exist in brain regions that are considered nonsignificant in studies with low within-subject power, but is all of the observed brain activity necessarily supporting a particular behavior? By thresholding out weak yet consistent effects, are we removing part of the complex ensemble of causation? What kinds of technical innovations or novel experimental methods would allow us to make progress in answering this question?

How might we incorporate theoretical frameworks, such as a predictive processing framework, to better understand the involvement of the whole-brain in producing a mental event? Such an approach hypothesizes the involvement of the whole-brain as a general computing system, without implying equipotentiality (i.e., that all areas of the brain are equally able to perform the same function).

Why are some reported effects (e.g., the Stroop effect) seemingly robust and replicable if psychological phenomena are necessarily degenerate? These effects should be explored to determine if they remain replicable outside of constrained laboratory contexts and to understand what makes them robust.

Given that measuring every signal in a complex system is unrealistic given the time and cost constraints of a standard neuroimaging experiment, how can we balance the measurement of meaningful signals in the brain, body, and world with the practical realities of experimental constraints?

Is the study of brain-behavior relationships actually in a replication crisis? And if so, is it merely a crisis of method? Traditional assumptions suggest that scientists should replicate sample summary statistics and tightly control variation in an effort to estimate a population summary statistic, but perhaps this goal should be reconsidered.