“Improving the study of brain-behavior relationships by revisiting basic assumptions” discusses how 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 the study of brain-behavior relationships, past failures to find replicable and robust effects have been attributed to methodological shortcomings.
Methodological rigor is of course important, but replication problems may stem, in part, from a more pernicious source: faulty assumptions (i.e., ontological commitments) that mis-specify the psychological phenomena of interest.
This paper reviews three questionable assumptions whose reconsideration may offer opportunities for a more robust and replicable science:
(1) The localization assumption: the instances that constitute a category of psychological events (e.g., instances of fear) are assumed to be caused by a single, dedicated psychological process implemented in a dedicated neural ensemble.
(2) The one-to-one assumption: the dedicated neural ensemble is assumed to map uniquely to that psychological category, such that the mapping generalizes across contexts, people, measurement strategies, and experimental designs.
(3) The independence assumption: the dedicated neural ensemble is thought to function independently of contextual factors, such as the rest of the brain, the body, and the surrounding world, so the ensemble can be studied alone without concern for those other factors. Contextual factors might moderate activity in the neural ensemble but should not fundamentally change its mapping to the instances of a psychological category.
These three assumptions are rooted in a typological view of the mind, brain, and behavior that was modeled on 19th century physics and continues to guide experimental practices in much of brain-behavior research to the present day. This paper has curated examples from studies of human functional magnetic resonance imaging (fMRI) and neuroscience research using nonhuman animals that call each assumption into question.
The beginnings of an alternative approach is sketched, to study brain-behavior relationships, grounded in different ontological commitments:
(i) a mental event comprises distributed activity across the whole brain;
(ii) brain and behavior are linked by degenerate (i.e., many-to-one) mappings; and
(iii) mental events emerge as a complex ensemble of weak, nonlinearly interacting signals from the brain, body, and external world
The brain complexity hypothesis
A system is a collection of regularly interacting parts, organized for a common purpose. Biological systems, such as the cell, have historically been described as machines. The machine metaphor implies that the system can be broken down into independent, separable mechanisms, where each mechanism can be studied independently of one another.
But many domains of biology have shown that biological systems cannot be studied as independent mechanisms, because the systems’ functions emerge through the collective interaction of their parts. Instead, biological systems are thought to function as complex systems, where many weak, causal factors interact in a nonlinear way to produce a larger-scale collective outcome. Accordingly, some neuroscientists have begun to consider the brain as a complex system, whose functions emerge from the dynamic interactions between neurons, glial cells, and other biological elements