Skip to toolbar

The Myth of Optimality in Clinical Neuroscience

The Myth of Optimality in Clinical Neuroscience

Published in: Trends in Cognitive Sciences, Volume 22, Issue 3, 241-257

“Implicit in modern dimensional theories of psychiatric illness is the assumption that population variability and illness vulnerability are interchangeable constructs.

Mounting evidence suggests that healthy variation is ubiquitous in natural populations, and must be interpreted in terms of cost–benefit tradeoffs.

Psychiatric illnesses arise through a web of interactions linking brain function, behavior, and a lifetime of experiences. Research on illness etiology will only progress through the collection of comprehensive phenomic-level datasets.

Large-scale collaborative efforts have begun to generate broad phenotypic batteries that encompass environmental and contextual factors, brain structure and function, as well as multiple domains of cognition, behavior, and genetics. These datasets hold great potential for clinical researchers seeking to map links across diverse neural and cognitive states.

Clear evidence supports a dimensional view of psychiatric illness. Within this framework the expression of disorder-relevant phenotypes is often interpreted as a breakdown or departure from normal brain function. Conversely, health is reified, conceptualized as possessing a single ideal state. We challenge this concept here, arguing that there is no universally optimal profile of brain functioning. The evolutionary forces that shape our species select for a staggering diversity of human behaviors. To support our position we highlight pervasive population-level variability within large-scale functional networks and discrete circuits. We propose that, instead of examining behaviors in isolation, psychiatric illnesses can be best understood through the study of domains of functioning and associated multivariate patterns of variation across distributed brain systems.”

Written by: Avram J. Holmes, Lauren M. Patrick

For full text:

Leave a Reply

twenty − one =