Neuroscience Needs Behavior: Correcting a Reductionist Bias

Abstract

There are ever more compelling tools available for neuroscience research, ranging from selective genetic targeting to optogenetic circuit control to mapping whole connectomes. These approaches are coupled with a deep-seated, often tacit, belief in the reductionist program for understanding the link between the brain and behavior. The aim of this program is causal explanation through neural manipulations that allow testing of necessity and sufficiency claims. We argue, however, that another equally important approach seeks an alternative form of understanding through careful theoretical and experimental decomposition of behavior. Specifically, the detailed analysis of tasks and of the behavior they elicit is best suited for discovering component processes and their underlying algorithms. In most cases, we argue that study of the neural implementation of behavior is best investigated after such behavioral work. Thus, we advocate a more pluralistic notion of neuroscience when it comes to the brain-behavior relationship: behavioral work provides understanding, whereas neural interventions test causality.

Converging evidence for the role of transmodal cortex in cognition

“…Both studies provide accounts of the transmodal cortex anchored in both neural and psychological measurements (16), and thus constrain accounts of the role that transmodal cortex, and in particular the DMN, plays in cognition. Historically, the DMN was argued to be task-negative, supporting forms of cognition irrelevant to external goals (17), because its activity emerged in simple nondemanding tasks (3), as well as states, such as mind-wandering (18) and attentional lapses (19).…”

Degeneracy in hippocampal physiology and plasticity

“…Specifically, although the biological system adapts to the "unplanned" absence of the single gene (Edelman and Gally, 2001), it is not always essential that the adaptations result in compensation of one specific behavioral readout (of the several possible on the behavioral manifold (Jazayeri and Afraz, 2017;Krakauer et al, 2017)). Any compensation has been argued as a statistical result of the tradeoffs that are inherent to this complex, adaptive and nonlinear system that manifests degeneracy that is emergent across multiple scales of organization (Edelman and Gally, 2001;.…”

“…In the second section, we build an argument that theoretical and experimental literature, spanning multiple scales of analysis, presents abundant support for the prevalence of degeneracy in almost all aspects of hippocampal physiology and plasticity. The third section explores the important question on the feasibility of establishing oneto-one structure-function relationships in systems that exhibit degeneracy through significant and Hacker, 2003;Bickle, 2015;Jazayeri and Afraz, 2017;Krakauer et al, 2017;Panzeri et al, 2017) to more focused debates on the specific cellular components that are involved in specific behavior (Bliss and Collingridge, 1993;Kandel et al, 2014;Kim and Linden, 2007;Martin et al, 2000;Mayford et al, 2012;Mozzachiodi and Byrne, 2010;Neves et al, 2008a;Zhang and Linden, 2003), have significantly contributed to our emerging understanding of neural systems and their links to behavior. Several studies have covered the breadth and depth of these debates (Bargmann and Marder, 2013;Bennett and Hacker, 2003;Bickle, 2015;Jazayeri and Afraz, 2017;Jonas and Kording, 2017;Kandel et al, 2014;Katz, 2016;Kim and Linden, 2007;Krakauer et al, 2017;Lazebnik, 2002;Marder, 1998Marder, , 2011Marder, , 2012Marder et al, 2014;Marder and Thirumalai, 2002;Mayford et al, 2012;Panzeri et al, 2017;Tytell et al, 2011), and will not be the focus of this review.…”

“…1B) through interactions among disparate parametric combinations in a lower scale (Edelman and Gally, 2001;Foster et al, 1993;Gjorgjieva et al, 2016;Goldman et al, 2001;Marder, 2011;Marder and Goaillard, 2006;Marder et al, 2015;Marder and Taylor, 2011; parameters (at the molecular scale) to achieve activity homeostasis (Gjorgjieva et al, 2016;Hengen et al, 2016;Nelson and Turrigiano, 2008;Turrigiano, 2011;Turrigiano, 1999Turrigiano, , 2008Turrigiano and Nelson, 2004). Thus, under the degeneracy framework, different uncorrelated clusters in the lower-scale parametric space could result in similar, if not identical, functional outcomes in the higher-scale measurement space, thereby suggesting a many-to-one relationship between the lower-and higher-scale manifolds (Edelman and Gally, 2001;Jazayeri and Afraz, 2017;Krakauer et al, 2017). Prominent lines of experimental evidence in support of degeneracy in neural systems have come from demonstrations of significant animal-to-animal variability in constituent components in providing analogous functional outcomes, and/or from results on many-to-many mappings between neural activity and behavior (Marder, 2011;Marder and Goaillard, 2006;Marder and Taylor, 2011;Schulz et al, 2006;Schulz et al, 2007;Vogelstein et al, 2014).…”

L’adaptation optimale du mouvement humain au milieu gravitaire

“…À une époque où le développement technologique est en pleine expansion, il est nécessaire de s'assurer que les nouvelles connaissances/technologies sont orientées et paramétrées de manière à favoriser une interaction avec le système moteur humain qui soit la plus bénéfique possible. Sans une compréhension profonde du comportement moteur, un tel objectif semble inatteignable [11]. ‡ Optimal adaptation of human movement to the gravity field …”