Neuroscience Needs Behavior: Correcting a Reductionist Bias.

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Human-level performance in 3D multiplayer games with population-based reinforcement learning (2018, background): “Analysis of temporally extended behaviours provided another view on the complexity of behavioural strategies learned by the agent ( 34 ).”
Cognitive computational neuroscience (2018, background): “Understanding the brain requires that we develop theory and experiment in tandem, and complement the bottom-up, data-driven approach by a top-down, theory-driven approach that starts with behavioral functions to be explained.(172,173) Unprecedentedly rich measurements and manipulations of brain acti”
Computational neuroethology: a call to action (2019, background): “And yet, the conceptual difficulties in reaching this understanding may sometimes appear rather daunting (Gomez-Marin et al., 2014; Jazayeri and Afraz, 2017; Krakauer et al., 2017).”
If deep learning is the answer, what is the question? (2020, background): “This is vital because the computations in a neural system can often profitably be understood in the context of the behaviour they produce 59 .”
DeepPoseKit, a software toolkit for fast and robust animal pose estimation using deep learning (2019, background): “Understanding the relationships between individual behavior, brain activity (reviewed by Krakauer et al. 2017 ), and collective and social behaviors ( Rosenthal et al., 2015 ; Strandburg-Peshkin et al., 2013 ; Jolles et al., 2017 ; and without markers.”