Throughout the last two decades, complex systems methodologies have gained an increasing importance in both neuroscience and the cognitive sciences. Researchers in these fields are increasingly interested in characterizing patterns of interactions between neurophysiological and bodily processes occurring simultaneously at different spatiotemporal scales, and how these interactions constitute psychological and behavioral phenomena in humans. In the contemporary philosophy of mind, there exist two general approaches to answering this fundamental question: First, mechanistic frameworks, which conceptualize cognitive systems as mechanisms, composed of functionally-individuated components whose functions are narrowly defined by their ranges of possible inputs and outputs in relation to other component states. Second, dynamicist frameworks, which conceptualize cognitive systems as assemblies of smaller-scale processes continuously shaping each others’ dynamics through interactions extended in time – a process which is, in turn, constrained by the dynamics of the larger-scale system they constitute. In this paper, I argue that dynamicist frameworks provide a superior philosophical toolkit for neuroscientists interested in conceptual questions about causal explanations in neural systems. I do so by showcasing an example in which the causal contribution of a neural system (a neuronal population) to a behavior is better explained within a dynamicist, rather than a mechanist framework of causal explanation. I then argue that general characteristics of such dynamicist causal explanations are applicable to other neural and cognitive systems as well, pointing out various shortcomings of mechanistic approaches in this area.