Imaging the living brain: An argument for ruthless reductionism from olfactory neurobiology

Causation in neuroscience: keeping mechanism meaningful

A fundamental goal of research in neuroscience is to uncover the causal structure of the brain. This focus on causation makes sense, because causal information can provide explanations of brain function and identify reliable targets with which to understand cognitive function and prevent or change neurological conditions and psychiatric disorders. In this research, one of the most frequently used causal concepts is 'mechanism' - this is seen in the literature and language of the field, in grant and funding inquiries that specify what research is supported, and in journal guidelines on which contributions are considered for publication. In these contexts, mechanisms are commonly tied to expressions of the main aims of the field and cited as the 'fundamental', 'foundational' and/or 'basic' unit for understanding the brain. Despite its common usage and perceived importance, mechanism is used in different ways that are rarely distinguished. Given that this concept is defined in different ways throughout the field - and that there is often no clarification of which definition is intended - there remains a marked ambiguity about the fundamental goals, orientation and principles of the field. Here we provide an overview of causation and mechanism from the perspectives of neuroscience and philosophy of science, in order to address these challenges.

Naturalising Agent Causation

The idea of agent causation—that a system such as a living organism can be a cause of things in the world—is often seen as mysterious and deemed to be at odds with the physicalist thesis that is now commonly embraced in science and philosophy. Instead, the causal power of organisms is attributed to mechanistic components within the system or derived from the causal activity at the lowest level of physical description. In either case, the ‘agent’ itself (i.e., the system as a whole) is left out of the picture entirely, and agent causation is explained away. We argue that this is not the right way to think about causation in biology or in systems more generally. We present a framework of eight criteria that we argue, collectively, describe a system that overcomes the challenges concerning agent causality in an entirely naturalistic and non-mysterious way. They are: (1) thermodynamic autonomy, (2) persistence, (3) endogenous activity, (4) holistic integration, (5) low-level indeterminacy, (6) multiple realisability, (7) historicity, (8) agent-level normativity. Each criterion is taken to be dimensional rather than categorical, and thus we conclude with a short discussion on how researchers working on quantifying agency may use this multidimensional framework to situate and guide their research.

Understanding responses to chemical mixtures: looking forward from the past

Our goal in this article is to provide a perspective on how to understand the nature of responses to chemical mixtures. In studying responses to mixtures, researchers often identify "mixture interactions"-responses to mixtures that are not accurately predicted from the responses to the mixture's individual components. Critical in these studies is how to predict responses to mixtures and thus to identify a mixture interaction. We explore this issue with a focus on olfaction and on the first level of neural processing-olfactory sensory neurons-although we use examples from taste systems as well and we consider responses beyond sensory neurons, including behavior and psychophysics. We provide a broadly comparative perspective that includes examples from vertebrates and invertebrates, from genetic and nongenetic animal models, and from literature old and new. In the end, we attempt to recommend how to approach these problems, including possible future research directions.