arXiv subjects

Ben Baker

Publications and source records attributed to Ben Baker.

3 recordsLinked to original sources

arXiv2026

Use and usability: concepts of representation in philosophy, neuroscience, cognitive science, and computer science

Representations play a central role in the study of both biological and artificial intelligence, as well as philosophy of mind. Across neuroscience, computer science, and philosophy, a recurring theme is that representations not only carry information but should be ``useful'' for or ``usable'' by an agent in some sense. Here, we review how the ``usefulness'' of representations has been conceptualized and how it figures into different conceptions of representation. We identify and explore four aspects of use and usability: representations generally carry \textit{information}; that information may or may not be \textit{useful} and it may or may not be encoded in a usable \textit{format}; and the representations may or may not be \textit{used downstream}. Building on these four aspects of information and use, we then organize existing perspectives on neural representations into three levels: Representations as Information (Level 1); Representations as Usable (Level 2); and Representations as Used (Level 3). Our account is meant to give readers an appreciation for the diversity of notions of ``neural representation,'' help them navigate the vast and multi-disciplinary literature on the topic, and help them clarify the appropriate notion of representation for their own investigations.

cs.OH↗

arXiv2023

The time is ripe to reverse engineer an entire nervous system: simulating behavior from neural interactions

Just like electrical engineers understand how microprocessors execute programs in terms of how transistor currents are affected by their inputs, neuroscientists want to understand behavior production in terms of how neuronal outputs are affected by their inputs and internal states. This dependency of neuronal outputs on inputs can be described by a state-dependent input-output (IO)-function. However, to reliably identify these IO-functions, we need to perturb each input and combinations of inputs while observing all the outputs. Here, we argue that such completeness is possible in C. elegans; a complete description that goes all the way from the activity of every neuron to predict behavior. The established and growing toolkit of optophysiology can non-invasively capture and control every neuron's activity and scale to countless experiments. The information from many such experiments can be pooled while capturing the inter-individual variability because neuronal identity and function are largely conserved across individuals. Just like electrical engineers use transistor IO-functions to simulate program execution, we argue that neuronal IO-functions could be used to simulate the impressive breadth of brain states and behaviors of C. elegans.

q-bio.NC↗

arXiv2021

A Philosophical Understanding of Representation for Neuroscience

Neuroscientists often describe neural activity as a representation of something, or claim to have found evidence for a neural representation. But what do these statements mean? The reasons to call some neural activity a representation and the assumptions that come with this term are not generally made clear from its common uses in neuroscience. Representation is a central concept in philosophy of mind, with a rich history going back to the ancient period. In order to clarify its usage in neuroscience, here we advance a link between the connotations of this term across these disciplines. We draw on a broad range of discourse in philosophy to distinguish three key aspects of representation: correspondence, functional role, and teleology. We argue that each of these aspects are implied by the explanatory role the term plays in neuroscience. However, evidence related to all three aspects is rarely presented or discussed in the course of individual studies that aim to identify representations. Overlooking the significance of all three aspects hinders communication in neuroscience, as it obscures the limitations of experimental paradigms and conceals gaps in our understanding of the phenomena of primary interest. Working from this three-part view, we discuss how to move toward clearer communication about representations in the brain.

q-bio.NC↗