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Structure and function in the predictive brain
Get PDFPredictive processing is an ambitious neurocomputational framework, offering an unified
explanation of all cognitive processes in terms of a single computational operation, namely
prediction error minimization. Whilst this ambitious unificatory claim has been thoroughly
analyzed, less attention has been paid to what predictive processing entails for structure-function
mappings in cognitive neuroscience. We argue that, taken at face value, predictive processing
entails an all-to-one structure-function mapping, wherein each individual neural structure is
assigned the same function, namely minimizing prediction error. Such a structure-function
mapping, we show, is highly problematic. For, barring few, rare occasions, such a
structure-function mapping fails to play the predictive, explanatory and heuristic roles
structure-function mappings are expected to play in cognitive neuroscience. Worse still, it offers a
picture of the brain that we know is wrong. For, it depicts the brain as an equipotential organ; an
organ wherein structural differences do not correspond to any appreciable functional difference,
and wherein each component can substitute for any other component without causing any loss or
degradation of functionality. Somewhat ironically, the very neuroscientific roots of predictive
processing motivate a form of skepticism concerning the framework’s most ambitious unificatory
claims. Do these problems force us to abandon predictive processing? Not necessarily. For, once
the assumption that all cognition can be accounted for exclusively in terms of prediction error
minimization is relaxed, the problems we diagnosed lose their bite
Homeostasis and Health: From Balance to Change
Get PDFAll living systems need to regulate themselves and coordinate the activities of their parts to maintain themselves under changing conditions. Historically, homeostasis is one of the central ideas that have been employed to understand biological regulation. In this article we examine the application of the concept of homeostasis to medicine and its implications for understanding health. We argue that while using homeostasis to characterize health is in line with current criticisms of ideas of health as a complete state of well-being or absence of disease, such an endeavor has been hindered by the adoption of a narrow cybernetic interpretation of homeostasis based on feedback mechanisms and setpoints. This latter interpretation emphasizes stability and balance as the hallmarks of health: a stable physiological state that needs to be preserved or to which an organism needs to return after a perturbation, with change or imbalance as something to be counteracted. William Bechtel has contributed to criticizing this view and reframing the concept of homeostasis by focusing on the organism as a whole. By building on this work and looking at regulation beyond error correction as the organism’s ability to modify its internal dynamics in response to varying conditions, we apply this interpretation of homeostasis to health by advocating for a change of perspective: from a notion of health based on stability and balance to one based on adaptive change. We propose an alternative perspective that emphasizes the capability for change as a new lens through which to understand health
The Universe Is Unknowable from Within It
Get PDFThis is a non-technical piece concerning the unknowability of the universe within the context of general relativity. It is well known that the region beyond the 'observable universe' is unknowable. What is not well known is this: even if one were somehow able to observe this unobservable region, the universe would remain unknowable. Indeed, the puzzling state of affairs would persist even if one were given an all-access pass to every possible observation at every possible place and time -- here, there, past, present, and future. Here, I argue that there is a sense in which the universe is fundamentally unknowable via observations made from within it
The Hallucination That Cannot Be: A Three-Axis Refutation of the Boltzmann Brain Problem
Get PDFThis paper develops a comprehensive refutation of the Boltzmann brain problem along three converging axes — semantic,
ontological, and probabilistic — while maintaining the methodological humility appropriate to cosmological reasoning. First, the
concept of “hallucination” presupposes a reference reality; absent correspondence, the term loses its content and cannot bear
skeptical weight. Second, a “brain” requires a substrate — spatiotemporal location, energy gradients, causal connectivity —
without which mentality is unintelligible; positing a mind in literal nothingness is incoherent, and positing an alien substrate
collapses the “brain” metaphor itself. Third, within any sufficiently large ensemble of fluctuation-generated states, the
combinatorial space of incoherence dwarfs the space of law-like, self-consistent structures; as a result, coherent, persisting
observer-worlds constitute a measure-zero subset and are thus statistically negligible. Together, these considerations dissolve the
threat that Boltzmann-brain observers dominate anthropic reasoning and underwrite the continued trustworthiness of scientific
inference from within a law-governed cosmos.
This argument was developed independently through first-principles reasoning, with iterative dialogue using a large language
model to stress-test the internal coherence of the claims. The intellectual content, structure, and conclusions are entirely the
author’s own
Review of "Closing the Hole Argument", by Hans Halvorson and J.B. Manchak
Get PDFI review the following article: "Closing the Hole Argument", by Hans Halvorson and J.B. Manchak (British Journal for the Philosophy of Science 76, 2025
Thomas Kuhn and the Causal Theory of Reference
Get PDFIt is typically held that Thomas Kuhn was committed to a descriptivist view of the meaning of theoretical terms, and that his most infamous thesis – incommensurability – was a consequence of this. The causal theory of reference supposedly rules out incommensurability by allowing the extension of a term, rather than merely the intension, to (at least partly) constitute the meaning of the term, thereby ensuring that part of the ‘meaning’ remains constant across theory changes. It is therefore surprising to find Kuhn endorsing aspects of the causal theory in several later essays while still maintaining the possibility of incommensurability. This paper will investigate how Kuhn understood both the causal theory and incommensurability, such that his endorsement of both was not the bald-faced contradiction it would be according to the standard reading. In fact, many of the affinities of Kuhn’s view with the causal theory are part of what make incommensurability possible, or so I will argue. More generally, I will suggest that Kuhn should be thought of as rejecting the very idea that the meaning of scientific terms is some aggregate of extension, and intension or sense
Do LLMs Speak? Framework-Relativity and Linguistic Participation
Get PDFLarge language models (LLMs) have reignited debate about whether machines without minds or intentions can genuinely participate in linguistic practice. Critics portray them as ‘stochastic parrots’ that manipulate form without meaning, whereas defenders emphasize their impressive functional capacities. This paper argues that these disputes conflate distinct dimensions of meaning and agency.
I extend Huw Price’s distinction between i-representation and e-representation (roughly, inferential versus environment-tracking types of representation) by differentiating physical e-representation—such as a fuel gauge, grounded in causal coupling—from symbolic e-representation, exemplified in language and mediated by agents. This refinement clarifies what is at issue: LLMs clearly display i-representational competence through their participation in inferentially structured discourse. Whether their outputs possess symbolic e-representational content, however, is contested and framework-relative. It depends on whether agent-mediated uptake is taken to suffice, or whether additional grounding conditions—such as intentions, causal connections, or proper functions—are required.
I further distinguish norm-sensitivity—the capacity to track and adapt to linguistic norms, which grounds their i-representational competence—from norm-responsibility, the reflexive capacity to own commitments and bear accountability. Technical analysis of LLM architectures shows that they exhibit advanced norm-sensitivity through statistical learning but entirely lack norm-responsibility. LLMs thus occupy a distinctive position: they are genuine functional participants in linguistic practices, yet fall short of the reflexive agency characteristic of responsible speakers
Bureaucratic Science: A Public Choice Analysis of Gatekeeping during COVID-19
Get PDFThis paper examines scientific gatekeeping during the COVID-19 pandemic through two key episodes: the suppression of the Great Barrington Declaration's critique of non-pharmaceutical interventions (NPIs) and the pre-mature, prejudicial dismissal of the lab leak hypothesis regarding SARS-CoV-2's origins. Drawing on public choice theory, I argue that scientist-bureaucrats' gatekeeping behaviors were motivated not solely by epistemic goals or public good, but by three distinct incentives: enhancing public perception of their importance, increasing political influence, and protecting captured resources. Analysis of communications between key figures like Fauci, Collins, and Anderson, along with the history of early 21st century pandemic preparedness debates in the United States, reveals discrepancies between private uncertainties and public pronouncements. The paper proposes a "public choice philosophy of science" framework to understand how scientist-bureaucrats operate when their avowed goal is advancing public good rather than knowledge. This approach helps explain why scientific disagreement was suppressed during the pandemic despite its value for both scientific progress and public trust
How to understand empirical adequacy as an aim of science
Get PDFConstructive empiricists consider the aim of constructing empirically adequate theories (roughly, theories that save the phenomena) to be the primary aim of science. This paper addresses the question of how to understand this aim in such a way that it can fruitfully guide scientific practice. My answer comes in two parts. First, there is the issue of how to understand the notion of empirical adequacy, specifically when it comes to the nature of the phenomena to be saved by a theory. I argue that an empirically adequate theory should be understood as a theory that saves the observed phenomena (past, present, and future). This view contrasts with the constructive empiricist view that an empirically adequate theory must save the observable phenomena (regardless of whether such phenomena have been or will ever be observed). Second, there is the issue of the primacy of the aim of constructing empirically adequate theories. I argue for a pluralist empiricism, according to which this aim is just one among many empiricist aims, none of which is primary. This view contrasts with the constructive empiricist view that constructing empirically adequate theories is the primary aim of science
Einstein's 1935 Letters to Schrödinger and Popper and the Boundaries of the PBR ψ-Epistemic Framework
Get PDFEinstein's 1935 critique of quantum mechanics is often associated with the Einstein-Podolsky-Rosen (EPR) argument, yet his private correspondence from that year reveals a more exact conceptual structure guiding his claim that the ψ-function is incomplete. This paper reconstructs Einstein's reasoning in his letters to Schrödinger and Popper and examines how it engages, and fails to engage with contemporary ψ-ontic/ψ-epistemic distinctions. Recent scholarship, most notably by Ben-Menahem, has interpreted Einstein as an early representative of the modern ψ-epistemic tradition within the Harrigan-Spekkens ontological models framework and the Pusey-Barrett-Rudolph (PBR) theorem. I argue, however, that this retrospective classification is undermined by Ben-Menahem's own distinction between realist and radical epistemic interpretations: Einstein's 1935 view lacks the structural assumptions - defined ontic state space, preparation distributions, and overlap structure - required for membership in the HS/PBR class of ψ-epistemic models. Any such identification, therefore, requires importing formal machinery foreign to Einstein's original argumen