Reductionistic Explanations of Cognitive Information Processing: Bottoming Out in Neurochemistry

Bechtel, William

doi:10.3389/fnint.2022.944303

Cited by 4 publications

(1 citation statement)

References 88 publications

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“…They typically originate in the midbrain/brainstem, with widespread cortical–subcortical projections, operate on longer time scales, and directly regulate the intracellular biochemistry via G protein coupled receptors . These systems modulate fast neural processing, and it has been suggested that they support unconventional computation and neuronal memory ( Bechtel, 2022 ; Bray, 2009 ; Koch, 1998 ).…”

Section: First Principles Of Neurobiologymentioning

confidence: 99%

Neurobiological Causal Models of Language Processing

Fitz,

Hagoort,

Petersson

2024

Neurobiology of Language

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The language faculty is physically realized in the neurobiological infrastructure of the human brain. Despite significant efforts, an integrated understanding of this system remains a formidable challenge. What is missing from most theoretical accounts is a specification of the neural mechanisms that implement language function. Computational models that have been put forward generally lack an explicit neurobiological foundation. We propose a neurobiologically informed causal modeling approach which offers a framework for how to bridge this gap. A neurobiological causal model is a mechanistic description of language processing that is grounded in, and constrained by, the characteristics of the neurobiological substrate. It intends to model the generators of language behavior at the level of implementational causality. We describe key features and neurobiological component parts from which causal models can be built and provide guidelines on how to implement them in model simulations. Then we outline how this approach can shed new light on the core computational machinery for language, the long-term storage of words in the mental lexicon and combinatorial processing in sentence comprehension. In contrast to cognitive theories of behavior, causal models are formulated in the ‘machine language’ of neurobiology which is universal to human cognition. We argue that neurobiological causal modeling should be pursued in addition to existing approaches. Eventually, this approach will allow us to develop an explicit computational neurobiology of language.

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Section: First Principles Of Neurobiologymentioning

confidence: 99%

Neurobiological Causal Models of Language Processing

Fitz,

Hagoort,

Petersson

2024

Neurobiology of Language

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Organisms Need Mechanisms; Mechanisms Need Organisms

Bechtel,

Bich

2023

History, Philosophy and Theory of the Life Sciences

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According to new mechanists, mechanisms explain how specific biological phenomena are produced. New mechanists have had little to say about how mechanisms relate to the organism in which they reside. A key feature of organisms, emphasized by the autonomy tradition, is that organisms maintain themselves. To do this, they rely on mechanisms. But mechanisms must be controlled so that they produce the phenomena for which they are responsible when and in the manner needed by the organism. To account for how they are controlled, we characterize mechanisms as sets of constraints on the flow of free energy. Some constraints are flexible and can be acted on by other mechanisms, control mechanisms, that utilize information procured from the organism and its environment to alter the flexible constraints in other mechanisms so that they produce phenomena appropriate to the circumstances. We further show that control mechanisms in living organisms are organized heterarchically—control is carried out primarily by local controllers that integrate information they acquire as well as that which they procure from other control mechanisms. The result is not a hierarchy of control but an integrated network of control mechanisms that has been crafted over the course of evolution.

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Eating and Cognition in Two Animals without Neurons: Sponges and Trichoplax

Bechtel,

Bich

2024

Biol Theory

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Eating is a fundamental behavior in which all organisms must engage in order to procure the material and energy from their environment that they need to maintain themselves. Since controlling eating requires procuring, processing, and assessing information, it constitutes a cognitive activity that provides a productive domain for pursuing cognitive biology as proposed by Ladislav Kováč. In agreement with Kováč, we argue that cognition is fundamentally grounded in chemical signaling and processing. To support this thesis, we adopt Cisek’s strategy of phylogenetic refinement, focusing on two animal phyla, Porifera and Placozoa, organisms that do not have neurons, muscles, or an alimentary canal, but nonetheless need to coordinate the activity of cells of multiple types in order to eat. We review what research has revealed so far about how these animals gather and process information to control their eating behavior.

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Reductionistic Explanations of Cognitive Information Processing: Bottoming Out in Neurochemistry

Cited by 4 publications

References 88 publications

Neurobiological Causal Models of Language Processing

Neurobiological Causal Models of Language Processing

Organisms Need Mechanisms; Mechanisms Need Organisms

Eating and Cognition in Two Animals without Neurons: Sponges and Trichoplax

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