M. Chirimuuta, "The Brain Abstracted: Simplification in the History and Philosophy of Neuroscience" (MIT Press, 2024)
Mar 10, 2025
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Mazviita Chirimuuta, a senior lecturer in philosophy at the University of Edinburgh, discusses her book on the oversimplification in neuroscience. She critiques how models misrepresent brain functions, emphasizing the efficiency of biological cognition compared to AI systems. Chirimuuta introduces 'haptic realism', highlighting the interplay between scientific methods and our understanding of the brain. The conversation also addresses misconceptions about AI, the energy demands of data centers, and the philosophical dilemmas in equating brain processes with computer operations.
Standard simplifications in neuroscience overlook critical biological processes, misleading our understanding of brain functionality and cognition.
Haptic realism emphasizes that our knowledge of the brain is shaped by direct interaction and scientific methodologies, rather than mere observation.
Deep dives
The Complexity of the Brain
The brain's functionality cannot be adequately modeled as a simple computational system, as the standard simplifications used in neuroscience overlook the intricate biological processes involved in cognition. Neuroscientists often rely on computational models that abstract away critical details, such as the roles of neurotransmitters and glial cells, which may mislead interpretations of how the brain operates. This complexity challenges the view that the brain can be equated to a computer, emphasizing that while simplification is necessary for scientific inquiry, it should not lead to a literal understanding of brain functions. The argument stresses that true comprehension of cognitive processes necessitates recognizing the brain's biological intricacies rather than relying solely on computational analogies.
Haptic Realism: A New Perspective
Haptic realism proposes that our understanding of the brain is mediated by our interactions with it, likening knowledge to the sense of touch, which necessitates direct engagement rather than distance. This philosophical approach suggests that scientific representations are shaped not only by how we observe but also by the tools and methodologies we employ during our investigations. Consequently, our scientific models should be viewed as approximations rather than literal reflections of reality, acknowledging the interplay between the observer and the observed. By adopting haptic realism, one can explore a more nuanced understanding of scientific inquiry that integrates active engagement with biological systems.
The Implications of Computational Models
The widespread acceptance of computational models in neuroscience leads to misconceptions about the brain's nature, primarily that it functions like a computer. Such beliefs have significant ramifications, particularly influencing public perception and expectations regarding artificial intelligence and machine learning. The assumption that scaling up artificial neural networks will lead to human-like intelligence fails to recognize the unique efficiency and complexity of biological cognition. This oversight contributes to environmental and resource concerns, as the increasing demand for data centers raises significant ecological challenges, highlighting the need for a more realistic understanding of cognitive processes and technology.
Future Directions in Neuroscience
Addressing the limitations of current neuroscience is essential for future research to uncover the fundamental characteristics of cognitive processes. Engaging with the biological realities of the brain, particularly in terms of energy efficiency and signaling, will yield insights into how cognition is structured across various organisms. The concept of basal cognition, which explores cognitive-like processes in single-celled organisms, could bridge the gap between understanding life and cognition, challenging the notion of cognition as exclusive to complex organisms. Advancements in this area can stimulate new frameworks for investigating intelligence that transcend conventional computational views and prioritize biological perspectives.
The Brain Abstracted: Simplification in the History and Philosophy of Neuroscience (MIT Press, 2024), Mazviita Chirimuuta argues that the standard ways neuroscientists simplify the human brain to build models for their research purposes mislead us about how the brain actually works. The key issue, instead, is to figure out which details of brain function are relevant for understanding its role in causing behavior; after all, the biological brain is a highly energetically efficient basis of cognition in contrast to the massive data centers driving AI that are based on the simplification that brain functionality is just a matter of neuronal action potentials. Chirimuuta, who is a senior lecturer in philosophy at the University of Edinburgh, also argues for a Kantian-inspired view of neuroscientific knowledge called haptic realism, according to which what we can know about the brain is the product of interaction between brains and the scientific methods and aims that guide how we investigate them.
