The Embedded Neuron, the Enactive Field?

Chirimuuta, Mazviita; Gold, Ian

doi:10.1093/oxfordhb/9780195304787.003.0010

Cited by 12 publications

(8 citation statements)

References 87 publications

(91 reference statements)

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“…A full history of the column would finally map the different research strategies that are possible today, after the proclaimed “death” of the column by Horton and Adams (for a similar treatment of the concept of a “receptive field”, see Chirimuuta and Gold 2009 , p. 212ff.).…”

Section: Discussionmentioning

confidence: 99%

“…The following paper attempts to answer the first of these questions as a step towards a larger project that follows the conceptual development of the column into the present. It thereby combines the approach of historians of science to follow the historical trajectories of scientific entities (Rheinberger 1997 ; Daston 1999 ) with the aim of philosophers of neuroscience to “examine the issues raised by central concepts of neuroscience” (Chirimuuta and Gold 2009 , p. 200). In the metaphorical diction of the title, this paper describes the “birth” of the column in neuroscientific practice.…”

Section: Introductionmentioning

confidence: 99%

“… 13 In contrast, psychophysical channel theory has used the concept of orientation selectivity since 1969 to explain how the visual system analyzes images by breaking them down into Fourier components (cf. Chirimuuta and Gold 2009 , p. 205). But as far as I can see, the channel theory played no role in the electrophysiological and anatomical investigation of orientation columns.…”

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confidence: 99%

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The life of the cortical column: opening the domain of functional architecture of the cortex (1955–1981)

Haueis

2016

HPLS

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The concept of the cortical column refers to vertical cell bands with similar response properties, which were initially observed by Vernon Mountcastle’s mapping of single cell recordings in the cat somatic cortex. It has subsequently guided over 50 years of neuroscientific research, in which fundamental questions about the modularity of the cortex and basic principles of sensory information processing were empirically investigated. Nevertheless, the status of the column remains controversial today, as skeptical commentators proclaim that the vertical cell bands are a functionally insignificant by-product of ontogenetic development. This paper inquires how the column came to be viewed as an elementary unit of the cortex from Mountcastle’s discovery in 1955 until David Hubel and Torsten Wiesel’s reception of the Nobel Prize in 1981. I first argue that Mountcastle’s vertical electrode recordings served as criteria for applying the column concept to electrophysiological data. In contrast to previous authors, I claim that this move from electrophysiological data to the phenomenon of columnar responses was concept-laden, but not theory-laden. In the second part of the paper, I argue that Mountcastle’s criteria provided Hubel Wiesel with a conceptual outlook, i.e. it allowed them to anticipate columnar patterns in the cat and macaque visual cortex. I argue that in the late 1970s, this outlook only briefly took a form that one could call a ‘theory’ of the cerebral cortex, before new experimental techniques started to diversify column research. I end by showing how this account of early column research fits into a larger project that follows the conceptual development of the column into the present.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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The life of the cortical column: opening the domain of functional architecture of the cortex (1955–1981)

Haueis

2016

HPLS

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“…Hence these models are sometimes referred to as "linear/nonlinear" (LN) models. Such models make fairly accurate predictions of responses to very simple stimuli displayed in the laboratory, such as dots or bars of light, but fail to predict responses to natural 18 https://www.simonsfoundation.org/2018/01/02/the-state-of-computationalneuroscience/ 19 See Chirimuuta and Gold (2009) on the RF concept and a more detailed discussion of first and second generation work in visual neuroscience described here. See Carandini et al (2005) for a useful review of the strengths and weaknesses of these models.…”

Section: Modelling the Visual Systemmentioning

confidence: 99%

Prediction versus understanding in computationally enhanced neuroscience

Chirimuuta

2020

Synthese

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The use of machine learning instead of traditional models in neuroscience raises significant questions about the epistemic benefits of the newer methods. I draw on the literature on model intelligibility in the philosophy of science to offer some benchmarks for the interpretability of artificial neural networks (ANN's) used as a predictive tool in neuroscience. Following two case studies on the use of ANN's to model motor cortex and the visual system, I argue that the benefit of providing the scientist with understanding of the brain trades off against the predictive accuracy of the models. This trade-off between prediction and understanding is better explained by a non-factivist account of scientific understanding.

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“…Note that amount of plasticity accompanying perceptual learning has probably been underestimated in the past (Chirimuuta and Gold 2009), though it has always been recognised to some degree. However, in a systems neuroscience experiment that does not focus on learning and plasticity specifically, neural activity is typically recorded only after training.…”

Section: Neuroplasticity In Non-bionic Experimentsmentioning

confidence: 99%

Extending, changing, and explaining the brain

Chirimuuta

2013

Biol Philos

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This paper addresses concerns raised recently by Edouardo Datteri (2009) and Carl Craver (2010) about the use of brain-extending prosthetics in experimental neuroscience. Since the operation of the implant induces plastic changes in neural circuits, it is reasonable to worry that operational knowledge of the hybrid system will not be an accurate basis for generalisation when modelling the unextended brain. I argue, however, that Datteri's no-plasticity constraint unwittingly rules out numerous experimental paradigms in behavioural and systems neuroscience which also elicit neural plasticity.Furthermore, I propose that Datteri and Craver's arguments concerning the limitations of prosthetic modelling in basic neuroscience, as opposed to neuroengineering, rests on too narrow a view of the ways models in neuroscience should be evaluated, and that a more pluralist approach is needed. I distinguish organisational validity of models from mechanistic validity. I argue that while prosthetic models may be deficient in the latter of these explanatory virtues because of neuroplasticity, they excel in the former since organisational validity tracks the extent to which a model captures coding principles that are invariant with plasticity. Changing the brain, I conclude, is one viable route towards explaining the brain.

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The Embedded Neuron, the Enactive Field?

Cited by 12 publications

References 87 publications

The life of the cortical column: opening the domain of functional architecture of the cortex (1955–1981)

The life of the cortical column: opening the domain of functional architecture of the cortex (1955–1981)

Prediction versus understanding in computationally enhanced neuroscience

Extending, changing, and explaining the brain

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