Abstract
The philosophical interest in experimental practice in neuroscience has brought renewed attention to the study of the development and use of techniques and tools for data production. John Bickle has argued that the construction and progression of theories in neuroscience are entirely dependent on the development and ingenious use of research tools. In Bickle's account, theory plays a tertiary role, as it depends on what the tools allow researchers to manipulate, and the tools, in turn, are developed not in order to test theories but as solutions to engineering problems. However, Bickle's account is not entirely precise in explaining what informs researchers' decision-making in their atheoretical laboratory tinkering. Identifying the sources that guide researchers in tool development and use is crucial if one wishes to contribute to the philosophical or meta-scientific understanding of experimental practice in neuroscience. In the following paper, I claim that decision-making in tools' development and use in neuroscience is doubly guided. Pre-existing theory and concepts determine information's relevance, whereas tools' functioning in controlled situations determines information's reliability. Accordingly, experimenters' decision-making is situated both in the context of analysing, modelling or interpreting information and in the context of producing information. I study the case of the tungsten microelectrode developed by David Hubel during the 1950s. First, I show that pre-existing theory and concepts (in particular, the "neuron doctrine" and the concepts of "receptive field" and "cortical column") determine in advance what information would be relevant to obtain from the microelectrode. Second, I show that Hubel's tinkering follows the guidelines derived from the very structure of what we recognise as reliable experimentally produced information. Finally, I suggest that data-production processes allow experimenters to assess what to expect from an experimental system in terms of concept- and theory-generation and confirmation, thereby endorsing Bickle's tenet on the tertiary role of theory in neuroscience.
Similar content being viewed by others
References
Abrahamsen, A., & Bechtel, W. (2012). From reactive to endogenously active dynamical conceptions of the brain. In K. S. Plaisance & T. A. C. Reydon (Eds.), Philosophy of behavioral biology (pp. 329–366). Springer.
Atanasova, N. A., Williams, M. T., & Vorhees, C. V. (2022). Science in practice in neuroscience. Cincinnati water maze in the making. In J. Bickle, C. F. Craver, & A.-S. Barwich (Eds.), The tools of neuroscience experiment. Philosophical and scientific perspectives (pp. 56–82). Routledge.
Baetu, T. M. (2016). From interventions to mechanistic explanations. Synthese, 193(10), 3311–3327.
Barlow, H. B. (1972). Single units and sensation: A neuron doctrine for perceptual psychology? Perception, 1(4), 371–394. https://doi.org/10.1068/p010371
Bechtel, W. (2008). Mental mechanisms: Philosophical perspectives on cognitive neuroscience. Routledge.
Bechtel, W. (2009). Looking down, around, and up: Mechanistic explanation in psychology. Philosophical Psychology, 22(5), 543–564. https://doi.org/10.1080/09515080903238948
Bechtel, W. (2013). The endogenously active brain: The need for an alternative cognitive architecture. Philosophia Scientae, 17, 3–30.
Bickle, J. (2016). Revolutions in neuroscience: Tool development. Frontiers in Systems Neuroscience. https://doi.org/10.3389/fnsys.2016.00024
Bickle, J. (2018). From microscopes to optogenetics: Ian hacking vindicated. Philosophy of Science, 85(5), 1065–1077. https://doi.org/10.1086/699760
Bickle, J. (2019). Linking mind to molecular pathways: The role of experiment tools. Axiomathes, 29(6), 577–597. https://doi.org/10.1007/s10516-019-09442-1
Bickle, J. (2020). Laser lights and designer drugs: New techniques for descending levels of mechanisms “in a single bound”? Topics in Cognitive Science. https://doi.org/10.1111/tops.12452
Bickle, J. (2022). Tinkering in the lab. In J. Bickle, C. F. Craver, & A.-S. Barwich (Eds.), The tools of neuroscience experiment. Philosophical and scientific perspectives (pp. 13–36). Routledge.
Bickle, J., Craver, C. F., & Barwich, A.-S. (Eds.). (2022). The tools of neuroscience experiment. Routledge.
Bickle, J., & Kostko, A. (2018). Connection experiments in neurobiology. Synthese, 195(12), 5271–5295. https://doi.org/10.1007/s11229-018-1838-0
Boyd, N. M. (2018). Evidence enriched. Philosophy of Science. https://doi.org/10.1086/697747
Burian, R. (1997). Exploratory Experimentation and the Role of Histochemical Techniques in the Work of Jean Brachet, 1938–1952. History and Philosophy of the Life Sciences, 19, 27–25.
Churchland, P. (1986). Neurophilosophy: Toward a unified science of the mind-brain. MIT Press.
Colaço, D. (2018). Rethinking the role of theory in exploratory experimentation. Biology and Philosophy, 33(5–6), 38.
Craver, C. F. (2007). Explaining the brain. Mechanisms and the mosaic unity of neuroscience. Oxford University Press.
Franklin, L. R. (2005). Exploratory experiments. Philosophy of Science, 72, 888–899.
Gervais, R., & Weber, E. (2015). The role of orientation experiments in discovering mechanisms. Studies in History and Philosophy of Science Part A, 54, 46–55. https://doi.org/10.1016/j.shpsa.2015.08.015
Gold, I., & Roskies, A. L. (2008). Philosophy of neuroscience. In M. Ruse (Ed.), Oxford handbook of philosophy of biology (pp. 349–380). Oxford: Oxford University Press.
Goodman, A., Pepe, A., Blocker, A. W., Borgman, C. L., Cranmer, K., Crosas, M., Di Stefano, R., Gil, Y., Groth, P., Hedstrom, M., Hogg, D. W., Kashyap, V., Mahabal, A., Siemiginowska, A., & Slavkovic, A. (2014). Ten simple rules for the care and feeding of scientific data. PLOS Computational Biology, 10(4), e1003542. https://doi.org/10.1371/journal.pcbi.1003542
Guttinger, S. (2019). A new account of replication in the experimental life sciences. Philosophy of Science, 86(3), 453–471. https://doi.org/10.1086/703555
Guttinger, S. (2020). The limits of replicability. European Journal for Philosophy of Science, 10(2), 10. https://doi.org/10.1007/s13194-019-0269-1
Hardcastle, V. G., & Matthew Stewart, C. (2002). What do brain data really show? Philosophy of Science, 69(S3), S72–S82. https://doi.org/10.1086/341769
Hardcastle, V. G., & Matthew Stewart, C. (2003). Neuroscience and the art of single cell recordings. Biology and Philosophy, 18(1), 195–208. https://doi.org/10.1023/A:1023356317286
Hartline, H. K. (1938). The response of single optic nerve fibers of the vertebrate eye to illumination of the retina. American Journal of Physiology-Legacy Content, 121(2), 400–415. https://doi.org/10.1152/ajplegacy.1938.121.2.400
Hartline, H. K. (1940). The receptive fields of optic nerve fibers. American Journal of Physiology-Legacy Content, 130(4), 690–699. https://doi.org/10.1152/ajplegacy.1940.130.4.690
Hartline, H. K., & Graham, C. H. (1932). Nerve impulses from single receptors in the eye. Journal of Cellular and Comparative Physiology, 1, 277–295.
Haueis, P. (2016). The life of the cortical column: Opening the domain of functional architecture of the cortex (1955–1981). History and Philosophy of the Life Sciences, 38(3), 2. https://doi.org/10.1007/s40656-016-0103-4
Haueis, P. (2020). The death of the cortical column? Patchwork structure and conceptual retirement in neuroscientific practice. Studies in History and Philosophy of Science Part A. https://doi.org/10.1016/j.shpsa.2020.09.010
Haueis, P., & Kästner, L. (2022). Mechanistic inquiry and scientific pursuit: The case of visual processing. Studies in History and Philosophy of Science, 93, 123–135. https://doi.org/10.1016/j.shpsa.2022.03.007
Holmgren, F. (1866). Undersökningar rörande iris’ rörelsemechanism med tillhjelp af kalabar och atropine. Upsala Läkareförenings Förhandlingar, 1(64–76), 160–177.
Hubel, D. H. (1957). Tungsten microelectrode for recording from single units. Science, 125(3247), 549. https://doi.org/10.1126/science.125.3247.549
Hubel, D. H. (1958). Cortical unit responses to visual stimuli in nonanesthetized cats. American Journal of Ophthalmology, 46(32), 110–121. https://doi.org/10.1016/0002-9394(58)90060-6
Hubel, D. H. (1959). Single unit activity in striate cortex of unrestrained cats. The Journal of Physiology, 147(2), 226–238. https://doi.org/10.1113/jphysiol.1959.sp006238
Hubel, D. H. (1996). David H. Hubel. In L. Squire (Ed.), The history of neuroscience in autobiography (Vol. 1, pp. 294–317). Society for Neuroscience.
Hubel, D. H., & Wiesel, T. N. (1959). Receptive fields of single neurones in the cat’s striate cortex. The Journal of Physiology, 148(3), 574–591. https://doi.org/10.1113/jphysiol.1959.sp006308
Hubel, D. H., & Wiesel, T. N. (1961). Integrative action in the cat’s lateral geniculate body. The Journal of Physiology, 155(2), 385–398. https://doi.org/10.1113/jphysiol.1961.sp006635
Hubel, D. H., & Wiesel, T. N. (1962). Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex. The Journal of Physiology, 160(1), 106–154. https://doi.org/10.1113/jphysiol.1962.sp006837
Hubel, D. H., & Wiesel, T. N. (1965). Receptive fields and functional architecture in two nonstriate visual areas (18 and 19) of the cat. Journal of Neurophysiology, 28, 229–289. https://doi.org/10.1152/jn.1965.28.2.229
Hubel, D. H., & Wiesel, T. N. (2005). Brain and visual perception. The story of a 25-year collaboration. Oxford University Press.
Johnson, G. (2022). Tools, experiments, and theories. An examination of the role of experiment tools. In J. Bickle, C. F. Craver, & A.-S. Barwich (Eds.), The tools of neuroscience experiment. Philosophical and scientific perspectives (pp. 37–55). Routledge.
Kantola, L., Piccolino, M., & Wade, N. J. (2019). The action of light on the retina: Translation and commentary of Holmgren (1866). Journal of the History of the Neurosciences, 28(4), 399–415. https://doi.org/10.1080/0964704X.2019.1622942
Kästner, L. (2017). Philosophy of cognitive neuroscience: Causal explanations, mechanisms, and experimental manipulations. Ontos/DeGruyter.
Kästner, L., & Andersen, L. M. (2018). Intervening into mechanisms: Prospects and challenges. Philosophy Compass, 13(11), e12546. https://doi.org/10.1111/phc3.12546
Kästner, L., & Haueis, P. (2019). Discovering patterns: On the norms of mechanistic inquiry. Erkenntnis. https://doi.org/10.1007/s10670-019-00174-7
Kuffler, S. W. (1953). Discharge patterns and functional organization of mammalian retina. Journal of Neurophysiology, 16, 37–68.
Leonelli, S. (2016). Data-centric biology: A philosophical study. Chicago University Press.
Leonelli, S., & Tempini, N. (Eds.). (2020). Data journeys in the sciences. Springer Open.
Levenstein, D., Alvarez, V. A., Amarasingham, A., Azab, H., Gerkin, R. C., Hasenstaub, A., Iyer, R., Jolivet, R. B., Marzen, S., Monaco, J.D. … Prinz, A. A. (2020). On the role of theory and modeling in neuroscience. Retrieved 01 March, 2020, from http://arxiv.org/abs/2003.13825.
Maldonado, P. (2007). What we see is how we are: New paradigms in visual research. Biological Research, 40, 439–450.
Mountcastle, V. B. (1957). Modality and topographic properties of single neurons of cat’s somatic sensory cortex. Journal of Neurophysiology, 20(4), 408–434. https://doi.org/10.1152/jn.1957.20.4.408
Powell, T. P., & Mountcastle, V. B. (1959). Some aspects of the functional organization of the cortex of the postcentral gyrus of the monkey: A correlation of findings obtained in a single unit analysis with cytoarchitecture. Bulletin of the Johns Hopkins Hospital, 105, 133–162.
Rheinberger, H.-J. (1997). Toward a history of epistemic things: Synthesizing proteins in the test tube. Stanford University Press.
Rust, N. C., & Anthony Movshon, J. (2005). In praise of artifice. Nature Neuroscience, 8(12), 1647–1650. https://doi.org/10.1038/nn1606
Schickore, J. (2018). The structure and function of experimental control in the life sciences. Philosophy of Science, 86(2), 203–218. https://doi.org/10.1086/701952
Schmidgen, H. (2014). Hirn und Zeit: die Geschichte eines Experiments, 1800–1950. Matthes & Seitz.
Shepherd, G. M. (2010). Creating modern neuroscience. The revolutionary 1950s. Oxford University Press.
Shepherd, G. M. (2016). Foundations of the neuron doctrine (25th (Anniversary). Oxford Univdrsity Press.
Silva, A. J. (2022). Dissemination and adaptiveness as key variables in tools that fuel scientific revolutions. In J. Bickle, C. F. Craver, & A.-S. Barwich (Eds.), The tools of neuroscience experiment. Philosophical and scientific perspectives (pp. 137–151). Routledge.
Silva, A. J., Landreth, A., & Bickle, J. (2013). Engineering the next revolution in neuroscience: The new science of experiment planning. Oxford University Press.
Steinle, F. (2016). Exploratory experiments. Ampère, Faraday, and the origins of electrodynamics. University of Pittsburgh Press.
Sullivan, J. A. (2007). Reliability and validity of experiment in the neurobiology of learning and memory. History and Philosophy of Science, University of Pittsburgh.
Sullivan, J. A. (2009). The multiplicity of experimental protocols: A challenge to reductionist and non-reductionist models of the unity of neuroscience. Synthese, 167(3), 511–539. https://doi.org/10.1007/s11229-008-9389-4
Sullivan, J. A. (2010). Reconsidering ‘spatial memory’ and the Morris water maze. Synthese, 177(2), 261–283. https://doi.org/10.1007/s11229-010-9849-5
Sullivan, J. (2015). Experimentation in cognitive neuroscience and cognitive neurobiology. In J. Clausen & N. Levy (Eds.), Handbook of neuroethics (pp. 31–47). Springer.
Sullivan, J. A. (2018). Optogenetics, pluralism, and progress. Philosophy of Science, 85(5), 1090–1101. https://doi.org/10.1086/699724
Talbot, S. A., & Kuffler, S. W. (1952). A multibeam ophthalmoscope for the study of retinal physiology. Journal of the Optical Society of America, 42(12), 931–936. https://doi.org/10.1364/josa.42.000931
Tetens, H. (1987). Experimentelle Erfahrung: eine wissenschaftstheoretische Studie über die Rolle des Experiments in der Begriffs- und Theoriebildung der Physik, Paradeigmata. F. Meiner.
Wainer, G., Manuel, J., Fardella, C., & Cristia, J. F. E. (2021). Arche-writing and data-production in theory-oriented scientific practice: The case of free-viewing as experimental system to test the temporal correlation hypothesis. History and Philosophy of the Life Sciences, 43(2), 70. https://doi.org/10.1007/s40656-021-00418-2
Wainer, G., Manuel, J., Espinosa, J. F., Hirmas, N., & Trujillo, N. (2020). Free-viewing as experimental system to test the temporal correlation hypothesis: A case of theory-generative experimental practice. Studies in History and Philosophy of Science Part c: Studies in History and Philosophy of Biological and Biomedical Sciences, 83, 101307. https://doi.org/10.1016/j.shpsc.2020.101307
Yuste, R. (2015). From the neuron doctrine to neural networks. Nature Reviews Neuroscience, 16(8), 487–497. https://doi.org/10.1038/nrn3962
Acknowledgements
This work was supported by the Agencia Nacional de Investigación y Desarrollo (ANID, Government of Chile) under Grant FONDECYT 1210091. I thank all the participants of the FONDECYT project, especially my colleagues José Tomás Alvarado and Abel Wajnerman Paz, for precious feedback and stimulating discussions. I am grateful to two anonymous reviewers whose objections and suggestions helped me improve this paper’s form and content substantially.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The author declares that he has no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Garrido Wainer, J.M. Understanding the development and use of tools in neuroscience: the case of the tungsten micro-electrode. Synthese 200, 446 (2022). https://doi.org/10.1007/s11229-022-03934-1
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s11229-022-03934-1