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Quantifying the role of neurons for behavior is a mediation question

Published online by Cambridge University Press:  28 November 2019

Ilenna Simone Jones  and
Konrad Paul Kording Open the ORCID record for Konrad Paul Kording [Opens in a new window]
Ilenna Simone Jones
Affiliation:
Department of Neuroscience, University of Pennsylvania, Philadelphia, [email protected]://kordinglab.com/people/ilenna_jones/index.html
Konrad Paul Kording
Affiliation:
Departments of Neuroscience and Bioengineering, University of Pennsylvania, Philadelphia, PA19104. [email protected]://koerding.com/
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Abstract

Many systems neuroscientists want to understand neurons in terms of mediation; we want to understand how neurons are involved in the causal chain from stimulus to behavior. Unfortunately, most tools are inappropriate for that while our language takes mediation for granted. Here we discuss the contrast between our conceptual drive toward mediation and the difficulty of obtaining meaningful evidence.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 42 , 2019 , e233
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Copyright
Copyright © Cambridge University Press 2019

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References

Angrist, J. & Krueger, A. (2001) Instrumental variables and the search for identification: From supply and demand to natural experiments. Journal of Economic Perspectives 15(4):69–85.CrossRefGoogle Scholar
Ashida, G. & Carr, C. E. (2011) Sound localization: Jeffress and beyond. Current Opinion in Neurobiology 21(5):745–51.CrossRefGoogle ScholarPubMed
Glaser, J. I., Perich, M. G., Ramkumar, P., Miller, L. E. & Kording, K. P. (2018) Population coding of conditional probability distributions in dorsal premotor cortex. Nature Communications 9:1788.CrossRefGoogle ScholarPubMed
Jazayeri, M. & Movshon, J. A. (2006) Optimal representation of sensory information by neural populations. Nature Neuroscience 9(5):690–96.CrossRefGoogle ScholarPubMed
Kawashima, T., Zwart, M. F., Yang, C.-T., Mensh, B. D. & Ahrens, M. B. (2016) The serotonergic system tracks the outcomes of actions to mediate short-term motor learning. Cell 167, 933–46.e20.CrossRefGoogle ScholarPubMed
Klein, D. J., König, P. & Körding, K. P. (2003) Sparse spectrotemporal coding of sounds. EURASIP Journal on Advances in Signal Processing 2003;2003:902061.CrossRefGoogle Scholar
Körding, K. P., Kayser, C., Einhäuser, W. & König, P. (2004) How are complex cell properties adapted to the statistics of natural stimuli? Journal of Neurophysiology 91:206–12.CrossRefGoogle ScholarPubMed
Körding, K. P. & Wolpert, D. M. (2004) Bayesian integration in sensorimotor learning. Nature 427:244–47.CrossRefGoogle ScholarPubMed
Körding, K. P. & Wolpert, D. M. (2006) Bayesian decision theory in sensorimotor control. Trends in Cognitive Sciences 10:319–26.CrossRefGoogle ScholarPubMed
Latimer, K. W., Yates, J. L., Meister, M. L. R., Huk, A. C. & Pillow, J. W. (2015) NEURONAL MODELING. Single-trial spike trains in parietal cortex reveal discrete steps during decision-making. Science 349:184–87.Google ScholarPubMed
Perlmutter, J. S. & Mink, J. W. (2006) Deep brain stimulation. Annual Review of Neuroscience 29:229–57.CrossRefGoogle ScholarPubMed
Serruya, M. D., Hatsopoulos, N. G., Paninski, L., Fellows, M. R. & Donoghue, J. P. (2002) Instant neural control of a movement signal. Nature 416:141–2.CrossRefGoogle ScholarPubMed
Stevenson, I. H., Cherian, A., London, B. M., Sachs, N. A., Lindberg, E., Reimer, J., Slutzky, M. W., Hatsopoulos, N. G., Miller, L. E. & Kording, K. P. (2011) Statistical assessment of the stability of neural movement representations. Journal of Neurophysiology 106(2):764–74.CrossRefGoogle ScholarPubMed
Stevenson, I. H. & Kording, K. P. (2011) How advances in neural recording affect data analysis. Nature Neuroscience 14:139–42.CrossRefGoogle Scholar
Vilares, I., Howard, J. D., Fernandes, H. L., Gottfried, J. A. & Kording, K. P. (2012) Differential representations of prior and likelihood uncertainty in the human brain. Current Biology 22:1641–48.CrossRefGoogle ScholarPubMed
Wolpaw, J. R., Birbaumer, N., Heetderks, W. J., McFarland, D. J., Peckham, P. H., Schalk, G., Donchin, E., Quatrano, L. A., Robinson, C. J. & Robinson, C. J. (2000) Brain-computer interface technology: A review of the first international meeting. IEEE Transactions on Rehabilitative Engineering 8:164–73.CrossRefGoogle ScholarPubMed
Wolpert, D. H. & Macready, W. G. (1997) No free lunch theorems for optimization. IEEE Transactions on Evolutionary Computation 1:67–82.CrossRefGoogle Scholar
Wurtz, R. H. (2009) Recounting the impact of Hubel and Wiesel. Journal of Physiology 587:2817–23.CrossRefGoogle ScholarPubMed