Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-19T05:46:25.805Z Has data issue: false hasContentIssue false
  • English
  • Français

Understanding brain circuits and their dynamics

Published online by Cambridge University Press:  22 October 2010

Antoni Gomila  and
Paco Calvo
Antoni Gomila
Affiliation:
Department of Psychology, University of the Balearic Islands, 070XX Palma, Spain. [email protected]
Paco Calvo
Affiliation:
Department of Philosophy, University of Murcia, 30003 Murcia, Spain. [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

We argue that Anderson's “massive redeployment hypothesis” (MRH) needs further development in several directions. First, a thoroughgoing criticism of the several “embodied cognition” alternatives is required. Second, the course between the Scylla of full holism and the Charybdis of structural-functional modularism must be plotted more distinctly. Third, methodologies better suited to reveal brain circuits must be brought in. Finally, the constraints that naturalistic settings provide should be considered.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 33 , Issue 4 , August 2010 , pp. 274 - 275
Copyright
Copyright © Cambridge University Press 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Behrens, T. E. & Johansen-Berg, H. (2005) Relating connectional architecture to grey matter function using diffusion imaging. Philosophical Transactions of the Royal Society of London, B: Biological Sciences 360:903–11.CrossRefGoogle ScholarPubMed
Casey, B. J., Tottenham, N., Liston, C. & Durston, S. (2005) Imaging the developing brain: What have we learned about cognitive development? Trends in Cognitive Sciences 9(3):104–10.CrossRefGoogle ScholarPubMed
Eguiluz, V. M., Chialvo, D. R., Cecchi, G., Baliki, M. & Apkarian, A. V. (2005) Scale-free brain functional networks. Physical Review Letters 94:18102.CrossRefGoogle ScholarPubMed
Fuentemilla, L. I., Cámara, E., Münte, Th., Krämer, U., Cunillera, A., Marco-Pallarés, J., Tempelmann, C. & Rodríguez-Fornells, A. (2009) Individual differences in true and false memory retrieval are related to white matter brain microstructure. Journal of Neuroscience 29:8698–703.CrossRefGoogle ScholarPubMed
Gomila, A. (2008) Mending or abandoning cognitivism? In: Symbols, embodiment and meaning, ed. Glenberg, A., de Vega, M. & Glaesser, A., pp. 799–834. Oxford University Press.Google Scholar
Kawato, M., Kuroda, T., Imamizu, H., Nakano, E., Miyauchi, S. & Yoshioka, T. (2003) Internal forward models in the cerebellum: fMRI study on grip force and load force coupling. Progress in Brain Research 142:171–88.CrossRefGoogle Scholar
Simon, H. A. (1962/1982) The architecture of complexity: Hierarchical systems. Reprinted in: Simon, H., The sciences of the artificial, 2nd edition, pp. 183–216. MIT Press, 1982.Google Scholar
Spiers, H. J. & Maguire, E. A. (2007) Decoding human brain activity during real-world experiences. Trends in Cognitive Sciences 11(8):356–65.Google Scholar
Sporns, O., Chialvo, D. R., Kaiser, M. & Hilgetag, C. C. (2004) Organization, development and function of complex brain networks. Trends in Cognitive Sciences 8:418–25.CrossRefGoogle ScholarPubMed