Abstract
The search for invariances outlined in the previous chapter is taken further with the analysis of empirical methods of behavioral invariance in the study of the mammalian brain. These methods are the bread and butter of the neuroscientist and cognitive neuroscientist: electrophysiology, functional magnetic resonance imaging, and diffusion tensor imaging all search for measurable invariances that may illuminate function and mechanism. This is a simple task as all these methods have inherent particularities, of both empirical and epistemological nature. A clear view on these issues is essential as they have strong bearing on the conclusions about the results of experiments, and by extension on the mechanisms of behavior.
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Notes
- 1.
Statements of the sort “These oscillations have multifold functions and act as universal operators or codes of brain functional activity” are too strong, and suffer from the confusion between correlate and cause [2].
- 2.
Timely. Logothetis [27] asks, “What can and what can’t we do with fMRI.”
- 3.
Recent articles have addressed the question of what precise cellular process is the closest correlate of the BOLD signal, whether it is from all neurons, only excitatory, inhibitory, or glial, cells, whether it applies equally to different areas, and so on. Recent articles have competently shown the different sources and how they contribute to the signal [28, 26].
- 4.
Also, a debate has recently arisen concerning unusually high correlations in fMRI studies of social cognition, where a fundamental flaw in some experimental designs has been unearthed [46].
- 5.
Also noteworthy in Fig. 3.4 is the presence of cores in the left hemisphere in participant C.
- 6.
Usually when there is already the requirement for surgical interventions, or when the patient has full body paralysis.
- 7.
Some popular science, as well as renowned scientists, have created much confusion on this particular topic.
- 8.
“Is the brain precise or noisy?” is a version of this paradox, which is also a rather poor way to pose the question.
- 9.
A variation of this argument applies to the search for dendrites computing logical operations. One finds, or does not find, the logical operations sought. Usually this is done by restricting the context of dendritic function way beyond its biological context.
References
Adolphs R (1999) Social cognition and the human brain. Trends Cogn Sci 3(12):469–479
Basar E, Basar-Eroglu C, Korokos S, Schrürmann M (1999) Oscillatory brain theory: A new trend in neuroscience IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society, 18(3):56–66
Batterman R (2000) Multiple realizability and universality. Br J Philos Sci 51(1):115–145
Carman G, Drury H, Van Essen D (1995) Computational methods for reconstructing and unfolding the cerebral cortex. Cerebr Cortex 5(6):506–517
Decety J, Grèzes J (2006) The power of simulation: Imagining one’s own and other’s behavior. Brain Res 1079(1):4–14
Deschamps M, Kervern G, Massiot D, Pintacuda G, Emsley L, Grandinetti P (2008) Superadiabaticity in magnetic resonance. J Chem Phy 129:204,110
Ding M, Chen Y, Bressler S (2006) Granger causality: Basic theory and application to neuroscience. Arxiv preprint q-bio/0608035
Douglas R, Martin K (1995) Vibrations in the memory. Nature 373(6515):563–564
Eckhorn R, Bauer R, Jordan W, Brosch M, Kruse W, Munk M, Reitboeck H (1988) Coherent oscillations: A mechanism of feature linking in the visual cortex? Biol Cybern 60(2):121–130
Edelman GM (1987) Neural darwinism. Basic Books, New York
Frank LM, Brown E, Wilson M (2000) Trajectory encoding in the hippocampus and entorhinal cortex. Neuron 27:169–178
Freeman W, Baird B (1989) Effects of applied electric current fields on cortical neural activity. Computational Neuroscience, New York, Plenum Press
Freeman WJ (1995) Society of Brains: A study in the neuroscience of love and hate. Laurence Erlbaum Associates Inc, Hillsdale, NJ
Gallese V, Fadiga L, Fogassi L, Rizzolati G (1996) Action recognition in the premotor cortex. Brain 119:593–609
Grossman E, Donnelly M, Price R, Pickens D, Morgan V, Neighbor G, Blake R (2000) Brain areas involved in perception of biological motion. J Cogn Neurosci 12(5):711–720
Hadjikhani N, Liu A, Dale A, Cavanagh P, Tootell R (1998) Retinotopy and color sensitivity in human visual cortical area V 8. Nat Neurosci 1(3):235–241
Hagmann P, Cammoun L, Gigandet X, Meuli R, Honey C, Wedeen V, Sporns O (2008) Mapping the structural core of human cerebral cortex. PLoS Biol 6(7):e159
Haynes J, Rees G (2005a) Predicting the orientation of invisible stimuli from activity in human primary visual cortex. Nat Neurosci 8:686–691
Haynes J, Rees G (2005b) Predicting the stream of consciousness from activity in human visual cortex. Curr Biol 15(14):1301–1307
Haynes J, Rees G (2006) Decoding mental states from brain activity in humans. Nat Rev Neurosci 7(7):523–534
Haynes J, Deichmann R, Rees G (2005) Eye-specific effects of binocular rivalry in the human lateral geniculate nucleus. Nature 438:496–499
Haynes J, Sakai K, Rees G, Gilbert S, Frith C, Passingham R (2007) Reading hidden intentions in the human brain. Curr Biol 17(4):323–328
Hyvärinen A, Oja E (2000) Independent component analysis: Algorithms and applications. Neural Netw 13(4–5):411–430
Jeffery KJ, Burgess N (2006) A metric for the cognitive map: Found at last? Trends Cogn Sci 10(1)
Livet J, Weissman T, Kang H, Draft R, Lu J, Bennis R, Sanes J, Lichtman J (2007) Transgenic strategies for combinatorial expression of fluorescent proteins in the nervous system. Nature 450:56–62
Logothetis NK (2003) The underpinnings of the BOLD functional magnetic resonance imaging signal. J Neurosci 23(10):3963–3971
Logothetis NK (2008) What we can do and what we cannot do with fMRI. Nature 453(7197):869–878
Logothetis NK, Pfeuffer J (2004) On the nature of the BOLD fMRI contrast mechanism. Magn Reson Imaging 22(10):1517–1531
Molnár G, Oláh S, Komlósi G, Füle M, Szabadics J, Varga C, Barzó P, Tamás G (2008) Complex Events Initiated by Individual Spikes in the Human Cerebral Cortex. PLoS Biol 6(9):e222
Mori S, Zhang J (2006) Principles of diffusion tensor imaging and its applications to basic neuroscience research. Neuron 51(5):527–539
Newberg A, Newberg S (2005) The neuropsychology of religious and spiritual experience. Handbook of the psychology of religion and spirituality. pp 199–215
O’Keefe J, Dostrovsky J (1971) The hippocampus as spatial map: preliminary evidence from unit activity in the freely moving rat. Brain Research 34:171–175
Panksepp J (1998) Affective Neuroscience, Oxford UP, chap The Varieties of emotional systems in the brain, pp 41–58
Peigneux P, Orban P, Balteau E, Degueldre C, Luxen A, Laureys S, Maquet P (2006) Offline persistence of memory-related cerebral activity during active wakefulness. PLOS Biology 4(4)
Platt ML, Glimcher PW (1999) Neural correlates of decision variables in parietal cortex. Nature 400:233–238
Preissl H, Pulvermüller F, Lutzenberger W, Birbaumer N (1995) Evoked potentials distinguish between nouns and verbs. Neuroscience Letters 197(1):81–83
Pulvermüller F (2001) Brain reflections of words and their meaning. Trends in Cognitive Sciences 5(12):517–524
Quiroga R, Reddy L, Kreiman G, Koch C, Fried I (2005) Invariant visual representation by single neurons in the human brain. Nature 435(7045):1102–1107
Rizzolatti G, Fadiga L, Gallese V, Fogassi L (1996) Premotor cortex and the recognition of motor actions. Cognitive Brain Research 3(2):131–141
Skaggs W, McNaughton B, Wilson M, Barnes C (1996) Theta phase precession in hippocampal neuronal populations and the compression of temporal sequences. Hippocampus 6(2)
Sporns O, Honey C (2006) Small worlds inside big brains. Proceedings of the National Academy of Sciences 103(51):19,219
Sporns O, Honey C, Kötter R (2007) Identification and classification of hubs in brain networks. PLoS ONE 2(10)
Sutton S, Braren M, Zubin J, John E (1965) Evoked-Potential Correlates of Stimulus Uncertainty. Science 150(3700):1187–1188
Varela F, Toro A, John E, Schwartz E (1981) Perceptual framing and cortical alpha rhythm. Neuropsychologia 19(5):675–86
Varela F, Lachaux J, Rodriguez E, Martinerie J, et al (2001) The brainweb: phase synchronization and large-scale integration. Nature Reviews Neuroscience 2(4):229–239
Vul E, Harris C, Winkielman P, Pashler H (2009 (to appear)) Voodoo correlations in social neuroscience. Perspectives on Psychological Science
Watts D, Strogatz S (1998) Small world. Nature 393:440–442
Wedeen V, Hagmann P, Tseng W, Reese T, Weisskoff R (2005) Mapping Complex Tissue Architecture With Diffusion Spectrum Magnetic Resonance Imaging. Magnetic Resonance in Medicine 54(6):1377
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Negrello, M. (2011). Empirical Assessments of Invariance. In: Invariants of Behavior. Springer Series in Cognitive and Neural Systems, vol 1. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-8804-1_3
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