Learned spatiotemporal sequence recognition and prediction in primary visual cortex

Nature Neuroscience

Volumn 17, Issue 5, 2014, Pages 732-737

  Gavornik, Jeffrey P ^a   Bear, Mark F ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANIMAL EXPERIMENT; ARTICLE; COGNITION; CONTROLLED STUDY; ELECTRIC POTENTIAL; EVOKED VISUAL RESPONSE; LEARNING; LONG TERM POTENTIATION; MEMBRANE CURRENT; MOUSE; NONHUMAN; PLASTICITY; PREDICTION; PRIORITY JOURNAL; RECOGNITION; SENSORY SYSTEM; SPATIOTEMPORAL SEQUENCE LEARNING; STRIATE CORTEX; THALAMOCORTICAL TRACT; VISION; VISUAL STIMULATION;

ALGORITHMS; ANIMALS; ATTENTION; CHOLINERGIC ANTAGONISTS; ELECTRODES, IMPLANTED; EVOKED POTENTIALS, VISUAL; EXCITATORY AMINO ACID ANTAGONISTS; MALE; MICE; MICE, INBRED C57BL; PHOTIC STIMULATION; PIPERAZINES; RECOGNITION (PSYCHOLOGY); SCOPOLAMINE HYDROBROMIDE; SERIAL LEARNING; TIME FACTORS; VISUAL CORTEX; VISUAL PATHWAYS; VISUAL PERCEPTION;

EID: 84899620130     PISSN: 10976256     EISSN: 15461726     Source Type: Journal    
DOI: 10.1038/nn.3683     Document Type: Article

References (41)

1. Lashley, K.S. The problem of serial order in behavior. in Cereberal Mechanisms in Behavior (ed. L.A. Jeffress) 112-131 (Wiley, New York, 1951).
2. Mauk, M.D. & Buonomano, D.V. The neural basis of temporal processing. Annu. Rev. Neurosci. 27, 307-340 (2004).
3. Rhodes, B.J., Bullock, D., Verwey, W.B., Averbeck, B.B. & Page, M.P.A. Learning and production of movement sequences: behavioral, neurophysiological, and modeling perspectives. Hum. Mov. Sci. 23, 699-746 (2004).
4. Song, S., Howard, J.H. & Howard, D.V. Perceptual sequence learning in a serial reaction time task. Exp. Brain Res. 189, 145-158 (2008).
5. Gheysen, F., Van Opstal, F., Roggeman, C., Van Waelvelde, H. & Fias, W. The neural basis of implicit perceptual sequence learning. Front. Hum. Neurosci. 5, 137 (2011).
6. Conway, C.M. & Christiansen, M.H. Sequential learning in non-human primates. Trends Cogn. Sci. 5, 539-546 (2001).
7. Espinosa, J.S. & Stryker, M.P. Development and plasticity of the primary visual cortex. Neuron 75, 230-249 (2012).
8. Frenkel, M.Y. et al. Instructive effect of visual experience in mouse visual cortex. Neuron 51, 339-349 (2006).
9. Cooke, S.F. & Bear, M.F. Visual experience induces long-term potentiation in the primary visual cortex. J. Neurosci. 30, 16304-16313 (2010).
10. Fahle, M. Perceptual learning: a case for early selection. J. Vis. 4, 879-890 (2004).
11. Bear, M.F. & Singer, W. Modulation of visual cortical plasticity by acetylcholine and noradrenaline. Nature 320, 172-176 (1986).
12. Chubykin, A.A., Roach, E.B., Bear, M.F. & Shuler, M.G. A cholinergic mechanism for reward timing within primary visual cortex. Neuron 77, 723-735 (2013).
13. Mitzdorf, U. Current source-density method and application in cat cerebral cortex: investigation of evoked potentials and EEG phenomena. Physiol. Rev. 65, 37-100 (1985).
14. Li, N. & DiCarlo, J.J. Unsupervised natural experience rapidly alters invariant object representation in visual cortex. Science 321, 1502-1507 (2008).
15. Meyer, T. & Olson, C.R. Statistical learning of visual transitions in monkey inferotemporal cortex. Proc. Natl. Acad. Sci. USA 108, 19401-19406 (2011).
16. Eagleman, S.L. & Dragoi, V. Image sequence reactivation in awake V4 networks. Proc. Natl. Acad. Sci. USA 109, 19450-19455 (2012).
17. Gollisch, T. & Meister, M. Eye smarter than scientists believed: neural computations in circuits of the retina. Neuron 65, 150-164 (2010).
18. McIntyre, C.K., Ragozzino, M.E. & Gold, P.E. Intra-amygdala infusions of scopolamine impair performance on a conditioned place preference task but not a spatial radial maze task. Behav. Brain Res. 95, 219-226 (1998).
19. Rao, R.P. & Ballard, D.H. Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects. Nat. Neurosci. 2, 79-87 (1999).
20. Bastos, A.M. et al. Canonical microcircuits for predictive coding. Neuron 76, 695-711 (2012).
21. Spratling, M.W. Predictive coding as a model of response properties in cortical area V1. J. Neurosci. 30, 3531-3543 (2010).
22. Lee, T.S. & Mumford, D. Hierarchical Bayesian inference in the visual cortex. J. Opt. Soc. Am. A Opt. Image Sci. Vis. 20, 1434-1448 (2003).
23. Wacongne, C., Changeux, J.P. & Dehaene, S. A neuronal model of predictive coding accounting for the mismatch negativity. J. Neurosci. 32, 3665-3678 (2012).
24. Shuler, M.G. & Bear, M.F. Reward timing in the primary visual cortex. Science 311, 1606-1609 (2006).
25. Wang, K.H. et al. In vivo two-photon imaging reveals a role of arc in enhancing orientation specificity in visual cortex. Cell 126, 389-402 (2006).
26. Xu, S., Jiang, W., Dan, Y. & Poo, M.-m. Activity recall in a visual cortical ensemble. Nat. Neurosci. 15, 449-455 (2012).
27. Bao, M., Yang, L., Rios, C., He, B. & Engel, S.A. Perceptual learning increases the strength of the earliest signals in visual cortex. J. Neurosci. 30, 15080-15084 (2010).
28. Jehee, J.F., Ling, S., Swisher, J.D., van Bergen, R.S. & Tong, F. Perceptual learning selectively refines orientation representations in early visual cortex. J. Neurosci. 32, 16747-16753 (2012).
29. Marr, D. Vision. A Computational Investigation into the Human Representation and Processing of Visual Information (W.H. Freeman and Company, San Francisco, 1982).
30. Cooke, S.F. & Bear, M.F. How the mechanisms of long-term synaptic potentiation and depression serve experience-dependent plasticity in primary visual cortex. Phil. Trans. R. Soc. Lond. B 369, 20130284 (2014).
31. Liu, J.K. & Buonomano, D.V. Embedding multiple trajectories in simulated recurrent neural networks in a self-organizing manner. J. Neurosci. 29, 13172-13181 (2009).
32. Hasselmo, M.E. The role of acetylcholine in learning and memory. Curr. Opin. Neurobiol. 16, 710-715 (2006).
33. Minces, V.H., Alexander, A.S., Datlow, M., Alfonso, S.I. & Chiba, A.A. The role of visual cortex acetylcholine in learning to discriminate temporally modulated visual stimuli. Front. Behav. Neurosci. 7, 16 (2013).
34. Pinto, L. et al. Fast modulation of visual perception by basal forebrain cholinergic neurons. Nat. Neurosci. 16, 1857-1863 (2013).
35. Cajal, S.R. Comparative study of the sensory areas of the human cortex. in Clark University, 1889-1899: Decennial Celebration (ed. W.E. Story) 311-382 (Clark University Press, Worcestor, Massachusetts, 1899).
36. Douglas, R.J. & Martin, K.A. Mapping the matrix: the ways of neocortex. Neuron 56, 226-238 (2007).
37. DiCarlo, J.J., Zoccolan, D. & Rust, N.C. How does the brain solve visual object recognition? Neuron 73, 415-434 (2012).
38. Howard, J.H. Jr., Howard, D.V., Japikse, K.C. & Eden, G.F. Dyslexics are impaired on implicit higher-order sequence learning, but not on implicit spatial context learning. Neuropsychologia 44, 1131-1144 (2006).
39. Carroll, C.A., Boggs, J., O'Donnell, B.F., Shekhar, A. & Hetrick, W.P. Temporal processing dysfunction in schizophrenia. Brain Cogn. 67, 150-161 (2008).
40. Siegert, R.J., Weatherall, M. & Bell, E.M. Is implicit sequence learning impaired in schizophrenia? A meta-analysis. Brain Cogn. 67, 351-359 (2008).
41. Smith, J.G. & McDowall, J. The implicit sequence learning deficit in patients with Parkinson's disease: A matter of impaired sequence integration? Neuropsychologia 44, 275-288 (2006).