Arousal increases the representational capacity of cortical tissue

Journal of Computational Neuroscience

Volumn 27, Issue 2, 2009, Pages 211-227

  Fekete, Tomer ^a,b   Pitowsky, Itamar ^b   Grinvald, Amiram ^a   Omer, David B ^a  

^a WEIZMANN INSTITUTE OF SCIENCE   (Israel)

^b HEBREW UNIVERSITY OF JERUSALEM   (Israel)

Author keywords

Arousal; Complexity; Optical imaging; Persistenthomology; Representational capacity; State dependent activity; States of consciousness; Voltage sensitive dye

Indexed keywords

TISSUE;

AROUSAL; COMPLEXITY; CORTICAL ACTIVITY; OPTICAL IMAGING; PERSISTENTHOMOLOGY; REPRESENTATIONAL CAPACITY; STATE DEPENDENT ACTIVITY; STATE OF CONSCIOUSNESS; STATE-DEPENDENT; VOLTAGE SENSITIVE DYES;

TOPOLOGY;

ADAPTIVE BEHAVIOR; ANIMAL EXPERIMENT; AROUSAL; ARTICLE; BRAIN CORTEX; BRAIN FUNCTION; CONCEPT FORMATION; CONTROLLED STUDY; ELECTRIC POTENTIAL; IMAGING SYSTEM; NONHUMAN; PERCEPTIVE THRESHOLD; PRIMATE; PRIORITY JOURNAL; STATISTICAL DISTRIBUTION; VISUAL CORTEX; VISUAL INFORMATION; WAKEFULNESS;

EID: 69549086399     PISSN: 09295313     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10827-009-0138-6     Document Type: Article

References (46)

1. Arieli, A., & Grinvald, A. (2002). Optical imaging combined with targeted electrical recordings, microstimulation, or tracer injections. Journal of Neuroscience Methods, 116(1), 15-28.
2. Arieli, A., Shoham, D., Hildesheim, R., & Grinvald, A. (1995). Coherent spatiotemporal patterns of ongoing activity revealed by real-time optical imaging coupled with single-unit recording in the cat visual cortex. Journal of Neurophysiology, 73, 2072-2093.
3. Arieli, A., Sterkin, A., Grinvald, A., & Aertsen, A. (1996). Dynamics of ongoing activity: Explanation of the large variability in evoked cortical responses. Science, 273, 1868-1871. doi: 10.1126/ science.273.5283.1868.
4. 0 complexity measure. J Neurosci Methods, 15, 159(1), 181-186.
5. Carlsson, G., & de Silva, V. (2004). Topological estimation using witness complexes. Symposium on Point-Based Graphics.
6. Carlsson, G., Ishkhanov, T., de Silva, V., & Zomorodian, A. (2008). On the local behavior of spaces of natural images. International Journal of Computer Vision, 76(1), 1-12. doi: 10.1007/s11263-007-0056-x.
7. Contreras, D., & Llinas, R. (2001). Voltage-sensitive dye imaging of neocortical spatiotemporal dynamics to afferent activation frequency. The Journal of Neuroscience, 21(23), 9403-9413.
8. de Silva, V. (2003). A weak definition of Delaunay triangulation. CoRR, cs.CG/0310031.
9. de Silva, V., & Carlsson, G. (2004). Topological estimation using witness complexes. Symposium on Point-Based Graphics, ETH, Zürich, Switzerland.
10. Edelman, S. (1998). Representation is representation of similarities. The Behavioral and Brain Sciences, 21, 449-498.
11. Edelman, S. (1999). Representation and recognition in vision. Cambridge, MA: Bradford Books.
12. Edelman, S. (2001). Neural spaces: A general framework for the understanding of cognition? The Behavioral and Brain Sciences, 24, 664-665. doi: 10.1017/S0140525X01320083.
13. Edelsbrunner, H., Letscher, D., & Zomorodian, A. (2002). Topological persistence and simplification. Discrete & Computational Geometry, 28(4), 511-533. doi: 10.1007/s00454-002-2885-2.
14. Fiser, J., Chiu, C., & Weliky, M. (2004). Small modulation of ongoing cortical dynamics by sensory input during natural vision. Nature, 431(7008), 573-578. doi: 10.1038/nature02907.
15. Gardenfors, P. (2000). Conceptual spaces. Cambridge, MA: Bradford Books.
16. Gervasoni, D., Lin, S. C., Ribeiro, S., Soares, E. S., Pantoja, J., & Nicolelis, M. A. (2004). Global forebrain dynamics predict rat behavioral states and their transitions. The Journal of Neuroscience, 24(49), 11137-11147. doi: 10.1523/JNEUROSCI.3524-04.2004.
17. Grinvald, A., & Hildesheim, R. (2004). VSDI: A new era in functional imaging of cortical dynamics. Nature Reviews Neuroscience, 5(11), 874-885. doi: 10.1038/nrn1536.
18. Grinvald, A., Shoham, D., Shmuel, A., Glaser, D., Vanzetta, I., Shtoyermann, E., et al. (2001). In-vivo optical imaging of cortical architecture and dynamics. In Modern techniques in neuroscience research. Berlin: Springer.
19. Hobson, A. J., Pace-Schott, E., & Stickgold, R. (2000). Dreaming and the brain: Toward a cognitive neuroscience of conscious states. The Behavioral and Brain Sciences, 23(6), 793-842, 904-1018, 1083-1121. doi: 10.1017/S0140525X00003976.
20. Kendall, D. G., Barden, D., Carne, T. K., & Le, H. (1999). Shape and shape theory. New York: Wiley.
21. Kenet, T., Bibitchkov, D., Tsodyks, M., Grinvald, A., & Arieli, A. (2003). Spontaneously emerging cortical representations of visual attributes. Nature, 425(6961), 954-956. doi: 10.1038/nature02078.
22. Lee, J. (2003). Introduction to smooth manifolds. Graduate texts in Mathematics 218. Berlin: Springer.
23. Leznik, E., Makarenko, V., & Llinas, R. (2002). Electrotonically mediated oscillatory patterns in neuronal ensembles: An in vitro voltage-dependent dye-imaging study in the inferior olive. The Journal of Neuroscience, 22(7), 2804-2815.
24. Llinas, R., Lang, E. J., Welsh, J. P., & Makarenko, V. I. (1997). A new approach to the analysis of multidimensional neuronal activity: Markov random fields. Neural Networks, 10(5), 785-789. doi: 10.1016/ S0893-6080(97)00025-7.
25. Longnecker, D. E., Brown, D. L., Newman, M. F., & Zapol, W. M. (2007). Anesthesiology pp. 863-864. New York: McGraw-Hill.
26. Munkres, J. R. (1984). Elements of algebraic topology. New York: Perseus Books.
27. Omer, D. B., Blumenfeld, B., Tsodyks, M., & Grinvald, A. (2009). A novel method to analyze optical imaging data. Neuron Technique (in press).
28. Petersen, C. C., Grinvald, A., & Sakmann, B. (2003a). Spatiotemporal dynamics of sensory responses in layer 2/3 of rat barrel cortex measured in vivo by voltage-sensitive dye imaging combined with whole-cell voltage recordings and neuron reconstructions. The Journal of Neuroscience, 23(4), 1298-1309.
29. Petersen, C. C., Hahn, T. T., Mehta, M., Grinvald, A., & Sakmann, B. (2003b). Interaction of sensory responses with spontaneous depolarization in layer 2/3 barrel cortex. Proceedings of the National Academy of Sciences of the United States of America, 100(23), 13638-13643. doi: 10.1073/pnas.2235811100.
30. Robins, V. (2000). Computational topology at multiple resolutions. PhD thesis, Department of Applied Mathematics, University of Colorado, Boulder.
31. Robins, V. (2002). Computational topology for point data: Betti numbers of alpha-shapes in morphology of condensed matter: Physics and geometry of spatially complex systems. In Mecke, K., & Stoyan, D. (Eds), Lecture notes in physics, vol. 600, (pp. 261-275). Berlin: Springer.
32. Robins, V. (2006). Betti number signatures of homogeneous Poisson point processes. Physical Review E, 74, 061107.
33. Sharma, J., Angelucci, A., & Sur, M. (2000). Induction of visual orientation modules in auditory cortex. Nature, 404(6780), 841-847.
34. Sharon, D., & Grinvald, A. (2002). Dynamics and constancy in cortical spatiotemporal patterns of orientation processing. Science, 295(5554), 512-515. doi: 10.1126/science.1065916.
35. Shepard, R. N. (1987). Toward a universal law of generalization for psychological science. Science, 237(4820), 1317-1323. doi: 10.1126/ science.3629243.
36. Shoham, D., Glaser, D. E., Arieli, A., Kenet, T., Wijnbergen, C., Toledo, Y., Hildesheim, R., & Grinvald, A. (1999). Imaging cortical dynamics at high spatial and temporal resolution with novel blue voltage-sensitive dyes. Neuron, 24, 791-802. doi: 10.1016/ S0896-6273(00)81027-2.
37. Slovin, H., Arieli, A., Hildesheim, R., & Grinvald, A. (2002). Long-term voltage-sensitive dye imaging reveals cortical dynamics in behaving monkeys. Journal of Neurophysiology, 88(6), 3421-3438. doi: 10.1152/jn.00194.2002.
38. Small, C. G. (1996). The statistical theory of shape. In Springer Series in Statistics. New York: Springer.
39. Sporns, O., Tononi, G., & Edelman, G. M. (2000). Connectivity and complexity: The relationship between neuroanatomy and brain dynamics. Neural Networks, 13(8-9), 909-922. doi: 10.1016/S0893-6080(00)00053-8.
40. Tononi, G. (2004). An information integration theory of consciousness. BMC Neuroscience, 5(1), 42. doi: 10.1186/1471-2202-5-42.
41. Tononi, G., & Edelman, G. M. (1998). Consciousness and complexity. Science, 282(5395), 1846-1851. doi: 10.1126/science.282.5395.1846.
42. Tsodyks, M., Kenet, T., Grinvald, A., & Arieli, A. (1999). Linking spontaneous activity of single cortical neurons and the underlying functional architecture. Science, 286, 1943-1946. doi: 10.1126/ science.286.5446.1943.
43. von Melchner, L., Pallas, S. L., & Sur, M. (2000). Visual behavior mediated by retinal projections directed to the auditory pathway. Nature, 404(6780), 871-876. doi: 10.1038/35009102.
44. Yaffe, E., Fishelovitch, D., Wolfson, H. J., Nussinov, R., & Halperin, D. (2008). MolAxis: Efficient and accurate identification of channels in macromolecules. PROTEINS: Structure, Function, and Bioinformatics, 73, 72-86.
45. Yerkes, R. M., & Dodson, J. D. (1908). The relation of strength of stimulus to rapidity of habit-formation. Journal of Comparative Neurology and Psychology, 18, 459-482. doi: 10.1002/cne.920180503.
46. Zomorodian, A., & Carlsson, G. (2005). Computing persistent homology. Discrete & Computational Geometry, 33(2), 249-274. doi: 10.1007/s00454-004-1146-y.