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Lateral Inhibition Organizes Beta Attentional Modulation in the Primary Visual Cortex

    https://doi.org/10.1142/S0129065718500478Cited by:3 (Source: Crossref)

    We have previously shown that during top-down attentional modulation (stimulus expectation) correlations of the beta signals across the primary visual cortex were uniform, while during bottom-up attentional processing (visual stimulation) their values were heterogeneous. These different patterns of attentional beta modulation may be caused by feed-forward lateral inhibitory interactions in the visual cortex, activated solely during stimulus processing. To test this hypothesis, we developed a large-scale computational model of the cortical network. We first identified the parameter range needed to support beta rhythm generation, and next, simulated the different activity states corresponding to experimental paradigms. The model matched our experimental data in terms of spatial organization of beta correlations during different attentional states and provided a computational confirmation of the hypothesis that the paradigm-specific beta activation spatial maps depend on the lateral inhibitory mechanism. The model also generated testable predictions that cross-correlation values depend on the distance between the activated columns and on their spatial position with respect to the location of the sensory inputs from the thalamus.

    References

    • 1. L. Leocani, C. Toro, P. Manganotti, P. Zhuang and M. Hallett, Event-related coherence and event-related desynchronization/synchronization in the 10Hz and 20Hz EEG during self-paced movements, Electroencephalogr. Clin. Neurophysiol. — Evoked Potentials 104 (1997) 199–206. MedlineGoogle Scholar
    • 2. M. Bekisz and A. Wróbel, 20Hz rhythm of activity in visual system of perceiving cat, Acta Neurobiol. Exp. 53 (1993) 175–182. MedlineGoogle Scholar
    • 3. T. J. Buschman and E. K. Miller, Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices, Science 315 (2007) 1860–1864. Medline, Web of ScienceGoogle Scholar
    • 4. Y. B. Saalmann, I. N. Pigarev and T. R. Vidyasagar, Neural mechanisms of visual attention: How top-down feedback highlights relevant locations, Science 316 (2007) 1612–1615. Medline, Web of ScienceGoogle Scholar
    • 5. C. A. Bosman, J. M. Schoffelen, N. Brunet, R. Oostenveld, A. M. Bastos, T. Womelsdorf, B. Rubehn, T. Stieglitz, P. De Weerd and P. Fries, Attentional stimulus selection through selective synchronization between monkey visual areas, Neuron 75 (2012) 875–888. Medline, Web of ScienceGoogle Scholar
    • 6. J. R. Iversen, B. H. Repp and A. D. Patel, Top-down control of rhythm perception modulates early auditory responses, Ann. N. Y. Acad. Sci. 1169 (2009) 58–73. Medline, Web of ScienceGoogle Scholar
    • 7. X.-J. Wang, Neurophysiological and computational principles of cortical rhythms in cognition, Physiol. Rev. 90 (2010) 1195–1268. Medline, Web of ScienceGoogle Scholar
    • 8. G. Pfurtscheller, A. Stancák and C. Neuper, Post-movement beta synchronization. A correlate of an idling motor area? Electroencephalogr. Clin. Neurophysiol. 98 (1996) 281–293. MedlineGoogle Scholar
    • 9. A. Pogosyan, L. D. Gaynor, A. Eusebio and P. Brown, Boosting cortical activity at beta-band frequencies slows movement in humans, Curr. Biol. 19 (2009) 1637–1641. Medline, Web of ScienceGoogle Scholar
    • 10. F. Lopes Da Silva, EEG: Origin and measurement, in EEG — fMRI: Physiological Basis, Technique, and Applications (Springer-Verlag, Berlin, 2010), pp. 19–38. Google Scholar
    • 11. S. Haegens, V. Nacher, A. Hernandez, R. Luna, O. Jensen and R. Romo, Beta oscillations in the monkey sensorimotor network reflect somatosensory decision making, Proc. Natl. Acad. Sci. 108 (2011) 10708–10713. Medline, Web of ScienceGoogle Scholar
    • 12. T. H. Donner, M. Siegel, R. Oostenveld, P. Fries, M. Bauer and A. K. Engel, Population activity in the human dorsal pathway predicts the accuracy of visual motion detection, J. Neurophysiol. 98 (2007) 345–359. Medline, Web of ScienceGoogle Scholar
    • 13. B. Pesaran, M. J. Nelson and R. A. Andersen, Free choice activates a decision circuit between frontal and parietal cortex, Nature 453 (2008) 406–409. Medline, Web of ScienceGoogle Scholar
    • 14. S. Weiss and H. M. Mueller, Too many betas do not spoil the broth: The role of beta brain oscillations in language processing, Front. Psychol. 3 (2012) 201. Medline, Web of ScienceGoogle Scholar
    • 15. T. J. Buschman, E. L. Denovellis, C. Diogo, D. Bullock and E. K. Miller, Synchronous oscillatory neural ensembles for rules in the prefrontal cortex, Neuron 76 (2012) 838–846. Medline, Web of ScienceGoogle Scholar
    • 16. A. K. Engel and P. Fries, Beta-band oscillations-signalling the status quo? Curr. Opin. Neurobiol. 20 (2010) 156–165. Medline, Web of ScienceGoogle Scholar
    • 17. M. Bekisz and A. Wróbel, Attention-dependent coupling between beta activities recorded in the cat’s thalamic and cortical representations of the central visual field, Eur. J. Neurosci. 17 (2003) 421–426. Medline, Web of ScienceGoogle Scholar
    • 18. A. Wróbel, A. Ghazaryan, M. Bekisz, W. Bogdan and J. Kamiński, Two streams of attention dependent beta activity in the striate recipient zone of cat’s lateral posterior — pulvinar complex, J. Neurosci. 27 (2007) 2230–2240. Medline, Web of ScienceGoogle Scholar
    • 19. M. Bekisz, W. Bogdan, A. Ghazaryan, W. J. Waleszczyk, E. Kublik and A. Wróbel, The primary visual cortex is differentially modulated by stimulus-driven and top-down attention, PLoS ONE 11 (2016) e0145379. Medline, Web of ScienceGoogle Scholar
    • 20. W. S. Anderson, P. Kudela, J. Cho, G. K. Bergey and P. J. Franaszczuk, Studies of stimulus parameters for seizure disruption using neural network simulations, Biol. Cyb. 97 (2007) 173–194. Medline, Web of ScienceGoogle Scholar
    • 21. R. J. Douglas and K. A. C. Martin, Neuronal circuits of the neocortex, Annu. Rev. Neurosci. 27 (2004) 419–451. Medline, Web of ScienceGoogle Scholar
    • 22. H. Markram, The blue brain project, Nature Rev. Neurosci. 7 (2006) 153–160. Medline, Web of ScienceGoogle Scholar
    • 23. J. Heinzle, P. König and R. F. Salazar, Modulation of synchrony without changes in firing rates, Cogn. Neurodyn. 1 (2007) 225–235. Medline, Web of ScienceGoogle Scholar
    • 24. M. Bazhenov, N. F. Rulkov and I. Timofeev, Effect of synaptic connectivity on long-range synchronization of fast cortical oscillations, J. Neurophysiol. 100 (2008) 1562–1575. Medline, Web of ScienceGoogle Scholar
    • 25. A. Bacci, J. R. Huguenard and D. A. Prince, Modulation of neocortical interneurons: Extrinsic influences and exercises in self-control, Trends Neurosci. 28 (2005) 602–10. Medline, Web of ScienceGoogle Scholar
    • 26. M. W. Reimann, C. A. Anastassiou, R. Perin, S. L. Hill, H. Markram and C. Koch, A biophysically detailed model of neocortical local field potentials predicts the critical role of active membrane currents, Neuron 79 (2013) 375–90. Medline, Web of ScienceGoogle Scholar
    • 27. T. Binzegger, A Quantitative map of the circuit of cat primary visual cortex, J. Neurosci. 24 (2004) 8441–8453. Medline, Web of ScienceGoogle Scholar
    • 28. A. Stepanyants, L. M. Martinez, A. S. Ferecsko and Z. F. Kisvarday, The fractions of short- and long-range connections in the visual cortex, Proc. Natl. Acad. Sci. 106 (2009) 3555–3560. Medline, Web of ScienceGoogle Scholar
    • 29. P. C. Bush and T. J. Sejnowski, Models of cortical networks, in The Cortical Neuron (Oxford University Press, Inc., 2012). Google Scholar
    • 30. X.-J. Wang, J. Tegner, C. Constantinidis and P. S. Goldman-Rakic, Division of labor among distinct subtypes of inhibitory neurons in a cortical microcircuit of working memory, Proc. Natl. Acad. Sci. 101 (2004) 1368–1373. Medline, Web of ScienceGoogle Scholar
    • 31. D. Ferster and S. Lindström, An intracellular analysis of geniculo-cortical connectivity in area 17 of the cat, J. Physiol. 342 (1983) 181–215. Medline, Web of ScienceGoogle Scholar
    • 32. R. Llinás, I. Z. Steinberg and K. Walton, Relationship between presynaptic calcium current and postsynaptic potential in squid giant synapse, Biophys. J. 33 (1981) 323–351. Medline, Web of ScienceGoogle Scholar
    • 33. V. Braitenberg and A. Schüz, Anatomy of the Cortex (Springer-Verlag, Berlin, 1991). Google Scholar
    • 34. S. Leski, H. Lindén, T. Tetzlaff, K. H. Pettersen and G. T. Einevoll, Frequency dependence of signal power and spatial reach of the local field potential, PLoS Comput. Biol. 9 (2013) e1003137. Medline, Web of ScienceGoogle Scholar
    • 35. A. Destexhe, D. Contreras and M. Steriade, Mechanisms underlying the synchronizing action of corticothalamic feedback through inhibition of thalamic relay cells, J. Neurophysiol. 79 (1998) 999–1016. Medline, Web of ScienceGoogle Scholar
    • 36. S. Grossberg and M. Versace, Spikes, synchrony, and attentive learning by laminar thalamocortical circuits, Brain Res. 1218 (2008) 278–312. Medline, Web of ScienceGoogle Scholar
    • 37. U. Mitzdorf, Current source-density method and application in cat cerebral cortex: Investigation of evoked potentials and EEG phenomena, Physiol. Rev. 65 (1985) 37–100. Medline, Web of ScienceGoogle Scholar
    • 38. P. L. Nunez and R. Srinivasan, Electric Fields of the Brain: The Neurophysics of EEG (Oxford University Press, 2006). Google Scholar
    • 39. G. Buzsáki, C. A. Anastassiou and C. Koch, The origin of extracellular fields and currents-EEG, ECoG, LFP and spikes, Nature Rev. Neurosci. 13 (2012) 407–420. Medline, Web of ScienceGoogle Scholar
    • 40. M.-O. Gewaltig and M. Diesmann, NEST (NEural Simulation Tool), Scholarpedia 2 (2007) 1430. Google Scholar
    • 41. M. A. Whittington, R. D. Traub, N. Kopell, B. Ermentrout and E. H. Buhl, Inhibition-based rhythms: Experimental and mathematical observations on network dynamics, Int. J. Psychophysiol. 38 (2000) 315–336. Medline, Web of ScienceGoogle Scholar
    • 42. R. D. Traub, M. A. Whittington, E. H. Buhl, J. G. Jefferys and H. J. Faulkner, On the mechanism of the gamma - > beta frequency shift in neuronal oscillations induced in rat hippocampal slices by tetanic stimulation, J. Neurosci. 19 (1999) 1088–1105. Medline, Web of ScienceGoogle Scholar
    • 43. C. Borgers, S. Epstein and N. J. Kopell, Background gamma rhythmicity and attention in cortical local circuits: A computational study, Proc. Natl. Acad. Sci. 102 (2005) 7002–7007. Medline, Web of ScienceGoogle Scholar
    • 44. P. Tiesinga and T. J. Sejnowski, Cortical enlightenment: Are attentional gamma oscillations driven by ING or PING? Neuron 63 (2009) 727–732. Medline, Web of ScienceGoogle Scholar
    • 45. D. Vierling-Claassen, J. A. Cardin, C. I. Moore and S. R. Jones, Computational modeling of distinct neocortical oscillations driven by cell-type selective optogenetic drive: Separable resonant circuits controlled by low-threshold spiking and fast-spiking interneurons, Front. Hum. Neurosci. 4 (2010) 198. Medline, Web of ScienceGoogle Scholar
    • 46. R. Baddeley, L. F. Abbott, M. C. Booth, F. Sengpiel, T. Freeman, E. A. Wakeman and E. T. Rolls, Responses of neurons in primary and inferior temporal visual cortices to natural scenes, Proc. Biol. Sci. 264 (1997) 1775–1783. Medline, Web of ScienceGoogle Scholar
    • 47. W. S. Pritchard, The brain in fractal time: 1/f-like power spectrum scaling of the human electroencephalogram, Int. J. Neurosci. 66 (1992) 119–129. Medline, Web of ScienceGoogle Scholar
    • 48. W. J. Freeman, L. J. Rogers, M. D. Holmes and D. L. Silbergeld, Spatial spectral analysis of human electrocorticograms including the alpha and gamma bands, J. Neurosci. Methods 95 (2000) 111–121. Medline, Web of ScienceGoogle Scholar
    • 49. C. Bedard, H. Kroger and A. Destexhe, Does the 1/f frequency scaling of brain signals reflect self-organized critical states? Phys. Rev. Lett. 97 (2006) 1–4. The page range is 1-4. Also, the authors are:. Web of ScienceGoogle Scholar
    • 50. W. J. Freeman and J. Zhai, Simulated power spectral density (PSD) of background electrocorticogram (ECoG), Cogn. Neurodyn. 3 (2009) 97–103. Medline, Web of ScienceGoogle Scholar
    • 51. H. Lindén, K. H. Pettersen and G. T. Einevoll, Intrinsic dendritic filtering gives low-pass power spectra of local field potentials, J. Comput. Neurosci. 29 (2010) 423–444. Medline, Web of ScienceGoogle Scholar
    • 52. T. van Kerkoerle, M. W. Self, B. Dagnino, M. A. Gariel-Mathis, J. Poort, C. van der Togt and P. R. Roelfsema, Alpha and gamma oscillations characterize feedback and feedforward processing in monkey visual cortex, Proc. Natl. Acad. Sci. 111 (2014) 14332–14341. Medline, Web of ScienceGoogle Scholar
    • 53. A. M. Bastos, J. Vezoli, C. A. Bosman, J. M. Schoffelen, R. Oostenveld, J. R. Dowdall, P. De Weerd, H. Kennedy and P. Fries, Visual areas exert feedforward and feedback influences through distinct frequency channels, Neuron 85 (2015) 390–401. Medline, Web of ScienceGoogle Scholar
    • 54. A. K. Roopun, M. A. Kramer, L. M. Carracedo, M. Kaiser, C. H. Davies, R. D. Traub, N. J. Kopell and M. A. Whittington, Period concatenation underlies interactions between gamma and beta rhythms in neocortex, Front. Cell. Neurosci. 2 (2008) 1. Medline, Web of ScienceGoogle Scholar
    • 55. W. H. Bosking, Y. Zhang, B. Schofield and D. Fitzpatrick, Orientation selectivity and the arrangement of horizontal connections in tree shrew striate cortex, J. Neurosci. 17 (1997) 2112–2127. Medline, Web of ScienceGoogle Scholar