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Recurrent Activation of Neural Circuits during Attention to Global and Local Visual Information

Published online by Cambridge University Press:  28 May 2018

Jorge Iglesias-Fuster*
Affiliation:
Centro de Neurociencias de Cuba (Cuba)
Daniela Piña-Novo
Affiliation:
Centro de Neurociencias de Cuba (Cuba)
Marlis Ontivero-Ortega
Affiliation:
Centro de Neurociencias de Cuba (Cuba)
Agustín Lage-Castellanos
Affiliation:
Centro de Neurociencias de Cuba (Cuba)
Mitchell Valdés-Sosa
Affiliation:
Centro de Neurociencias de Cuba (Cuba)
*
*Correspondence concerning this article should be addressed to Jorge Iglesias-Fuster, Centro de Neurociencias de Cuba. Neurociencia Cognitiva. 1600. La Habana (Cuba). E-mail: [email protected]; [email protected]

Abstract

The attentional selection of different hierarchical level within compound (Navon) figures has been studied with event related potentials (ERPs), by controlling the ERPs obtained during attention to the global or the local echelon. These studies, using the canonical Navon figures, have produced contradictory results, with doubts regarding the scalp distribution of the effects. Moreover, the evidence about the temporal evolution of the processing of these two levels is not clear. Here, we unveiled global and local letters at distinct times, which enabled separation of their ERP responses. We combine this approach with the temporal generalization methodology, a novel multivariate technique which facilitates exploring the temporal structure of these ERPs. Opposite lateralization patterns were obtained for the selection negativities generated when attending global and local distracters (D statistics, p < .005), with maxima in right and left occipito-temporal scalp regions, respectively (η2 = .111, p < .01; η2 = .042, p < .04). However, both discrimination negativities elicited when comparing targets and distractors at the global or the local level were lateralized to the left hemisphere (η2 = .25, p < .03 and η2 = .142, p < .05 respectively). Recurrent activation patterns were found for both global and local stimuli, with scalp topographies corresponding to early preparatory stages reemerging during the attentional selection process, thus indicating recursive attentional activation. This implies that selective attention to global and local hierarchical levels recycles similar neural correlates at different time points. These neural correlates appear to be mediated by visual extra-striate areas.

Type
Research Article
Copyright
Copyright © Universidad Complutense de Madrid and Colegio Oficial de Psicólogos de Madrid 2018 

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Footnotes

This study was funded by Fondo Financiero de Ciencia e Innovación (FONCI), CNEURO–12–15.

How to cite this article:

Iglesias-Fuster, J., Piña-Novo, D., Ontivero-Ortega, M., Lage-Castellanos, A., & Valdés-Sosa, M. (2018). Recurrent activation of neural circuits during attention to global and local visual information. The Spanish Journal of Psychology, 21. e17. Doi:10.1017/sjp.2018.9

References

Barak, O., & Tsodyks, M. (2014). Working models of working memory. Current Opinion in Neurobiology, 25, 2024. https://doi.org/10.1016/j.conb.2013.10.008Google Scholar
Boles, D. B., & Karner, T. A. (1996) Hemispheric differences in global versus local processing: Still unclear. Brain and Cognition, 30, 232243. https://doi.org/10.1006/brcg.1996.0015Google Scholar
Corbetta, M., & Shulman, G. L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews Neuroscience, 3, 201215. https://doi.org/10.1038/nrn755Google Scholar
Delis, D. C., Robertson, L. C., & Efron, R. (1986). Hemispheric specialization of memory for visual hierarchical stimuli. Neuropsychologia, 24, 205214. https://doi.org/10.1016/0028-3932(86)90053-9Google Scholar
Desimone, R., & Duncan, J. (1995). Neural mechanisms of selective visual attention. Annual Review of Neuroscience, 18, 193222. https://doi.org/10.1146/annurev.ne.18.030195.001205Google Scholar
Fink, G. R., Marshall, J. C., Halligan, P. W., Frith, C. D., Frackowiak, R. S. J., & Dolan, R. J. (1997). Hemispheric specialization for global and local processing: the effect of stimulus category. Proceedings of the Royal Society B: Biological Sciences, 264, 487494. https://doi.org/10.1098/rspb.1997.0070Google Scholar
Fink, G. R., Halligan, P. W., Marshall, J. C., Frith, C. D., Frackowiak, R. S. J., & Dolan, R. J. (1996). Where in the brain does visual attention select the forest and the trees? Nature, 382, 626628. https://doi.org/10.1038/382626a0CrossRefGoogle ScholarPubMed
Flevaris, A. V., Bentin, S., & Robertson, L. C. (2011). Attentional selection of relative SF mediates global versus local processing: Evidence from EEG. Journal of Vision, 11, 11. https://doi.org/10.1167/11.7.11Google Scholar
Flevaris, A. V., Martínez, A., & Hillyard, S. A. (2014). Attending to global versus local stimulus features modulates neural processing of low versus high spatial frequencies: An analysis with event-related brain potentials. Frontiers in Psychology, 5, 277. https://doi.org/10.3389/fpsyg.2014.00277Google Scholar
Fu, K. M., Foxe, J. J., Murray, M. M., Higgins, B. A., Javitt, D. C., & Schroeder, C. E. (2001). Attention-dependent suppression of distracter visual input can be cross-modally cued as indexed by anticipatory parieto–occipital alpha-band oscillations. Cognitive Brain Research, 12, 145152. https://doi.org/10.1016/S0926-6410(01)00034-9Google Scholar
Galán, L., Biscay, R., Rodríguez, J. L., Pérez-Abalo, M. C., & Rodriguez, R. (1997). Testing topographic differences between event-related brain potentials by using non-parametric combinations of permutation tests. Electroencephalography and Clinical Neurophysiology, 102, 240247. https://doi.org/10.1016/S0013-4694(96)95155-3Google Scholar
Han, S., Fan, S., Chen, L., & Zhuo, Y. (1999). Modulation of brain activities by hierarchical processing: A high-density ERP study. Brain Topography, 11, 171183. https://doi.org/10.1023/A:1022244727182Google Scholar
Han, S., Fan, S., Chen, L., & Zhuo, Y. (1997). On the different processing of wholes and parts: A psychophysiological analysis. Journal of Cognitive Neuroscience, 9, 687698. https://doi.org/10.1162/jocn.1997.9.5.687Google Scholar
Heinze, H. J., & Münte, T. F. (1993). Electrophysiological correlates of hierarchical stimulus processing: Dissociation between onset and later stages of global and local target processing. Neuropsychologia, 31, 841852. https://doi.org/10.1016/0028-3932(93)90132-JGoogle Scholar
Hillyard, S. A., & Anllo-Vento, L. (1998). Event-related brain potentials in the study of visual selective attention. Proceedings of the National Academy of Sciences of the United States of America, 95, 781787. https://doi.org/10.1073/pnas.95.3.781Google Scholar
Iglesias-Fuster, J., Santos-Rodríguez, Y., Trujillo-Barreto, N., & Valdés-Sosa, M. J. (2015). Asynchronous presentation of global and local information reveals effects of attention on brain electrical activity specific to each level. Frontiers in psychology, 5, 1570. https://doi.org/10.3389/fpsyg.2014.01570Google Scholar
Kimchi, R. (2015). The perception of hierarchical structure. In Wagemans, J. (Ed.), Oxford handbook of perceptual organization (pp. 129–49). Oxford, U.K.: Oxford University Press.Google Scholar
King, J. R., & Dehaene, S. (2014). Characterizing the dynamics of mental representations: The temporal generalization method. Trends in Cognitive Sciences, 18, 203210. https://doi.org/10.1016/j.tics.2014.01.002Google Scholar
Kriegeskorte, N., & Bandettini, P. (2007). Analyzing for information, not activation, to exploit high-resolution fMRI. NeuroImage, 38, 649662. https://doi.org/10.1016/j.neuroimage.2007.02.022Google Scholar
López, K., Torres, R., & Valdés-Sosa, M. (2002). Medición directa del tiempo de tránsito atencional entre distintos niveles de figuras jerárquicas: observadores normales y autistas. [Direct index of the speed when shifting attention between different levels in hierarchically organized figures: Autistic observers and healthy controls]. Revista CENIC Ciencias Biológicas, 33, 111117.Google Scholar
Luck, S. J., Chelazzi, L., Hillyard, S. A., & Desimone, R. (1997). Neural mechanisms of spatial selective attention in areas V1, V2, and V4 of macaque visual cortex. Journal of Neurophysiology, 77, 2442. https://doi.org/10.1152/jn.1997.77.1.24Google Scholar
Luck, S. J. (1998). Sources of dual-task interference: Evidence from human electrophysiology. Psychological Science, 9, 223227. https://doi.org/10.1111/1467-9280.00043Google Scholar
Luck, S. J. (2005). Ten simple rules for designing ERP experiments. In Handy, T. C. (Ed.), Event-related potentials: A methods handbook (pp. 1732). Cambridge, MA: MIT Press.Google Scholar
Maris, E., & Oostenveld, R. (2007). Nonparametric statistical testing of EEG and MEG data. Journal of Neuroscience Methods, 164, 177190. https://doi.org/10.1016/j.jneumeth.2007.03.024Google Scholar
Martinez, A., Moses, P., Frank, L., Buxton, R., Wong, E., & Stiles, J. (1997). Hemispheric asymmetries in global and local processing: Evidence from fMRI. Neuroreport, 8, 16851689. https://doi.org/10.1097/00001756-199705060-00025Google Scholar
Martınez, A., Di Russo, F., Anllo-Vento, L., & Hillyard, S. A. (2001). Electrophysiological analysis of cortical mechanisms of selective attention to high and low spatial frequencies. Clinical Neurophysiology, 112, 19801998. https://doi.org/10.1016/S1388-2457(01)00660-5Google Scholar
Michel, C. M., Murray, M. M., Lantz, G., Gonzalez, S., Spinelli, L., & de Peralta, R. G. (2004). EEG source imaging. Clinical Neurophysiology, 115, 21952222. https://doi.org/10.1016/j.clinph.2004.06.001Google Scholar
Murray, M. M., Brunet, D., & Michel, C. M. (2008). Topographic ERP analyses: A step-by-step tutorial review. Brain Topography, 20, 249264. https://doi.org/10.1007/s10548-008-0054-5Google Scholar
Navon, D. (1977). Forest before trees: The precedence of global features in visual perception. Cognitive Psychology, 9, 353383. https://dx.doi.org/10.1016/0010-0285(77)90012-3Google Scholar
Polster, M. R., & Rapcsak, S. Z. (1994). Hierarchical stimuli and hemispheric specialization: Two case studies. Cortex, 30, 487497. https://doi.org/10.1016/S0010-9452(13)80344-9Google Scholar
Robertson, L. C., & Lamb, M. R. (1991). Neuropsychological contributions to theories of part/whole organization. Cognitive Psychology, 23, 299330. https://doi.org/10.1016/0010-0285(91)90012-DGoogle Scholar
Sasaki, Y., Hadjikhani, N., Fischl, B., Liu, A. K., Marret, S., Dale, A. M., & Tootell, R. B. H. (2001). Local and global attention are mapped retinotopically in human occipital cortex. Proceedings of the National Academy of Sciences, 98, 20772082. https://doi.org/10.1073/pnas.98.4.2077Google Scholar
Shibata, K., Yamagishi, N., Goda, N., Yoshioka, T., Yamashita, O., Sato, M. A., & Kawato, M. (2008). The effects of feature attention on prestimulus cortical activity in the human visual system. Cerebral Cortex, 18, 16641675. https://doi.org/10.1093/cercor/bhm194Google Scholar
Stokes, M. G. (2015). ‘Activity-silent’ working memory in prefrontal cortex: A dynamic coding framework. Trends in Cognitive Sciences, 19, 394405. https://doi.org/10.1016/j.tics.2015.05.004Google Scholar
Valdés-Sosa, M. J., Iglesias-Fuster, J., & Torres, R. (2014). Attentional selection of levels within hierarchically organized figures is mediated by object-files. Frontiers in Integrative Neuroscience, 8, 91. https://doi.org/10.3389/fnint.2014.00091Google Scholar
Volberg, G., & Hübner, R. (2004). On the role of response conflicts and stimulus position for hemispheric differences in global/local processing: An ERP study. Neuropsychologia, 42, 18051813. https://doi.org/10.1016/j.neuropsychologia.2004.04.017Google Scholar