More Web Proxy on the site http://driver.im/

article

Brain oscillatory activity during spatial navigation: Theta and gamma activity link medial temporal and parietal regions

Authors:

David J. White,

Joseph Ciorciari,

Richard B. SilbersteinAuthors Info & Claims

Journal of Cognitive Neuroscience, Volume 24, Issue 3

Pages 686 - 697

https://doi.org/10.1162/jocn_a_00098

Published: 01 March 2012 Publication History

Abstract

Brain oscillatory correlates of spatial navigation were investigated using blind source separation (BSS) and standardized low resolution electromagnetic tomography (sLORETA) analyses of 62-channel EEG recordings. Twenty-five participants were instructed to navigate to distinct landmark buildings in a previously learned virtual reality town environment. Data from periods of navigation between landmarks were subject to BSS analyses to obtain source components. Two of these cortical sources were found to exhibit significant spectral power differences during navigation with respect to a resting eyes open condition and were subject to source localization using sLORETA. These two sources were localized as a right parietal component with gamma activation and a right medial-temporal-parietal component with activation in theta and gamma bandwidths. The parietal gamma activity was thought to reflect visuospatial processing associated with the task. The medial-temporal-parietal activity was thought to be more specific to the navigational processing, representing the integration of ego-and allo-centric representations of space required for successful navigation, suggesting theta and gamma oscillations may have a role in integrating information from parietal and medial-temporal regions. Theta activity on this medial-temporal-parietal source was positively correlated with more efficient navigation performance. Results are discussed in light of the depth and proposed closed field structure of the hippocampus and potential implications for scalp EEG data. The findings of the present study suggest that appropriate BSS methods are ideally suited to minimizing the effects of volume conduction in noninvasive recordings, allowing more accurate exploration of deep brain processes.

References

[1]

Alhaj, H. A., Massey, A. E., & McAllister-Williams, R. H. (2006). Effects of DHEA administration on episodic memory, cortisol and mood in healthy young men: A double-blind, placebo-controlled study. Psychopharmacology, 188, 541-551.

[2]

Astur, R. S., Taylor, L. B., Mamelak, A. N., Philpott, L., & Sutherland, R. J. (2002). Humans with hippocampus damage display severe spatial memory impairments in a virtual Morris water maze. Behavioral Brain Research, 132, 77-84.

[3]

Attal, Y., Bhattacharjee, M., Yelnik, J., Cottereau, B., Lefèvre, J., Okada, J., et al. (2009). Modelling and detecting deep brain activity with MEG and EEG. Ingénierie et Recherche Biomédicale, 30, 133-138.

[4]

Babiloni, C., Vecchio, F., Mirabella, G., Buttliglione, M., Sebastiano, F., Picardi, A., et al. (2009). Hippocampal, amygdala, and neocortical synchronization of theta rhythms is related to an immediate recall during Rey Auditory Verbal Learning Test. Human Brain Mapping, 30, 2077-2089.

[5]

Bastiaansen, M., & Hagoort, P. (2003). Event-induced theta responses as a window on the dynamics of memory. Cortex, 39, 967-992.

[6]

Bischof, W. F., & Boulanger, P. (2003). Spatial navigation in virtual reality environments: An EEG analysis. Cyberpsychology & Behavior, 6, 487-495.

[7]

Bloomfield, P. (2000). Fourier analysis of time series (2nd ed.). New York: John Wiley & Sons.

[8]

Bohbot, V. D., Kalina, M., Stepankova, K., Spackova, N., Petrides, M., & Nadel, L. (1998). Spatial memory deficits in patients with lesions to the right hippocampus and to the right parahippocampal cortex. Neuropsychologia, 36, 1217-1238.

[9]

Burgess, N. (2008). Spatial cognition and the brain. Annals of the New York Academy of Sciences, 1124, 77-97.

[10]

Burwell, R. D. (2000). The parahippocampal region: Corticocortical connectivity. Annals of the New York Academy of Sciences, 911, 25-42.

[11]

Buzsáki, G. (2005). Theta rhythm of navigation: Link between path integration and landmark navigation, episodic and semantic memory. Hippocampus, 15, 827-840.

[12]

Byrne, P., Becker, S., & Burgess, N. (2007). Remembering the past and imagining the future: A neural model of spatial memory and imagery. Psychological Review, 114, 340-375.

[13]

Caplan, J. B., Madsen, J. R., Raghavachari, S., & Kahana, M. J. (2001). Distinct patterns of brain oscillations underlie to basic parameters of human maze learning. Journal of Neurophysiology, 86, 368-380.

[14]

Caplan, J. B., Madsen, J. R., Schulze-Bonhage, A., Aschenbrenner-Scheibe, R., Newman, E. L., & Kahana, M. J. (2003). Human theta oscillations related to sensorimotor integration and spatial learning. Journal of Neuroscience, 23, 4726-4736.

[15]

Chen, A. C. N., Feng, W., Zhao, H., Yin, Y., & Wang, P. (2008). EEG default mode network in the human brain: Spectral regional field powers. Neuroimage, 41, 561-574.

[16]

Collins, D. L., Neelin, P., Peters, T. M., & Evans, A. C. (1994). Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. Journal of Computer Assisted Tomography, 18, 192-205.

[17]

Congedo, M. (2006). Subspace projection filters for real-time brain electromagnetic imaging. IEEE Transactions on Bio-Medical Engineering, 53, 1624-1634.

[18]

Congedo, M., Gouy-Pailler, C., & Jutten, C. (2008). On the blind source separation of human electroencephalogram by approximate joint diagonalization of second order statistics. Clinical Neurophysiology, 119, 2677-2686.

[19]

Congedo, M., John, E. R., De Ridder, D., & Prichep, L. (2010). Group independent component analysis of resting-state EEG in large normative samples. International Journal of Psychophysiology, 78, 89-99.

[20]

Congedo, M., Ozen, C., & Sherlin, L. (2002). Notes on EEG resampling by natural cubic spline interpolation. Journal of Neurotherapy, 6, 73-80.

[21]

Cornwell, B. R., Johnson, L. L., Holroyd, T., Carver, F. W., & Grillon, C. (2008). Human hippocampal and parahippocampal theta during goal-directed spatial navigation predicts performance on a virtual Morris water maze. Journal of Neuroscience, 28, 5983-5990.

[22]

Cornwell, B. R., Salvadore, G., Colon-Rosario, V., Latov, D. R., Holroyd, T., Carver, F. W., et al. (2010). Abnormal hippocampal functioning and impaired spatial navigation in depressed individuals: Evidence from whole-head magnetoencephalography. American Journal of Psychiatry, 167, 836-844.

[23]

de Araújo, D. B., Baffa, O., & Wakai, R. T. (2002). Theta oscillations and human navigation: A magnetoencephalography study. Journal of Cognitive Neuroscience, 14, 70-78.

Digital Library

[24]

Delorme, A., Sejnowski, T., & Makeig, S. (2007). Enhanced detection of artifacts in EEG data using higher-order statistics and independent component analysis. Neuroimage, 34, 1443-1449.

[25]

Delorme, A., Westerfield, M., & Makeig, S. (2007). Medial prefrontal theta bursts precede rapid motor responses during visual selective attention. Journal of Neuroscience, 27, 11949-11959.

[26]

Ekstrom, A. D., Caplan, J. B., Ho, E., Shattuck, K., Fried, I., & Kahana, M. J. (2005). Human hippocampal theta activity during virtual navigation. Hippocampus, 15, 881-889.

[27]

Ekstrom, A. D., Kahana, M. J., Caplan, J. B., Fields, T. A., Isham, E. A., Newman, E. L., et al. (2003). Cellular networks underlying human spatial navigation. Nature, 25, 184-187.

[28]

Fernández, G., Effern, A., Grunwald, T., Pezer, N., Lehnertz, K., Dümpelmann, M., et al. (1999). Real-time tracking of memory formation in the human rhinal cortex and hippocampus. Science, 285, 1582-1585.

[29]

Fernández, G., Klaver, P., Fell, J., Grunwald, T., & Elger, C. E. (2002). Human declarative memory function: Separating rhinal and hippocampal contributions. Hippocampus, 12, 514-519.

[30]

Fiori, S. (2003). Overview of independent component analysis technique with an application to synthetic aperture radar (SAR) imagery processing. Neural Network, 16, 453-467.

Digital Library

[31]

González-Hernández, J. A., Céspedes-Garcia, Y., Campbell, K., Scherbaum, W. A., Bosch-Bayard, J., & Figueredo-Rodríguez, P. (2005). A pre-task resting condition neither "baseline" nor "zero". Neuroscience Letters, 391, 43-47.

[32]

Grau, C., Fuentemilla, L., & Marco-Pallarés, J. (2007). Functional neural dynamics underlying auditory event-related N1 and N1 suppression response. Neuroimage, 36, 522-531.

[33]

Grön, G., Wunderlich, A. P., Spitzer, M., Tomczak, R., & Riepe, M. W. (2000). Brain activation during human navigation: Gender-different neural networks as substrate of performance. Nature Neuroscience, 3, 404-408.

[34]

Hafting, T., Fyhn, M., Molden, S., Moser, M.-B., & Moser, E. I. (2005). Microstructure of a spatial map in the entorhinal cortex. Nature, 436, 801-806.

[35]

Hartley, J., Maguire, E. A., Spiers, H. J., & Burgess, N. (2003). The well-worn route and the path less traveled: Distinct neural bases of route following and wayfinding in humans. Neuron, 7, 877-888.

[36]

Hori, E., Nishio, Y., Kazui, K., Umeno, K., Tabuchi, E., Sasaki, K., et al. (2005). Place-related neural responses in the monkey hippocampal formation in a virtual space. Hippocampus, 15, 991-996.

[37]

Huang, R. S., Jung, T. P., Delorme, A., & Makeig, S. (2008). Tonic and phasic electroencephalographic dynamics during continuous compensatory tracking. Neuroimage, 39, 1896-1909.

[38]

Iaria, G., Chen, J. K., Guariglia, C., Ptito, A., & Petrides, M. (2007). Retrosplenial and hippocampal brain regions in human navigation: Complimentary functional contributions to the formation and use of cognitive maps. European Journal of Neuroscience, 25, 890-899.

[39]

Jacobs, J., Korolev, I. O., Caplan, J. B., Ekstrom, A. D., Litt, B., Baltuch, G., et al. (2010). Right-lateralized brain oscillations in human spatial navigation. Journal of Cognitive Neuroscience, 22, 824-836.

Digital Library

[40]

James, C. J., & Hesse, C. W. (2005). Independent component analysis for biomedical signals. Physiological Measurement, 26, R15-R39.

[41]

Jang, G. J., Lee, T. W., & Oh, Y. H. (2002). Learning statistically efficient features for speaker recognition. Neurocomputing, 49, 329-348.

[42]

Kahana, M. J., Sekuler, R., Caplan, J. B., Kirschen, M., & Madsen, J. R. (1999). Human theta oscillations exhibit task dependence during virtual maze navigation. Nature, 399, 781-784.

[43]

Klee, M., & Rall, W. (1977). Computed potentials of cortically arranged populations of neurons. Journal of Neurophysiology, 40, 647-666.

[44]

Leal, A. J. R., Dias, A. I., Vieira, J. P., Moreira, A., Távora, L., & Calado, E. (2008). Analysis of the dynamics and origin of epileptic activity in patients with tuberous sclerosis evaluated for surgery of epilepsy. Clinical Neurophysiology, 119, 853-861.

[45]

Leal, A. J. R., Nunes, S., Dias, A. I., Vieira, J. P., Moreira, A., & Calado, E. (2007). Analysis of the generators of epileptic activity in early-onset childhood benign occipital lobe epilepsy. Clinical Neurophysiology, 118, 1341-1347.

[46]

Lee, A. C. H., Buckley, M. J., Pegman, S. J., Spiers, H., Scahill, V. L., Gaffan, D., et al. (2005). Specialization in the medial temporal lobe for processing of objects and scenes. Hippocampus, 15, 782-797.

[47]

Lisman, J. (2005). The theta/gamma discrete phase code occurring during the hippocampal phase precession may be a more general brain coding scheme. Hippocampus, 15, 913-922.

[48]

Lisman, J., & Buzsáki, G. (2008). A neural coding scheme formed by the combined function of gamma and theta oscillations. Schizophrenia Bulletin, 34, 974-980.

[49]

Lorente de Nò, R. (1947). Action potential of motoneurons of the hypoglossus nucleus. Journal of Cellular and Comparative Physiology, 29, 207-287.

[50]

Mackay, J. C., Kirk, I. J., Hamm, J. P., & Johnson, B. W. (2001). Human theta oscillations in virtual maze navigation and Sternberg tasks. International Journal of Neuroscience, 109, 180.

[51]

Maguire, E. A., Burgess, N., Donnett, J. G., Frackowiak, R. S. J., Frith, C. D., & O'Keefe, J. (1998). Knowing where and getting there: A human navigation network. Science, 280, 921-924.

[52]

Marco-Pallarés, J., Grau, C., & Ruffini, G. (2005). Combined ICA-LORETA analysis of mismatch negativity. Neuroimage, 25, 471-477.

[53]

Matsumura, N., Nishijo, H., Tamura, R., Eifuku, S., Endo, S., & Ono, T. (1999). Spatial- and task-dependent neuronal responses during real and virtual translocation in the monkey hippocampal formation. Journal of Neuroscience, 19, 2381-2393.

[54]

Moser, E. I., Kropff, E., & Moser, M. B. (2008). Place cells, grid cells, and the brain's spatial representation system. Annual Review of Neuroscience, 31, 69-89.

[55]

Mutihac, R., & Mutihac, R. C. (2007). A comparative study of independent component analysis algorithms for electroencephalography. Romanian Reports in Physics, 59, 831-860.

[56]

Nunez, P. L., & Srinivasan, R. (2006). Electric fields of the brain: The neurophysics of EEG (2nd ed.). New York: Oxford University Press.

[57]

Nunn, J. A., Graydon, F. J. X., Polkey, C. E., & Morris, R. G. (1999). Differential spatial memory impairment after right temporal lobectomy demonstrated using temporal titration. Brain, 122, 47-59.

[58]

O'Keefe, J., & Nadel, L. (1978). The hippocampus as a cognitive map. Oxford: Oxford University Press.

[59]

Onton, J., Delorme, A., & Makeig, S. (2005). Frontal midline EEG dynamics during working memory. Neuroimage, 27, 341-356.

[60]

Onton, J., Westerfield, M., Townsend, J., & Makeig, S. (2006). Imaging human EEG dynamics using independent component analysis. Neuroscience & Biobehavioral Reviews, 30, 808-822.

[61]

Parslow, D. M., Morris, R. G., Fleminger, S., Rahman, Q., Abrahams, S., & Recce, M. (2005). Allocentric spatial memory in humans with hippocampal lesions. Acta Psychologica, 118, 123-147.

[62]

Pascual-Marqui, R. D. (2002). Standardized low resolution brain electromagnetic tomography (sLORETA): Technical details. Methods & Findings in Experimental & Clinical Pharmacology, 24(Suppl. D), 5-12.

[63]

Romero, S., Mañanas, M. A., & Barbanoj, M. J. (2008). A comparative study of automatic techniques for ocular artifact reduction in spontaneous EEG signals based on clinical target variables: A simulation case. Computers in Biology & Medicine, 38, 348-360.

Digital Library

[64]

Rosburg, T., Trautner, P., Ludowig, E., Scaller, C., Kurthen, M., Elger, C. E., et al. (2007). Hippocampal event-related potentials to tone duration deviance in a passive oddball paradigm in humans. Neuroimage, 37, 274-281.

[65]

Seixas, S., Brotchie, P., Crewther, D., & Ip, S. (2006). Spatial coordinate systems within the parietal lobes: Localization of a cognitive spatial map in humans. Clinical EEG & Neuroscience, 37, 167-168.

[66]

Sirota, A., Montgomery, S., Fujisawa, S., Isomura, Y., Zugaro, M., & Buzsáki, G. (2008). Entrainment of neocortical neurons and gamma oscillations by the hippocampal theta rhythm. Neuron, 60, 683-697.

[67]

Stark, C. E. L., & Squire, L. R. (2001). When zero is not zero: The problem of ambiguous baseline conditions in fMRI. Proceedings of the National Academy of Sciences, U.S.A., 98, 12760-12766.

[68]

Talairach, J., & Tournoux, P. (1988). Co-planar stereotaxic atlas of the human brain: Three-dimensional proportional system. Stuttgart: Georg Thieme.

[69]

Tesche, C. D., & Karhu, J. (2000). Theta oscillations index human hippocampal activation during a working memory task. Proceedings of the National Academy of Sciences, U.S.A., 97, 919-924.

[70]

Tichavsky, P., & Yeredor, A. (2009). Fast approximate joint diagonalization incorporating weight matrices. IEEE Transactions on Signal Processing, 57, 878-891.

Digital Library

[71]

Towle, V. L., Bolaños, J., Suarez, D., Tan, K., Grzeszczuk, R., Levin, D. N., et al. (1993). The spatial location of EEG electrodes: Locating the best fitting sphere relative to cortical anatomy. Electroencephalography and Clinical Neuroscience, 86, 1-6.

[72]

van der Loo, E., Congedo, M., Plazier, M., Van de Heyning, P., & De Ridder, D. (2007). Correlation between independent components of scalp EEG and intracranial EEG (iEEG) time series. International Journal of Bioelectromagnetism, 9, 270-275.

[73]

van der Veen, A. J., Talwar, S., & Paulraj, A. (1997). A subspace approach to blind space-time signal processing for wireless communication systems. IEEE Transactions on Signal Processing, 45, 173-190.

Digital Library

[74]

Wagner, M., Fuchs, M., & Kastner, J. (2004). Evaluation of sLORETA in the presence of noise and multiple sources. Brain Topography, 16, 277-280.

[75]

Welch, P. D. (1967). The use of Fast Fourier Transform for the estimation of power spectra: A method based on time averaging over short, modified periodograms. IEEE Transactions on Audio & Electroacoustics, 15, 70-74.

[76]

Westfall, P. H., & Young, S. S. (1993). Resampling-based multiple testing. New York: John Wiley & Sons.

[77]

Whitlock, J. R., Sutherland, R. J., Witter, M. P., Moser, M. B., & Moser, E. I. (2008). Navigating from hippocampus to parietal cortex. Proceedings of the National Academy of Sciences, U.S.A., 105, 14755-14762.

[78]

Yuen, P. C., & Lai, J. H. (2002). Face representation using independent component analysis. Pattern Recognition, 35, 1247-1257.

Cited By

Lekova AChavdarov I(2021)A Fuzzy Shell for Developing an Interpretable BCI Based on the Spatiotemporal Dynamics of the Evoked OscillationsComputational Intelligence and Neuroscience10.1155/2021/66856722021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/6685672
Wang GSuh A(2021)A Literature Review on a Neuro-Psychological Approach to Immersive Technology ResearchAugmented Cognition10.1007/978-3-030-78114-9_8(97-115)Online publication date: 24-Jul-2021
https://dl.acm.org/doi/10.1007/978-3-030-78114-9_8

Recommendations

Brain networks related to beta oscillatory activity during episodic memory retrieval

Evidence from fMRI has consistently located a widespread network of frontal, parietal, and temporal lobe regions during episodic retrieval. However, the temporal limitations of the fMRI methodology have made it difficult to assess the transient network ...
Patterns of Brain Activity during Visual Imagery of Letters

Cortical signals associated with visual imagery of letters were recorded from 10 healthy adults with a whole-scalp 122-channel neuromagnetometer. The auditory stimulus sequence consisted of 20 different phonemes corresponding to single letters of the ...
Brain activity underlying mental imagery: Event-related potentials during mental image generation

This article addresses two issues about the neural bases of mental imagery. The first issue concerns the modality-specificity of mental images, that is, whether or not they involve activity in visual areas of the brain. The second issue concerns ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Journal of Cognitive Neuroscience

Journal of Cognitive Neuroscience Volume 24, Issue 3

March 2012

243 pages

ISSN:0898-929X

EISSN:1530-8898

Issue’s Table of Contents

Publisher

MIT Press

Cambridge, MA, United States

Publication History

Published: 01 March 2012

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

2
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 24 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Lekova AChavdarov I(2021)A Fuzzy Shell for Developing an Interpretable BCI Based on the Spatiotemporal Dynamics of the Evoked OscillationsComputational Intelligence and Neuroscience10.1155/2021/66856722021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/6685672
Wang GSuh A(2021)A Literature Review on a Neuro-Psychological Approach to Immersive Technology ResearchAugmented Cognition10.1007/978-3-030-78114-9_8(97-115)Online publication date: 24-Jul-2021
https://dl.acm.org/doi/10.1007/978-3-030-78114-9_8

View Options

View options

Media

Figures

Other

Tables

View Issue’s Table of Contents