Abstract
To comprehensively investigate the potential temporal dynamic and static abnormalities of spontaneous brain activity (SBA) in left temporal lobe epilepsy (LTLE) and right temporal lobe epilepsy (RTLE) and to detect whether these alterations correlate with cognition. Twelve SBA metrics, including ALFF, dALFF, fALFF, dfALFF, ReHo, dReHo, DC, dDC, GSCorr, dGSCorr, VMHC, and dVMHC, in 46 LTLE patients, 43 RTLE patients, and 53 healthy volunteers were compared in the voxel-wise analysis. Correlation analyses between metrics in regions showing statistic differences and epilepsy duration, epilepsy severity, and cognition scores were also performed. Compared with the healthy volunteers, the alteration of SBA was identified both in LTLE and RTLE patients. The ALFF, fALFF, and dALFF values in LTLE, as well as the fALFF values in RTLE, increased in the bilateral thalamus, basal ganglia, mesial temporal lobe, cerebellum, and vermis. Increased dfALFF in the bilateral basal ganglia, increased ReHo and dReHo in the bilateral thalamus in the LTLE group, increased ALFF and dALFF in the pons, and increased ReHo and dReHo in the right hippocampus in the RTLE group were also detected. However, the majority of deactivation clusters were in the ipsilateral lateral temporal lobe. For LTLE, the fALFF, DC, dDC, and GSCorr values in the left lateral temporal lobe and the ReHo and VMHC values in the bilateral lateral temporal lobe all decreased. For RTLE, the ALFF, fALFF, dfALFF, ReHo, dReHo, and DC values in the right lateral temporal lobe and the VMHC values in the bilateral lateral temporal lobe all decreased. Moreover, for both the LTLE and RTLE groups, the dVMHC values decreased in the calcarine cortex. The most significant difference between LTLE and RTLE was the higher activation in the cerebellum of the LTLE group. The alterations of many SBA metrics were correlated with cognition and epilepsy duration. The patterns of change in SBA abnormalities in the LTLE and RTLE patients were generally similar. The integrated application of temporal dynamic and static SBA metrics might aid in the investigation of the propagation and suppression pathways of seizure activity as well as the cognitive impairment mechanisms in TLE.
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs11682-023-00835-w/MediaObjects/11682_2023_835_Fig1_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs11682-023-00835-w/MediaObjects/11682_2023_835_Fig2_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs11682-023-00835-w/MediaObjects/11682_2023_835_Fig3_HTML.png)
Similar content being viewed by others
Data availability
The datasets presented in this article are not readily available because of the privacy of all the participants. The data that support the findings of this study are available from the corresponding author on reasonable request.
Code availability
Not applicable.
References
Alessio, A., Pereira, F. R., Sercheli, M. S., et al. (2013). Brain plasticity for verbal and visual memories in patients with mesial temporal lobe epilepsy and hippocampal sclerosis: An fMRI study. Human Brain Mapping, 34(1), 186–199. https://doi.org/10.1002/hbm.21432
Allone, C., Lo Buono, V., Corallo, F., et al. (2017). Neuroimaging and cognitive functions in temporal lobe epilepsy: A review of the literature. Journal of the Neurological Sciences, 381, 7–15. https://doi.org/10.1016/j.jns.2017.08.007
Araújo, D., Santos, A. C., Velasco, T. R., et al. (2006). Volumetric evidence of bilateral damage in unilateral mesial temporal lobe epilepsy. Epilepsia, 47(8), 1354–1359. https://doi.org/10.1111/j.1528-1167.2006.00605.x
Behrens, T. E., Johansen-Berg, H., Woolrich, M. W., et al. (2003). Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging. Nature Neuroscience, 6(7), 750–757. https://doi.org/10.1038/nn1075
Bernasconi, N., Bernasconi, A., Caramanos, Z., et al. (2003). Mesial temporal damage in temporal lobe epilepsy: A volumetric MRI study of the hippocampus, amygdala and parahippocampal region. Brain, 126(Pt 2), 462–469. https://doi.org/10.1093/brain/awg034
Besson, P., Dinkelacker, V., Valabregue, R., et al. (2014). Structural connectivity differences in left and right temporal lobe epilepsy. NeuroImage, 100, 135–144. https://doi.org/10.1016/j.neuroimage.2014.04.071
Bettus, G., Wendling, F., Guye, M., et al. (2008). Enhanced EEG functional connectivity in mesial temporal lobe epilepsy. Epilepsy Research, 81(1), 58–68. https://doi.org/10.1016/j.eplepsyres.2008.04.020
Blumenfeld, H., McNally, K. A., Vanderhill, S. D., et al. (2004). Positive and negative network correlations in temporal lobe epilepsy. Cerebral Cortex, 14(8), 892–902. https://doi.org/10.1093/cercor/bhh048
Burianová, H., Faizo, N. L., Gray, M., et al. (2017). Altered functional connectivity in mesial temporal lobe epilepsy. Epilepsy Research, 137, 45–52. https://doi.org/10.1016/j.eplepsyres.2017.09.001
Burwell, R. D. (2000). The parahippocampal region: Corticocortical connectivity. Annals of the New York Academy of Sciences, 911, 25–42. https://doi.org/10.1111/j.1749-6632.2000.tb06717.x
Cataldi, M., Avoli, M., & de Villers-Sidani, E. (2013). Resting state networks in temporal lobe epilepsy. Epilepsia, 54(12), 2048–2059. https://doi.org/10.1111/epi.12400
Chang, Y. A., Marshall, A., Bahrami, N., et al. (2019). Differential sensitivity of structural, diffusion, and resting-state functional MRI for detecting brain alterations and verbal memory impairment in temporal lobe epilepsy. Epilepsia, 60(5), 935–947. https://doi.org/10.1111/epi.14736
Chao-Gan, Y., & Yu-Feng, Z. (2010). DPARSF: A MATLAB toolbox for “Pipeline” data analysis of resting-state fMRI. Frontiers in Systems Neuroscience, 4, 13. https://doi.org/10.3389/fnsys.2010.00013
Chen, J. E., Rubinov, M., & Chang, C. (2017). Methods and considerations for dynamic analysis of functional MR imaging data. Neuroimaging Clinics of North America, 27(4), 547–560. https://doi.org/10.1016/j.nic.2017.06.009
Chiang, S., Stern, J. M., Engel, J., Jr., et al. (2014). Differences in graph theory functional connectivity in left and right temporal lobe epilepsy. Epilepsy Research, 108(10), 1770–1781. https://doi.org/10.1016/j.eplepsyres.2014.09.023
Christoff, K., Irving, Z. C., Fox, K. C., Spreng, R. N., & Andrews-Hanna, J. R. (2016). Mind-wandering as spontaneous thought: A dynamic framework. Nature Reviews Neuroscience, 17(11), 718–731. https://doi.org/10.1038/nrn.2016.113
Concha, L., Beaulieu, C., & Gross, D. W. (2005). Bilateral limbic diffusion abnormalities in unilateral temporal lobe epilepsy. Annals of Neurology, 57(2), 188–196. https://doi.org/10.1002/ana.20334
Engel, J., Jr., International League Against Epilepsy (ILAE). (2001). A proposed diagnostic scheme for people with epileptic seizures and with epilepsy: Report of the ILAE Task Force on Classification and Terminology. Epilepsia, 42(6), 796–803. https://doi.org/10.1046/j.1528-1157.2001.10401.x
Fahoum, F., Lopes, R., Pittau, F., Dubeau, F., & Gotman, J. (2012). Widespread epileptic networks in focal epilepsies: EEG-fMRI study. Epilepsia, 53(9), 1618–1627. https://doi.org/10.1111/j.1528-1167.2012.03533.x
Fox, M. D., & Raichle, M. E. (2007). Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nature Reviews Neuroscience, 8(9), 700–711. https://doi.org/10.1038/nrn2201
Gao, Y. J., Wang, X., Xiong, P. G., et al. (2021). Abnormalities of the default-mode network homogeneity and executive dysfunction in people with first-episode, treatment-naive left temporal lobe epilepsy. European Review for Medical and Pharmacological Sciences, 25(4), 2039–2049. https://doi.org/10.26355/eurrev_202102_25108
Hindriks, R., Adhikari, M. H., Murayama, Y., et al. (2016). Corrigendum to “Can sliding-window correlations reveal dynamic functional connectivity in resting-state fMRI?” [NeuroImage 127 (2016) 242–256]. NeuroImage, 132, 115. https://doi.org/10.1016/j.neuroimage.2016.02.007
Holmes, M., Folley, B. S., Sonmezturk, H. H., et al. (2014). Resting state functional connectivity of the hippocampus associated with neurocognitive function in left temporal lobe epilepsy. Human Brain Mapping, 35(3), 735–744. https://doi.org/10.1002/hbm.22210
Ishai, A., Haxby, J. V., & Ungerleider, L. G. (2002). Visual imagery of famous faces: Effects of memory and attention revealed by fMRI. NeuroImage, 17(4), 1729–1741. https://doi.org/10.1006/nimg.2002.1330
La Grutta, V., & Sabatino, M. (1988). Focal hippocampal epilepsy: Effect of caudate stimulation. Experimental Neurology, 99(1), 38–49.
Liang, X., Pang, X., Liu, J., et al. (2020). Comparison of topological properties of functional brain networks with graph theory in temporal lobe epilepsy with different duration of disease. Annals of Translational Medicine, 8(22), 1503. https://doi.org/10.21037/atm-20-6823
Liao, W., Li, J., Ji, G. J., et al. (2019). Endless fluctuations: Temporal dynamics of the amplitude of low frequency fluctuations. IEEE Transactions on Medical Imaging, 38(11), 2523–2532. https://doi.org/10.1109/TMI.2019.2904555
Liao, W., Wu, G. R., Xu, Q., et al. (2014). DynamicBC: A MATLAB toolbox for dynamic brain connectome analysis. Brain Connect., 4(10), 780–790. https://doi.org/10.1089/brain.2014.0253
Logothetis, N. K., Pauls, J., Augath, M., Trinath, T., & Oeltermann, A. (2001). Neurophysiological investigation of the basis of the fMRI signal. Nature, 412(6843), 150–157. https://doi.org/10.1038/35084005
Maneshi, M., Vahdat, S., Fahoum, F., Grova, C., & Gotman, J. (2014). Specific resting-state brain networks in mesial temporal lobe epilepsy. Frontiers in Neurology, 5, 127. https://doi.org/10.3389/fneur.2014.00127
Nakai, Y., Nishibayashi, H., Donishi, T., et al. (2021). Regional abnormality of functional connectivity is associated with clinical manifestations in individuals with intractable focal epilepsy. Scientific Reports, 11(1), 1545. https://doi.org/10.1038/s41598-021-81207-6
Olson, I. R., Plotzker, A., & Ezzyat, Y. (2007). The Enigmatic temporal pole: A review of findings on social and emotional processing. Brain, 130(Pt 7), 1718–1731. https://doi.org/10.1093/brain/awm052
Pang, X., Liang, X., Zhao, J., et al. (2022). Abnormal static and dynamic functional connectivity in left and right temporal lobe epilepsy. Frontiers in Neuroscience, 15, 820641. https://doi.org/10.3389/fnins.2021.820641
Park, H. J., Friston, K. J., Pae, C., et al. (2018). Dynamic effective connectivity in resting state fMRI. NeuroImage, 180(Pt B), 594–608. https://doi.org/10.1016/j.neuroimage.2017.11.033
Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2012). Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. NeuroImage, 59(3), 2142–2154. https://doi.org/10.1016/j.neuroimage.2011.10.018
Power, J. D., Plitt, M., Laumann, T. O., et al. (2017). Sources and implications of whole-brain fMRI signals in humans. NeuroImage, 146, 609–625. https://doi.org/10.1016/j.neuroimage.2016.09.038
Preti, M. G., Bolton, T. A., & Van De Ville, D. (2017). The dynamic functional connectome: State-of-the-art and perspectives. NeuroImage, 160, 41–54. https://doi.org/10.1016/j.neuroimage.2016.12.061
Raichle, M. E. (2010). Two views of brain function. Trends in Cognitive Sciences, 14(4), 180–190. https://doi.org/10.1016/j.tics.2010.01.008
Raichle, M. E. (2015). The restless brain: How intrinsic activity organizes brain function. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 370(1668), 20140172. https://doi.org/10.1098/rstb.2014.0172
Reyes, A., Thesen, T., Wang, X., et al. (2016). Resting-state functional MRI distinguishes temporal lobe epilepsy subtypes. Epilepsia, 57(9), 1475–1484. https://doi.org/10.1111/epi.13456
Reyes, A., Uttarwar, V. S., Chang, Y. A., et al. (2018). Decreased neurite density within frontostriatal networks is associated with executive dysfunction in temporal lobe epilepsy. Epilepsy & Behavior, 78, 187–193. https://doi.org/10.1016/j.yebeh.2017.09.012
Sakoğlu, U., Pearlson, G. D., Kiehl, K. A., et al. (2010). A method for evaluating dynamic functional network connectivity and task-modulation: Application to schizophrenia. Magma, 23(5–6), 351–366. https://doi.org/10.1007/s10334-010-0197-8
Schmahmann, J. D. (2019). The cerebellum and cognition. Neuroscience Letters, 688, 62–75. https://doi.org/10.1016/j.neulet.2018.07.005
Schwartz, T. H., & Bonhoeffer, T. (2001). In vivo optical mapping of epileptic foci and surround inhibition in ferret cerebral cortex. Nature Medicine, 7(9), 1063–1067. https://doi.org/10.1038/nm0901-1063
Shi, K., Pang, X., Wang, Y., et al. (2021). Altered interhemispheric functional homotopy and connectivity in temporal lobe epilepsy based on fMRI and multivariate pattern analysis. Neuroradiology, 63(11), 1873–1882. https://doi.org/10.1007/s00234-021-02706-x
Singh, T. B., Aisikaer, A., He, C., et al. (2020). The assessment of brain functional changes in the temporal lobe epilepsy patient with cognitive impairment by resting-state functional magnetic resonance imaging. Journal of Clinical Imaging Science, 10, 50. https://doi.org/10.25259/JCIS_55_2020
Song, C., Zhang, X., Han, S., et al. (2022). More than just statics: Static and temporal dynamic changes in intrinsic brain activity in unilateral temporal lobe epilepsy. Frontiers in Human Neuroscience, 16, 971062. https://doi.org/10.3389/fnhum.2022.971062
Spencer, S. S. (2002). Neural networks in human epilepsy: Evidence of and implications for treatment. Epilepsia, 43(3), 219–227. https://doi.org/10.1046/j.1528-1157.2002.26901.x
Trimmel, K., van Graan, A. L., Caciagli, L., et al. (2018). Left temporal lobe language network connectivity in temporal lobe epilepsy. Brain, 141(8), 2406–2418. https://doi.org/10.1093/brain/awy164
Tuchscherer, V., Seidenberg, M., Pulsipher, D., et al. (2010). Extrahippocampal integrity in temporal lobe epilepsy and cognition: Thalamus and executive functioning. Epilepsy & Behavior, 17(4), 478–482. https://doi.org/10.1016/j.yebeh.2010.01.019
Van Paesschen, W., Dupont, P., Van Driel, G., Van Billoen, H., & Maes, A. (2003). SPECT perfusion changes during complex partial seizures in patients with hippocampal sclerosis. Brain, 126(Pt 5), 1103–1111. https://doi.org/10.1093/brain/awg108
Vaughan, D. N., Rayner, G., Tailby, C., & Jackson, G. D. (2016). MRI-negative temporal lobe epilepsy: A network disorder of neocortical connectivity. Neurology, 87(18), 1934–1942. https://doi.org/10.1212/WNL.0000000000003289
Viard, A., Piolino, P., Desgranges, B., et al. (2007). Hippocampal activation for autobiographical memories over the entire lifetime in healthy aged subjects: An fMRI study. Cerebral Cortex, 17(10), 2453–2467. https://doi.org/10.1093/cercor/bhl153
Výtvarová, E., Mareček, R., Fousek, J., et al. (2016). Large-scale cortico-subcortical functional networks in focal epilepsies: The role of the basal ganglia. Neuroimage Clinical, 14, 28–36. https://doi.org/10.1016/j.nicl.2016.12.014
Wang, K., Zhang, X., Song, C., et al. (2021). Decreased intrinsic neural timescales in mesial temporal lobe epilepsy. Frontiers in Human Neuroscience, 15, 772365. https://doi.org/10.3389/fnhum.2021.772365
Xu, Q., Zhang, Z., Liao, W., et al. (2014). Time-shift homotopic connectivity in mesial temporal lobe epilepsy. AJNR. American Journal of Neuroradiology, 35(9), 1746–1752. https://doi.org/10.3174/ajnr.A3934
Yan, C. G., Wang, X. D., Zuo, X. N., & Zang, Y. F. (2016). DPABI: Data processing & analysis for (Resting-State) brain imaging. Neuroinformatics, 14(3), 339–351. https://doi.org/10.1007/s12021-016-9299-4
Yan, C. G., Yang, Z., Colcombe, S. J., et al. (2017). Concordance among indices of intrinsic brain function: Insights from inter individual variation and temporal dynamics. Science Bulletin, 62(23), 1572–1584. https://doi.org/10.1016/j.scib.2017.09.015
Yang, H., Long, X. Y., Yang, Y., et al. (2007). Amplitude of low frequency fluctuation within visual areas revealed by resting-state functional MRI. NeuroImage, 36(1), 144–152. https://doi.org/10.1016/j.neuroimage.2007.01.054
Yu, W., & Krook-Magnuson, E. (2015). Cognitive collaborations: Bidirectional functional connectivity between the cerebellum and the hippocampus. Frontiers in Systems Neuroscience, 9, 177. https://doi.org/10.3389/fnsys.2015.00177
Zang, Y. F., He, Y., Zhu, C. Z., et al. (2007). Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI [published correction appears in Brain Dev. 2012 Apr;34(4):336]. Brain and Development, 29(2), 83–91. https://doi.org/10.1016/j.braindev.2006.07.002
Zang, Y., Jiang, T., Lu, Y., He, Y., & Tian, L. (2004). Regional homogeneity approach to fMRI data analysis. NeuroImage, 22(1), 394–400. https://doi.org/10.1016/j.neuroimage.2003.12.030
Zeng, H., Pizarro, R., Nair, V. A., et al. (2013). Alterations in regional homogeneity of resting-state brain activity in mesial temporal lobe epilepsy. Epilepsia, 54(4), 658–666. https://doi.org/10.1111/epi.12066
Zhang, Z., Lu, G., Zhong, Y., et al. (2009). Impaired perceptual networks in temporal lobe epilepsy revealed by resting fMRI. Journal of Neurology, 256(10), 1705–1713. https://doi.org/10.1007/s00415-009-5187-2
Zhang, Z., Lu, G., Zhong, Y., et al. (2010). fMRI study of mesial temporal lobe epilepsy using amplitude of low-frequency fluctuation analysis. Human Brain Mapping, 31(12), 1851–1861. https://doi.org/10.1002/hbm.20982
Zhao, B., Yang, B., Tan, Z., et al. (2020). Intrinsic brain activity changes in temporal lobe epilepsy patients revealed by regional homogeneity analysis. Seizure, 81, 117–122. https://doi.org/10.1016/j.seizure.2020.07.030
Zou, Q. H., Zhu, C. Z., Yang, Y., et al. (2008). An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: Fractional ALFF. Journal of Neuroscience Methods, 172(1), 137–141. https://doi.org/10.1016/j.jneumeth.2008.04.012
Zuo, X. N., Ehmke, R., Mennes, M., et al. (2012). Network centrality in the human functional connectome. Cerebral Cortex, 22(8), 1862–1875. https://doi.org/10.1093/cercor/bhr269
Zuo, X. N., Kelly, C., Di Martino, A., et al. (2010). Growing together and growing apart: Regional and sex differences in the lifespan developmental trajectories of functional homotopy. Journal of Neuroscience, 30(45), 15034–15043. https://doi.org/10.1523/JNEUROSCI.2612-10.2010
Acknowledgements
The researchers thank everyone who took part in the study.
Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Author information
Authors and Affiliations
Contributions
Author contributions included conception and study design (CS, JC, YZ), data collection or acquisition (CS, XZ, YL, KM, XM), methodology (SH), interpretation of results (CS, XZ, YL, SH), drafting the manuscript work or revising it critically for important intellectual content (CS, SX, JC, YZ) and approval of the final version to be published and agreement to be accountable for the integrity and accuracy of all aspects of the work (All authors).
Corresponding authors
Ethics declarations
Ethics approval
The studies involving human participants were reviewed and approved by the Research Ethical Committee of the first affiliated hospital of Zhengzhou University.
Consent to participate
Written informed consent to participate in this study was provided by the participant’s legal guardian/next of kin.
Consent for publication
All participants provided consent to publication of results of the analyses of deidentifed data.
Competing interests
The authors declare no competing interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Song, C., Xie, S., Zhang, X. et al. Similarities and differences of dynamic and static spontaneous brain activity between left and right temporal lobe epilepsy. Brain Imaging and Behavior 18, 352–367 (2024). https://doi.org/10.1007/s11682-023-00835-w
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11682-023-00835-w