The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
Gamma frequency entrainment attenuates amyloid load and modifies microglia
Open accessAbstract
Changes in gamma oscillations (20-50 Hz) have been observed in several neurological disorders. However, the relationship between gamma oscillations and cellular pathologies is unclear. Here we show reduced, behaviourally driven gamma oscillations before the onset of plaque formation or cognitive decline in a mouse model of Alzheimer's disease. Optogenetically driving fast-spiking parvalbumin-positive (FS-PV)-interneurons at gamma (40 Hz), but not other frequencies, reduces levels of amyloid-β (Aβ)1-40 and Aβ 1-42 isoforms. Gene expression profiling revealed induction of genes associated with morphological transformation of microglia, and histological analysis confirmed increased microglia co-localization with Aβ. Subsequently, we designed a non-invasive 40 Hz light-flickering regime that reduced Aβ 1-40 and Aβ 1-42 levels in the visual cortex of pre-depositing mice and mitigated plaque load in aged, depositing mice. Our findings uncover a previously unappreciated function of gamma rhythms in recruiting both neuronal and glial responses to attenuate Alzheimer's-disease-associated pathology.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“By genetically engineering these proteins into target neurons and controlling the light around them, these neurons can be activated or inhibited, which is particularly important for sensory and motor recovery and rehabilitation.[555]”
From Flexible Electronics and Devices as Human–Machine Interfaces for Medical Robotics (2022) · cites this paper as [555]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Optogenetic stimulation is based on opsins that are sensitive to light signals and only expressed in certain types of cells.”
From Flexible Electronics and Devices as Human–Machine Interfaces for Medical Robotics (2022) · cites this paper as [555]
The cited source says what the claim attributes to it.
In the citing paper
“Indeed, gamma frequency modulation was beneficial in models with amyloid and/or tau pathology54.”
From The R136S mutation in the APOE3 gene confers resilience against tau pathology via inhibition of the cGAS-STING-IFN pathway (2025) · cites this paper as [54]
The cited source says what the claim attributes to it.
In the citing paper
“Indeed, gamma frequency modulation was found to be beneficial in models with either amyloid and/or tau pathology52”
From APOE3 - R136S mutation confers resilience against tau pathology via cGAS-STING-IFN inhibition (2024) · cites this paper as [52]
The cited source says what the claim attributes to it.
In the citing paper
“our sample sizes are similar to those reported in previous publications.15,24,86”
From TERT activation targets DNA methylation and multiple aging hallmarks (2024) · cites this paper as [86]
In the citing paper
“Interestingly, entraining gamma oscillation at 40 Hz in 5xFAD mice induced amyloid reductions that were associated with an increase in microglial numbers and morphological changes such as soma enlargement and shortening of processes loaded with Aβ.”
From Microglia in Alzheimer's disease (2017) · cites this paper as [158]
In the citing paper
“Interestingly, entraining gamma oscillation at 40 Hz in 5xFAD mice induced amyloid reductions that were associated with an increase in microglial numbers and morphological changes such as soma enlargement and shortening of processes loaded with Aβ.”
From Microglia in Alzheimer's disease (2017) · cites this paper as [158]
In the citing paper
“Gamma oscillations arise from the activation of local circuits of excitatory and fast-spiking inhibitory neurons resonating at 20-50 Hz, and changes in gamma oscillation have been observed in neurological diseases (158).”
From Microglia in Alzheimer's disease (2017) · cites this paper as [158]
In the citing paper
“Gamma oscillations arise from the activation of local circuits of excitatory and fast-spiking inhibitory neurons resonating at 20-50 Hz, and changes in gamma oscillation have been observed in neurological diseases (158).”
From Microglia in Alzheimer's disease (2017) · cites this paper as [158]
In the citing paper
“Interestingly, entraining gamma oscillation at 40 Hz in 5xFAD mice induced amyloid reductions that were associated with an increase in microglial numbers and morphological changes such as soma enlargement and shortening of processes loaded with Aβ.”
From Microglia in Alzheimer's disease (2017) · cites this paper as [158]
In the citing paper
“Notably, levels of proinflammatory genes (Il1b, Il6, Cd11b) and antiinflammatory genes (Igf1) were not changed (158), suggesting that it is possible to use immunomodulation to polarize microglia toward a beneficial activation state that is characterized by increased phagocytic activity without the induction of sustained inflammatory responses.”
From Microglia in Alzheimer's disease (2017) · cites this paper as [158]
In the citing paper
“Notably, levels of proinflammatory genes (Il1b, Il6, Cd11b) and antiinflammatory genes (Igf1) were not changed (158), suggesting that it is possible to use immunomodulation to polarize microglia toward a beneficial activation state that is characterized by increased phagocytic activity without the induction of sustained inflammatory responses.”
From Microglia in Alzheimer's disease (2017) · cites this paper as [158]
In the citing paper
“RNA sequencing analysis showed an increase in phagocytic genes, such as Cd68, β 2 -microglobulin (B2m), Icam, and lysozyme 2 (Lyz2), and in the proliferation markers Csf1, Csf1r, and Csf2ra.”
From Microglia in Alzheimer's disease (2017) · cites this paper as [158]
In the citing paper
“RNA sequencing analysis showed an increase in phagocytic genes, such as Cd68, β 2 -microglobulin (B2m), Icam, and lysozyme 2 (Lyz2), and in the proliferation markers Csf1, Csf1r, and Csf2ra.”
From Microglia in Alzheimer's disease (2017) · cites this paper as [158]
In the citing paper
“In mice, slow gamma frequency visual or audio input entrains neural firing to this frequency in the cortex and hippocampus and reduces Aβ pathology and microglial abnormalities [204, 205].”
From Apolipoprotein E4, inhibitory network dysfunction, and Alzheimer’s disease (2019) · cites this paper as [204]
In the citing paper
“Transgenic mice with AD-like pathology were found to have reduced gamma power that, in one model, precedes cognitive impairment and amyloid plaque formation [21,22].”
From Parvalbumin interneuron vulnerability and brain disorders (2021) · cites this paper as [21]
In the citing paper
“Interestingly, amyloid plaques were reduced when hippocampal PV-INs artificially produced gamma oscillations in optogenetics paradigms [21].”
From Parvalbumin interneuron vulnerability and brain disorders (2021) · cites this paper as [21]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Zhang, Y., Chen, K., Sloan, S. A., Bennett, M. L., Scholze, A. R., O'Keeffe, S., Phatnani, H. P., Guarnieri, P., Caneda, C., Ruderisch, N., et al. (2014) · The Journal of Neuroscience · doi:10.1523/jneurosci.1860-14.2014 · Cited by 4,875 · cited 1×
“To understand the cellular and molecular mechanisms from our RNA-seq data, 14 of publicly available RNA-seq datasets 35 were processed for cell-type-specific analysis.”
Buzsáki, G. (2006) · doi:10.1093/acprof:oso/9780195301069.001.0001 · Cited by 4,873
Gray, C. M., König, P., Engel, A. K., & Singer, W. (1989) · Nature · doi:10.1038/338334a0 · Cited by 4,183
Host microbiota constantly control maturation and function of microglia in the CNS
Erny, D., Hrabě de Angelis, A. L., Jaitin, D., Wieghofer, P., Staszewski, O., David, E., Keren-Shaul, H., Mahlakoiv, T., Jakobshagen, K., Buch, T., et al. (2015) · Nature Neuroscience · doi:10.1038/nn.4030 · Cited by 3,569
Oakley, H., Cole, S. L., Logan, S., Maus, E., Shao, P., Craft, J., Guillozet-Bongaarts, A., Ohno, M., Disterhoft, J., Van Eldik, L., et al. (2006) · The Journal of Neuroscience · doi:10.1523/jneurosci.1202-06.2006 · Cited by 3,530
Theta oscillations in the hippocampus
Buzsáki, G. (2002) · Neuron · doi:10.1016/s0896-6273(02)00586-x · Cited by 3,332
Driving fast-spiking cells induces gamma rhythm and controls sensory responses
Cardin, J. A., Carlén, M., Meletis, K., Knoblich, U., Zhang, F., Deisseroth, K., Tsai, L.-H., & Moore, C. I. (2009) · Nature · doi:10.1038/nature08002 · Cited by 2,603
Self-citationCoherent oscillations: A mechanism of feature linking in the visual cortex?
Eckhorn, R., Bauer, R., Jordan, W., Brosch, M., Kruse, W., Munk, M., & Reitboeck, H. J. (1988) · Biological Cybernetics · doi:10.1007/bf00202899 · Cited by 2,329
Synapse Loss and Microglial Activation Precede Tangles in a P301S Tauopathy Mouse Model
Yoshiyama, Y., Higuchi, M., Zhang, B., Huang, S.-M., Iwata, N., Saido, T. C., Maeda, J., Suhara, T., Trojanowski, J. Q., & Lee, V. M.-Y. (2007) · Neuron · doi:10.1016/j.neuron.2007.01.010 · Cited by 2,208
Synaptic mechanisms of synchronized gamma oscillations in inhibitory interneuron networks
Bartos, M., Vida, I., & Jonas, P. (2007) · Nature Reviews Neuroscience · doi:10.1038/nrn2044 · Cited by 2,070
Flagged first, then by citations
Cited by
Sorted by citations
Items 401–500 of 1,003
Tran, T., Bridi, M., Koh, M. T., Gallagher, M., & Kirkwood, A. (2019) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2019.07.010 · Cited by 26
Sandrini, M., Manenti, R., Sahin, H., & Cotelli, M. (2020) · Ageing Research Reviews · doi:10.1016/j.arr.2020.101065 · Cited by 26
Hristovska, I., Verdonk, F., Comte, J., Tsai, E. S., Desestret, V., Honnorat, J., Chrétien, F., & Pascual, O. (2020) · PLoS ONE · doi:10.1371/journal.pone.0236594 · Cited by 26
Rochart, R., Liu, Q., Fonteh, A. N., Harrington, M. G., & Arakaki, X. (2020) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2020.574214 · Cited by 28
Sedghizadeh, M. J., Aghajan, H. K., Vahabi, Z., Fatemi, N., & Afzal, A. (2022) · Brain Structure and Function · doi:10.1007/s00429-022-02554-2 · Cited by 26
Ghatak, S., Nakamura, T., & Lipton, S. A. (2023) · Frontiers in Neural Circuits · doi:10.3389/fncir.2023.1099467 · Cited by 26
A Systematic Review of the Effects of Capsaicin on Alzheimer’s Disease
Inyang, D., Saumtally, T., Nnadi, C. N., Devi, S., & So, P. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms241210176 · Cited by 28
A guide to using functional magnetic resonance imaging to study Alzheimer's disease in animal models
Asaad, M., & Lee, J. H. (2018) · Disease Models & Mechanisms · doi:10.1242/dmm.031724 · Cited by 26
Pignataro, A., Meli, G., Pagano, R., Fontebasso, V., Battistella, R., Conforto, G., Ammassari‐Teule, M., & Middei, S. (2018) · Biological Psychiatry · doi:10.1016/j.biopsych.2018.10.018 · Cited by 27
Early Mitochondrial Fragmentation and Dysfunction in a Drosophila Model for Alzheimer’s Disease
Wang, X., & Davis, R. L. (2020) · Molecular Neurobiology · doi:10.1007/s12035-020-02107-w · Cited by 27
Drabik, D., Chodaczek, G., & Kraszewski, S. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms22010018 · Cited by 26
Phan, D. T., Mondal, S., Tran, L. H., Thien, V. T. M., Nguyen, H. V., Nguyen, C. H., Park, S., Choi, J., & Oh, J. (2021) · Flexible and Printed Electronics · doi:10.1088/2058-8585/ac2c50 · Cited by 26
APOE3 - R136S mutation confers resilience against tau pathology via cGAS-STING-IFN inhibition
Naguib, S., Lopez-Lee, C., Torres, E. R., Lee, S.-I., Zhu, J., Zhu, D., Ye, P., Norman, K., Zhao, M., Wong, M. Y., et al. (2024) · doi:10.1101/2024.04.25.591140 · Cited by 25
Prabhu, P., Morise, H., Kudo, K., Beagle, A. J., Mizuiri, D., Syed, F., Kotegar, K. A., Findlay, A. M., Miller, B. L., Kramer, J. H., et al. (2024) · Brain Communications · doi:10.1093/braincomms/fcae121 · Cited by 26
Auditory gamma-band entrainment enhances default mode network connectivity in dementia patients
Lahijanian, M., Aghajan, H. K., & Vahabi, Z. (2024) · Scientific Reports · doi:10.1038/s41598-024-63727-z · Cited by 26
Application of Optogenetics in Neurodegenerative Diseases
Zhang, Q., Li, T., Xu, M., Islam, B., & Wang, J. (2024) · Cellular and Molecular Neurobiology · doi:10.1007/s10571-024-01486-1 · Cited by 25
Advancing Neuroscience and Therapy: Insights into Genetic and Non-Genetic Neuromodulation Approaches
Zhi, W., Li, Y., Wang, L., & Hu, X. (2025) · Cells · doi:10.3390/cells14020122 · Cited by 25
Li, N., Li, Y., Li, L.-J., Zhu, K., Zheng, Y., & Wang, X. (2019) · Neural Regeneration Research · doi:10.4103/1673-5374.250625 · Cited by 28
Network resonance can be generated independently at distinct levels of neuronal organization
Stark, E., Levi, A., & Rotstein, H. G. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010364 · Cited by 27
Bok, J., Ha, J., Ahn, B. J., & Jang, Y. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms24010679 · Cited by 25
Yang, Y. L., & Lai, T. W. (2023) · eNeuro · doi:10.1523/eneuro.0189-23.2023 · Cited by 25
Zang, L., Liu, X., Li, Y., Liu, J., Lu, Q., Zhang, Y., & Meng, Q. (2023) · PLoS ONE · doi:10.1371/journal.pone.0293977 · Cited by 25
Pacing Hippocampal Sharp-Wave Ripples With Weak Electric Stimulation
Jiang, H., Liu, S., Geng, X., Caccavano, A., Conant, K. E., Vicini, S., & Wu, J. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00164 · Cited by 26
Cortical volume and sex influence visual gamma
van Pelt, S., Shumskaya, E., & Fries, P. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.06.005 · Cited by 26
Gil, V., & del Rı́o, J. A. (2019) · Cells · doi:10.3390/cells8030206 · Cited by 25
A Role for Matrix Metalloproteases in Antidepressant Efficacy
Alaiyed, S., & Conant, K. E. (2019) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2019.00117 · Cited by 26
Yao, D., Zhang, Y., Liu, T., Xu, P., Gong, D., Lu, J., Xia, Y., Luo, C., Guo, D., Dong, L., et al. (2020) · Cognitive Neurodynamics · doi:10.1007/s11571-020-09577-7 · Cited by 25
Xing, Y., Wei, P., Wang, C., Shan, Y., Yu, Y., Qiao, Y., Xie, B., Shi, X., Zhu, Z., Lu, J., et al. (2020) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1002/trc2.12005 · Cited by 25
Maiella, M., Mencarelli, L., Casula, E. P., Borghi, I., Assogna, M., Lorenzo, F. D., Bonnı̀, S., Pezzopane, V., Martorana, A., & Koch, G. (2024) · Clinical Neurophysiology · doi:10.1016/j.clinph.2024.09.007 · Cited by 26
The role of parvalbumin interneuron dysfunction across neurodegenerative dementias
Smeralda, C. L., Pandit, S., Turrini, S., Reilly, J., Palmisano, A., Sprugnoli, G., Hampel, H. J., Benussi, A., Borroni, B., Press, D. Z., et al. (2024) · Ageing Research Reviews · doi:10.1016/j.arr.2024.102509 · Cited by 26
Zikereya, T., Lin, Y., Zhang, Z., Taguas, I., Shi, K., & Han, C. (2024) · NeuroImage · doi:10.1016/j.neuroimage.2024.120945 · Cited by 24
The mechanisms of electrical neuromodulation
Balbinot, G. C., Milosevic, M., Morshead, C. M., Iwasa, S. N., Zariffa, J., Milosevic, L., Valiante, T. A., Hoffer, J. A., & Popović, M. R. (2024) · The Journal of Physiology · doi:10.1113/jp286205 · Cited by 24
Tkemaladze, J. (2026) · Longevity Horizon · doi:10.65649/3hm9b025 · Cited by 24
Tichko, P., Kim, J. C., Large, E. W., & Loui, P. (2020) · European Journal of Neuroscience · doi:10.1111/ejn.15059 · Cited by 25
Jeong, W.-H., Kim, W.-I., Lee, J.-W., Park, H., Song, M., Choi, I., & Han, J. (2021) · Brain Sciences · doi:10.3390/brainsci11111532 · Cited by 24
Effect of light therapy on delirium in older patients with Alzheimer's disease-related dementia
Zou, C., Mei, X., Li, X., Hu, J., Xu, T., & Zheng, C. (2022) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2022.03.003 · Cited by 26
Synaptic Effects of Palmitoylethanolamide in Neurodegenerative Disorders
Assogna, M., Lorenzo, F. D., Martorana, A., & Koch, G. (2022) · Biomolecules · doi:10.3390/biom12081161 · Cited by 26
Traikapi, A., Kalli, I., Kyriakou, A., Stylianou, E., Symeou, R. T., Kardama, A., Christou, Y. P., Phylactou, P., & Konstantinou, N. (2022) · Journal of Neuropsychology · doi:10.1111/jnp.12299 · Cited by 24
Altomare, D., Benussi, A., Cantoni, V., Premi, E., Rivolta, J., Cupidi, C., Martorana, A., Santarnecchi, E., Padovani, A., Koch, G., et al. (2023) · Alzheimer s Research & Therapy · doi:10.1186/s13195-023-01297-4 · Cited by 24
Optogenetic control of neural activity: The biophysics of microbial rhodopsins in neuroscience
Piatkevich, K. D., & Boyden, E. S. (2023) · Quarterly Reviews of Biophysics · doi:10.1017/s0033583523000033 · Cited by 25
Self-citationBiological Considerations of Optical Interfaces for Neuromodulation
Hart, W. L., Kameneva, T., Wise, A. K., & Stoddart, P. R. (2019) · Advanced Optical Materials · doi:10.1002/adom.201900385 · Cited by 25
Neuronal network dysfunction precedes storage and neurodegeneration in a lysosomal storage disorder
Ahrens‐Nicklas, R. C., Tecedor, L., Hall, A. F., Лысенко, Е., Cohen, A. S., Davidson, B. L., & Marsh, E. D. (2019) · JCI Insight · doi:10.1172/jci.insight.131961 · Cited by 24
SomaticTARDBPvariants as a cause of semantic dementia
van Rooij, J., Mol, M. O., Melhem, S., van der Wal, P., Arp, P., Paron, F., Kaat, L. D., Seelaar, H., Bank, N. B., Miedema, S. S. M., et al. (2020) · Brain · doi:10.1093/brain/awaa317 · Cited by 26
Impact of TRPV1 on Pathogenesis and Therapy of Neurodegenerative Diseases
Wang, W., & Sun, T. (2023) · Molecules · doi:10.3390/molecules29010181 · Cited by 24
Microglia in animal models of autism spectrum disorders
Andoh, M., Ikegaya, Y., & Koyama, R. (2020) · Progress in molecular biology and translational science · doi:10.1016/bs.pmbts.2020.04.012 · Cited by 25
Sharp Wave Ripples in Alzheimer's Disease: In Search of Mechanisms
Sánchez-Aguilera, A., & Quintanilla, J. P. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.2020-20.2020 · Cited by 26
Ahnaou, A., & Drinkenburg, W. H. I. M. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.06.039 · Cited by 24
Multi-mechanical waves against Alzheimer’s disease pathology: a systematic review
Monteiro, F., Sotiropoulos, I., Carvalho, Ó. S. N., Sousa, N., & Silva, F. S. (2021) · Translational Neurodegeneration · doi:10.1186/s40035-021-00256-z · Cited by 23
Mencarelli, L., Monti, L., Romanella, S. M., Neri, F., Koch, G., Salvador, R., Ruffini, G., Sprugnoli, G., Rossi, S., & Santarnecchi, E. (2022) · Neural Plasticity · doi:10.1155/2022/6197505 · Cited by 24
Zhang, H., Chen, L., Johnston, K. G., Crapser, J. D., Green, K. N., Ha, N. M.-L., Tenner, A. J., Holmes, T. C., Nitz, D. A., & Xu, X. (2022) · Neurobiology of Disease · doi:10.1016/j.nbd.2022.105939 · Cited by 25
Liu, Y., Liu, S., Tang, C., Tang, K., Liu, D., Chen, M., Mao, Z., & Xia, X. (2023) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2022.1068175 · Cited by 23
Wang, W., Zhang, X., He, R., Li, S., Fang, D., & Pang, C. (2023) · CNS Neuroscience & Therapeutics · doi:10.1111/cns.14096 · Cited by 23
Theta-gamma phase amplitude coupling in a hippocampal CA1 microcircuit
Ponzi, A. P. D., Durá-Bernal, S., & Migliore, M. (2023) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010942 · Cited by 23
Jones, K. T., Gallen, C. L., Ostrand, A. E., Rojas, J. C., Wais, P. E., Rini, J. F., Chan, B., Lago, A. L., Boxer, A. L., Zhao, M., et al. (2023) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2023.04.005 · Cited by 23
Transcranial Low-Level Laser Therapy for Depression and Alzheimer’s Disease
Chang, J., Ren, Y., Wang, R., Li, C., Wang, Y., & Chu, X. (2018) · Neuropsychiatry · doi:10.4172/neuropsychiatry.1000369 · Cited by 23
Visual temporal frequency preference shows a distinct cortical architecture using fMRI
Chai, Y., Handwerker, D. A., Marrett, S., Gonzalez-Castillo, J., Merriam, E. P., Hall, A., Molfese, P. J., & Bandettini, P. A. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.04.048 · Cited by 22
Targeting Neural Oscillations for Cognitive Enhancement in Alzheimer’s Disease
Palacino, F., Manganotti, P., & Benussi, A. (2025) · Medicina · doi:10.3390/medicina61030547 · Cited by 23
Gamma sensory stimulation in mild Alzheimer's dementia: An open‐label extension study
Chan, D., de Weck, G., Jackson, B., Suk, H., Milman, N., Kitchener, E. G., Avalos, V. S. F., Quay, M. J., Aoki, K., Ruiz, E., et al. (2025) · Alzheimer s & Dementia · doi:10.1002/alz.70792 · Cited by 22
Self-citationJacob, S., Davies, G., Bock, M. D., Hermans, B., Wintmolders, C., Bottelbergs, A., Borgers, M., Theunis, C., Broeck, B. V., Manyakov, N. V., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-51928-w · Cited by 22
Lourenço, J., Koukouli, F., & Bacci, A. (2020) · Cortex · doi:10.1016/j.cortex.2020.08.015 · Cited by 25
Sun, L., Wang, Q., & Ai, J. (2024) · Ageing Research Reviews · doi:10.1016/j.arr.2024.102265 · Cited by 25
Roy, K., Zhou, X., Otani, R., Yuan, P., Ioka, S., Vogt, K. E., Kondo, T., Farag, N. H. T., Ijiri, H., Wu, Z., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-47964-4 · Cited by 22
Lanni, I., Chiacchierini, G., Papagno, C., Santangelo, V., & Campolongo, P. (2024) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2024.105831 · Cited by 22
Arakaki, X., Lee, R. Y., King, K. S., Fonteh, A. N., & Harrington, M. G. (2019) · PLoS ONE · doi:10.1371/journal.pone.0208517 · Cited by 22
Tau-Mediated Dysregulation of Neuroplasticity and Glial Plasticity
Koller, E. J., & Chakrabarty, P. (2020) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2020.00151 · Cited by 23
Marson, F., Lasaponara, S., & Cavallo, M. (2021) · Medicina · doi:10.3390/medicina57030215 · Cited by 25
Black, R. D., & Rogers, L. L. (2020) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2020.00012 · Cited by 23
Li, X., Tang, X., Zeng, J., Duan, L., Hou, Z., Li, L., Guo, Y., Chai, C., Liu, J., Wang, Y., et al. (2026) · Cell · doi:10.1016/j.cell.2025.12.020 · Cited by 21
The gut–brain axis in Alzheimer’s disease: how gut microbiota modulate microglial function
Wang, H., Yang, F., Gao, Z., Cheng, Z.-D., & Liang, X. (2025) · Frontiers in Aging · doi:10.3389/fragi.2025.1704047 · Cited by 22
Home-Based Gamma Transcranial Alternating Current Stimulation in Patients With Alzheimer Disease
Cantoni, V., Casula, E. P., Tarantino, B., Cupidi, C., Huber, N., Altomare, D., Premi, E., Zummo, E., Esposito, R., Leonardi, C., et al. (2025) · JAMA Network Open · doi:10.1001/jamanetworkopen.2025.46556 · Cited by 21
Robust light–dark patterns and reduced amyloid load in an Alzheimer’s disease transgenic mouse model
Nagare, R., Possidente, B. P., Lagalwar, S., & Figueiro, M. G. (2020) · Scientific Reports · doi:10.1038/s41598-020-68199-5 · Cited by 21
Hasan, S., Tam, S. K. E., Foster, F., Vyazovskiy, V. V., Bannerman, D. M., & Peirson, S. N. (2021) · Biochemical Pharmacology · doi:10.1016/j.bcp.2020.114404 · Cited by 21
Yang, Q., Song, D. F., Xie, Z., He, G., Zhao, J., Wang, Z., Dong, Z., Zhang, H., Yang, L., Jiang, M., et al. (2021) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2021.102209 · Cited by 22
Altered visual entrainment in patients with Alzheimer’s disease: magnetoencephalography evidence
Springer, S. D., Wiesman, A. I., May, P. E., Schantell, M. D., Johnson, H. J., Willett, M. P., Castelblanco, C. A., Eastman, J. A., Christopher‐Hayes, N. J., Wolfson, S. L., et al. (2022) · Brain Communications · doi:10.1093/braincomms/fcac198 · Cited by 21
Kumari, E., Xu, A., Chen, R., Yan, Y., Yang, Z. R., & Zhang, T. (2022) · Experimental Neurology · doi:10.1016/j.expneurol.2022.114231 · Cited by 21
Tamura, H., Shiosaka, S., & Morikawa, S. (2017) · Neurochemistry International · doi:10.1016/j.neuint.2017.12.002 · Cited by 22
Ruan, Q., Yu, Z., Zhang, W., Ruan, J., Liu, C., & Zhang, R. (2018) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2018.00098 · Cited by 21
Peña‐Ortega, F. (2019) · Current Alzheimer Research · doi:10.2174/1567205017666191213162233 · Cited by 21
Das, M., Mao, W., Shao, E., Tamhankar, S., Yu, G.-Q., Yu, X., Ho, K., Wang, X., Wang, J., & Mucke, L. (2021) · iScience · doi:10.1016/j.isci.2021.103245 · Cited by 21
Sherman, J., Bortz, E., Antonio, E. S., Tseng, H.-A., Raiff, L., & Han, X. (2024) · Journal of Neural Engineering · doi:10.1088/1741-2552/ad731c · Cited by 20
The interplay of neurovasculature and adult hippocampal neurogenesis
Kim, T. A., Chen, L., & Ge, S. (2021) · Neuroscience Letters · doi:10.1016/j.neulet.2021.136071 · Cited by 20
Sun, J., He, J., & Gao, X. (2021) · Neuroscience · doi:10.1016/j.neuroscience.2021.08.010 · Cited by 20
The Dual Nature of Microglia in Alzheimer’s Disease: A Microglia-Neuron Crosstalk Perspective
Xie, Z., Meng, J., Wu, Z., Nakanishi, H., Hayashi, Y., Kong, W., Lan, F., Narengaowa, Yang, Q., Qing, H., et al. (2023) · The Neuroscientist · doi:10.1177/10738584211070273 · Cited by 19
Adaikkan, C., Wang, J., Abdelaal, K., Middleton, S. J., Bozzelli, P. L., Wickersham, I. R., McHugh, T. J., & Tsai, L. (2021) · Neuron · doi:10.1016/j.neuron.2022.07.023 · Cited by 20
Self-citationEarly Mitochondrial Defects in the 5xFAD Mouse Model of Alzheimer’s Disease
Sharma, N., Banerjee, R., & Davis, R. L. (2023) · Journal of Alzheimer s Disease · doi:10.3233/jad-220884 · Cited by 20
Enhancement of neural regeneration as a therapeutic strategy for Alzheimer's disease (Review)
Gao, J., & Li, L. (2023) · Experimental and Therapeutic Medicine · doi:10.3892/etm.2023.12143 · Cited by 21
Parvalbumin interneuron cell-to-network plasticity: mechanisms and therapeutic avenues
Hadler, M. D., Alle, H., & Geiger, J. R. P. (2024) · Trends in Pharmacological Sciences · doi:10.1016/j.tips.2024.04.003 · Cited by 21
Cheng, C., Pho, Q.-H., Wu, X., Chin, T., Chen, C., Fang, P.-H., Lin, Y., & Hsieh, M. (2018) · Polymers · doi:10.3390/polym10050519 · Cited by 20
Pinpointing the locus of GABAergic vulnerability in Alzheimer’s disease
Melgosa-Ecenarro, L., Doostdar, N., Radulescu, C. I., Jackson, J., & Barnes, S. J. (2022) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2022.06.017 · Cited by 20
Chen, G., Andrade‐Talavera, Y., Zhong, X., Hassan, S., Biverstål, H., Poska, H., Abelein, A., Leppert, A., Kronqvist, N., Rising, A., et al. (2022) · RSC Chemical Biology · doi:10.1039/d2cb00187j · Cited by 20
Arroyo‐García, L. E., Bachiller, S., Ruiz, R., Boza‐Serrano, A., Moreno, A. R., Deierborg, T., Andrade‐Talavera, Y., & Fisahn, A. (2023) · Translational Neurodegeneration · doi:10.1186/s40035-023-00338-0 · Cited by 22
40 Hz light preserves synaptic plasticity and mitochondrial function in Alzheimer’s disease model
Behrooz, A. B., Aghanoori, M., Nazari, M., Latifi‐Navid, H., Vosoughian, F., Anjomani, M., Lotfi, J., Ahmadiani, A., Eliassi, A., Nabavizadeh, F., et al. (2024) · Scientific Reports · doi:10.1038/s41598-024-78528-7 · Cited by 19
Kang, J., Schroeder, M. E., Lee, Y.-M., Kapoor, C., Yu, E., Tarr, T. B., Titterton, K., Zeng, M., Park, D., Niederst, E. D., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-53729-w · Cited by 19
Self-citationMicroglial modulation of neuronal network function and plasticity
Peña‐Ortega, F. (2025) · Journal of Neurophysiology · doi:10.1152/jn.00458.2024 · Cited by 19
Reduced ULK1 links impaired autophagy and mitophagy to Alzheimer’s disease pathology
Pan, J., Wang, P.-J., Zhang, J., Knapskog, A., Watne, L. O., Wang, H.-L., Lagartos-Donate, M. J., Lautrup, S., Mao, L.-P., Wang, Q., et al. (2026) · Nature Aging · doi:10.1038/s43587-026-01108-z · Cited by 20
Müller, J., Nowak, S., Dewey, M., Vogelgesang, A., von Sarnowski, B., Rathmann, E., Schmidt, S., Sebastian, R., Usichenko, T. I., Kertscho, H., et al. (2020) · JMIR Research Protocols · doi:10.2196/15488 · Cited by 20
Monteiro‐Fernandes, D., Silva, J. M., Soares‐Cunha, C., Dalla, C., Kokras, N., Arnaud, F., Billiras, R., Zhuravleva, V., Waites, C. L., Bretin, S., et al. (2020) · Molecular Psychiatry · doi:10.1038/s41380-020-0794-5 · Cited by 20
Chen, Z., Qin, H., Lin, S., Lu, Z., Fan, X., Liu, X., & Liu, M. (2021) · Journal of Photochemistry and Photobiology B Biology · doi:10.1016/j.jphotobiol.2021.112127 · Cited by 19
Sprugnoli, G., Rossi, S., Rotenberg, A., Pascual‐Leone, Á., Fakhri, G. E., Golby, A. J., & Santarnecchi, E. (2021) · EBioMedicine · doi:10.1016/j.ebiom.2021.103514 · Cited by 20
Funane, T., Jun, H., Sutoko, S., Saido, T. C., Kandori, A., & Igarashi, K. M. (2022) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2022.955178 · Cited by 19
Metadata
- Authors
- Iaccarino, H. F., Singer, A. C., Martorell, A. J., Rudenko, A., Gao, F., Gillingham, T. Z., Mathys, H., Seo, J., Kritskiy, O., Abdurrob, F., Adaikkan, C., Canter, R. G., Rueda, R., Brown, E. N., Boyden, E. S., & Tsai, L.-H.
- Affiliations
- McGovern Institute for Brain Research (US)
- Massachusetts Institute of Technology (US)
- Massachusetts General Hospital (US)
- Broad Institute (US)
- Corresponding author
- Tsai, Li-Huei
- ORCID
- Venue
- Nature
- Published
- 2016-12-07
- Volume
- 540
- Issue
- 7632
- Pages
- 230-235
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC5656389
- OpenAlex
- W2560234750
- Cited by
- 1,328
- References
- 41
- Citations by year
- 2026: 169 · 2025: 191 · 2024: 172 · 2023: 160 · 2022: 147 · 2021: 150 · 2020: 131 · 2019: 85 · 2018: 76 · 2017: 42 · 2016: 2
- FWCI
- 54.95
- Type
- journal article
- Language
- en
- Update notices
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion)
- PMC
- Funders
- National Institute on Aging (RF1AG047661)
- National Eye Institute (R01EY023173)
- National Institute of General Medical Sciences (R01GM104948)
- National Institute of Neurological Disorders and Stroke (DP1NS087724)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Keywords
- gamma oscillations, Alzheimer's disease, amyloid-beta, microglia, parvalbumin interneurons, optogenetics, amyloid plaques, 5xFAD mice, APP/PS1 mice, visual cortex, neurodegeneration
- MeSH terms
- Alzheimer Disease, Amyloid, Animals, Disease Models, Animal, Female, Interneurons, Light, Male, Parvalbumins, Peptide Fragments, Visual Cortex, Amyloid beta-Peptides, Microglia, Cell Shape, Mice, CA1 Region, Hippocampal, Plaque, Amyloid, Transcriptome, Optogenetics, Gamma Rhythm
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review