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Abdelmissih S, Hosny SA, Elwi HM, Sayed WM, Eshra MA, Shaker OG, Samir NF. Chronic Caffeine Consumption, Alone or Combined with Agomelatine or Quetiapine, Reduces the Maximum EEG Peak, As Linked to Cortical Neurodegeneration, Ovarian Estrogen Receptor Alpha, and Melatonin Receptor 2. Psychopharmacology (Berl) 2024:10.1007/s00213-024-06619-4. [PMID: 38842700 DOI: 10.1007/s00213-024-06619-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 05/16/2024] [Indexed: 06/07/2024]
Abstract
RATIONALE Evidence of the effects of chronic caffeine (CAFF)-containing beverages, alone or in combination with agomelatine (AGO) or quetiapine (QUET), on electroencephalography (EEG), which is relevant to cognition, epileptogenesis, and ovarian function, remains lacking. Estrogenic, adenosinergic, and melatonergic signaling is possibly linked to the dynamics of these substances. OBJECTIVES The brain and ovarian effects of CAFF were compared with those of AGO + CAFF and QUET + CAFF. The implications of estrogenic, adenosinergic, and melatonergic signaling and the brain-ovarian crosstalk were investigated. METHODS Adult female rats were administered AGO (10 mg/kg), QUET (10 mg/kg), CAFF, AGO + CAFF, or QUET + CAFF, once daily for 8 weeks. EEG, estrous cycle progression, and microstructure of the brain and ovaries were examined. Brain and ovarian 17β-estradiol (E2), antimullerian hormone (AMH), estrogen receptor alpha (E2Rα), adenosine receptor 2A (A2AR), and melatonin receptor 2 (MT2R) were assessed. RESULTS CAFF, alone or combined with AGO or QUET, reduced the maximum EEG peak, which was positively linked to ovarian E2Rα, negatively correlated to cortical neurodegeneration and ovarian MT2R, and associated with cystic ovaries. A large corpus luteum emerged with AGO + CAFF and QUET + CAFF, antagonizing the CAFF-mediated increased ovarian A2AR and reduced cortical E2Rα. AGO + CAFF provoked TTP delay and increased ovarian AMH, while QUET + CAFF slowed source EEG frequency to δ range and increased brain E2. CONCLUSIONS CAFF treatment triggered brain and ovarian derangements partially antagonized with concurrent AGO or QUET administration but with no overt affection of estrus cycle progression. Estrogenic, adenosinergic, and melatonergic signaling and brain-ovarian crosstalk may explain these effects.
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Affiliation(s)
- Sherine Abdelmissih
- Department of Medical Pharmacology, Faculty of Medicine Kasr Al-Ainy, Cairo University, Cairo, Egypt.
| | - Sara Adel Hosny
- Department of Medical Histology, Faculty of Medicine Kasr Al-Ainy, Cairo University, Cairo, Egypt
| | - Heba M Elwi
- Department of Medical Biochemistry and Molecular Biology, Faculty of Medicine Kasr Al-Ainy, Cairo University, Cairo, Egypt
| | - Walaa Mohamed Sayed
- Department of Anatomy and Embryology, Faculty of Medicine Kasr Al-Ainy, Cairo University, Cairo, Egypt
| | - Mohamed Ali Eshra
- Department of Medical Physiology, Faculty of Medicine Kasr Al-Ainy, Cairo University, Cairo, Egypt
| | - Olfat Gamil Shaker
- Department of Medical Biochemistry and Molecular Biology, Faculty of Medicine Kasr Al-Ainy, Cairo University, Cairo, Egypt
| | - Nancy F Samir
- Department of Medical Physiology, Faculty of Medicine Kasr Al-Ainy, Cairo University, Cairo, Egypt
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Katsuki F, Spratt TJ, Brown RE, Basheer R, Uygun DS. Sleep-Deep-Learner is taught sleep-wake scoring by the end-user to complete each record in their style. SLEEP ADVANCES : A JOURNAL OF THE SLEEP RESEARCH SOCIETY 2024; 5:zpae022. [PMID: 38638581 PMCID: PMC11025629 DOI: 10.1093/sleepadvances/zpae022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 03/24/2024] [Indexed: 04/20/2024]
Abstract
Sleep-wake scoring is a time-consuming, tedious but essential component of clinical and preclinical sleep research. Sleep scoring is even more laborious and challenging in rodents due to the smaller EEG amplitude differences between states and the rapid state transitions which necessitate scoring in shorter epochs. Although many automated rodent sleep scoring methods exist, they do not perform as well when scoring new datasets, especially those which involve changes in the EEG/EMG profile. Thus, manual scoring by expert scorers remains the gold standard. Here we take a different approach to this problem by using a neural network to accelerate the scoring of expert scorers. Sleep-Deep-Learner creates a bespoke deep convolution neural network model for individual electroencephalographic or local-field-potential (LFP) records via transfer learning of GoogLeNet, by learning from a small subset of manual scores of each EEG/LFP record as provided by the end-user. Sleep-Deep-Learner then automates scoring of the remainder of the EEG/LFP record. A novel REM sleep scoring correction procedure further enhanced accuracy. Sleep-Deep-Learner reliably scores EEG and LFP data and retains sleep-wake architecture in wild-type mice, in sleep induced by the hypnotic zolpidem, in a mouse model of Alzheimer's disease and in a genetic knock-down study, when compared to manual scoring. Sleep-Deep-Learner reduced manual scoring time to 1/12. Since Sleep-Deep-Learner uses transfer learning on each independent recording, it is not biased by previously scored existing datasets. Thus, we find Sleep-Deep-Learner performs well when used on signals altered by a drug, disease model, or genetic modification.
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Affiliation(s)
- Fumi Katsuki
- Department of Psychiatry, VA Boston Healthcare System and Harvard Medical School, West Roxbury, MA, USA
| | - Tristan J Spratt
- Department of Psychiatry, VA Boston Healthcare System and Harvard Medical School, West Roxbury, MA, USA
| | - Ritchie E Brown
- Department of Psychiatry, VA Boston Healthcare System and Harvard Medical School, West Roxbury, MA, USA
| | - Radhika Basheer
- Department of Psychiatry, VA Boston Healthcare System and Harvard Medical School, West Roxbury, MA, USA
| | - David S Uygun
- Department of Psychiatry, VA Boston Healthcare System and Harvard Medical School, West Roxbury, MA, USA
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Chmiel J, Rybakowski F, Leszek J. EEG in Down Syndrome-A Review and Insights into Potential Neural Mechanisms. Brain Sci 2024; 14:136. [PMID: 38391711 PMCID: PMC10886507 DOI: 10.3390/brainsci14020136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Revised: 01/23/2024] [Accepted: 01/26/2024] [Indexed: 02/24/2024] Open
Abstract
Introduction: Down syndrome (DS) stands out as one of the most prevalent genetic disorders, imposing a significant burden on both society and the healthcare system. Scientists are making efforts to understand the neural mechanisms behind the pathophysiology of this disorder. Among the valuable methods for studying these mechanisms is electroencephalography (EEG), a non-invasive technique that measures the brain's electrical activity, characterised by its excellent temporal resolution. This review aims to consolidate studies examining EEG usage in individuals with DS. The objective was to identify shared elements of disrupted EEG activity and, crucially, to elucidate the neural mechanisms underpinning these deviations. Searches were conducted on Pubmed/Medline, Research Gate, and Cochrane databases. Results: The literature search yielded 17 relevant articles. Despite the significant time span, small sample size, and overall heterogeneity of the included studies, three common features of aberrant EEG activity in people with DS were found. Potential mechanisms for this altered activity were delineated. Conclusions: The studies included in this review show altered EEG activity in people with DS compared to the control group. To bolster these current findings, future investigations with larger sample sizes are imperative.
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Affiliation(s)
- James Chmiel
- Institute of Neurofeedback and tDCS Poland, 70-393 Szczecin, Poland
| | - Filip Rybakowski
- Department and Clinic of Psychiatry, Poznan University of Medical Sciences, 61-701 Poznań, Poland
| | - Jerzy Leszek
- Department and Clinic of Psychiatry, Wrocław Medical University, 54-235 Wrocław, Poland
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Katsuki F, Spratt TJ, Brown RE, Basheer R, Uygun DS. Sleep-Deep-Net learns sleep wake scoring from the end-user and completes each record in their style. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.22.573151. [PMID: 38187568 PMCID: PMC10769368 DOI: 10.1101/2023.12.22.573151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Sleep-wake scoring is a time-consuming, tedious but essential component of clinical and pre-clinical sleep research. Sleep scoring is even more laborious and challenging in rodents due to the smaller EEG amplitude differences between states and the rapid state transitions which necessitate scoring in shorter epochs. Although many automated rodent sleep scoring methods exist, they do not perform as well when scoring new data sets, especially those which involve changes in the EEG/EMG profile. Thus, manual scoring by expert scorers remains the gold-standard. Here we take a different approach to this problem by using a neural network to accelerate the scoring of expert scorers. Sleep-Deep-Net (SDN) creates a bespoke deep convolution neural network model for individual electroencephalographic or local-field-potential records via transfer learning of GoogleNet, by learning from a small subset of manual scores of each EEG/LFP record as provided by the end-user. SDN then automates scoring of the remainder of the EEG/LFP record. A novel REM scoring correction procedure further enhanced accuracy. SDN reliably scores EEG and LFP data and retains sleep-wake architecture in wild-type mice, in sleep induced by the hypnotic zolpidem, in a mouse model of Alzheimer's disease and in a genetic knock-down study, when compared to manual scoring. SDN reduced manual scoring time to 1/12. Since SDN uses transfer learning on each independent recording, it is not biased by previously scored existing data sets. Thus, we find SDN performs well when used on signals altered by a drug, disease model or genetic modification.
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Affiliation(s)
- Fumi Katsuki
- VA Boston Healthcare System and Harvard Medical School, Dept. of Psychiatry, West Roxbury, MA 02132, USA
| | - Tristan J Spratt
- VA Boston Healthcare System and Harvard Medical School, Dept. of Psychiatry, West Roxbury, MA 02132, USA
| | - Ritchie E Brown
- VA Boston Healthcare System and Harvard Medical School, Dept. of Psychiatry, West Roxbury, MA 02132, USA
| | - Radhika Basheer
- VA Boston Healthcare System and Harvard Medical School, Dept. of Psychiatry, West Roxbury, MA 02132, USA
| | - David S Uygun
- VA Boston Healthcare System and Harvard Medical School, Dept. of Psychiatry, West Roxbury, MA 02132, USA
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Haam J, Gunin S, Wilson L, Fry S, Bernstein B, Thomson E, Noblet H, Cushman J, Yakel JL. Entorhinal cortical delta oscillations drive memory consolidation. Cell Rep 2023; 42:113267. [PMID: 37838945 PMCID: PMC10872950 DOI: 10.1016/j.celrep.2023.113267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 08/30/2023] [Accepted: 09/28/2023] [Indexed: 10/17/2023] Open
Abstract
Long-term memories are formed by creating stable memory representations via memory consolidation, which mainly occurs during sleep following the encoding of labile memories in the hippocampus during waking. The entorhinal cortex (EC) has intricate connections with the hippocampus, but its role in memory consolidation is largely unknown. Using cell-type- and input-specific in vivo neural activity recordings, here we show that the temporoammonic pathway neurons in the EC, which directly innervate the output area of the hippocampus, exhibit potent oscillatory activities during anesthesia and sleep. Using in vivo individual and populational neuronal activity recordings, we demonstrate that a subpopulation of the temporoammonic pathway neurons, which we termed sleep cells, generate delta oscillations via hyperpolarization-activated cyclic-nucleotide-gated channels during sleep. The blockade of these oscillations significantly impaired the consolidation of hippocampus-dependent memory. Together, our findings uncover a key driver of delta oscillations and memory consolidation that are found in the EC.
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Affiliation(s)
- Juhee Haam
- Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA; Neurobiology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC 27709, USA.
| | - Suman Gunin
- Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA
| | - Leslie Wilson
- Neurobiology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC 27709, USA
| | - Sydney Fry
- Neurobiology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC 27709, USA
| | - Briana Bernstein
- Neurobiology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC 27709, USA
| | - Eric Thomson
- Neurobiology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC 27709, USA
| | - Hayden Noblet
- Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA
| | - Jesse Cushman
- Neurobiology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC 27709, USA
| | - Jerrel L Yakel
- Neurobiology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC 27709, USA.
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Li T, Gao Y, He M, Gui Z, Zhao B, Cao Y, Chen T, Zhu J, Wang J, Zhong Q, Zhang Z. P2X7 receptor-activated microglia in cortex is critical for sleep disorder under neuropathic pain. Front Neurosci 2023; 17:1095718. [PMID: 36816134 PMCID: PMC9936193 DOI: 10.3389/fnins.2023.1095718] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 01/16/2023] [Indexed: 02/05/2023] Open
Abstract
Neuropathic pain (NP) is associated with sleep disturbances, which may substantially influence the quality of life. Clinical and animal studies demonstrated that neurotransmitter is one of the main contributors to cause sleep disturbances induced by NP. Recently, it was reported that P2X7 receptors (P2X7R) are widely expressed in microglia, which serves crucial role in neuronal activity in the pain and sleep-awake cycle. In this study, we adopted the chronic constriction injury (CCI) model to establish the progress of chronic pain and investigated whether P2X7R of microglia in cortex played a critical role in sleep disturbance induced by NP. At electroencephalogram (EEG) level, sleep disturbance was observed in mice treated with CCI as they exhibited mechanical and thermal hypersensitivity, and inhibition of P2X7R ameliorated these changes. We showed a dramatic high level of P2X7R and Iba-1 co-expression in the cortical region, and the inhibition of P2X7R also adversely affected it. Furthermore, the power of LFPs in ventral posterior nucleus (VP) and primary somatosensory cortex (S1) which changed in the CCI group was adverse after the inhibition of P2X7R. Furthermore, inhibition of P2X7R also decreased the VP-S1 coherence which increased in CCI group. Nuclear magnetic resonance demonstrated inhibition of P2X7R decreased glutamate (Glu) levels in thalamic and cortical regions which were significantly increased in the CCI mice. Our findings provide evidence that NP has a critical effect on neuronal activity linked to sleep and may built up a new target for the development of sleep disturbances under chronic pain conditions.
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Affiliation(s)
- Tingting Li
- Department of Anesthesiology, Zhongnan Hospital, Wuhan University, Wuhan, Hubei, China
| | - Yunling Gao
- Xiangyang Central Hospital, Institute of Neuroscience and Brain Diseases, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, Hubei, China
| | - Mengying He
- Department of Anesthesiology, Zhongnan Hospital, Wuhan University, Wuhan, Hubei, China,Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan National Laboratory for Optoelectronics, Wuhan, China
| | - Zhu Gui
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan National Laboratory for Optoelectronics, Wuhan, China,University of Chinese Academy of Sciences, Beijing, China
| | - Bingchu Zhao
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan National Laboratory for Optoelectronics, Wuhan, China,School of Computer Science, Wuhan University, Wuhan, Hubei, China
| | - Yue Cao
- Department of Anesthesiology, Zhongnan Hospital, Wuhan University, Wuhan, Hubei, China
| | - Ting Chen
- Department of Anesthesiology, Zhongnan Hospital, Wuhan University, Wuhan, Hubei, China
| | - Jinpiao Zhu
- Department of Anesthesiology, Zhongnan Hospital, Wuhan University, Wuhan, Hubei, China,Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan National Laboratory for Optoelectronics, Wuhan, China
| | - Jie Wang
- Xiangyang Central Hospital, Institute of Neuroscience and Brain Diseases, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, Hubei, China,Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan National Laboratory for Optoelectronics, Wuhan, China,University of Chinese Academy of Sciences, Beijing, China
| | - Qi Zhong
- Department of Anesthesiology, Zhongnan Hospital, Wuhan University, Wuhan, Hubei, China,*Correspondence: Qi Zhong,
| | - Zongze Zhang
- Department of Anesthesiology, Zhongnan Hospital, Wuhan University, Wuhan, Hubei, China,Zongze Zhang,
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Brown RE, Kaplan GB. Introduction to special issue: Sleep and arousal in health and disease. Brain Res Bull 2022; 188:131-132. [PMID: 35918033 PMCID: PMC9903342 DOI: 10.1016/j.brainresbull.2022.07.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Affiliation(s)
- Ritchie E Brown
- Laboratory of Neuroscience, VA Boston Healthcare System and Harvard Medical School, Dept. of Psychiatry, 1400 VFW Parkway, West Roxbury, MA 02132, USA.
| | - Gary B Kaplan
- Mental Health Service (151), VA Boston Healthcare System, West Roxbury, MA 02312, USA; Departments of Psychiatry and Pharmacology & Experimental Therapeutics, Boston University School of Medicine, Boston, MA 02118, USA.
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Katsuki F, Gerashchenko D, Brown RE. Alterations of sleep oscillations in Alzheimer's disease: A potential role for GABAergic neurons in the cortex, hippocampus, and thalamus. Brain Res Bull 2022; 187:181-198. [PMID: 35850189 DOI: 10.1016/j.brainresbull.2022.07.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 06/01/2022] [Accepted: 07/06/2022] [Indexed: 02/07/2023]
Abstract
Sleep abnormalities are widely reported in patients with Alzheimer's disease (AD) and are linked to cognitive impairments. Sleep abnormalities could be potential biomarkers to detect AD since they are often observed at the preclinical stage. Moreover, sleep could be a target for early intervention to prevent or slow AD progression. Thus, here we review changes in brain oscillations observed during sleep, their connection to AD pathophysiology and the role of specific brain circuits. Slow oscillations (0.1-1 Hz), sleep spindles (8-15 Hz) and their coupling during non-REM sleep are consistently reduced in studies of patients and in AD mouse models although the timing and magnitude of these alterations depends on the pathophysiological changes and the animal model studied. Changes in delta (1-4 Hz) activity are more variable. Animal studies suggest that hippocampal sharp-wave ripples (100-250 Hz) are also affected. Reductions in REM sleep amount and slower oscillations during REM are seen in patients but less consistently in animal models. Thus, changes in a variety of sleep oscillations could impact sleep-dependent memory consolidation or restorative functions of sleep. Recent mechanistic studies suggest that alterations in the activity of GABAergic neurons in the cortex, hippocampus and thalamic reticular nucleus mediate sleep oscillatory changes in AD and represent a potential target for intervention. Longitudinal studies of the timing of AD-related sleep abnormalities with respect to pathology and dysfunction of specific neural networks are needed to identify translationally relevant biomarkers and guide early intervention strategies to prevent or delay AD progression.
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Affiliation(s)
- Fumi Katsuki
- VA Boston Healthcare System and Harvard Medical School, Dept. of Psychiatry, West Roxbury, MA 02132, USA.
| | - Dmitry Gerashchenko
- VA Boston Healthcare System and Harvard Medical School, Dept. of Psychiatry, West Roxbury, MA 02132, USA
| | - Ritchie E Brown
- VA Boston Healthcare System and Harvard Medical School, Dept. of Psychiatry, West Roxbury, MA 02132, USA
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