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Neyhart E, Zhou N, Munn BR, Law RG, Smith C, Mridha ZH, Blanco FA, Li G, Li Y, McGinley MJ, Shine JM, Reimer J. Cortical acetylcholine dynamics are predicted by cholinergic axon activity and behavior state. bioRxiv 2024:2023.11.14.567116. [PMID: 38352527 PMCID: PMC10862699 DOI: 10.1101/2023.11.14.567116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/19/2024]
Abstract
Even under spontaneous conditions and in the absence of changing environmental demands, awake animals alternate between increased or decreased periods of alertness. These changes in brain state can occur rapidly, on a timescale of seconds, and neuromodulators such as acetylcholine (ACh) are thought to play an important role in driving these spontaneous state transitions. Here, we perform the first simultaneous imaging of ACh sensors and GCaMP-expressing axons in vivo, to examine the spatiotemporal properties of cortical ACh activity and release during spontaneous changes in behavioral state. We observed a high correlation between simultaneously recorded basal forebrain axon activity and neuromodulator sensor fluorescence around periods of locomotion and pupil dilation. Consistent with volume transmission of ACh, increases in axon activity were accompanied by increases in local ACh levels that fell off with the distance from the nearest axon. GRAB-ACh fluorescence could be accurately predicted from axonal activity alone, providing the first validation that neuromodulator axon activity is a reliable proxy for nearby neuromodulator levels. Deconvolution of fluorescence traces allowed us to account for the kinetics of the GRAB-ACh sensor and emphasized the rapid clearance of ACh for smaller transients outside of running periods. Finally, we trained a predictive model of ACh fluctuations from the combination of pupil size and running speed; this model performed better than using either variable alone, and generalized well to unseen data. Overall, these results contribute to a growing understanding of the precise timing and spatial characteristics of cortical ACh during fast brain state transitions.
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Affiliation(s)
- Erin Neyhart
- Neuroscience Department, Baylor College of Medicine, Houston, Texas, USA
| | - Na Zhou
- Neuroscience Department, Baylor College of Medicine, Houston, Texas, USA
| | - Brandon R Munn
- Brain and Mind Centre, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Australia
- Complex Systems Group, School of Physics, Faculty of Science, The University of Sydney, Australia
| | - Robert G Law
- Neuroscience Department, Baylor College of Medicine, Houston, Texas, USA
| | - Cameron Smith
- Neuroscience Department, Baylor College of Medicine, Houston, Texas, USA
| | - Zakir H Mridha
- Neuroscience Department, Baylor College of Medicine, Houston, Texas, USA
| | - Francisco A Blanco
- Neuroscience Department, Baylor College of Medicine, Houston, Texas, USA
| | - Guochuan Li
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Yulong Li
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Matthew J McGinley
- Neuroscience Department, Baylor College of Medicine, Houston, Texas, USA
| | - James M Shine
- Brain and Mind Centre, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Australia
- Complex Systems Group, School of Physics, Faculty of Science, The University of Sydney, Australia
| | - Jacob Reimer
- Neuroscience Department, Baylor College of Medicine, Houston, Texas, USA
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Kozhemiako N, Jiang C, Sun Y, Guo Z, Chapman S, Gai G, Wang Z, Zhou L, Li S, Law RG, Wang LA, Mylonas D, Shen L, Murphy M, Qin S, Zhu W, Zhou Z, Stickgold R, Huang H, Tan S, Manoach DS, Wang J, Hall MH, Pan JQ, Purcell SM. A spectrum of altered non-rapid eye movement sleep in schizophrenia. bioRxiv 2023:2023.12.28.573548. [PMID: 38234726 PMCID: PMC10793442 DOI: 10.1101/2023.12.28.573548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Background Multiple facets of sleep neurophysiology, including electroencephalography (EEG) metrics such as non-rapid eye movement (NREM) spindles and slow oscillations (SO), are altered in individuals with schizophrenia (SCZ). However, beyond group-level analyses which treat all patients as a unitary set, the extent to which NREM deficits vary among patients is unclear, as are their relationships to other sources of heterogeneity including clinical factors, illness duration and ageing, cognitive profiles and medication regimens. Using newly collected high density sleep EEG data on 103 individuals with SCZ and 68 controls, we first sought to replicate our previously reported (Kozhemiako et. al, 2022) group-level mean differences between patients and controls (original N=130). Then in the combined sample (N=301 including 175 patients), we characterized patient-to-patient variability in NREM neurophysiology. Results We replicated all group-level mean differences and confirmed the high accuracy of our predictive model (Area Under the ROC Curve, AUC = 0.93 for diagnosis). Compared to controls, patients showed significantly increased between-individual variability across many (26%) sleep metrics, with patterns only partially recapitulating those for group-level mean differences. Although multiple clinical and cognitive factors were associated with NREM metrics including spindle density, collectively they did not account for much of the general increase in patient-to-patient variability. Medication regimen was a greater (albeit still partial) contributor to variability, although original group mean differences persisted after controlling for medications. Some sleep metrics including fast spindle density showed exaggerated age-related effects in SCZ, and patients exhibited older predicted biological ages based on an independent model of ageing and the sleep EEG. Conclusion We demonstrated robust and replicable alterations in sleep neurophysiology in individuals with SCZ and highlighted distinct patterns of effects contrasting between-group means versus within-group variances. We further documented and controlled for a major effect of medication use, and pointed to greater age-related change in NREM sleep in patients. That increased NREM heterogeneity was not explained by standard clinical or cognitive patient assessments suggests the sleep EEG provides novel, nonredundant information to support the goals of personalized medicine. Collectively, our results point to a spectrum of NREM sleep deficits among SCZ patients that can be measured objectively and at scale, and that may offer a unique window on the etiological and genetic diversity that underlies SCZ risk, treatment response and prognosis.
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Affiliation(s)
- Nataliia Kozhemiako
- Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School; Boston, USA
| | - Chenguang Jiang
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University; Wuxi, China
| | - Yifan Sun
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University; Wuxi, China
| | - Zhenglin Guo
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Boston, USA
| | - Sinéad Chapman
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Boston, USA
| | - Guanchen Gai
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University; Wuxi, China
| | - Zhe Wang
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University; Wuxi, China
| | - Lin Zhou
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Boston, USA
| | - Shen Li
- Department of Psychiatry, McLean Hospital, Harvard Medical School; Boston, USA
| | - Robert G. Law
- Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School; Boston, USA
| | - Lei A. Wang
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Boston, USA
| | - Dimitrios Mylonas
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School; Boston, USA
| | - Lu Shen
- Bio-X Institutes, Shanghai Jiao Tong University; Shanghai China
| | - Michael Murphy
- Department of Psychiatry, McLean Hospital, Harvard Medical School; Boston, USA
| | - Shengying Qin
- Bio-X Institutes, Shanghai Jiao Tong University; Shanghai China
| | - Wei Zhu
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University; Wuxi, China
| | - Zhenhe Zhou
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University; Wuxi, China
| | - Robert Stickgold
- Beth Israel Deaconess Medical Center; Boston, USA
- Department of Psychiatry, Harvard Medical School; Boston, USA
| | - Hailiang Huang
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Boston, USA
- ATGU, MGH, Harvard Medical School; Boston, USA
| | - Shuping Tan
- Huilong Guan Hospital, Beijing University; Beijing China
| | - Dara S. Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School; Boston, USA
| | - Jun Wang
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University; Wuxi, China
| | - Mei-Hua Hall
- Department of Psychiatry, McLean Hospital, Harvard Medical School; Boston, USA
| | - Jen Q. Pan
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Boston, USA
| | - Shaun M. Purcell
- Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School; Boston, USA
- Department of Psychiatry, Harvard Medical School; Boston, USA
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Law RG, Pugliese S, Shin H, Sliva DD, Lee S, Neymotin S, Moore C, Jones SR. Thalamocortical Mechanisms Regulating the Relationship between Transient Beta Events and Human Tactile Perception. Cereb Cortex 2021; 32:668-688. [PMID: 34401898 PMCID: PMC8841599 DOI: 10.1093/cercor/bhab221] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2019] [Revised: 04/20/2021] [Accepted: 05/25/2021] [Indexed: 12/27/2022] Open
Abstract
Transient neocortical events with high spectral power in the 15–29 Hz beta band are among the most reliable predictors of sensory perception. Prestimulus beta event rates in primary somatosensory cortex correlate with sensory suppression, most effectively 100–300 ms before stimulus onset. However, the neural mechanisms underlying this perceptual association are unknown. We combined human magnetoencephalography (MEG) measurements with biophysical neural modeling to test potential cellular and circuit mechanisms that underlie observed correlations between prestimulus beta events and tactile detection. Extending prior studies, we found that simulated bursts from higher-order, nonlemniscal thalamus were sufficient to drive beta event generation and to recruit slow supragranular inhibition acting on a 300 ms timescale to suppress sensory information. Further analysis showed that the same beta-generating mechanism can lead to facilitated perception for a brief period when beta events occur simultaneously with tactile stimulation before inhibition is recruited. These findings were supported by close agreement between model-derived predictions and empirical MEG data. The postevent suppressive mechanism explains an array of studies that associate beta with decreased processing, whereas the during-event facilitatory mechanism may demand a reinterpretation of the role of beta events in the context of coincident timing.
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Affiliation(s)
- Robert G Law
- Department of Neuroscience, Brown University, Providence, RI 02912, USA.,Center for Neurorestoration and Neurotechnology, Providence VA Medical Center, Providence, RI 02908, USA.,Department of Psychiatry, Harvard Medical School, Cambridge, MA 02215, USA
| | - Sarah Pugliese
- Department of Neuroscience, Brown University, Providence, RI 02912, USA
| | - Hyeyoung Shin
- Department of Neuroscience, Brown University, Providence, RI 02912, USA.,Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Danielle D Sliva
- Department of Neuroscience, Brown University, Providence, RI 02912, USA
| | - Shane Lee
- Department of Neuroscience, Brown University, Providence, RI 02912, USA.,Department of Neurosurgery, Rhode Island Hospital, Providence, RI 02903, USA.,Norman Prince Neurosciences Institute, Rhode Island Hospital, Providence, RI 02903, USA
| | - Samuel Neymotin
- Department of Neuroscience, Brown University, Providence, RI 02912, USA.,Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA
| | - Christopher Moore
- Department of Neuroscience, Brown University, Providence, RI 02912, USA
| | - Stephanie R Jones
- Department of Neuroscience, Brown University, Providence, RI 02912, USA.,Center for Neurorestoration and Neurotechnology, Providence VA Medical Center, Providence, RI 02908, USA
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Abstract
By means of a light pen coupled with a microprocessor, the fetal head circumference of 594 fetuses was measured and the results compared with the biparietal diameter and abdominal circumference. In a statistically significant proportion of cases, the head circumference was more closely related than the biparietal diameter to both the abdominal circumference and the gestational age of the fetus as calculated from the mother's menstrual history. Possible reasons for this finding are discussed. It is concluded that the head circumference is a more accurate index of the age of the fetus and its growth potential than is the biparietal diameter, and that use of the head circumference should, in consequence, replace that of the biparietal diameter in obstetric scanning.
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Law RG. Prolonged labour. Nurs Mirror Midwives J 1971; 133:24-6. [PMID: 5210071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
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Law RG. Long labour. Midwife Health Visit 1970; 6:177-84. [PMID: 5206007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
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Law RG. Caesarean delivery. Midwives Chron 1969; 83:160-3. [PMID: 5192340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
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Law RG. Domiciliary confinement in three high risk obstetric groups. Proc R Soc Med 1968; 61:1029-32. [PMID: 5682626 PMCID: PMC1902762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
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Law RG. Foetal aspects of twin pregnancy. 2. Management. Midwife Health Visit 1968; 4:286-8. [PMID: 5186990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
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Law RG. Foetal aspects of twin pregnancy. I. Foetal hazards. Midwife Health Visit 1968; 4:251-3. [PMID: 5185707] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
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Law RG. Management of breech presentations. Midwife Health Visit 1967; 3:49-53. [PMID: 5180510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
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