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Wodeyar A, Chinappen D, Mylonas D, Baxter B, Manoach DS, Eden UT, Kramer MA, Chu CJ. Thalamic epileptic spikes disrupt sleep spindles in patients with epileptic encephalopathy. Brain 2024:awae119. [PMID: 38650060 DOI: 10.1093/brain/awae119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 03/01/2024] [Accepted: 03/24/2024] [Indexed: 04/25/2024] Open
Abstract
In severe epileptic encephalopathies, epileptic activity contributes to progressive cognitive dysfunction. Epileptic encephalopathies share the trait of spike-wave activation during non-rapid eye movement sleep (EE-SWAS), a sleep stage dominated by sleep spindles, brain oscillations known to coordinate offline memory consolidation. Epileptic activity has been proposed to hijack the circuits driving these thalamocortical oscillations, thereby contributing to cognitive impairment. Using a unique dataset of simultaneous human thalamic and cortical recordings in subjects with and without EE-SWAS, we provide evidence for epileptic spike interference of thalamic sleep spindle production in patients with EE-SWAS. First, we show that epileptic spikes and sleep spindles are both predicted by slow oscillations during stage two sleep (N2), but at different phases of the slow oscillation. Next, we demonstrate that sleep activated cortical epileptic spikes propagate to the thalamus (thalamic spike rate increases after a cortical spike, p≈0). We then show that epileptic spikes in the thalamus increase the thalamic spindle refractory period (p≈0). Finally, we show that in three patients with EE-SWAS, there is a downregulation of sleep spindles for 30 seconds after each thalamic spike (p<0.01). These direct human thalamocortical observations support a proposed mechanism for epileptiform activity to impact cognitive function, wherein epileptic spikes inhibit thalamic sleep spindles in epileptic encephalopathy with spike and wave activation during sleep.
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Affiliation(s)
- Anirudh Wodeyar
- Department of Mathematics and Statistics, Boston University, Boston, MA 02215, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114 USA
- Neurology, Harvard Medical School, Boston, MA 02115, USA
| | - Dhinakaran Chinappen
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114 USA
- Graduate Program in Neuroscience, Boston University, Boston, MA 02215, USA
| | - Dimitris Mylonas
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02215, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Bryan Baxter
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02215, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02215, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Uri T Eden
- Department of Mathematics and Statistics, Boston University, Boston, MA 02215, USA
- Center for Systems Neuroscience, Boston University, Boston, MA 02215 USA
| | - Mark A Kramer
- Department of Mathematics and Statistics, Boston University, Boston, MA 02215, USA
- Center for Systems Neuroscience, Boston University, Boston, MA 02215 USA
| | - Catherine J Chu
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114 USA
- Neurology, Harvard Medical School, Boston, MA 02115, USA
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Mylonas D, Schapiro AC, Verfaellie M, Baxter B, Vangel M, Stickgold R, Manoach DS. Maintenance of Procedural Motor Memory across Brief Rest Periods Requires the Hippocampus. J Neurosci 2024; 44:e1839232024. [PMID: 38351000 PMCID: PMC10993031 DOI: 10.1523/jneurosci.1839-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 01/04/2024] [Accepted: 01/23/2024] [Indexed: 03/26/2024] Open
Abstract
Research on the role of the hippocampus in memory acquisition has generally focused on active learning. But to understand memory, it is at least as important to understand processes that happen offline, during both wake and sleep. In a study of patients with amnesia, we previously demonstrated that although a functional hippocampus is not necessary for the acquisition of procedural motor memory during training session, it is required for its offline consolidation during sleep. Here, we investigated whether an intact hippocampus is also required for the offline consolidation of procedural motor memory while awake. Patients with amnesia due to hippocampal damage (n = 4, all male) and demographically matched controls (n = 10, 8 males) trained on the finger tapping motor sequence task. Learning was measured as gains in typing speed and was divided into online (during task execution) and offline (during interleaved 30 s breaks) components. Amnesic patients and controls showed comparable total learning, but differed in the pattern of performance improvement. Unlike younger adults, who gain speed across breaks, both groups gained speed only while typing. Only controls retained these gains over the breaks; amnesic patients slowed down and compensated for these losses during subsequent typing. In summary, unlike their peers, whose motor performance remained stable across brief breaks in typing, amnesic patients showed evidence of impaired access to motor procedural memory. We conclude that in addition to being necessary for the offline consolidation of motor memories during sleep, the hippocampus maintains access to motor memory across brief offline periods during wake.
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Affiliation(s)
- Dimitrios Mylonas
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts 02114
- Harvard Medical School, Boston, Massachusetts 02115
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts 02129
| | - Anna C Schapiro
- Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Mieke Verfaellie
- Memory Disorders Research Center, VA Boston Healthcare System, Boston, Massachusetts 02130
- Department of Psychiatry, Boston University Chobanian and Avedisian School of Medicine, Boston, Massachusetts 02215
| | - Bryan Baxter
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts 02114
- Harvard Medical School, Boston, Massachusetts 02115
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts 02129
| | - Mark Vangel
- Harvard Medical School, Boston, Massachusetts 02115
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts 02129
- Department of Biostatistics, Massachusetts General Hospital, Boston, Massachusetts 02114
| | - Robert Stickgold
- Harvard Medical School, Boston, Massachusetts 02115
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, Massachusetts 02215
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts 02114
- Harvard Medical School, Boston, Massachusetts 02115
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts 02129
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Fang A, Baran B, Feusner JD, Phan KL, Beatty CC, Crane J, Jacoby RJ, Manoach DS, Wilhelm S. Self-focused brain predictors of cognitive behavioral therapy response in a transdiagnostic sample. J Psychiatr Res 2024; 171:108-115. [PMID: 38266332 PMCID: PMC10922639 DOI: 10.1016/j.jpsychires.2024.01.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2023] [Revised: 01/09/2024] [Accepted: 01/15/2024] [Indexed: 01/26/2024]
Abstract
BACKGROUND Effective biomarkers of cognitive behavioral therapy (CBT) response provide information beyond available behavioral or self-report measures and may optimize treatment selection for patients based on likelihood of benefit. No single biomarker reliably predicts CBT response. In this study, we evaluated patterns of brain connectivity associated with self-focused attention (SFA) as biomarkers of CBT response for anxiety and obsessive-compulsive disorders. We hypothesized that pre-treatment as well as pre-to post-treatment changes in functional connectivity would be associated with improvement during CBT in a transdiagnostic sample. METHODS Twenty-seven patients with primary social anxiety disorder (n = 14) and primary body dysmorphic disorder (n = 13) were scanned before and after 12 sessions of CBT targeting their primary disorder. Eligibility was based on elevated trait SFA scores on the Public Self-Consciousness Scale. Seed-based resting state functional connectivity associated with symptom improvement was computed using a seed in the posterior cingulate cortex of the default mode network. RESULTS At pre-treatment, stronger positive connectivity of the seed with the cerebellum, and stronger negative connectivity with the putamen, were associated with greater clinical improvement. Between pre-to post-treatment, greater anticorrelation between the seed and postcentral gyrus, extending into the inferior parietal lobule and precuneus/superior parietal lobule was associated with clinical improvement, although this did not survive thresholding. CONCLUSIONS Pre-treatment functional connectivity with the default mode network was associated with CBT response. Behavioral and self-report measures of SFA did not contribute to predictions, thus highlighting the value of neuroimaging-based measures of SFA. CLINICAL TRIALS REGISTRATION ClinicalTrials.gov Identifier: NCT02808702 https://clinicaltrials.gov/ct2/show/NCT02808702.
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Affiliation(s)
- Angela Fang
- Department of Psychology, University of Washington, Seattle, WA, 98195-1525, USA.
| | - Bengi Baran
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA, 52242-1407, USA
| | - Jamie D Feusner
- Centre for Addiction and Mental Health, Brain Imaging Health Center, Ontario, Toronto, Canada, M5T1R8; Department of Psychiatry, University of Toronto, Ontario, Toronto, Canada, M5T1R8; Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - K Luan Phan
- Department of Psychiatry and Behavioral Health, Ohio State University Wexner Medical Center, Columbus, OH, 43210-1240, USA
| | - Clare C Beatty
- Department of Psychology, Stony Brook University, Stony Brook, NY, 11794-2500, USA
| | - Jessica Crane
- Department of Psychology, University of Washington, Seattle, WA, 98195-1525, USA
| | - Ryan J Jacoby
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114-2696, USA
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114-2696, USA; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, 02129-2020, USA
| | - Sabine Wilhelm
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114-2696, 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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Denis D, Baran B, Mylonas D, Spitzer C, Raymond N, Talbot C, Kohnke E, Stickgold R, Keshavan M, Manoach DS. NREM sleep oscillations and their relations with sleep-dependent memory consolidation in early course psychosis and first-degree relatives. bioRxiv 2023:2023.10.30.564703. [PMID: 37961668 PMCID: PMC10634996 DOI: 10.1101/2023.10.30.564703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Sleep spindles are believed to mediate sleep-dependent memory consolidation, particularly when coupled to neocortical slow oscillations. Schizophrenia is characterized by a deficit in sleep spindles that correlates with reduced overnight memory consolidation. Here, we examined sleep spindle activity, slow oscillation-spindle coupling, and both motor procedural and verbal declarative memory consolidation in early course, minimally medicated psychosis patients and non-psychotic first-degree relatives. Using a four-night experimental procedure, we observed significant deficits in spindle density and amplitude in patients relative to controls that were driven by individuals with schizophrenia. Schizophrenia patients also showed reduced sleep-dependent consolidation of motor procedural memory, which correlated with spindle density. Contrary to expectations, there were no group differences in the consolidation of declarative memory on a word pairs task. Nor did the relatives of patients differ in spindle activity or memory consolidation compared with controls, however increased consistency in the timing of SO-spindle coupling were seen in both patient and relatives. Our results extend prior work by demonstrating correlated deficits in sleep spindles and sleep-dependent motor procedural memory consolidation in early course, minimally medicated patients with schizophrenia, but not in first-degree relatives. This is consistent with other work in suggesting that impaired sleep-dependent memory consolidation has some specificity for schizophrenia and is a core feature rather than reflecting the effects of medication or chronicity.
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Affiliation(s)
- Dan Denis
- Department of Psychology, University of York, York, UK
| | - Bengi Baran
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA, USA
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - Dimitrios Mylonas
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | | | | | - Christine Talbot
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Erin Kohnke
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Robert Stickgold
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Matcheri Keshavan
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Dara S Manoach
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
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Baxter BS, Mylonas D, Kwok KS, Talbot CE, Patel R, Zhu L, Vangel M, Stickgold R, Manoach DS. The effects of closed-loop auditory stimulation on sleep oscillatory dynamics in relation to motor procedural memory consolidation. Sleep 2023; 46:zsad206. [PMID: 37531587 PMCID: PMC11009689 DOI: 10.1093/sleep/zsad206] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 05/13/2023] [Indexed: 08/04/2023] Open
Abstract
STUDY OBJECTIVES Healthy aging and many disorders show reduced sleep-dependent memory consolidation and corresponding alterations in non-rapid eye movement sleep oscillations. Yet sleep physiology remains a relatively neglected target for improving memory. We evaluated the effects of closed-loop auditory stimulation during sleep (CLASS) on slow oscillations (SOs), sleep spindles, and their coupling, all in relation to motor procedural memory consolidation. METHODS Twenty healthy young adults had two afternoon naps: one with auditory stimulation during SO upstates and another with no stimulation. Twelve returned for a third nap with stimulation at variable times in relation to SO upstates. In all sessions, participants trained on the motor sequence task prior to napping and were tested afterward. RESULTS Relative to epochs with no stimulation, upstate stimuli disrupted sleep and evoked SOs, spindles, and SO-coupled spindles. Stimuli that successfully evoked oscillations were delivered closer to the peak of the SO upstate and when spindle power was lower than stimuli that failed to evoke oscillations. Across conditions, participants showed similar significant post-nap performance improvement that correlated with the density of SO-coupled spindles. CONCLUSIONS Despite its strong effects on sleep physiology, CLASS failed to enhance motor procedural memory. Our findings suggest methods to overcome this failure, including better sound calibration to preserve sleep continuity and the use of real-time predictive algorithms to more precisely target SO upstates and to avoid disrupting endogenous SO-coupled spindles and their mnemonic function. They motivate continued development of CLASS as an intervention to manipulate sleep oscillatory dynamics and improve memory.
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Affiliation(s)
- Bryan S Baxter
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Dimitrios Mylonas
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Kristi S Kwok
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Christine E Talbot
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Rudra Patel
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Lin Zhu
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Mark Vangel
- Department of Biostatistics, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Robert Stickgold
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
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Fang A, Baran B, Feusner JD, Phan KL, Beatty CC, Crane J, Jacoby RJ, Manoach DS, Wilhelm S. Self-Focused Brain Predictors of Cognitive Behavioral Therapy Response in a Transdiagnostic Sample. medRxiv 2023:2023.08.30.23294878. [PMID: 37693433 PMCID: PMC10491350 DOI: 10.1101/2023.08.30.23294878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Background Effective biomarkers of cognitive behavioral therapy (CBT) response provide information beyond available behavioral or self-report measures and may optimize treatment selection for patients based on likelihood of benefit. No single biomarker reliably predicts CBT response. In this study, we evaluated patterns of brain connectivity associated with self-focused attention (SFA) as biomarkers of CBT response for anxiety and obsessive-compulsive disorders. We hypothesized that pre-treatment as well as pre- to post-treatment changes in functional connectivity would be associated with improvement during CBT in a transdiagnostic sample. Methods Twenty-seven patients with primary social anxiety disorder (n=14) and primary body dysmorphic disorder (n=13) were scanned before and after 12 sessions of CBT targeting their primary disorder. Eligibility was based on elevated trait SFA scores on the Public Self-Consciousness Scale. Seed-based resting state functional connectivity associated with symptom improvement was computed using a seed in the posterior cingulate cortex/precuneus that delineated a self-other functional network. Results At pre-treatment, stronger positive connectivity of the seed with the cerebellum, insula, middle occipital gyrus, postcentral gyrus, and precuneus/superior parietal lobule, and stronger negative connectivity with the putamen, were associated with greater clinical improvement. Between pre- to post-treatment, greater anticorrelation between the seed and precuneus/superior parietal lobule was associated with clinical improvement, although this did not survive thresholding. Conclusions Pre-treatment functional connectivity between regions involved in attentional salience, self-generated thoughts, and external attention predicted greater CBT response. Behavioral and self-report measures of SFA did not contribute to predictions, thus highlighting the value of neuroimaging-based measures of SFA. Clinical Trials Registration ClinicalTrials.gov Identifier: NCT02808702 https://clinicaltrials.gov/ct2/show/NCT02808702.
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Affiliation(s)
- Angela Fang
- Department of Psychology, University of Washington, Seattle, WA, 98195-1525
| | - Bengi Baran
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA, 52242-1407
| | - Jamie D. Feusner
- Centre for Addiction and Mental Health, Brain Imaging Health Center, Ontario, Toronto, Canada, M5T1R8
- Department of Psychiatry, University of Toronto, Ontario, Toronto, Canada, M5T1R8
- Department of Women’s and Children’s Health, Karolinska Institutet, Stockholm, Sweden
| | - K. Luan Phan
- Department of Psychiatry and Behavioral Health, Ohio State University Wexner Medical Center, Columbus, OH, 43210-1240
| | - Clare C. Beatty
- Department of Psychology, Stony Brook University, Stony Brook, NY, 11794-2500
| | - Jessica Crane
- Department of Psychology, University of Washington, Seattle, WA, 98195-1525
| | - Ryan J. Jacoby
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114-2696
| | - Dara S. Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114-2696
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, 02129-2020
| | - Sabine Wilhelm
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114-2696
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Kwon H, Walsh KG, Berja ED, Manoach DS, Eden UT, Kramer MA, Chu CJ. Sleep spindles in the healthy brain from birth through 18 years. Sleep 2023; 46:zsad017. [PMID: 36719044 PMCID: PMC10091086 DOI: 10.1093/sleep/zsad017] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 12/16/2022] [Indexed: 02/01/2023] Open
Abstract
STUDY OBJECTIVE Sleep spindles are present from birth and reflect cognitive functions across the lifespan, but normative values for this cognitive biomarker across development are lacking. This study aims to establish normative spindle features over development. METHODS All available normal 19-channel electroencephalograms from developmentally normal children between February 2002 and June 2021 in the MGH EEG lab were analyzed. Approximately, 20 000 spindles were hand-marked to train and validate an automated spindle detector across ages. Normative values for spindle rate, duration, frequency, refractory period, and interhemispheric lag are provided for each channel and each age. RESULTS Sleep EEGs from 567 developmentally normal children (range 0 days to 18 years) were included. The detector had excellent performance (F1 = 0.47). Maximal spindle activity is seen over central regions during infancy and adolescence and frontopolar regions during childhood. Spindle rate and duration increase nonlinearly, with the most rapid changes during the first 4 months of life and between ages 3 and 14 years. Peak spindle frequency follows a U-shaped curve and discrete frontal slow and central fast spindles are evident by 18 months. Spindle refractory periods decrease between ages 1 and 14 years while interhemispheric asynchrony decreases over the first 3 months of life and between ages 1 and 14 years. CONCLUSIONS These data provide age- and region-specific normative values for sleep spindles across development, where measures that deviate from these values can be considered pathological. As spindles provide a noninvasive biomarker for cognitive function across the lifespan, these normative measures can accelerate the discovery and diagnosis in neurodevelopmental disorders.
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Affiliation(s)
- Hunki Kwon
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Katherine G Walsh
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Erin D Berja
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Dara S Manoach
- Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Uri T Eden
- Department of Mathematics and Statistics, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, USA
| | - Mark A Kramer
- Department of Mathematics and Statistics, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, USA
| | - Catherine J Chu
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
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Baran B, Trang Huong Nguyen Q, Mylonas D, Santangelo SL, Manoach DS. Increased resting-state thalamocortical functional connectivity in children and young adults with autism spectrum disorder. Autism Res 2023; 16:271-279. [PMID: 36546577 PMCID: PMC10619334 DOI: 10.1002/aur.2875] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 11/28/2022] [Indexed: 12/24/2022]
Abstract
There is converging evidence that abnormal thalamocortical interactions contribute to attention deficits and sensory sensitivities in autism spectrum disorder (ASD). However, previous functional MRI studies of thalamocortical connectivity in ASD have produced inconsistent findings in terms of both the direction (hyper vs. hypoconnectivity) and location of group differences. This may reflect, in part, the confounding effects of head motion during scans. In the present study, we investigated resting-state thalamocortical functional connectivity in 8-25 year-olds with ASD and their typically developing (TD) peers. We used pre-scan training, on-line motion correction, and rigorous data quality assurance protocols to minimize motion confounds. ASD participants showed increased thalamic connectivity with temporal cortex relative to TD. Both groups showed similar age-related decreases in thalamic connectivity with occipital cortex, consistent with a process of circuit refinement. Findings of thalamocortical hyperconnectivity in ASD are consistent with other evidence that decreased thalamic inhibition leads to increase and less filtered sensory information reaching the cortex where it disrupts attention and contributes to sensory sensitivity. This literature motivates studies of mechanisms, functional consequences, and treatment of thalamocortical circuit dysfunction in ASD.
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Affiliation(s)
- Bengi Baran
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA
| | | | - Dimitrios Mylonas
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Susan L. Santangelo
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Maine Medical Center Research Institute, Scarborough, ME
- Tufts University School of Medicine, Department of Psychiatry, Boston, MA
| | - Dara S. Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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10
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Stokes PA, Rath P, Possidente T, He M, Purcell S, Manoach DS, Stickgold R, Prerau MJ. Transient oscillation dynamics during sleep provide a robust basis for electroencephalographic phenotyping and biomarker identification. Sleep 2022; 46:6701543. [PMID: 36107467 PMCID: PMC9832519 DOI: 10.1093/sleep/zsac223] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [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: 07/28/2022] [Revised: 08/30/2022] [Indexed: 01/19/2023] Open
Abstract
Transient oscillatory events in the sleep electroencephalogram represent short-term coordinated network activity. Of particular importance, sleep spindles are transient oscillatory events associated with memory consolidation, which are altered in aging and in several psychiatric and neurodegenerative disorders. Spindle identification, however, currently contains implicit assumptions derived from what waveforms were historically easiest to discern by eye, and has recently been shown to select only a high-amplitude subset of transient events. Moreover, spindle activity is typically averaged across a sleep stage, collapsing continuous dynamics into discrete states. What information can be gained by expanding our view of transient oscillatory events and their dynamics? In this paper, we develop a novel approach to electroencephalographic phenotyping, characterizing a generalized class of transient time-frequency events across a wide frequency range using continuous dynamics. We demonstrate that the complex temporal evolution of transient events during sleep is highly stereotyped when viewed as a function of slow oscillation power (an objective, continuous metric of depth-of-sleep) and phase (a correlate of cortical up/down states). This two-fold power-phase representation has large intersubject variability-even within healthy controls-yet strong night-to-night stability for individuals, suggesting a robust basis for phenotyping. As a clinical application, we then analyze patients with schizophrenia, confirming established spindle (12-15 Hz) deficits as well as identifying novel differences in transient non-rapid eye movement events in low-alpha (7-10 Hz) and theta (4-6 Hz) ranges. Overall, these results offer an expanded view of transient activity, describing a broad class of events with properties varying continuously across spatial, temporal, and phase-coupling dimensions.
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Affiliation(s)
- Patrick A Stokes
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
| | - Preetish Rath
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA,Department of Computer Science, Tufts University, Medford, MA, USA
| | - Thomas Possidente
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
| | - Mingjian He
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA,Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA,Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Shaun Purcell
- Department of Psychiatry, Brigham and Women’s Hospital, Boston, MA, USA
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Robert Stickgold
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Michael J Prerau
- Corresponding author. Michael J. Prerau, Brigham and Women's Hospital, Division of Sleep and Circadian Disorders, 221 Longwood Avenue, Boston, MA, 02115, USA.
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11
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Fu JM, Satterstrom FK, Peng M, Brand H, Collins RL, Dong S, Wamsley B, Klei L, Wang L, Hao SP, Stevens CR, Cusick C, Babadi M, Banks E, Collins B, Dodge S, Gabriel SB, Gauthier L, Lee SK, Liang L, Ljungdahl A, Mahjani B, Sloofman L, Smirnov AN, Barbosa M, Betancur C, Brusco A, Chung BHY, Cook EH, Cuccaro ML, Domenici E, Ferrero GB, Gargus JJ, Herman GE, Hertz-Picciotto I, Maciel P, Manoach DS, Passos-Bueno MR, Persico AM, Renieri A, Sutcliffe JS, Tassone F, Trabetti E, Campos G, Cardaropoli S, Carli D, Chan MCY, Fallerini C, Giorgio E, Girardi AC, Hansen-Kiss E, Lee SL, Lintas C, Ludena Y, Nguyen R, Pavinato L, Pericak-Vance M, Pessah IN, Schmidt RJ, Smith M, Costa CIS, Trajkova S, Wang JYT, Yu MHC, Cutler DJ, De Rubeis S, Buxbaum JD, Daly MJ, Devlin B, Roeder K, Sanders SJ, Talkowski ME. Rare coding variation provides insight into the genetic architecture and phenotypic context of autism. Nat Genet 2022; 54:1320-1331. [PMID: 35982160 PMCID: PMC9653013 DOI: 10.1038/s41588-022-01104-0] [Citation(s) in RCA: 137] [Impact Index Per Article: 68.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 05/24/2022] [Indexed: 01/11/2023]
Abstract
Some individuals with autism spectrum disorder (ASD) carry functional mutations rarely observed in the general population. We explored the genes disrupted by these variants from joint analysis of protein-truncating variants (PTVs), missense variants and copy number variants (CNVs) in a cohort of 63,237 individuals. We discovered 72 genes associated with ASD at false discovery rate (FDR) ≤ 0.001 (185 at FDR ≤ 0.05). De novo PTVs, damaging missense variants and CNVs represented 57.5%, 21.1% and 8.44% of association evidence, while CNVs conferred greatest relative risk. Meta-analysis with cohorts ascertained for developmental delay (DD) (n = 91,605) yielded 373 genes associated with ASD/DD at FDR ≤ 0.001 (664 at FDR ≤ 0.05), some of which differed in relative frequency of mutation between ASD and DD cohorts. The DD-associated genes were enriched in transcriptomes of progenitor and immature neuronal cells, whereas genes showing stronger evidence in ASD were more enriched in maturing neurons and overlapped with schizophrenia-associated genes, emphasizing that these neuropsychiatric disorders may share common pathways to risk.
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Affiliation(s)
- Jack M Fu
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - F Kyle Satterstrom
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Minshi Peng
- Department of Statistics and Data Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Harrison Brand
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Pediatric Surgical Research Laboratories, Department of Surgery, Massachusetts General Hospital, Boston, MA, USA
| | - Ryan L Collins
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Program in Bioinformatics and Integrative Genomics, Harvard Medical School, Boston, MA, USA
| | - Shan Dong
- Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Brie Wamsley
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Lambertus Klei
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Lily Wang
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Bioinformatics and Integrative Genomics, Harvard Medical School, Boston, MA, USA
| | - Stephanie P Hao
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Pediatric Surgical Research Laboratories, Department of Surgery, Massachusetts General Hospital, Boston, MA, USA
| | - Christine R Stevens
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Caroline Cusick
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Mehrtash Babadi
- Data Sciences Platform, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Eric Banks
- Data Sciences Platform, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Brett Collins
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sheila Dodge
- Genomics Platform, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Stacey B Gabriel
- Genomics Platform, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Laura Gauthier
- Data Sciences Platform, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Samuel K Lee
- Data Sciences Platform, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Lindsay Liang
- Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Alicia Ljungdahl
- Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Behrang Mahjani
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Laura Sloofman
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Andrey N Smirnov
- Data Sciences Platform, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Mafalda Barbosa
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Catalina Betancur
- Sorbonne Université, INSERM, CNRS, Neuroscience Paris Seine, Institut de Biologie Paris Seine, Paris, France
| | - Alfredo Brusco
- Department of Medical Sciences, University of Torino, Turin, Italy
- Medical Genetics Unit, 'Città della Salute e della Scienza' University Hospital, Turin, Italy
| | - Brian H Y Chung
- Department of Pediatrics and Adolescent Medicine, Duchess of Kent Children's Hospital, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Edwin H Cook
- Institute for Juvenile Research, Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA
| | - Michael L Cuccaro
- The John P Hussman Institute for Human Genomics, The University of Miami Miller School of Medicine, Miami, FL, USA
| | - Enrico Domenici
- Department of Cellular, Computational and Integrative Biology, , University of Trento, Trento, Italy
| | | | - J Jay Gargus
- Center for Autism Research and Translation, University of California Irvine, Irvine, CA, USA
| | - Gail E Herman
- The Research Institute at Nationwide Children's Hospital, Columbus, OH, USA
| | - Irva Hertz-Picciotto
- MIND (Medical Investigation of Neurodevelopmental Disorders) Institute, University of California Davis, Davis, CA, USA
| | - Patricia Maciel
- Life and Health Sciences Research Institute, School of Medicine, University of Minho, Braga, Portugal
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Maria Rita Passos-Bueno
- Centro de Pesquisas sobre o Genoma Humano e Células tronco, Instituto de Biociências, Universidade de São Paulo, São Paulo, Brazil
| | - Antonio M Persico
- Interdepartmental Program 'Autism 0-90', 'Gaetano Martino' University Hospital, University of Messina, Messina, Italy
| | - Alessandra Renieri
- Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Siena, Italy
- Medical Genetics, , University of Siena, Siena, Italy
- Genetica Medica, Azienda Ospedaliera Universitaria Senese, Siena, Italy
| | - James S Sutcliffe
- Department of Molecular Physiology & Biophysics and Psychiatry, Vanderbilt University School of Medicine, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Flora Tassone
- MIND (Medical Investigation of Neurodevelopmental Disorders) Institute, University of California Davis, Davis, CA, USA
- Department of Biochemistry and Molecular Medicine, University of California Davis, School of Medicine, Sacramento, CA, USA
| | - Elisabetta Trabetti
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Biology and Genetics, University of Verona, Verona, Italy
| | - Gabriele Campos
- Centro de Pesquisas sobre o Genoma Humano e Células tronco, Instituto de Biociências, Universidade de São Paulo, São Paulo, Brazil
| | - Simona Cardaropoli
- Department of Public Health and Pediatrics, University of Torino, Turin, Italy
| | - Diana Carli
- Department of Public Health and Pediatrics, University of Torino, Turin, Italy
| | - Marcus C Y Chan
- Department of Pediatrics and Adolescent Medicine, Duchess of Kent Children's Hospital, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Chiara Fallerini
- Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Siena, Italy
- Medical Genetics, , University of Siena, Siena, Italy
| | - Elisa Giorgio
- Department of Medical Sciences, University of Torino, Turin, Italy
| | - Ana Cristina Girardi
- Centro de Pesquisas sobre o Genoma Humano e Células tronco, Instituto de Biociências, Universidade de São Paulo, São Paulo, Brazil
| | - Emily Hansen-Kiss
- Department of Diagnostic and Biomedical Sciences, University of Texas Health Science Center at Houston, School of Dentistry, Houston, TX, USA
| | - So Lun Lee
- Department of Pediatrics and Adolescent Medicine, Duchess of Kent Children's Hospital, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Carla Lintas
- Service for Neurodevelopmental Disorders, University Campus Bio-medico of Rome, Rome, Italy
| | - Yunin Ludena
- MIND (Medical Investigation of Neurodevelopmental Disorders) Institute, University of California Davis, Davis, CA, USA
| | - Rachel Nguyen
- Center for Autism Research and Translation, University of California Irvine, Irvine, CA, USA
| | - Lisa Pavinato
- Department of Medical Sciences, University of Torino, Turin, Italy
| | - Margaret Pericak-Vance
- The John P Hussman Institute for Human Genomics, The University of Miami Miller School of Medicine, Miami, FL, USA
| | - Isaac N Pessah
- MIND (Medical Investigation of Neurodevelopmental Disorders) Institute, University of California Davis, Davis, CA, USA
- Department of Molecular Biosciences, University of California Davis, School of Veterinary Medicine, Davis, CA, USA
| | - Rebecca J Schmidt
- MIND (Medical Investigation of Neurodevelopmental Disorders) Institute, University of California Davis, Davis, CA, USA
| | - Moyra Smith
- Center for Autism Research and Translation, University of California Irvine, Irvine, CA, USA
| | - Claudia I S Costa
- Centro de Pesquisas sobre o Genoma Humano e Células tronco, Instituto de Biociências, Universidade de São Paulo, São Paulo, Brazil
| | - Slavica Trajkova
- Department of Medical Sciences, University of Torino, Turin, Italy
| | - Jaqueline Y T Wang
- Centro de Pesquisas sobre o Genoma Humano e Células tronco, Instituto de Biociências, Universidade de São Paulo, São Paulo, Brazil
| | - Mullin H C Yu
- Department of Pediatrics and Adolescent Medicine, Duchess of Kent Children's Hospital, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - David J Cutler
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Silvia De Rubeis
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Joseph D Buxbaum
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Mark J Daly
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
| | - Bernie Devlin
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
| | - Kathryn Roeder
- Department of Statistics and Data Science, Carnegie Mellon University, Pittsburgh, PA, USA.
- Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA, USA.
| | - Stephan J Sanders
- Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA.
| | - Michael E Talkowski
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Program in Bioinformatics and Integrative Genomics, Harvard Medical School, Boston, MA, USA.
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12
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Fang A, Baran B, Beatty CC, Mosley J, Feusner JD, Phan KL, Wilhelm S, Manoach DS. Maladaptive self-focused attention and default mode network connectivity: a transdiagnostic investigation across social anxiety and body dysmorphic disorders. Soc Cogn Affect Neurosci 2022; 17:645-654. [PMID: 34875086 PMCID: PMC9250304 DOI: 10.1093/scan/nsab130] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [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: 06/16/2021] [Revised: 11/12/2021] [Accepted: 12/06/2021] [Indexed: 11/13/2022] Open
Abstract
Maladaptive self-focused attention (SFA) is a bias toward internal thoughts, feelings and physical states. Despite its role as a core maintaining factor of symptoms in cognitive theories of social anxiety and body dysmorphic disorders (BDDs), studies have not examined its neural basis. In this study, we hypothesized that maladaptive SFA would be associated with hyperconnectivity in the default mode network (DMN) in self-focused patients with these disorders. Thirty patients with primary social anxiety disorder or primary BDD and 28 healthy individuals were eligible and scanned. Eligibility was determined by scoring greater than 1SD or below 1SD of the Public Self-Consciousness Scale normative mean, respectively, for each group. Seed-to-voxel functional connectivity was computed using a DMN posterior cingulate cortex (PCC) seed. There was no evidence of increased DMN functional connectivity in patients compared to controls. Patients (regardless of diagnosis) showed reduced functional connectivity of the PCC with several brain regions, including the bilateral superior parietal lobule (SPL), compared to controls, which was inversely correlated with maladaptive SFA but not associated with social anxiety, body dysmorphic, depression severity or rumination. Abnormal PCC-SPL connectivity may represent a transdiagnostic neural marker of SFA that reflects difficulty shifting between internal versus external attention.
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Affiliation(s)
- Angela Fang
- Department of Psychology, University of Washington, Seattle, WA 98195-1525, USA
| | - Bengi Baran
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA 52242-1407, USA
| | - Clare C Beatty
- Department of Psychology, Stony Brook University, Stony Brook, NY 11794-2500, USA
| | - Jennifer Mosley
- Department of Psychology, University of Washington, Seattle, WA 98195-1525, USA
| | - Jamie D Feusner
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095-8346, USA.,Centre for Addiction and Mental Health, Toronto, Ontario M5T 1R8, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario M5T 1R8, Canada
| | - K Luan Phan
- Department of Psychiatry and Behavioral Health, Ohio State University Wexner Medical Center, Columbus, OH 43210-1240, USA
| | - Sabine Wilhelm
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114-2696, USA
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114-2696, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129-2020, USA
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13
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Mylonas D, Sjøgård M, Shi Z, Baxter B, Hämäläinen M, Manoach DS, Khan S. A Novel Approach to Estimating the Cortical Sources of Sleep Spindles Using Simultaneous EEG/MEG. Front Neurol 2022; 13:871166. [PMID: 35785365 PMCID: PMC9243385 DOI: 10.3389/fneur.2022.871166] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 05/18/2022] [Indexed: 11/15/2022] Open
Abstract
Sleep spindles, defining oscillations of stage II non-rapid eye movement sleep (N2), mediate sleep-dependent memory consolidation. Spindles are disrupted in several neurodevelopmental, neuropsychiatric, and neurodegenerative disorders characterized by cognitive impairment. Increasing spindles can improve memory suggesting spindles as a promising physiological target for the development of cognitive enhancing therapies. This effort would benefit from more comprehensive and spatially precise methods to characterize spindles. Spindles, as detected with electroencephalography (EEG), are often widespread across electrodes. Available evidence, however, suggests that they act locally to enhance cortical plasticity in the service of memory consolidation. Here, we present a novel method to enhance the spatial specificity of cortical source estimates of spindles using combined EEG and magnetoencephalography (MEG) data constrained to the cortex based on structural MRI. To illustrate this method, we used simultaneous EEG and MEG recordings from 25 healthy adults during a daytime nap. We first validated source space spindle detection using only EEG data by demonstrating strong temporal correspondence with sensor space EEG spindle detection (gold standard). We then demonstrated that spindle source estimates using EEG alone, MEG alone and combined EEG/MEG are stable across nap sessions. EEG detected more source space spindles than MEG and each modality detected non-overlapping spindles that had distinct cortical source distributions. Source space EEG was more sensitive to spindles in medial frontal and lateral prefrontal cortex, while MEG was more sensitive to spindles in somatosensory and motor cortices. By combining EEG and MEG data this method leverages the differential spatial sensitivities of the two modalities to obtain a more comprehensive and spatially specific source estimation of spindles than possible with either modality alone.
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Affiliation(s)
- Dimitrios Mylonas
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
- *Correspondence: Dimitrios Mylonas
| | - Martin Sjøgård
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
| | - Zhaoyue Shi
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
- Carle Illinois Advanced Imaging Center, Carle Foundation Hospital, Urbana, IL, United States
| | - Bryan Baxter
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
| | - Matti Hämäläinen
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Dara S. Manoach
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
| | - Sheraz Khan
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
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14
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Heller Murray ES, Segawa J, Karahanoglu FI, Tocci C, Tourville JA, Nieto-Castanon A, Tager-Flusberg H, Manoach DS, Guenther FH. Increased Intra-Subject Variability of Neural Activity During Speech Production in People with Autism Spectrum Disorder. Res Autism Spectr Disord 2022; 94:101955. [PMID: 35601992 PMCID: PMC9119427 DOI: 10.1016/j.rasd.2022.101955] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Background Communication difficulties are a core deficit in many people with autism spectrum disorder (ASD). The current study evaluated neural activation in participants with ASD and neurotypical (NT) controls during a speech production task. Methods Neural activities of participants with ASD (N = 15, M = 16.7 years, language abilities ranged from low verbal abilities to verbally fluent) and NT controls (N = 12, M = 17.1 years) was examined using functional magnetic resonance imaging with a sparse-sampling paradigm. Results There were no differences between the ASD and NT groups in average speech activation or inter-subject run-to-run variability in speech activation. Intra-subject run-to-run neural variability was greater in the ASD group and was positively correlated with autism severity in cortical areas associated with speech. Conclusions These findings highlight the importance of understanding intra-subject neural variability in participants with ASD.
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Affiliation(s)
- Elizabeth S. Heller Murray
- Boston University, Department of Speech, Language, & Hearing Sciences, 635 Commonwealth Avenue, Boston, MA, 02215
| | - Jennifer Segawa
- Boston University, Department of Speech, Language, & Hearing Sciences, 635 Commonwealth Avenue, Boston, MA, 02215
| | - F. Isik Karahanoglu
- Massachusetts General Hospital, Department of Psychiatry, Harvard Medical School, 55 Fruit Street, Boston, MA, 02215
| | - Catherine Tocci
- Massachusetts General Hospital, Department of Psychiatry, Harvard Medical School, 55 Fruit Street, Boston, MA, 02215
| | - Jason A. Tourville
- Boston University, Department of Speech, Language, & Hearing Sciences, 635 Commonwealth Avenue, Boston, MA, 02215
| | - Alfonso Nieto-Castanon
- Boston University, Department of Speech, Language, & Hearing Sciences, 635 Commonwealth Avenue, Boston, MA, 02215
| | - Helen Tager-Flusberg
- Boston University, Department of Psychological and Brain Sciences, 64 Cummington Mall Boston, MA, 02115
| | - Dara S. Manoach
- Massachusetts General Hospital, Department of Psychiatry, Harvard Medical School, 55 Fruit Street, Boston, MA, 02215
- Athinoula A. Martinos Center for Biomedical Imaging, 149 13th Street, Room 2618, Charlestown, MA 02129
| | - Frank H. Guenther
- Boston University, Department of Speech, Language, & Hearing Sciences, 635 Commonwealth Avenue, Boston, MA, 02215
- Boston University, Department of Biomedical Engineering, 44 Cummington Mall Boston, MA, 02115
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15
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Mylonas D, Machado S, Larson O, Patel R, Cox R, Vangel M, Maski K, Stickgold R, Manoach DS. Dyscoordination of non-rapid eye movement sleep oscillations in autism spectrum disorder. Sleep 2022; 45:6505127. [DOI: 10.1093/sleep/zsac010] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 12/13/2021] [Indexed: 11/14/2022] Open
Abstract
Abstract
Study Objectives
Converging evidence from neuroimaging, sleep, and genetic studies suggest that dysregulation of thalamocortical interactions mediated by the thalamic reticular nucleus (TRN) contribute to autism spectrum disorder (ASD). Sleep spindles assay TRN function, and their coordination with cortical slow oscillations (SOs) indexes thalamocortical communication. These oscillations mediate memory consolidation during sleep. In the present study, we comprehensively characterized spindles and their coordination with SOs in relation to memory and age in children with ASD.
Methods
Nineteen children and adolescents with ASD, without intellectual disability, and 18 typically developing (TD) peers, aged 9–17, completed a home polysomnography study with testing on a spatial memory task before and after sleep. Spindles, SOs, and their coordination were characterized during stages 2 (N2) and 3 (N3) non-rapid eye movement sleep.
Results
ASD participants showed disrupted SO-spindle coordination during N2 sleep. Spindles peaked later in SO upstates and their timing was less consistent. They also showed a spindle density (#/min) deficit during N3 sleep. Both groups showed significant sleep-dependent memory consolidation, but their relations with spindle density differed. While TD participants showed the expected positive correlations, ASD participants showed the opposite.
Conclusions
The disrupted SO-spindle coordination and spindle deficit provide further evidence of abnormal thalamocortical interactions and TRN dysfunction in ASD. The inverse relations of spindle density with memory suggest a different function for spindles in ASD than TD. We propose that abnormal sleep oscillations reflect genetically mediated disruptions of TRN-dependent thalamocortical circuit development that contribute to the manifestations of ASD and are potentially treatable.
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Affiliation(s)
- Dimitrios Mylonas
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Sasha Machado
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Olivia Larson
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychology, University of Pennsylvania, Philadelphia, PA,USA
| | - Rudra Patel
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Roy Cox
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, Amsterdam,The Netherlands
| | - Mark Vangel
- Department of Biostatistics, Massachusetts General Hospital, Harvard Medical School, Boston, MA,USA
| | - Kiran Maski
- Department of Neurology, Boston Children’s Hospital, Boston, MA, USA
| | - Robert Stickgold
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
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16
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Spencer ER, Chinappen D, Emerton BC, Morgan AK, Hämäläinen MS, Manoach DS, Eden UT, Kramer MA, Chu CJ. Source EEG reveals that Rolandic epilepsy is a regional epileptic encephalopathy. Neuroimage Clin 2022; 33:102956. [PMID: 35151039 PMCID: PMC8844714 DOI: 10.1016/j.nicl.2022.102956] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [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: 10/15/2021] [Revised: 01/10/2022] [Accepted: 02/03/2022] [Indexed: 01/15/2023]
Abstract
Children with RE have fewer spindles but they have typical time–frequency features. Spindle deficits extend to multiple cortical regions in Rolandic epilepsy. Cognitive deficits are predicted by spindle rate in Rolandic epilepsy. Regional spindle rate predicts motor deficits better than Rolandic spindle deficit. Spindle features in RE identify a regional thalamocortical epileptic encephalopathy.
Rolandic epilepsy is the most common form of epileptic encephalopathy, characterized by sleep-potentiated inferior Rolandic epileptiform spikes, seizures, and cognitive deficits in school-age children that spontaneously resolve by adolescence. We recently identified a paucity of sleep spindles, physiological thalamocortical rhythms associated with sleep-dependent learning, in the Rolandic cortex during the active phase of this disease. Because spindles are generated in the thalamus and amplified through regional thalamocortical circuits, we hypothesized that: 1) deficits in spindle rate would involve but extend beyond the inferior Rolandic cortex in active epilepsy and 2) regional spindle deficits would better predict cognitive function than inferior Rolandic spindle deficits alone. To test these hypotheses, we obtained high-resolution MRI, high-density EEG recordings, and focused neuropsychological assessments in children with Rolandic epilepsy during active (n = 8, age 9–14.7 years, 3F) and resolved (seizure free for > 1 year, n = 10, age 10.3–16.7 years, 1F) stages of disease and age-matched controls (n = 8, age 8.9–14.5 years, 5F). Using a validated spindle detector applied to estimates of electrical source activity in 31 cortical regions, including the inferior Rolandic cortex, during stages 2 and 3 of non-rapid eye movement sleep, we compared spindle rates in each cortical region across groups. Among detected spindles, we compared spindle features (power, duration, coherence, bilateral synchrony) between groups. We then used regression models to examine the relationship between spindle rate and cognitive function (fine motor dexterity, phonological processing, attention, and intelligence, and a global measure of all functions). We found that spindle rate was reduced in the inferior Rolandic cortices in active but not resolved disease (active P = 0.007; resolved P = 0.2) compared to controls. Spindles in this region were less synchronous between hemispheres in the active group (P = 0.005; resolved P = 0.1) compared to controls; but there were no differences in spindle power, duration, or coherence between groups. Compared to controls, spindle rate in the active group was also reduced in the prefrontal, insular, superior temporal, and posterior parietal regions (i.e., “regional spindle rate”, P < 0.039 for all). Independent of group, regional spindle rate positively correlated with fine motor dexterity (P < 1e-3), attention (P = 0.02), intelligence (P = 0.04), and global cognitive performance (P < 1e-4). Compared to the inferior Rolandic spindle rate alone, models including regional spindle rate trended to improve prediction of global cognitive performance (P = 0.052), and markedly improved prediction of fine motor dexterity (P = 0.006). These results identify a spindle disruption in Rolandic epilepsy that extends beyond the epileptic cortex and a potential mechanistic explanation for the broad cognitive deficits that can be observed in this epileptic encephalopathy.
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Affiliation(s)
- Elizabeth R Spencer
- Graduate Program in Neuroscience, Boston University, Boston, MA 02215; Department of Neurology, Massachusetts General Hospital, Boston, MA 02114
| | - Dhinakaran Chinappen
- Graduate Program in Neuroscience, Boston University, Boston, MA 02215; Department of Neurology, Massachusetts General Hospital, Boston, MA 02114
| | - Britt C Emerton
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114
| | - Amy K Morgan
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114
| | - Matti S Hämäläinen
- Harvard Medical School, Boston, MA 02115; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA 02129; Massachusetts General Hospital, Department of Radiology, Boston, MA 02114
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114; Harvard Medical School, Boston, MA 02115; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA 02129
| | - Uri T Eden
- Department of Mathematics and Statistics, Boston University, Boston, MA 02215; Center for Systems Neuroscience, Boston University, Boston, MA 02215
| | - Mark A Kramer
- Department of Mathematics and Statistics, Boston University, Boston, MA 02215; Center for Systems Neuroscience, Boston University, Boston, MA 02215
| | - Catherine J Chu
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02114; Department of Psychiatry, Massachusetts General Hospital, Boston, MA 02114.
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17
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Becker LA, Penagos H, Flores FJ, Manoach DS, Wilson MA, Varela C. Eszopiclone and Zolpidem Produce Opposite Effects on Hippocampal Ripple Density. Front Pharmacol 2022; 12:792148. [PMID: 35087405 PMCID: PMC8787044 DOI: 10.3389/fphar.2021.792148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [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: 10/09/2021] [Accepted: 12/13/2021] [Indexed: 12/03/2022] Open
Abstract
Clinical populations have memory deficits linked to sleep oscillations that can potentially be treated with sleep medications. Eszopiclone and zolpidem (two non-benzodiazepine hypnotics) both enhance sleep spindles. Zolpidem improved sleep-dependent memory consolidation in humans, but eszopiclone did not. These divergent results may reflect that the two drugs have different effects on hippocampal ripple oscillations, which correspond to the reactivation of neuronal ensembles that represent previous waking activity and contribute to memory consolidation. We used extracellular recordings in the CA1 region of rats and systemic dosing of eszopiclone and zolpidem to test the hypothesis that these two drugs differentially affect hippocampal ripples and spike activity. We report evidence that eszopiclone makes ripples sparser, while zolpidem increases ripple density. In addition, eszopiclone led to a drastic decrease in spike firing, both in putative pyramidal cells and interneurons, while zolpidem did not substantially alter spiking. These results provide an explanation of the different effects of eszopiclone and zolpidem on memory in human studies and suggest that sleep medications can be used to regulate hippocampal ripple oscillations, which are causally linked to sleep-dependent memory consolidation.
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Affiliation(s)
- Logan A Becker
- Department of Neuroscience and Behavior, Stony Brook University, Stony Brook, NY, United States.,Department of Neuroscience, University of Texas at Austin, Austin, TX, United States.,Psychology Department, Florida Atlantic University, Boca Raton, FL, United States
| | - Hector Penagos
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, United States.,Center for Brains Minds and Machines, Massachusetts Institute of Technology, Boston, MA, United States
| | - Francisco J Flores
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, United States.,Center for Brains Minds and Machines, Massachusetts Institute of Technology, Boston, MA, United States.,Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
| | - Matthew A Wilson
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, United States.,Center for Brains Minds and Machines, Massachusetts Institute of Technology, Boston, MA, United States
| | - Carmen Varela
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, United States.,Center for Brains Minds and Machines, Massachusetts Institute of Technology, Boston, MA, United States.,Psychology Department, Florida Atlantic University, Boca Raton, FL, United States
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18
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Lai M, Hegde R, Kelly S, Bannai D, Lizano P, Stickgold R, Manoach DS, Keshavan M. Investigating sleep spindle density and schizophrenia: A meta-analysis. Psychiatry Res 2022; 307:114265. [PMID: 34922240 DOI: 10.1016/j.psychres.2021.114265] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 10/25/2021] [Accepted: 10/31/2021] [Indexed: 11/26/2022]
Abstract
Sleep abnormalities are an early feature of schizophrenia (SZ) characterized by reductions in sleep spindles that are associated with deficits in brain connectivity and cognitive function. This study investigated sleep spindle density (SSD) differences between SZ, first episode psychosis (FEP), and family high-risk (FHR) populations and matched healthy controls (HC) by investigating recent studies via a meta-analysis. We collected experimental, demographic, and methodological metrics from eligible studies across multiple online databases. 14 total studies survived the inclusion and exclusion criteria for a total of 337 patients and relatives and 339 HC. R-Studio was used to run the meta-analysis via the meta and metaphor packages. A heterogeneity score of I2 = 80% was calculated and thus a random effects model was chosen. We report a large effect size for SSD in patients compared to controls. Furthermore, illness duration was significantly associated with SSD. Our next step to understanding sleep spindles would be to investigate SSD's use as a predictor for SZ or attempt to normalize SSD deficits as a therapeutic option.
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Affiliation(s)
- Matthew Lai
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Massachusetts Mental Health Center, Boston, MA, United States
| | - Rachal Hegde
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Massachusetts Mental Health Center, Boston, MA, United States
| | - Sinead Kelly
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Massachusetts Mental Health Center, Boston, MA, United States; Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Department of Psychiatry, Brigham and Women's Hospital, Boston, MA, United States
| | - Deepthi Bannai
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Massachusetts Mental Health Center, Boston, MA, United States
| | - Paulo Lizano
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Massachusetts Mental Health Center, Boston, MA, United States; Department of Psychiatry, Harvard Medical School, Boston, MA, United States
| | - Robert Stickgold
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Massachusetts Mental Health Center, Boston, MA, United States; Department of Psychiatry, Harvard Medical School, Boston, MA, United States
| | - Dara S Manoach
- Department of Psychiatry, Harvard Medical School, Boston, MA, United States; Department of Psychiatry, Massachusetts General Hospital, Boston, MA, United States
| | - Matcheri Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Massachusetts Mental Health Center, Boston, MA, United States; Department of Psychiatry, Harvard Medical School, Boston, MA, United States.
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19
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Stoyell SM, Baxter BS, McLaren J, Kwon H, Chinappen DM, Ostrowski L, Zhu L, Grieco JA, Kramer MA, Morgan AK, Emerton BC, Manoach DS, Chu CJ. Diazepam induced sleep spindle increase correlates with cognitive recovery in a child with epileptic encephalopathy. BMC Neurol 2021; 21:355. [PMID: 34521381 PMCID: PMC8438890 DOI: 10.1186/s12883-021-02376-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2021] [Accepted: 08/31/2021] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND Continuous spike and wave of sleep with encephalopathy (CSWS) is a rare and severe developmental electroclinical epileptic encephalopathy characterized by seizures, abundant sleep activated interictal epileptiform discharges, and cognitive regression or deceleration of expected cognitive growth. The cause of the cognitive symptoms is unknown, and efforts to link epileptiform activity to cognitive function have been unrevealing. Converging lines of evidence implicate thalamocortical circuits in these disorders. Sleep spindles are generated and propagated by the same thalamocortical circuits that can generate spikes and, in healthy sleep, support memory consolidation. As such, sleep spindle deficits may provide a physiologically relevant mechanistic biomarker for cognitive dysfunction in epileptic encephalopathies. CASE PRESENTATION We describe the longitudinal course of a child with CSWS with initial cognitive regression followed by dramatic cognitive improvement after treatment. Using validated automated detection algorithms, we analyzed electroencephalograms for epileptiform discharges and sleep spindles alongside contemporaneous neuropsychological evaluations over the course of the patient's disease. We found that sleep spindles increased dramatically with high-dose diazepam treatment, corresponding with marked improvements in cognitive performance. We also found that the sleep spindle rate was anticorrelated to spike rate, consistent with a competitively shared underlying thalamocortical circuitry. CONCLUSIONS Epileptic encephalopathies are challenging electroclinical syndromes characterized by combined seizures and a deceleration or regression in cognitive skills over childhood. This report identifies thalamocortical circuit dysfunction in a case of epileptic encephalopathy and motivates future investigations of sleep spindles as a biomarker of cognitive function and a potential therapeutic target in this challenging disease.
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Affiliation(s)
- S M Stoyell
- Department of Neurology, Massachusetts General Hospital, 175 Cambridge St, Suite 340, Boston, MA, 02114, USA
| | - B S Baxter
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, 02114, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - J McLaren
- Department of Neurology, Massachusetts General Hospital, 175 Cambridge St, Suite 340, Boston, MA, 02114, USA
| | - H Kwon
- Department of Neurology, Massachusetts General Hospital, 175 Cambridge St, Suite 340, Boston, MA, 02114, USA
| | - D M Chinappen
- Department of Neurology, Massachusetts General Hospital, 175 Cambridge St, Suite 340, Boston, MA, 02114, USA
| | - L Ostrowski
- Department of Neurology, Massachusetts General Hospital, 175 Cambridge St, Suite 340, Boston, MA, 02114, USA
| | - L Zhu
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - J A Grieco
- Massachusetts General Hospital, Psychology Assessment Center, Boston, MA, 02114, USA
| | - M A Kramer
- Department of Mathematics and Statistics, Boston University, Boston, MA, 02115, USA
| | - A K Morgan
- Massachusetts General Hospital, Psychology Assessment Center, Boston, MA, 02114, USA
| | - B C Emerton
- Massachusetts General Hospital, Psychology Assessment Center, Boston, MA, 02114, USA
| | - D S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, 02114, USA
- Harvard Medical School, Boston, MA, 02115, USA
| | - C J Chu
- Department of Neurology, Massachusetts General Hospital, 175 Cambridge St, Suite 340, Boston, MA, 02114, USA.
- Harvard Medical School, Boston, MA, 02115, USA.
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20
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Chamadia S, Hobbs L, Marota S, Ibala R, Hahm E, Gitlin J, Mekonnen J, Ethridge B, Colon KM, Sheppard KS, Manoach DS, DiBiasio A, Nguyen S, Pedemonte JC, Akeju O. Oral Dexmedetomidine Promotes Non-rapid Eye Movement Stage 2 Sleep in Humans. Anesthesiology 2020; 133:1234-1243. [PMID: 33001139 DOI: 10.1097/aln.0000000000003567] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
BACKGROUND The administration of dexmedetomidine is limited to highly monitored care settings because it is only available for use in humans as intravenous medication. An oral formulation of dexmedetomidine may broaden its use to all care settings. The authors investigated the effect of a capsule-based solid oral dosage formulation of dexmedetomidine on sleep polysomnography. METHODS The authors performed a single-site, placebo-controlled, randomized, crossover, double-blind phase II study of a solid oral dosage formulation of dexmedetomidine (700 mcg; n = 15). The primary outcome was polysomnography sleep quality. Secondary outcomes included performance on the motor sequence task and psychomotor vigilance task administered to each subject at night and in the morning to assess motor memory consolidation and psychomotor function, respectively. Sleep questionnaires were also administered. RESULTS Oral dexmedetomidine increased the duration of non-rapid eye movement (non-REM) stage 2 sleep by 63 (95% CI, 19 to 107) min (P = 0.010) and decreased the duration of rapid eye movement (REM) sleep by 42 (5 to 78) min (P = 0.031). Overnight motor sequence task performance improved after placebo sleep (7.9%; P = 0.003) but not after oral dexmedetomidine-induced sleep (-0.8%; P = 0.900). In exploratory analyses, we found a positive correlation between spindle density during non-REM stage 2 sleep and improvement in the overnight test performance (Spearman rho = 0.57; P = 0.028; n = 15) for placebo but not oral dexmedetomidine (Spearman rho = 0.04; P = 0.899; n = 15). Group differences in overnight motor sequence task performance, psychomotor vigilance task metrics, and sleep questionnaires did not meet the threshold for statistical significance. CONCLUSIONS These results demonstrate that the nighttime administration of a solid oral dosage formulation of dexmedetomidine is associated with increased non-REM 2 sleep and decreased REM sleep. Spindle density during dexmedetomidine sleep was not associated with overnight improvement in the motor sequence task. EDITOR’S PERSPECTIVE
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21
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Abstract
Although schizophrenia is defined by waking phenomena, a growing literature documents a deficit in sleep spindles, a defining oscillation of stage 2 non-rapid eye movement sleep. Compelling evidence supports an important role for spindles in cognition, and particularly memory. In schizophrenia, although the spindle deficit correlates with impaired sleep-dependent memory consolidation, recent clinical trials find that increasing spindles does not improve memory. This may reflect that sleep-dependent memory consolidation relies not on spindles alone, but also on their precise temporal coordination with cortical slow oscillations and hippocampal sharp-wave ripples. Consequently, interventions to improve memory in schizophrenia must not only increase spindles, but also preserve or enhance slow oscillations, hippocampal ripples and their temporal relations. Because hippocampal ripples and the activity of the thalamic spindle generator are difficult to measure noninvasively, screening potential interventions requires complementary animal and human studies. In this review we (i) propose that sleep oscillations are novel pathophysiological targets for therapy to improve cognition in schizophrenia; (ii) summarize our understanding of how these oscillations interact to consolidate memory; (iii) suggest that a systems neuroscience strategy is essential to selecting and evaluating effective treatments, and illustrate this with findings from clinical trials; and (iv) selectively review the interventional literature relevant to sleep and cognition, covering both pharmacological and noninvasive brain stimulation approaches. We conclude that coordinated sleep oscillations are promising targets for improving cognition in schizophrenia and that effective therapies will need to preserve or enhance sleep oscillatory dynamics and restore function at the network level.
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Affiliation(s)
- Dara S Manoach
- Department of Psychiatry Massachusetts General Hospital, Harvard Medical School, Boston, MA 02215, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA.
| | - Dimitrios Mylonas
- Department of Psychiatry Massachusetts General Hospital, Harvard Medical School, Boston, MA 02215, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Bryan Baxter
- Department of Psychiatry Massachusetts General Hospital, Harvard Medical School, Boston, MA 02215, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
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22
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Mylonas D, Tocci C, Coon WG, Baran B, Kohnke EJ, Zhu L, Vangel MG, Stickgold R, Manoach DS. Naps reliably estimate nocturnal sleep spindle density in health and schizophrenia. J Sleep Res 2019; 29:e12968. [PMID: 31860157 DOI: 10.1111/jsr.12968] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2019] [Revised: 11/21/2019] [Accepted: 11/23/2019] [Indexed: 01/10/2023]
Abstract
Sleep spindles, defining oscillations of non-rapid eye movement stage 2 sleep (N2), mediate memory consolidation. Spindle density (spindles/minute) is a stable, heritable feature of the sleep electroencephalogram. In schizophrenia, reduced spindle density correlates with impaired sleep-dependent memory consolidation and is a promising treatment target. Measuring sleep spindles is also important for basic studies of memory. However, overnight sleep studies are expensive, time consuming and require considerable infrastructure. Here we investigated whether afternoon naps can reliably and accurately estimate nocturnal spindle density in health and schizophrenia. Fourteen schizophrenia patients and eight healthy controls had polysomnography during two overnights and three afternoon naps. Although spindle density was lower during naps than nights, the two measures were highly correlated. For both groups, naps and nights provided highly reliable estimates of spindle density. We conclude that naps provide an accurate, reliable and more scalable alternative to measuring spindle density overnight.
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Affiliation(s)
- Dimitrios Mylonas
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Catherine Tocci
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA, USA
| | - William G Coon
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Bengi Baran
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Erin J Kohnke
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA, USA
| | - Lin Zhu
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA, USA
| | - Mark G Vangel
- Department of Radiology, Massachussets General Hospital, Charlestown, MA, USA.,Department of Biostatistics, Harvard Medical School, Boston, MA, USA
| | - Robert Stickgold
- Harvard Medical School, Boston, MA, USA.,Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA.,Harvard Medical School, Boston, MA, USA
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23
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Cox R, Mylonas DS, Manoach DS, Stickgold R. Large-scale structure and individual fingerprints of locally coupled sleep oscillations. Sleep 2019; 41:5089926. [PMID: 30184179 DOI: 10.1093/sleep/zsy175] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2018] [Indexed: 11/14/2022] Open
Abstract
Slow oscillations and sleep spindles, the canonical electrophysiological oscillations of nonrapid eye movement sleep, are thought to gate incoming sensory information, underlie processes of sleep-dependent memory consolidation, and are altered in various neuropsychiatric disorders. Accumulating evidence of the predominantly local expression of these individual oscillatory rhythms suggests that their cross-frequency interactions may have a similar local component. However, it is unclear whether locally coordinated sleep oscillations exist across the cortex, and whether and how these dynamics differ between fast and slow spindles, and sleep stages. Moreover, substantial individual variability in the expression of both spindles and slow oscillations raises the possibility that their temporal organization shows similar individual differences. Using two nights of multichannel electroencephalography recordings from 24 healthy individuals, we characterized the topography of slow oscillation-spindle coupling. We found that while slow oscillations are highly restricted in spatial extent, the phase of the local slow oscillation modulates local spindle activity at virtually every cortical site. However, coupling dynamics varied with spindle class, sleep stage, and cortical region. Moreover, the slow oscillation phase at which spindles were maximally expressed differed markedly across individuals while remaining stable across nights. These findings both add an important spatial aspect to our understanding of the temporal coupling of sleep oscillations and demonstrate the heterogeneity of coupling dynamics, which must be taken into account when formulating mechanistic accounts of sleep-related memory processing.
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Affiliation(s)
- Roy Cox
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA.,Department of Psychiatry, Harvard Medical School, Boston, MA.,Department of Epileptology, University of Bonn, Germany
| | - Dimitris S Mylonas
- Department of Psychiatry, Harvard Medical School, Boston, MA.,Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA
| | - Dara S Manoach
- Department of Psychiatry, Harvard Medical School, Boston, MA.,Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA
| | - Robert Stickgold
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA.,Department of Psychiatry, Harvard Medical School, Boston, MA
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24
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Shinn AK, Yuksel C, Masters G, Pfaff D, Wamsley E, Djonlagic I, Öngür D, Manoach DS, Stickgold R. Procedural memory consolidation after a night of sleep in bipolar disorder with psychotic features. Schizophr Res 2019; 210:299-300. [PMID: 30611654 PMCID: PMC6688974 DOI: 10.1016/j.schres.2018.12.044] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2018] [Revised: 12/22/2018] [Accepted: 12/25/2018] [Indexed: 11/28/2022]
Affiliation(s)
- Ann K. Shinn
- Psychotic Disorders Division, McLean Hospital, Belmont, MA,Harvard Medical School, Boston, MA
| | - Cagri Yuksel
- Psychotic Disorders Division, McLean Hospital, Belmont, MA, United States of America; Harvard Medical School, Boston, MA, United States of America.
| | - Grace Masters
- Psychotic Disorders Division, McLean Hospital, Belmont, MA
| | - Danielle Pfaff
- Psychotic Disorders Division, McLean Hospital, Belmont, MA
| | - Erin Wamsley
- Department of Psychology, Furman University, Greenville, SC
| | - Ina Djonlagic
- Harvard Medical School, Boston, MA,Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA
| | - Dost Öngür
- Psychotic Disorders Division, McLean Hospital, Belmont, MA,Harvard Medical School, Boston, MA
| | - Dara S. Manoach
- Harvard Medical School, Boston, MA,Department of Psychiatry, Massachusetts General Hospital, Boston, MA,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA
| | - Robert Stickgold
- Harvard Medical School, Boston, MA,Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA
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25
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Schapiro AC, Reid AG, Morgan A, Manoach DS, Verfaellie M, Stickgold R. The hippocampus is necessary for the consolidation of a task that does not require the hippocampus for initial learning. Hippocampus 2019; 29:1091-1100. [PMID: 31157946 DOI: 10.1002/hipo.23101] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Revised: 04/02/2019] [Accepted: 04/29/2019] [Indexed: 11/09/2022]
Abstract
During sleep, the hippocampus plays an active role in consolidating memories that depend on it for initial encoding. There are hints in the literature that the hippocampus may have a broader influence, contributing to the consolidation of memories that may not initially require the area. We tested this possibility by evaluating learning and consolidation of the motor sequence task (MST) in hippocampal amnesics and demographically matched control participants. While the groups showed similar initial learning, only controls exhibited evidence of overnight consolidation. These results demonstrate that the hippocampus can be required for normal consolidation of a task without being required for its acquisition, suggesting that the area plays a broader role in coordinating memory consolidation than has previously been assumed.
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Affiliation(s)
- Anna C Schapiro
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts.,Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Allison G Reid
- Memory Disorders Research Center, VA Boston Healthcare System, Boston, Massachusetts
| | - Alexandra Morgan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, Massachusetts
| | - Dara S Manoach
- Harvard Medical School, Boston, Massachusetts.,Department of Psychiatry, Massachusetts General Hospital, Charlestown, Massachusetts.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts
| | - Mieke Verfaellie
- Memory Disorders Research Center, VA Boston Healthcare System, Boston, Massachusetts.,Department of Psychiatry, Boston University School of Medicine, Boston, Massachusetts
| | - Robert Stickgold
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, Massachusetts.,Harvard Medical School, Boston, Massachusetts
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26
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Baran B, Karahanoglu FI, Mylonas D, Denis D, Keshavan M, Stickgold R, Manoach DS. 0065 Sleep and Wake Biomarkers of Psychotic Disorders and Their Relations with Thalamocortical Connectivity. Sleep 2019. [DOI: 10.1093/sleep/zsz067.064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
| | | | | | - Dan Denis
- Harvard Medical School, Boston, MA, USA
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27
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Mylonas D, Demanuele C, Baran B, Cox R, Stickgold R, Manoach DS. 0915 The Effects of Eszopiclone on Spindles, Slow Oscillations and their Coordination in Health and Schizophrenia. Sleep 2019. [DOI: 10.1093/sleep/zsz067.913] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Dimitris Mylonas
- Harvard Medical School, Boston, MA, Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA, USA
| | - Charmaine Demanuele
- Harvard Medical School, Boston, MA, Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA, USA
| | - Bengi Baran
- Harvard Medical School, Boston, MA, Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA, USA
| | - Roy Cox
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Robert Stickgold
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Dara S Manoach
- Harvard Medical School, Boston, MA, Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA, USA
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28
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Abstract
There is overwhelming evidence that sleep is crucial for memory consolidation. Patients with schizophrenia and their unaffected relatives have a specific deficit in sleep spindles, a defining oscillation of non-rapid eye movement (NREM) Stage 2 sleep that, in coordination with other NREM oscillations, mediate memory consolidation. In schizophrenia, the spindle deficit correlates with impaired sleep-dependent memory consolidation, positive symptoms, and abnormal thalamocortical connectivity. These relations point to dysfunction of the thalamic reticular nucleus (TRN), which generates spindles, gates the relay of sensory information to the cortex, and modulates thalamocortical communication. Genetic studies are beginning to provide clues to possible neurodevelopmental origins of TRN-mediated thalamocortical circuit dysfunction and to identify novel targets for treating the related memory deficits and symptoms. By forging empirical links in causal chains from risk genes to thalamocortical circuit dysfunction, spindle deficits, memory impairment, symptoms, and diagnosis, future research can advance our mechanistic understanding, treatment, and prevention of schizophrenia.
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Affiliation(s)
- Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114, USA; .,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts 02129, USA
| | - Robert Stickgold
- Department of Psychiatry, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts 02215;
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29
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Baran B, Correll D, Vuper TC, Morgan A, Durrant SJ, Manoach DS, Stickgold R. Spared and impaired sleep-dependent memory consolidation in schizophrenia. Schizophr Res 2018; 199:83-89. [PMID: 29706447 PMCID: PMC6151291 DOI: 10.1016/j.schres.2018.04.019] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2017] [Revised: 02/03/2018] [Accepted: 04/11/2018] [Indexed: 10/17/2022]
Abstract
OBJECTIVE Cognitive deficits in schizophrenia are the strongest predictor of disability and effective treatment is lacking. This reflects our limited mechanistic understanding and consequent lack of treatment targets. In schizophrenia, impaired sleep-dependent memory consolidation correlates with reduced sleep spindle activity, suggesting sleep spindles as a potentially treatable mechanism. In the present study we investigated whether sleep-dependent memory consolidation deficits in schizophrenia are selective. METHODS Schizophrenia patients and healthy individuals performed three tasks that have been shown to undergo sleep-dependent consolidation: the Word Pair Task (verbal declarative memory), the Visual Discrimination Task (visuoperceptual procedural memory), and the Tone Task (statistical learning). Memory consolidation was tested 24 h later, after a night of sleep. RESULTS Compared with controls, schizophrenia patients showed reduced overnight consolidation of word pair learning. In contrast, both groups showed similar significant overnight consolidation of visuoperceptual procedural memory. Neither group showed overnight consolidation of statistical learning. CONCLUSION The present findings extend the known deficits in sleep-dependent memory consolidation in schizophrenia to verbal declarative memory, a core, disabling cognitive deficit. In contrast, visuoperceptual procedural memory was spared. These findings support the hypothesis that sleep-dependent memory consolidation deficits in schizophrenia are selective, possibly limited to tasks that rely on spindles. These findings reinforce the importance of deficient sleep-dependent memory consolidation among the cognitive deficits of schizophrenia and suggest sleep physiology as a potentially treatable mechanism.
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Affiliation(s)
- Bengi Baran
- Harvard Medical School, Boston, MA, USA; Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA.
| | - David Correll
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Tessa C. Vuper
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Alexandra Morgan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Simon J. Durrant
- School of Psychology, University of Lincoln, Lincoln, UK,School of Psychological Sciences, University of Manchester, Brunswick Street, Manchester, UK
| | - Dara S. Manoach
- Harvard Medical School, Boston, MA,Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Robert Stickgold
- Harvard Medical School, Boston, MA,Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
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30
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Karahanoğlu FI, Baran B, Nguyen QTH, Meskaldji DE, Yendiki A, Vangel M, Santangelo SL, Manoach DS. Diffusion-weighted imaging evidence of altered white matter development from late childhood to early adulthood in Autism Spectrum Disorder. Neuroimage Clin 2018; 19:840-847. [PMID: 29946509 PMCID: PMC6008282 DOI: 10.1016/j.nicl.2018.06.002] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2017] [Revised: 05/18/2018] [Accepted: 06/03/2018] [Indexed: 12/01/2022]
Abstract
Autism Spectrum Disorder (ASD) is thought to reflect disrupted development of brain connectivity characterized by white matter abnormalities and dyscoordination of activity across brain regions that give rise to core features. But there is little consensus about the nature, timing and location of white matter abnormalities as quantified with diffusion-weighted MRI. Inconsistent findings likely reflect small sample sizes, motion confounds and sample heterogeneity, particularly different age ranges across studies. We examined the microstructural integrity of major white matter tracts in relation to age in 38 high functioning ASD and 35 typically developing (TD) participants, aged 8-25, whose diffusion-weighted scans met strict data-quality criteria and survived group matching for motion. While there were no overall group differences in diffusion measures, the groups showed different relations with age. Only the TD group showed the expected positive correlations of fractional anisotropy with age. In parallel, axial diffusivity was unrelated to age in TD, but showed inverse correlations with age in ASD. Younger participants with ASD tended to have higher fractional anisotropy and axial diffusivity than their TD peers, while the opposite was true for older participants. Most of the affected tracts - cingulum bundle, inferior and superior longitudinal fasciculi - are association bundles related to cognitive, social and emotional functions that are abnormal in ASD. The manifestations of abnormal white matter development in ASD as measured by diffusion-weighted MRI depend on age and this may contribute to inconsistent findings across studies. We conclude that ASD is characterized by altered white matter development from childhood to early adulthood that may underlie abnormal brain function and contribute to core features.
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Affiliation(s)
- Fikret Işık Karahanoğlu
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States.
| | - Bengi Baran
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
| | - Quynh Trang Huong Nguyen
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
| | - Djalel-Eddine Meskaldji
- Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Anastasia Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States; Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Mark Vangel
- Department of Biostatistics, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Susan L Santangelo
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Maine Medical Center Research Institute, Scarborough, ME, United States; Tufts University School of Medicine, Department of Psychiatry, Boston, MA, United States
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
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31
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Agcaoglu O, Miller R, Damaraju E, Rashid B, Bustillo J, Cetin MS, Van Erp TGM, McEwen S, Preda A, Ford JM, Lim KO, Manoach DS, Mathalon DH, Potkin SG, Calhoun VD. Decreased hemispheric connectivity and decreased intra- and inter- hemisphere asymmetry of resting state functional network connectivity in schizophrenia. Brain Imaging Behav 2018; 12:615-630. [PMID: 28434159 PMCID: PMC5651208 DOI: 10.1007/s11682-017-9718-7] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Many studies have shown that schizophrenia patients have aberrant functional network connectivity (FNC) among brain regions, suggesting schizophrenia manifests with significantly diminished (in majority of the cases) connectivity. Schizophrenia is also associated with a lack of hemispheric lateralization. Hoptman et al. (2012) reported lower inter-hemispheric connectivity in schizophrenia patients compared to controls using voxel-mirrored homotopic connectivity. In this study, we merge these two points of views together using a group independent component analysis (gICA)-based approach to generate hemisphere-specific timecourses and calculate intra-hemisphere and inter-hemisphere FNC on a resting state fMRI dataset consisting of age- and gender-balanced 151 schizophrenia patients and 163 healthy controls. We analyzed the group differences between patients and healthy controls in each type of FNC measures along with age and gender effects. The results reveal that FNC in schizophrenia patients shows less hemispheric asymmetry compared to that of the healthy controls. We also found a decrease in connectivity in all FNC types such as intra-left (L_FNC), intra-right (R_FNC) and inter-hemisphere (Inter_FNC) in the schizophrenia patients relative to healthy controls, but general patterns of connectivity were preserved in patients. Analyses of age and gender effects yielded results similar to those reported in whole brain FNC studies.
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Affiliation(s)
- O Agcaoglu
- Mind Research Network, 1001 Yale Blvd. NE, Albuquerque, NM, 87106, USA.
- Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USA.
| | - R Miller
- Mind Research Network, 1001 Yale Blvd. NE, Albuquerque, NM, 87106, USA
| | - E Damaraju
- Mind Research Network, 1001 Yale Blvd. NE, Albuquerque, NM, 87106, USA
- Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USA
| | - B Rashid
- Mind Research Network, 1001 Yale Blvd. NE, Albuquerque, NM, 87106, USA
- Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USA
| | - J Bustillo
- Department of Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, NM, USA
| | - M S Cetin
- Mind Research Network, 1001 Yale Blvd. NE, Albuquerque, NM, 87106, USA
- Computer Science Department, University of New Mexico, Albuquerque, NM, USA
| | - T G M Van Erp
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - S McEwen
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
| | - A Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - J M Ford
- Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA
- San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA
| | - K O Lim
- Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA
| | - D S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - D H Mathalon
- Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA
| | - S G Potkin
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
| | - V D Calhoun
- Mind Research Network, 1001 Yale Blvd. NE, Albuquerque, NM, 87106, USA
- Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USA
- Department of Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, NM, USA
- Computer Science Department, University of New Mexico, Albuquerque, NM, USA
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32
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Blokland GAM, del Re EC, Mesholam-Gately RI, Jovicich J, Trampush JW, Keshavan MS, DeLisi LE, Walters JTR, Turner JA, Malhotra AK, Lencz T, Shenton ME, Voineskos AN, Rujescu D, Giegling I, Kahn RS, Roffman JL, Holt DJ, Ehrlich S, Kikinis Z, Dazzan P, Murray RM, Di Forti M, Lee J, Sim K, Lam M, Wolthusen RPF, de Zwarte SMC, Walton E, Cosgrove D, Kelly S, Maleki N, Osiecki L, Picchioni MM, Bramon E, Russo M, David AS, Mondelli V, Reinders AATS, Falcone MA, Hartmann AM, Konte B, Morris DW, Gill M, Corvin AP, Cahn W, Ho NF, Liu JJ, Keefe RSE, Gollub RL, Manoach DS, Calhoun VD, Schulz SC, Sponheim SR, Goff DC, Buka SL, Cherkerzian S, Thermenos HW, Kubicki M, Nestor PG, Dickie EW, Vassos E, Ciufolini S, Marques TR, Crossley NA, Purcell SM, Smoller JW, van Haren NEM, Toulopoulou T, Donohoe G, Goldstein JM, Seidman LJ, McCarley RW, Petryshen TL. The Genetics of Endophenotypes of Neurofunction to Understand Schizophrenia (GENUS) consortium: A collaborative cognitive and neuroimaging genetics project. Schizophr Res 2018; 195:306-317. [PMID: 28982554 PMCID: PMC5882601 DOI: 10.1016/j.schres.2017.09.024] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2017] [Revised: 09/15/2017] [Accepted: 09/20/2017] [Indexed: 01/02/2023]
Abstract
BACKGROUND Schizophrenia has a large genetic component, and the pathways from genes to illness manifestation are beginning to be identified. The Genetics of Endophenotypes of Neurofunction to Understand Schizophrenia (GENUS) Consortium aims to clarify the role of genetic variation in brain abnormalities underlying schizophrenia. This article describes the GENUS Consortium sample collection. METHODS We identified existing samples collected for schizophrenia studies consisting of patients, controls, and/or individuals at familial high-risk (FHR) for schizophrenia. Samples had single nucleotide polymorphism (SNP) array data or genomic DNA, clinical and demographic data, and neuropsychological and/or brain magnetic resonance imaging (MRI) data. Data were subjected to quality control procedures at a central site. RESULTS Sixteen research groups contributed data from 5199 psychosis patients, 4877 controls, and 725 FHR individuals. All participants have relevant demographic data and all patients have relevant clinical data. The sex ratio is 56.5% male and 43.5% female. Significant differences exist between diagnostic groups for premorbid and current IQ (both p<1×10-10). Data from a diversity of neuropsychological tests are available for 92% of participants, and 30% have structural MRI scans (half also have diffusion-weighted MRI scans). SNP data are available for 76% of participants. The ancestry composition is 70% European, 20% East Asian, 7% African, and 3% other. CONCLUSIONS The Consortium is investigating the genetic contribution to brain phenotypes in a schizophrenia sample collection of >10,000 participants. The breadth of data across clinical, genetic, neuropsychological, and MRI modalities provides an important opportunity for elucidating the genetic basis of neural processes underlying schizophrenia.
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Affiliation(s)
- Gabriëlla A. M. Blokland
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic
Medicine, Massachusetts General Hospital, Boston, MA, United States,Department of Psychiatry, Massachusetts General Hospital, Boston,
MA, United States,Department of Psychiatry, Harvard Medical School, Boston, MA, United
States,Stanley Center for Psychiatric Research, Broad Institute of MIT and
Harvard, Cambridge, MA, United States
| | - Elisabetta C. del Re
- Department of Psychiatry, Harvard Medical School, Boston, MA, United
States,Department of Psychiatry, Veterans Affairs Boston Healthcare System,
Brockton, MA, United States,Psychiatry Neuroimaging Laboratory, Department of Psychiatry,
Brigham and Women’s Hospital, Boston, MA, United States
| | - Raquelle I. Mesholam-Gately
- Department of Psychiatry, Harvard Medical School, Boston, MA, United
States,Massachusetts Mental Health Center Public Psychiatry Division, Beth
Israel Deaconess Medical Center, Boston, MA, United States
| | - Jorge Jovicich
- Center for Mind/Brain Sciences (CiMEC), University of Trento,
Trento, Italy
| | - Joey W. Trampush
- Center for Psychiatric Neuroscience, The Feinstein Institute for
Medical Research, Division of Northwell Health, Manhasset, NY, United States;
Division of Psychiatry Research, The Zucker Hillside Hospital, Division of Northwell
Health, Glen Oaks, NY, United States; Hofstra Northwell School of Medicine,
Departments of Psychiatry and Molecular Medicine, Hempstead, NY, United States,BrainWorkup, LLC, Los Angeles, CA, United States
| | - Matcheri S. Keshavan
- Department of Psychiatry, Harvard Medical School, Boston, MA, United
States,Massachusetts Mental Health Center Public Psychiatry Division, Beth
Israel Deaconess Medical Center, Boston, MA, United States,University of Pittsburgh Medical Center, Pittsburgh, PA, United
States
| | - Lynn E. DeLisi
- Department of Psychiatry, Harvard Medical School, Boston, MA, United
States,Department of Psychiatry, Veterans Affairs Boston Healthcare System,
Brockton, MA, United States
| | - James T. R. Walters
- Department of Psychological Medicine, Cardiff University, Cardiff,
United Kingdom
| | - Jessica A. Turner
- The Mind Research Network, Albuquerque, NM, United States,Department of Psychology and Neuroscience Institute, Georgia State
University, GA, United States
| | - Anil K. Malhotra
- Center for Psychiatric Neuroscience, The Feinstein Institute for
Medical Research, Division of Northwell Health, Manhasset, NY, United States;
Division of Psychiatry Research, The Zucker Hillside Hospital, Division of Northwell
Health, Glen Oaks, NY, United States; Hofstra Northwell School of Medicine,
Departments of Psychiatry and Molecular Medicine, Hempstead, NY, United States
| | - Todd Lencz
- Center for Psychiatric Neuroscience, The Feinstein Institute for
Medical Research, Division of Northwell Health, Manhasset, NY, United States;
Division of Psychiatry Research, The Zucker Hillside Hospital, Division of Northwell
Health, Glen Oaks, NY, United States; Hofstra Northwell School of Medicine,
Departments of Psychiatry and Molecular Medicine, Hempstead, NY, United States
| | - Martha E. Shenton
- Department of Psychiatry, Harvard Medical School, Boston, MA, United
States,Department of Psychiatry, Veterans Affairs Boston Healthcare System,
Brockton, MA, United States,Psychiatry Neuroimaging Laboratory, Department of Psychiatry,
Brigham and Women’s Hospital, Boston, MA, United States,Department of Radiology, Brigham and Women’s Hospital,
Harvard Medical School, Boston, MA, United States
| | - Aristotle N. Voineskos
- Kimel Family Translational Imaging Genetics Laboratory, Research
Imaging Centre, Campbell Family Mental Health Institute, Centre for Addiction and
Mental Health, Department of Psychiatry, Faculty of Medicine, University of Toronto,
Toronto, ON, Canada,Department of Psychiatry and Institute of Medical Science,
University of Toronto, Toronto, ON, Canada
| | - Dan Rujescu
- Department of Psychiatry, Psychotherapy and Psychosomatics,
University of Halle-Wittenberg, Halle an der Saale, Germany,Department of Psychiatry, Ludwig Maximilians University, Munich,
Germany
| | - Ina Giegling
- Department of Psychiatry, Psychotherapy and Psychosomatics,
University of Halle-Wittenberg, Halle an der Saale, Germany
| | - René S. Kahn
- Brain Centre Rudolf Magnus, Department of Psychiatry, University
Medical Centre Utrecht, Utrecht, The Netherlands
| | - Joshua L. Roffman
- Department of Psychiatry, Massachusetts General Hospital, Boston,
MA, United States,Department of Psychiatry, Harvard Medical School, Boston, MA, United
States,MGH/HST Athinoula A. Martinos Center for Biomedical Imaging,
Massachusetts General Hospital, Charlestown, MA, United States
| | - Daphne J. Holt
- Department of Psychiatry, Massachusetts General Hospital, Boston,
MA, United States,Department of Psychiatry, Harvard Medical School, Boston, MA, United
States,MGH/HST Athinoula A. Martinos Center for Biomedical Imaging,
Massachusetts General Hospital, Charlestown, MA, United States
| | - Stefan Ehrlich
- Department of Psychiatry, Harvard Medical School, Boston, MA, United
States,MGH/HST Athinoula A. Martinos Center for Biomedical Imaging,
Massachusetts General Hospital, Charlestown, MA, United States,Division of Psychological & Social Medicine and Developmental
Neurosciences, Faculty of Medicine, Technische Universität Dresden, Dresden,
Germany
| | - Zora Kikinis
- Department of Psychiatry, Harvard Medical School, Boston, MA, United
States,Psychiatry Neuroimaging Laboratory, Department of Psychiatry,
Brigham and Women’s Hospital, Boston, MA, United States
| | - Paola Dazzan
- Institute of Psychiatry, Psychology, and Neuroscience,
King’s College London, London, United Kingdom,National Institute for Health Research (NIHR) Mental Health
Biomedical Research Centre at South London and Maudsley NHS Foundation Trust,
London, United Kingdom
| | - Robin M. Murray
- Institute of Psychiatry, Psychology, and Neuroscience,
King’s College London, London, United Kingdom,National Institute for Health Research (NIHR) Mental Health
Biomedical Research Centre at South London and Maudsley NHS Foundation Trust,
London, United Kingdom
| | - Marta Di Forti
- Institute of Psychiatry, Psychology, and Neuroscience,
King’s College London, London, United Kingdom,National Institute for Health Research (NIHR) Mental Health
Biomedical Research Centre at South London and Maudsley NHS Foundation Trust,
London, United Kingdom
| | - Jimmy Lee
- Institute of Mental Health, Woodbridge Hospital, Singapore
| | - Kang Sim
- Institute of Mental Health, Woodbridge Hospital, Singapore
| | - Max Lam
- Institute of Mental Health, Woodbridge Hospital, Singapore
| | - Rick P. F. Wolthusen
- Department of Psychiatry, Harvard Medical School, Boston, MA, United
States,MGH/HST Athinoula A. Martinos Center for Biomedical Imaging,
Massachusetts General Hospital, Charlestown, MA, United States,Division of Psychological & Social Medicine and Developmental
Neurosciences, Faculty of Medicine, Technische Universität Dresden, Dresden,
Germany
| | - Sonja M. C. de Zwarte
- Brain Centre Rudolf Magnus, Department of Psychiatry, University
Medical Centre Utrecht, Utrecht, The Netherlands
| | - Esther Walton
- Division of Psychological & Social Medicine and Developmental
Neurosciences, Faculty of Medicine, Technische Universität Dresden, Dresden,
Germany
| | - Donna Cosgrove
- The Cognitive Genetics and Cognitive Therapy Group, Department of
Psychology, National University of Ireland, Galway, Ireland
| | - Sinead Kelly
- Neuropsychiatric Genetics Research Group, Department of Psychiatry,
Institute of Molecular Medicine, Trinity College Dublin, Dublin, Ireland; Trinity
College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland,Laboratory of NeuroImaging, Keck School of Medicine, University of
Southern California, Los Angeles, CA, United States
| | - Nasim Maleki
- Department of Psychiatry, Massachusetts General Hospital, Boston,
MA, United States,Department of Psychiatry, Harvard Medical School, Boston, MA, United
States,MGH/HST Athinoula A. Martinos Center for Biomedical Imaging,
Massachusetts General Hospital, Charlestown, MA, United States
| | - Lisa Osiecki
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic
Medicine, Massachusetts General Hospital, Boston, MA, United States
| | - Marco M. Picchioni
- Institute of Psychiatry, Psychology, and Neuroscience,
King’s College London, London, United Kingdom,National Institute for Health Research (NIHR) Mental Health
Biomedical Research Centre at South London and Maudsley NHS Foundation Trust,
London, United Kingdom
| | - Elvira Bramon
- Institute of Psychiatry, Psychology, and Neuroscience,
King’s College London, London, United Kingdom,National Institute for Health Research (NIHR) Mental Health
Biomedical Research Centre at South London and Maudsley NHS Foundation Trust,
London, United Kingdom,Mental Health Neuroscience Research Department, UCL Division of
Psychiatry, University College London, United Kingdom
| | - Manuela Russo
- Institute of Psychiatry, Psychology, and Neuroscience,
King’s College London, London, United Kingdom,National Institute for Health Research (NIHR) Mental Health
Biomedical Research Centre at South London and Maudsley NHS Foundation Trust,
London, United Kingdom
| | - Anthony S. David
- Institute of Psychiatry, Psychology, and Neuroscience,
King’s College London, London, United Kingdom,National Institute for Health Research (NIHR) Mental Health
Biomedical Research Centre at South London and Maudsley NHS Foundation Trust,
London, United Kingdom
| | - Valeria Mondelli
- Institute of Psychiatry, Psychology, and Neuroscience,
King’s College London, London, United Kingdom,National Institute for Health Research (NIHR) Mental Health
Biomedical Research Centre at South London and Maudsley NHS Foundation Trust,
London, United Kingdom
| | - Antje A. T. S. Reinders
- Institute of Psychiatry, Psychology, and Neuroscience,
King’s College London, London, United Kingdom,National Institute for Health Research (NIHR) Mental Health
Biomedical Research Centre at South London and Maudsley NHS Foundation Trust,
London, United Kingdom
| | - M. Aurora Falcone
- Institute of Psychiatry, Psychology, and Neuroscience,
King’s College London, London, United Kingdom,National Institute for Health Research (NIHR) Mental Health
Biomedical Research Centre at South London and Maudsley NHS Foundation Trust,
London, United Kingdom
| | - Annette M. Hartmann
- Department of Psychiatry, Psychotherapy and Psychosomatics,
University of Halle-Wittenberg, Halle an der Saale, Germany
| | - Bettina Konte
- Department of Psychiatry, Psychotherapy and Psychosomatics,
University of Halle-Wittenberg, Halle an der Saale, Germany
| | - Derek W. Morris
- Cognitive Genetics and Cognitive Therapy Group, Neuroimaging and
Cognitive Genomics (NICOG) Centre and NCBES Galway Neuroscience Centre, School of
Psychology and Discipline of Biochemistry, National University of Ireland, Galway,
Ireland
| | - Michael Gill
- Neuropsychiatric Genetics Research Group, Department of Psychiatry,
Institute of Molecular Medicine, Trinity College Dublin, Dublin, Ireland; Trinity
College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Aiden P. Corvin
- Neuropsychiatric Genetics Research Group, Department of Psychiatry,
Institute of Molecular Medicine, Trinity College Dublin, Dublin, Ireland; Trinity
College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Wiepke Cahn
- Brain Centre Rudolf Magnus, Department of Psychiatry, University
Medical Centre Utrecht, Utrecht, The Netherlands
| | - New Fei Ho
- Institute of Mental Health, Woodbridge Hospital, Singapore
| | | | - Richard S. E. Keefe
- Department of Psychiatry and Behavioral Sciences, Duke University
Medical Center, Durham, NC, United States
| | - Randy L. Gollub
- Department of Psychiatry, Massachusetts General Hospital, Boston,
MA, United States,Department of Psychiatry, Harvard Medical School, Boston, MA, United
States,MGH/HST Athinoula A. Martinos Center for Biomedical Imaging,
Massachusetts General Hospital, Charlestown, MA, United States
| | - Dara S. Manoach
- Department of Psychiatry, Massachusetts General Hospital, Boston,
MA, United States,Department of Psychiatry, Harvard Medical School, Boston, MA, United
States,MGH/HST Athinoula A. Martinos Center for Biomedical Imaging,
Massachusetts General Hospital, Charlestown, MA, United States
| | - Vince D. Calhoun
- The Mind Research Network, Albuquerque, NM, United States,Department of Electrical and Computer Engineering, University of
New Mexico, Albuquerque, NM, United States
| | - S. Charles Schulz
- Department of Psychiatry, University of Minnesota, Minneapolis, MN,
United States
| | - Scott R. Sponheim
- Department of Psychiatry, University of Minnesota, Minneapolis, MN,
United States
| | - Donald C. Goff
- Department of Psychiatry, Harvard Medical School, Boston, MA, United
States,Nathan S. Kline Institute for Psychiatric Research, Department of
Psychiatry, New York University Langone Medical Center, New York, NY, United
States
| | - Stephen L. Buka
- Department of Epidemiology, Brown University, Providence, RI,
United States
| | - Sara Cherkerzian
- Department of Medicine, Division of Women’s Health, Brigham
and Women’s Hospital, Harvard Medical School, Boston, MA, United
States
| | - Heidi W. Thermenos
- Department of Psychiatry, Massachusetts General Hospital, Boston,
MA, United States,Department of Psychiatry, Harvard Medical School, Boston, MA, United
States,Massachusetts Mental Health Center Public Psychiatry Division, Beth
Israel Deaconess Medical Center, Boston, MA, United States
| | - Marek Kubicki
- Department of Psychiatry, Harvard Medical School, Boston, MA, United
States,Psychiatry Neuroimaging Laboratory, Department of Psychiatry,
Brigham and Women’s Hospital, Boston, MA, United States,Department of Radiology, Brigham and Women’s Hospital,
Harvard Medical School, Boston, MA, United States,MGH/HST Athinoula A. Martinos Center for Biomedical Imaging,
Massachusetts General Hospital, Charlestown, MA, United States
| | - Paul G. Nestor
- Department of Psychiatry, Harvard Medical School, Boston, MA, United
States,Department of Psychiatry, Veterans Affairs Boston Healthcare System,
Brockton, MA, United States,Laboratory of Applied Neuropsychology, University of Massachusetts,
Boston, MA, United States
| | - Erin W. Dickie
- Kimel Family Translational Imaging Genetics Laboratory, Research
Imaging Centre, Campbell Family Mental Health Institute, Centre for Addiction and
Mental Health, Department of Psychiatry, Faculty of Medicine, University of Toronto,
Toronto, ON, Canada
| | - Evangelos Vassos
- Institute of Psychiatry, Psychology, and Neuroscience,
King’s College London, London, United Kingdom,National Institute for Health Research (NIHR) Mental Health
Biomedical Research Centre at South London and Maudsley NHS Foundation Trust,
London, United Kingdom
| | - Simone Ciufolini
- Institute of Psychiatry, Psychology, and Neuroscience,
King’s College London, London, United Kingdom,National Institute for Health Research (NIHR) Mental Health
Biomedical Research Centre at South London and Maudsley NHS Foundation Trust,
London, United Kingdom
| | - Tiago Reis Marques
- Institute of Psychiatry, Psychology, and Neuroscience,
King’s College London, London, United Kingdom,National Institute for Health Research (NIHR) Mental Health
Biomedical Research Centre at South London and Maudsley NHS Foundation Trust,
London, United Kingdom
| | - Nicolas A. Crossley
- Institute of Psychiatry, Psychology, and Neuroscience,
King’s College London, London, United Kingdom,National Institute for Health Research (NIHR) Mental Health
Biomedical Research Centre at South London and Maudsley NHS Foundation Trust,
London, United Kingdom
| | - Shaun M. Purcell
- Department of Psychiatry, Harvard Medical School, Boston, MA, United
States,Stanley Center for Psychiatric Research, Broad Institute of MIT and
Harvard, Cambridge, MA, United States,Department of Psychiatry, Brigham and Women’s Hospital,
Boston, MA, United States,Division of Psychiatric Genomics, Departments of Psychiatry and
Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York,
NY, United States
| | - Jordan W. Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic
Medicine, Massachusetts General Hospital, Boston, MA, United States,Department of Psychiatry, Massachusetts General Hospital, Boston,
MA, United States,Department of Psychiatry, Harvard Medical School, Boston, MA, United
States,Stanley Center for Psychiatric Research, Broad Institute of MIT and
Harvard, Cambridge, MA, United States
| | - Neeltje E. M. van Haren
- Brain Centre Rudolf Magnus, Department of Psychiatry, University
Medical Centre Utrecht, Utrecht, The Netherlands
| | - Timothea Toulopoulou
- Institute of Psychiatry, Psychology, and Neuroscience,
King’s College London, London, United Kingdom,Department of Psychology, Bilkent University, Bilkent, Ankara,
Turkey,Department of Psychology, The University of Hong Kong, Pokfulam,
Hong Kong, SAR, China
| | - Gary Donohoe
- Neuropsychiatric Genetics Research Group, Department of Psychiatry,
Institute of Molecular Medicine, Trinity College Dublin, Dublin, Ireland; Trinity
College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland,Cognitive Genetics and Cognitive Therapy Group, Neuroimaging and
Cognitive Genomics (NICOG) Centre and NCBES Galway Neuroscience Centre, School of
Psychology and Discipline of Biochemistry, National University of Ireland, Galway,
Ireland
| | - Jill M. Goldstein
- Department of Psychiatry, Massachusetts General Hospital, Boston,
MA, United States,Department of Psychiatry, Harvard Medical School, Boston, MA, United
States,Department of Medicine, Division of Women’s Health, Brigham
and Women’s Hospital, Harvard Medical School, Boston, MA, United
States,Department of Psychiatry, Brigham and Women’s Hospital,
Boston, MA, United States
| | - Larry J. Seidman
- Department of Psychiatry, Massachusetts General Hospital, Boston,
MA, United States,Department of Psychiatry, Harvard Medical School, Boston, MA, United
States,Massachusetts Mental Health Center Public Psychiatry Division, Beth
Israel Deaconess Medical Center, Boston, MA, United States
| | - Robert W. McCarley
- Department of Psychiatry, Harvard Medical School, Boston, MA, United
States,Department of Psychiatry, Veterans Affairs Boston Healthcare System,
Brockton, MA, United States
| | - Tracey L. Petryshen
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic
Medicine, Massachusetts General Hospital, Boston, MA, United States,Department of Psychiatry, Massachusetts General Hospital, Boston,
MA, United States,Department of Psychiatry, Harvard Medical School, Boston, MA, United
States,Stanley Center for Psychiatric Research, Broad Institute of MIT and
Harvard, Cambridge, MA, United States
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Stokes PA, Rath P, Manoach DS, Stickgold R, Prerau MJ. 0999 Characterizing Clinical Population Differences in Transient Oscillation Features in the Sleep EEG. Sleep 2018. [DOI: 10.1093/sleep/zsy061.998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- P A Stokes
- Massachusetts General Hospital, Charlestown, MA
| | - P Rath
- Massachusetts General Hospital, Charlestown, MA
| | - D S Manoach
- Massachusetts General Hospital, Charlestown, MA
| | - R Stickgold
- Beth Israel Deaconess Medical Center, Boston, MA
| | - M J Prerau
- Massachusetts General Hospital, Charlestown, MA
- Massachusetts General Hospital, Charlestown, MA
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34
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Stickgold R, Manoach DS. The Importance of Sleep in Fear Conditioning and Posttraumatic Stress Disorder. Biol Psychiatry Cogn Neurosci Neuroimaging 2018; 2:109-110. [PMID: 29560912 DOI: 10.1016/j.bpsc.2017.01.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2017] [Accepted: 01/26/2017] [Indexed: 02/03/2023]
Affiliation(s)
- Robert Stickgold
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.
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35
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Demanuele C, Bartsch U, Baran B, Khan S, Vangel MG, Cox R, Hämäläinen M, Jones MW, Stickgold R, Manoach DS. Coordination of Slow Waves With Sleep Spindles Predicts Sleep-Dependent Memory Consolidation in Schizophrenia. Sleep 2017; 40:2739498. [PMID: 28364465 DOI: 10.1093/sleep/zsw013] [Citation(s) in RCA: 57] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/20/2016] [Indexed: 01/21/2023] Open
Abstract
Study Objectives Schizophrenia patients have correlated deficits in sleep spindle density and sleep-dependent memory consolidation. In addition to spindle density, memory consolidation is thought to rely on the precise temporal coordination of spindles with slow waves (SWs). We investigated whether this coordination is intact in schizophrenia and its relation to motor procedural memory consolidation. Methods Twenty-one chronic medicated schizophrenia patients and 17 demographically matched healthy controls underwent two nights of polysomnography, with training on the finger tapping motor sequence task (MST) on the second night and testing the following morning. We detected SWs (0.5-4 Hz) and spindles during non-rapid eye movement (NREM) sleep. We measured SW-spindle phase-amplitude coupling and its relation with overnight improvement in MST performance. Results Patients did not differ from controls in the timing of SW-spindle coupling. In both the groups, spindles peaked during the SW upstate. For patients alone, the later in the SW upstate that spindles peaked and the more reliable this phase relationship, the greater the overnight MST improvement. Regression models that included both spindle density and SW-spindle coordination predicted overnight improvement significantly better than either parameter alone, suggesting that both contribute to memory consolidation. Conclusion Schizophrenia patients show intact spindle-SW temporal coordination, and these timing relationships, together with spindle density, predict sleep-dependent memory consolidation. These relations were seen only in patients suggesting that their memory is more dependent on optimal spindle-SW timing, possibly due to reduced spindle density. Interventions to improve memory may need to increase spindle density while preserving or enhancing the coordination of NREM oscillations.
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Affiliation(s)
- Charmaine Demanuele
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA.,Harvard Medical School, Boston, MA
| | - Ullrich Bartsch
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA.,School of Physiology and Pharmacology, University of Bristol, Bristol, United Kingdom
| | - Bengi Baran
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA.,Harvard Medical School, Boston, MA
| | - Sheraz Khan
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA.,Harvard Medical School, Boston, MA
| | - Mark G Vangel
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA.,Harvard Medical School, Boston, MA
| | - Roy Cox
- Harvard Medical School, Boston, MA.,Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA
| | - Matti Hämäläinen
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA.,Harvard Medical School, Boston, MA
| | - Matthew W Jones
- School of Physiology and Pharmacology, University of Bristol, Bristol, United Kingdom
| | - Robert Stickgold
- Harvard Medical School, Boston, MA.,Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA.,Harvard Medical School, Boston, MA
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36
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Cox R, Schapiro AC, Manoach DS, Stickgold R. Individual Differences in Frequency and Topography of Slow and Fast Sleep Spindles. Front Hum Neurosci 2017; 11:433. [PMID: 28928647 PMCID: PMC5591792 DOI: 10.3389/fnhum.2017.00433] [Citation(s) in RCA: 110] [Impact Index Per Article: 15.7] [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: 06/08/2017] [Accepted: 08/15/2017] [Indexed: 11/25/2022] Open
Abstract
Sleep spindles are transient oscillatory waveforms that occur during non-rapid eye movement (NREM) sleep across widespread cortical areas. In humans, spindles can be classified as either slow or fast, but large individual differences in spindle frequency as well as methodological difficulties have hindered progress towards understanding their function. Using two nights of high-density electroencephalography recordings from 28 healthy individuals, we first characterize the individual variability of NREM spectra and demonstrate the difficulty of determining subject-specific spindle frequencies. We then introduce a novel spatial filtering approach that can reliably separate subject-specific spindle activity into slow and fast components that are stable across nights and across N2 and N3 sleep. We then proceed to provide detailed analyses of the topographical expression of individualized slow and fast spindle activity. Group-level analyses conform to known spatial properties of spindles, but also uncover novel differences between sleep stages and spindle classes. Moreover, subject-specific examinations reveal that individual topographies show considerable variability that is stable across nights. Finally, we demonstrate that topographical maps depend nontrivially on the spindle metric employed. In sum, our findings indicate that group-level approaches mask substantial individual variability of spindle dynamics, in both the spectral and spatial domains. We suggest that leveraging, rather than ignoring, such differences may prove useful to further our understanding of the physiology and functional role of sleep spindles.
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Affiliation(s)
- Roy Cox
- Department of Psychiatry, Beth Israel Deaconess Medical CenterBoston, MA, United States.,Department of Psychiatry, Harvard Medical SchoolBoston, MA, United States
| | - Anna C Schapiro
- Department of Psychiatry, Beth Israel Deaconess Medical CenterBoston, MA, United States.,Department of Psychiatry, Harvard Medical SchoolBoston, MA, United States
| | - Dara S Manoach
- Department of Psychiatry, Harvard Medical SchoolBoston, MA, United States.,Department of Psychiatry, Massachusetts General HospitalCharlestown, MA, United States.,Athinoula A. Martinos Center for Biomedical ImagingCharlestown, MA, United States
| | - Robert Stickgold
- Department of Psychiatry, Beth Israel Deaconess Medical CenterBoston, MA, United States.,Department of Psychiatry, Harvard Medical SchoolBoston, MA, United States
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37
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Purcell SM, Manoach DS, Demanuele C, Cade BE, Mariani S, Cox R, Panagiotaropoulou G, Saxena R, Pan JQ, Smoller JW, Redline S, Stickgold R. Characterizing sleep spindles in 11,630 individuals from the National Sleep Research Resource. Nat Commun 2017. [PMID: 28649997 PMCID: PMC5490197 DOI: 10.1038/ncomms15930] [Citation(s) in RCA: 212] [Impact Index Per Article: 30.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Sleep spindles are characteristic electroencephalogram (EEG) signatures of stage 2 non-rapid eye movement sleep. Implicated in sleep regulation and cognitive functioning, spindles may represent heritable biomarkers of neuropsychiatric disease. Here we characterize spindles in 11,630 individuals aged 4 to 97 years, as a prelude to future genetic studies. Spindle properties are highly reliable but exhibit distinct developmental trajectories. Across the night, we observe complex patterns of age- and frequency-dependent dynamics, including signatures of circadian modulation. We identify previously unappreciated correlates of spindle activity, including confounding by body mass index mediated by cardiac interference in the EEG. After taking account of these confounds, genetic factors significantly contribute to spindle and spectral sleep traits. Finally, we consider topographical differences and critical measurement issues. Taken together, our findings will lead to an increased understanding of the genetic architecture of sleep spindles and their relation to behavioural and health outcomes, including neuropsychiatric disorders. Sleep patterns vary and are associated with health and disease. Here Purcell et al characterize sleep spindle activity in 11,630 individuals and describe age-related changes, genetic influences, and possible confounding effects, serving as a resource for further understanding the physiology of sleep.
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Affiliation(s)
- S M Purcell
- Department of Psychiatry, Brigham and Women's Hospital, Boston, Massachusetts 02115, USA.,Harvard Medical School, Boston, Massachusetts 02115, USA.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - D S Manoach
- Harvard Medical School, Boston, Massachusetts 02115, USA.,Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts 02114, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts 02129, USA
| | - C Demanuele
- Harvard Medical School, Boston, Massachusetts 02115, USA.,Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts 02114, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts 02129, USA
| | - B E Cade
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, Massachusetts 02115, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - S Mariani
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, Massachusetts 02115, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - R Cox
- Harvard Medical School, Boston, Massachusetts 02115, USA.,Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, Massachusetts 02215, USA
| | - G Panagiotaropoulou
- Harvard Medical School, Boston, Massachusetts 02115, USA.,Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts 02114, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts 02129, USA
| | - R Saxena
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts 02114, USA.,Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts 02114, USA.,Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts 02142, USA
| | - J Q Pan
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142, USA
| | - J W Smoller
- Harvard Medical School, Boston, Massachusetts 02115, USA.,Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts 02114, USA.,Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
| | - S Redline
- Harvard Medical School, Boston, Massachusetts 02115, USA.,Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, Massachusetts 02115, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - R Stickgold
- Harvard Medical School, Boston, Massachusetts 02115, USA.,Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, Massachusetts 02215, USA
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Mylonas DS, Demanuele C, Baran B, Kohnke EJ, Tocci C, Stickgold R, Hamalainen M, Manoach DS. 1126 SPINDLE ACTIVITY RELATED TO MOTOR PROCEDURAL LEARNING IN PATIENTS WITH SCHIZOPHRENIA. Sleep 2017. [DOI: 10.1093/sleepj/zsx050.1125] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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Baran B, Demanuele C, Vuper TC, Seicol B, Fowler RA, Correll D, Parr E, Callahan CE, Morgan A, Stickgold R, Manoach DS. 1113 THE EFFECTS OF ESZOPICLONE ON SLEEP SPINDLES AND MEMORY CONSOLIDATION IN SCHIZOPHRENIA: A DOUBLE-BLIND RANDOMIZED TRIAL. Sleep 2017. [DOI: 10.1093/sleepj/zsx050.1112] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
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40
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Tocci C, Kohnke E, Mylonas D, Baran B, Parr E, Stickgold R, Manoach DS. 1125 COMPARISON OF SPINDLE DENSITY AND PROCEDURAL MEMORY RELIABILITY IN NAP AND OVERNIGHT SLEEP. Sleep 2017. [DOI: 10.1093/sleepj/zsx050.1124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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41
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Lee PH, Baker JT, Holmes AJ, Jahanshad N, Ge T, Jung JY, Cruz Y, Manoach DS, Hibar DP, Faskowitz J, McMahon KL, de Zubicaray GI, Martin NH, Wright MJ, Öngür D, Buckner R, Roffman J, Thompson PM, Smoller JW. Partitioning heritability analysis reveals a shared genetic basis of brain anatomy and schizophrenia. Mol Psychiatry 2016; 21:1680-1689. [PMID: 27725656 PMCID: PMC5144575 DOI: 10.1038/mp.2016.164] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2015] [Revised: 07/14/2016] [Accepted: 08/11/2016] [Indexed: 01/18/2023]
Abstract
Schizophrenia is a devastating neurodevelopmental disorder with a complex genetic etiology. Widespread cortical gray matter loss has been observed in patients and prodromal samples. However, it remains unresolved whether schizophrenia-associated cortical structure variations arise due to disease etiology or secondary to the illness. Here we address this question using a partitioning-based heritability analysis of genome-wide single-nucleotide polymorphism (SNP) and neuroimaging data from 1750 healthy individuals. We find that schizophrenia-associated genetic variants explain a significantly enriched proportion of trait heritability in eight brain phenotypes (false discovery rate=10%). In particular, intracranial volume and left superior frontal gyrus thickness exhibit significant and robust associations with schizophrenia genetic risk under varying SNP selection conditions. Cross-disorder comparison suggests that the neurogenetic architecture of schizophrenia-associated brain regions is, at least in part, shared with other psychiatric disorders. Our study highlights key neuroanatomical correlates of schizophrenia genetic risk in the general population. These may provide fundamental insights into the complex pathophysiology of the illness, and a potential link to neurocognitive deficits shaping the disorder.
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Affiliation(s)
- Phil H. Lee
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114, USA,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02138, USA,Department of Psychiatry, Harvard Medical School Boston, MA, USA
| | - Justin T. Baker
- Department of Psychiatry, Harvard Medical School Boston, MA, USA,Schizophrenia and Bipolar Disorder Program, Psychotic Disorders Division, McLean Hospital Belmont, MA, USA
| | - Avram J. Holmes
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital / Harvard Medical School, Charlestown, MA 02129, USA,Department of Psychology, Yale University, New Haven, CT 06520, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA 90292 USA
| | - Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114, USA,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02138, USA,Department of Psychiatry, Harvard Medical School Boston, MA, USA,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital / Harvard Medical School, Charlestown, MA 02129, USA
| | - Jae-Yoon Jung
- Department of Pediatrics, Division of Systems Medicine, Stanford University, CA 94305, USA
| | - Yanela Cruz
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114, USA,Harvard Graduate School of Education, Cambridge, MA, 02138, USA
| | - Dara S. Manoach
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital / Harvard Medical School, Charlestown, MA 02129, USA
| | - Derrek P. Hibar
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA 90292 USA
| | - Joshua Faskowitz
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA 90292 USA
| | - Katie L. McMahon
- Centre for Advanced Imaging, University of Queensland, Brisbane, QLD 4072, Australia
| | - Greig I. de Zubicaray
- Faculty of Health and Institute of Health and Biomedical Innovation, Queensland University of Technology (QUT), Brisbane, QLD 4059, Australia
| | - Nicolas H. Martin
- Queensland Institute of Medical Research (QIMR) Berghofer, Brisbane, QLD, Australia
| | - Margaret J. Wright
- Centre for Advanced Imaging, University of Queensland, Brisbane, QLD 4072, Australia,Queensland Brain Institute, University of Queensland, Brisbane, QLD 4072, Australia
| | - Dost Öngür
- Department of Psychiatry, Harvard Medical School Boston, MA, USA,Schizophrenia and Bipolar Disorder Program, Psychotic Disorders Division, McLean Hospital Belmont, MA, USA
| | - Randy Buckner
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital / Harvard Medical School, Charlestown, MA 02129, USA,Department of Psychology and Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Joshua Roffman
- Department of Psychiatry, Harvard Medical School Boston, MA, USA,Schizophrenia Clinical and Research Program, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Paul M. Thompson
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA 90292 USA
| | - Jordan W. Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114, USA,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02138, USA,Department of Psychiatry, Harvard Medical School Boston, MA, USA
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Baran B, Karahanoğlu FI, Agam Y, Mantonakis L, Manoach DS. Failure to mobilize cognitive control for challenging tasks correlates with symptom severity in schizophrenia. Neuroimage Clin 2016; 12:887-893. [PMID: 27872811 PMCID: PMC5109850 DOI: 10.1016/j.nicl.2016.10.020] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/17/2016] [Revised: 10/20/2016] [Accepted: 10/26/2016] [Indexed: 12/31/2022]
Abstract
Deficits in the adaptive, flexible control of behavior contribute to the clinical manifestations of schizophrenia. We used functional MRI and an antisaccade paradigm to examine the neural correlates of cognitive control deficits and their relations to symptom severity. Thirty-three chronic medicated outpatients with schizophrenia and 31 healthy controls performed an antisaccade paradigm. We examined differences in recruitment of the cognitive control network and task performance for Hard (high control) versus Easy (low control) antisaccade trials within and between groups. We focused on the key regions involved in ‘top-down’ control of ocular motor structures – dorsal anterior cingulate cortex, dorsolateral and ventrolateral prefrontal cortex. In patients, we examined whether difficulty implementing cognitive control correlated with symptom severity. Patients made more errors overall, and had shorter saccadic latencies than controls on correct Hard vs. Easy trials. Unlike controls, patients failed to increase activation in the cognitive control network for Hard vs. Easy trials. Reduced activation for Hard vs. Easy trials predicted higher error rates in both groups and increased symptom severity in schizophrenia. These findings suggest that patients with schizophrenia are impaired in mobilizing cognitive control when presented with challenges and that this contributes to deficits suppressing prepotent but contextually inappropriate responses, to behavior that is stimulus-bound and error-prone rather than flexibly guided by context, and to symptom expression. Therapies aimed at increasing cognitive control may improve both cognitive flexibility and reduce the impact of symptoms. Patients with schizophrenia fail to mobilize the cognitive control network during a challenging cognitive task. This deficit results in behavior that is stimulus-bound and error-prone rather than flexibly guided by context. Therapies aimed at increasing cognitive control may improve both cognitive flexibility and reduce the impact of symptoms.
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Affiliation(s)
- Bengi Baran
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
| | - F Işık Karahanoğlu
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
| | - Yigal Agam
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
| | - Leonidas Mantonakis
- Psychiatry Department, National and Kapodistrian University of Athens, Medical School, Eginition Hospital, Athens, Greece
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
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Manoach DS, Pan JQ, Purcell SM, Stickgold R. Reduced Sleep Spindles in Schizophrenia: A Treatable Endophenotype That Links Risk Genes to Impaired Cognition? Biol Psychiatry 2016; 80:599-608. [PMID: 26602589 PMCID: PMC4833702 DOI: 10.1016/j.biopsych.2015.10.003] [Citation(s) in RCA: 131] [Impact Index Per Article: 16.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2015] [Revised: 09/18/2015] [Accepted: 10/05/2015] [Indexed: 11/26/2022]
Abstract
Although schizophrenia (SZ) is defined by waking phenomena, abnormal sleep is a common feature. In particular, there is accumulating evidence of a sleep spindle deficit. Sleep spindles, a defining thalamocortical oscillation of non-rapid eye movement stage 2 sleep, correlate with IQ and are thought to promote long-term potentiation and enhance memory consolidation. We review evidence that reduced spindle activity in SZ is an endophenotype that impairs sleep-dependent memory consolidation, contributes to symptoms, and is a novel treatment biomarker. Studies showing that spindles can be pharmacologically enhanced in SZ and that increasing spindles improves memory in healthy individuals suggest that treating spindle deficits in patients with SZ may improve cognition. Spindle activity is highly heritable, and recent large-scale genome-wide association studies have identified SZ risk genes that may contribute to spindle deficits and illuminate their mechanisms. For example, the SZ risk gene CACNA1I encodes a calcium channel that is abundantly expressed in the thalamic spindle generator and plays a critical role in spindle activity based on a mouse knockout. Future genetic studies of animals and humans can delineate the role of this and other genes in spindles. Such cross-disciplinary research, by forging empirical links in causal chains from risk genes to proteins and cellular functions to endophenotypes, cognitive impairments, symptoms, and diagnosis, has the potential to advance the mechanistic understanding, treatment, and prevention of SZ. This review highlights the importance of deficient sleep-dependent memory consolidation among the cognitive deficits of SZ and implicates reduced sleep spindles as a potentially treatable mechanism.
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Affiliation(s)
- Dara S. Manoach
- Department of Psychiatry and Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02215, USA,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Jen Q. Pan
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Shaun M. Purcell
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02215, USA,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA,Division of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Robert Stickgold
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA,Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA 02215 Harvard Medical School, Boston, MA, 02215
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Roffman JL, Tanner AS, Eryilmaz H, Rodriguez-Thompson A, Silverstein NJ, Ho NF, Nitenson AZ, Chonde DB, Greve DN, Abi-Dargham A, Buckner RL, Manoach DS, Rosen BR, Hooker JM, Catana C. Dopamine D1 signaling organizes network dynamics underlying working memory. Sci Adv 2016; 2:e1501672. [PMID: 27386561 PMCID: PMC4928887 DOI: 10.1126/sciadv.1501672] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2015] [Accepted: 05/11/2016] [Indexed: 05/04/2023]
Abstract
Local prefrontal dopamine signaling supports working memory by tuning pyramidal neurons to task-relevant stimuli. Enabled by simultaneous positron emission tomography-magnetic resonance imaging (PET-MRI), we determined whether neuromodulatory effects of dopamine scale to the level of cortical networks and coordinate their interplay during working memory. Among network territories, mean cortical D1 receptor densities differed substantially but were strongly interrelated, suggesting cross-network regulation. Indeed, mean cortical D1 density predicted working memory-emergent decoupling of the frontoparietal and default networks, which respectively manage task-related and internal stimuli. In contrast, striatal D1 predicted opposing effects within these two networks but no between-network effects. These findings specifically link cortical dopamine signaling to network crosstalk that redirects cognitive resources to working memory, echoing neuromodulatory effects of D1 signaling on the level of cortical microcircuits.
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Affiliation(s)
- Joshua L. Roffman
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA
- Corresponding author.
| | - Alexandra S. Tanner
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02114, USA
| | - Hamdi Eryilmaz
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02114, USA
| | - Anais Rodriguez-Thompson
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02114, USA
| | - Noah J. Silverstein
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02114, USA
| | - New Fei Ho
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02114, USA
| | - Adam Z. Nitenson
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02114, USA
| | - Daniel B. Chonde
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA
| | - Douglas N. Greve
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA
| | - Anissa Abi-Dargham
- Department of Psychiatry, Columbia University Medical Center, Harkness Pavilion, 180 Fort Washington Avenue, New York, NY 10032, USA
| | - Randy L. Buckner
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA
| | - Dara S. Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA
| | - Bruce R. Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA
| | - Jacob M. Hooker
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA
| | - Ciprian Catana
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th Street, Charlestown, MA 02129, USA
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45
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Hwang K, Ghuman AS, Manoach DS, Jones SR, Luna B. Frontal preparatory neural oscillations associated with cognitive control: A developmental study comparing young adults and adolescents. Neuroimage 2016; 136:139-48. [PMID: 27173759 DOI: 10.1016/j.neuroimage.2016.05.017] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2015] [Revised: 03/24/2016] [Accepted: 05/05/2016] [Indexed: 01/22/2023] Open
Abstract
Functional magnetic resonance imaging (fMRI) studies suggest that age-related changes in the frontal cortex may underlie developmental improvements in cognitive control. In the present study we used magnetoencephalography (MEG) to identify frontal oscillatory neurodynamics that support age-related improvements in cognitive control during adolescence. We characterized the differences in neural oscillations in adolescents and adults during the preparation to suppress a prepotent saccade (antisaccade trials-AS) compared to preparing to generate a more automatic saccade (prosaccade trials-PS). We found that for adults, AS were associated with increased beta-band (16-38Hz) power in the dorsal lateral prefrontal cortex (DLPFC), enhanced alpha- to low beta-band (10-18Hz) power in the frontal eye field (FEF) that predicted performance, and increased cross-frequency alpha-beta (10-26Hz) amplitude coupling between the DLPFC and the FEF. Developmental comparisons between adults and adolescents revealed similar engagement of DLPFC beta-band power but weaker FEF alpha-band power, and lower cross-frequency coupling between the DLPFC and the FEF in adolescents. These results suggest that lateral prefrontal neural activity associated with cognitive control is adult-like by adolescence; the development of cognitive control from adolescence to adulthood is instead associated with increases in frontal connectivity and strengthening of inhibition signaling for suppressing task-incompatible processes.
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Affiliation(s)
- Kai Hwang
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, United States; Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States; Department of Psychology, University of Pittsburgh, Pittsburgh, PA, United States; Center for the Neural Basis of Cognition, Carnegie Mellon University and University of Pittsburgh, Pittsburgh, PA, United States.
| | - Avniel S Ghuman
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States; Center for the Neural Basis of Cognition, Carnegie Mellon University and University of Pittsburgh, Pittsburgh, PA, United States; Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, United States
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
| | - Stephanie R Jones
- Department of Neuroscience, Brown University, Providence, RI, United States
| | - Beatriz Luna
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, United States; Department of Psychology, University of Pittsburgh, Pittsburgh, PA, United States; Center for the Neural Basis of Cognition, Carnegie Mellon University and University of Pittsburgh, Pittsburgh, PA, United States
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Abstract
Unihemispheric sleep, during which one half of the brain sleeps while the other half remains awake, is seen in some aquatic mammals and birds, particularly in risky situations. It now appears that humans sleeping in unfamiliar environments do something quite similar.
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Affiliation(s)
- Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02215, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA.
| | - Robert Stickgold
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA; Harvard Medical School, Boston, MA 02215, USA
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Gregory MD, Robertson EM, Manoach DS, Stickgold R. Thinking About a Task Is Associated with Increased Connectivity in Regions Activated by Task Performance. Brain Connect 2016; 6:164-8. [PMID: 26650337 DOI: 10.1089/brain.2015.0386] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
We investigated whether functional neuroimaging of quiet "rest" can reveal the neural correlates of conscious thought. Using resting-state functional MRI, we measured functional connectivity during a resting scan that immediately followed performance of a finger tapping motor sequence task. Self-reports of the amount of time spent thinking about the task during the resting scan correlated with connectivity between regions of the motor network activated during task performance. Thus, thinking about a task is associated with coordinated activity in brain regions responsible for that task's performance. More generally, this study demonstrates the feasibility of using the combination of functional connectivity MRI and self-reports to examine the neural correlates of thought.
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Affiliation(s)
- Michael D Gregory
- 1 Department of Neurology, Beth Israel Deaconess Medical Center , Boston, Massachusetts.,2 Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts.,3 Harvard Medical School , Boston, Massachusetts
| | - Edwin M Robertson
- 4 Centre for Cognitive Neuroimaging, Institute of Neuroscience & Psychology , Glasgow, United Kingdom
| | - Dara S Manoach
- 2 Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts.,3 Harvard Medical School , Boston, Massachusetts.,5 Department of Psychiatry, Massachusetts General Hospital , Charlestown, Massachusetts
| | - Robert Stickgold
- 3 Harvard Medical School , Boston, Massachusetts.,6 Department of Psychiatry, Beth Israel Deaconess Medical Center , Boston, Massachusetts
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Shaffer JJ, Peterson MJ, McMahon MA, Bizzell J, Calhoun V, van Erp TGM, Ford JM, Lauriello J, Lim KO, Manoach DS, McEwen SC, Mathalon DH, O'Leary D, Potkin SG, Preda A, Turner J, Voyvodic J, Wible CG, Belger A. Neural Correlates of Schizophrenia Negative Symptoms: Distinct Subtypes Impact Dissociable Brain Circuits. Mol Neuropsychiatry 2015; 1:191-200. [PMID: 27606313 DOI: 10.1159/000440979] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2015] [Accepted: 09/09/2015] [Indexed: 11/19/2022]
Abstract
BACKGROUND The negative symptoms of schizophrenia include deficits in emotional expression and motivation. These deficits are stable over the course of illness and respond poorly to current medications. Previous studies have focused on negative symptoms as a single category; however, individual symptoms might be related to separate neurological disturbances. We analyzed data from the Functional Biomedical Informatics Research Network dataset to explore the relationship between individual negative symptoms and functional brain activity during an auditory oddball task. METHODS Functional magnetic resonance imaging was conducted on 89 schizophrenia patients and 106 healthy controls during a two-tone auditory oddball task. Blood oxygenation level-dependent (BOLD) signal during the target tone was correlated with severity of five negative symptom domains from the Scale for the Assessment of Negative Symptoms. RESULTS The severity of alogia, avolition/apathy and anhedonia/asociality was negatively correlated with BOLD activity in distinct sets of brain regions associated with processing of the target tone, including basal ganglia, thalamus, insular cortex, prefrontal cortex, posterior cingulate and parietal cortex. CONCLUSIONS Individual symptoms were related to different patterns of functional activation during the oddball task, suggesting that individual symptoms might arise from distinct neural mechanisms. This work has potential to inform interventions that target these symptom-related neural disruptions.
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Affiliation(s)
- Joseph J Shaffer
- Department of Psychiatry, University of North Carolina, Chapel Hill, N.C., USA
| | - Michael J Peterson
- Department of Psychiatry, University of North Carolina, Chapel Hill, N.C., USA
| | - Mary Agnes McMahon
- Colorado Clinical and Translational Sciences Institute, University of Colorado, Denver, Colo., USA
| | - Joshua Bizzell
- Department of Psychiatry, University of North Carolina, Chapel Hill, N.C., USA; Duke/University of North Carolina Brain Imaging and Analysis Center, Durham, N.C., USA
| | - Vince Calhoun
- The Mind Research Network, University of New Mexico, Albuquerque, N. Mex., USA; Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, N. Mex., USA
| | - Theo G M van Erp
- Departments of Psychiatry and Human Behavior, University of California Irvine, Irvine, Calif., USA
| | - Judith M Ford
- Department of Psychiatry, University of California San Francisco, San Francisco, Calif., USA
| | - John Lauriello
- Department of Psychiatry, University of Missouri, Columbia, Mo., USA
| | - Kelvin O Lim
- Department of Psychiatry, University of Minnesota, Minneapolis, Minn., USA
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, Mass., USA
| | - Sarah C McEwen
- Department of Psychology, University of California Los Angeles, Los Angeles, Calif., USA
| | - Daniel H Mathalon
- Department of Psychiatry, University of California San Francisco, San Francisco, Calif., USA
| | - Daniel O'Leary
- Department of Neuroscience, University of Iowa, Iowa City, Iowa, USA
| | - Steven G Potkin
- Departments of Psychiatry, University of California Irvine, Irvine, Calif., USA; Department of Psychiatry, University of California San Francisco, San Francisco, Calif., USA
| | - Adrian Preda
- Departments of Psychiatry, University of California Irvine, Irvine, Calif., USA
| | - Jessica Turner
- Department of Psychology, Georgia State University, Atlanta, Ga., USA
| | - Jim Voyvodic
- Duke/University of North Carolina Brain Imaging and Analysis Center, Durham, N.C., USA
| | - Cynthia G Wible
- Department of Psychiatry, Harvard Medical School, Boston, Mass., USA; Department of Psychiatry, VA Medical Center Brockton, Brockton, Mass., USA
| | - Aysenil Belger
- Department of Psychiatry, University of North Carolina, Chapel Hill, N.C., USA; Duke/University of North Carolina Brain Imaging and Analysis Center, Durham, N.C., USA
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49
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Affiliation(s)
- Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA; Harvard Medical School, Boston, MA.
| | - Robert Stickgold
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA; Harvard Medical School, Boston, MA
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50
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Manoach DS, Demanuele C, Wamsley EJ, Vangel M, Montrose DM, Miewald J, Kupfer D, Buysse D, Stickgold R, Keshavan MS. Sleep spindle deficits in antipsychotic-naïve early course schizophrenia and in non-psychotic first-degree relatives. Front Hum Neurosci 2014; 8:762. [PMID: 25339881 PMCID: PMC4188028 DOI: 10.3389/fnhum.2014.00762] [Citation(s) in RCA: 107] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2014] [Accepted: 09/09/2014] [Indexed: 12/31/2022] Open
Abstract
INTRODUCTION Chronic medicated patients with schizophrenia have marked reductions in sleep spindle activity and a correlated deficit in sleep-dependent memory consolidation. Using archival data, we investigated whether antipsychotic-naïve early course patients with schizophrenia and young non-psychotic first-degree relatives of patients with schizophrenia also show reduced sleep spindle activity and whether spindle activity correlates with cognitive function and symptoms. METHOD Sleep spindles during Stage 2 sleep were compared in antipsychotic-naïve adults newly diagnosed with psychosis, young non-psychotic first-degree relatives of schizophrenia patients and two samples of healthy controls matched to the patients and relatives. The relations of spindle parameters with cognitive measures and symptom ratings were examined. RESULTS Early course schizophrenia patients showed significantly reduced spindle activity relative to healthy controls and to early course patients with other psychotic disorders. Relatives of schizophrenia patients also showed reduced spindle activity compared with controls. Reduced spindle activity correlated with measures of executive function in early course patients, positive symptoms in schizophrenia and IQ estimates across groups. CONCLUSIONS Like chronic medicated schizophrenia patients, antipsychotic-naïve early course schizophrenia patients and young non-psychotic relatives of individuals with schizophrenia have reduced sleep spindle activity. These findings indicate that the spindle deficit is not an antipsychotic side-effect or a general feature of psychosis. Instead, the spindle deficit may predate the onset of schizophrenia, persist throughout its course and be an endophenotype that contributes to cognitive dysfunction.
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Affiliation(s)
- Dara S. Manoach
- Department of Psychiatry, Massachusetts General HospitalCharlestown, MA, USA
- Athinoula A. Martinos Center for Biomedical ImagingCharlestown, MA, USA
- Harvard Medical SchoolBoston, MA, USA
| | - Charmaine Demanuele
- Department of Psychiatry, Massachusetts General HospitalCharlestown, MA, USA
- Athinoula A. Martinos Center for Biomedical ImagingCharlestown, MA, USA
- Harvard Medical SchoolBoston, MA, USA
| | - Erin J. Wamsley
- Harvard Medical SchoolBoston, MA, USA
- Department of Psychiatry, Beth Israel Deaconess Medical CenterBoston, MA, USA
| | - Mark Vangel
- Athinoula A. Martinos Center for Biomedical ImagingCharlestown, MA, USA
- Harvard Medical SchoolBoston, MA, USA
| | - Debra M. Montrose
- Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh School of MedicinePittsburgh, PA, USA
| | - Jean Miewald
- Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh School of MedicinePittsburgh, PA, USA
| | - David Kupfer
- Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh School of MedicinePittsburgh, PA, USA
| | - Daniel Buysse
- Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh School of MedicinePittsburgh, PA, USA
| | - Robert Stickgold
- Harvard Medical SchoolBoston, MA, USA
- Department of Psychiatry, Beth Israel Deaconess Medical CenterBoston, MA, USA
| | - Matcheri S. Keshavan
- Harvard Medical SchoolBoston, MA, USA
- Department of Psychiatry, Beth Israel Deaconess Medical CenterBoston, MA, USA
- Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh School of MedicinePittsburgh, PA, USA
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