1
|
Townsend PH, Jones A, Patel AD, Race E. Rhythmic Temporal Cues Coordinate Cross-frequency Phase-amplitude Coupling during Memory Encoding. J Cogn Neurosci 2024; 36:2100-2116. [PMID: 38991125 DOI: 10.1162/jocn_a_02217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/13/2024]
Abstract
Accumulating evidence suggests that rhythmic temporal cues in the environment influence the encoding of information into long-term memory. Here, we test the hypothesis that these mnemonic effects of rhythm reflect the coupling of high-frequency (gamma) oscillations to entrained lower-frequency oscillations synchronized to the beat of the rhythm. In Study 1, we first test this hypothesis in the context of global effects of rhythm on memory, when memory is superior for visual stimuli presented in rhythmic compared with arrhythmic patterns at encoding [Jones, A., & Ward, E. V. Rhythmic temporal structure at encoding enhances recognition memory, Journal of Cognitive Neuroscience, 31, 1549-1562, 2019]. We found that rhythmic presentation of visual stimuli during encoding was associated with greater phase-amplitude coupling (PAC) between entrained low-frequency (delta) oscillations and higher-frequency (gamma) oscillations. In Study 2, we next investigated cross-frequency PAC in the context of local effects of rhythm on memory encoding, when memory is superior for visual stimuli presented in-synchrony compared with out-of-synchrony with a background auditory beat [Hickey, P., Merseal, H., Patel, A. D., & Race, E. Memory in time: Neural tracking of low-frequency rhythm dynamically modulates memory formation. Neuroimage, 213, 116693, 2020]. We found that the mnemonic effect of rhythm in this context was again associated with increased cross-frequency PAC between entrained low-frequency (delta) oscillations and higher-frequency (gamma) oscillations. Furthermore, the magnitude of gamma power modulations positively scaled with the subsequent memory benefit for in- versus out-of-synchrony stimuli. Together, these results suggest that the influence of rhythm on memory encoding may reflect the temporal coordination of higher-frequency gamma activity by entrained low-frequency oscillations.
Collapse
Affiliation(s)
- Paige Hickey Townsend
- Massachusetts General Hospital, Charlestown, MA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA
| | | | - Aniruddh D Patel
- Tufts University, Medford, MA
- Canadian Institute for Advanced Research
| | | |
Collapse
|
2
|
Liu X, Han J, Zhang X, Zhou Q, Huang Z, Wang Y, Zhang J, Lin Y. Dynamic evolution of frontal-temporal network connectivity in temporal lobe epilepsy: A magnetoencephalography study. Hum Brain Mapp 2024; 45:e70033. [PMID: 39319686 PMCID: PMC11423264 DOI: 10.1002/hbm.70033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Revised: 09/06/2024] [Accepted: 09/11/2024] [Indexed: 09/26/2024] Open
Abstract
Temporal lobe epilepsy (TLE) frequently involves an intricate, extensive epileptic frontal-temporal network. This study aimed to investigate the interactions between temporal and frontal regions and the dynamic patterns of the frontal-temporal network in TLE patients with different disease durations. The magnetoencephalography data of 36 postoperative seizure-free patients with long-term follow-up of at least 1 year, and 21 age- and sex-matched healthy subjects were included in this study. Patients were initially divided into LONG-TERM (n = 18, DURATION >10 years) and SHORT-TERM (n = 18, DURATION ≤10 years) groups based on 10-year disease duration. For reliability, supplementary analyses were conducted with alternative cutoffs, creating three groups: 0 < DURATION ≤7 years (n = 11), 7 < DURATION ≤14 years (n = 11), and DURATION >14 years (n = 14). This study examined the intraregional phase-amplitude coupling (PAC) between theta phase and alpha amplitude across the whole brain. The interregional directed phase transfer entropy (dPTE) between frontal and temporal regions in the alpha and theta bands, and the interregional cross-frequency directionality (CFD) between temporal and frontal regions from the theta phase to the alpha amplitude were further computed and compared among groups. Partial correlation analysis was conducted to investigate correlations between intraregional PAC, interregional dPTE connectivity, interregional CFD, and disease duration. Whole-brain intraregional PAC analyses revealed enhanced theta phase-alpha amplitude coupling within the ipsilateral temporal and frontal regions in TLE patients, and the ipsilateral temporal PAC was positively correlated with disease duration (r = 0.38, p <.05). Interregional dPTE analyses demonstrated a gradual increase in frontal-to-temporal connectivity within the alpha band, while the direction of theta-band connectivity reversed from frontal-to-temporal to temporal-to-frontal as the disease duration increased. Interregional CFD analyses revealed that the inhibitory effect of frontal regions on temporal regions gradually increased with prolonged disease duration (r = -0.36, p <.05). This study clarified the intrinsic reciprocal connectivity between temporal and frontal regions with TLE duration. We propose a dynamically reorganized triple-stage network that transitions from balanced networks to constrained networks and further develops into imbalanced networks as the disease duration increases.
Collapse
Affiliation(s)
- Xinyan Liu
- School of Biological Science and Medical EngineeringBeihang UniversityBeijingChina
- Beijing Advanced Innovation Center for Big Data‐Based Precision MedicineBeihang UniversityBeijingChina
- Beijing Advanced Innovation Centre for Biomedical EngineeringBeihang UniversityBeijingChina
| | - Jiaqi Han
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Xiating Zhang
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Department of Neurologythe First Hospital of Hebei Medical UniversityShijiazhuangHebeiChina
| | - Qilin Zhou
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Zhaoyang Huang
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Department of Neurologythe First Hospital of Hebei Medical UniversityShijiazhuangHebeiChina
| | - Yuping Wang
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Department of Neurologythe First Hospital of Hebei Medical UniversityShijiazhuangHebeiChina
- Beijing Key Laboratory of NeuromodulationXuanwu Hospital, Capital Medical UniversityBeijingChina
| | - Jicong Zhang
- School of Biological Science and Medical EngineeringBeihang UniversityBeijingChina
- Beijing Advanced Innovation Center for Big Data‐Based Precision MedicineBeihang UniversityBeijingChina
- Beijing Advanced Innovation Centre for Biomedical EngineeringBeihang UniversityBeijingChina
- Hefei Innovation Research InstituteBeihang UniversityBeijingChina
| | - Yicong Lin
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Department of Neurologythe First Hospital of Hebei Medical UniversityShijiazhuangHebeiChina
- Beijing Key Laboratory of NeuromodulationXuanwu Hospital, Capital Medical UniversityBeijingChina
| |
Collapse
|
3
|
Bittar A, Garner PN. Exploring neural oscillations during speech perception via surrogate gradient spiking neural networks. Front Neurosci 2024; 18:1449181. [PMID: 39385848 PMCID: PMC11461475 DOI: 10.3389/fnins.2024.1449181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2024] [Accepted: 08/28/2024] [Indexed: 10/12/2024] Open
Abstract
Understanding cognitive processes in the brain demands sophisticated models capable of replicating neural dynamics at large scales. We present a physiologically inspired speech recognition architecture, compatible and scalable with deep learning frameworks, and demonstrate that end-to-end gradient descent training leads to the emergence of neural oscillations in the central spiking neural network. Significant cross-frequency couplings, indicative of these oscillations, are measured within and across network layers during speech processing, whereas no such interactions are observed when handling background noise inputs. Furthermore, our findings highlight the crucial inhibitory role of feedback mechanisms, such as spike frequency adaptation and recurrent connections, in regulating and synchronizing neural activity to improve recognition performance. Overall, on top of developing our understanding of synchronization phenomena notably observed in the human auditory pathway, our architecture exhibits dynamic and efficient information processing, with relevance to neuromorphic technology.
Collapse
Affiliation(s)
- Alexandre Bittar
- Idiap Research Institute, Audio Inference, Martigny, Switzerland
- École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | | |
Collapse
|
4
|
Zhang C, Wang Y, Li M, Niu P, Li S, Hu Z, Shi C, Li Y. Phase-Amplitude Coupling in Theta and Beta Bands: A Potential Electrophysiological Marker for Obstructive Sleep Apnea. Nat Sci Sleep 2024; 16:1469-1482. [PMID: 39323903 PMCID: PMC11423842 DOI: 10.2147/nss.s470617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Accepted: 09/10/2024] [Indexed: 09/27/2024] Open
Abstract
Background Phase-amplitude coupling (PAC) between the phase of low-frequency signals and the amplitude of high-frequency activities plays many physiological roles and is involved in the pathological processed of various neurological disorders. However, how low-frequency and high-frequency neural oscillations or information synchronization activities change under chronic central hypoxia in OSA patients and whether these changes are closely associated with OSA remains largely unexplored. This study arm to elucidate the long-term consequences of OSA-related oxygen deprivation on central nervous system function. Methods : We screened 521 patients who were clinically suspected of having OSA at our neurology and sleep centers. Through polysomnography (PSG) and other clinical examinations, 103 patients were ultimately included in the study and classified into mild, moderate, and severe OSA groups based on the severity of hypoxia determined by PSG. We utilized the phase-amplitude coupling (PAC) method to analyze the modulation index (MI) trends between different frequency bands during NREM (N1/N2/N3), REM, and wakefulness stages in OSA patients with varying severity levels. We also examined the correlation between the MI index and OSA hypoxia indices. Results Apart from reduced N2 sleep duration and increased microarousal index, the sleep architecture remained largely unchanged among OSA patients with varying severity levels. Compared to the mild OSA group, patients with moderate and severe OSA exhibited higher MI values of PAC in the low-frequency theta phase and high-frequency beta amplitude in the frontal and occipital regions during N1 sleep and wakefulness. No significant differences in the MI of phase-amplitude coupling were observed during N2/3 and REM sleep. Moreover, the MI of phase-amplitude coupling in theta and beta bands positively correlated with hypoxia-related indices, including the apnea-hypopnea index (AHI) and oxygenation desaturation index (ODI), and the percentage of oxygen saturation below 90% (SaO2<90%). Conclusion OSA patients demonstrated increased MI values of theta phase and beta amplitude in the frontal and occipital regions during N1 sleep and wakefulness. This suggests that cortical coupling is prevalent and exhibits sleep-stage-specific patterns in OSA. Theta-beta PAC during N1 and wakefulness was positively correlated with hypoxia-related indices, suggesting a potential relationship between these neural oscillations and OSA severity. The present study provides new insights into the relationship between neural oscillations and respiratory hypoxia in OSA patients.
Collapse
Affiliation(s)
- Chan Zhang
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, 450000, People’s Republic of China
- NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, Zhengzhou, Henan, People’s Republic of China
- Henan Neurological Function Detection and Regulation Center, Zhengzhou, Henan, 450000, People’s Republic of China
| | - Yanhui Wang
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, 450000, People’s Republic of China
- Henan Neurological Function Detection and Regulation Center, Zhengzhou, Henan, 450000, People’s Republic of China
- The Academy of Medical Sciences of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, People’s Republic of China
| | - Mengjie Li
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, 450000, People’s Republic of China
- The Academy of Medical Sciences of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, People’s Republic of China
| | - Pengpeng Niu
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, 450000, People’s Republic of China
- NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, Zhengzhou, Henan, People’s Republic of China
| | - Shuo Li
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, 450000, People’s Republic of China
- NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, Zhengzhou, Henan, People’s Republic of China
| | - Zhuopeng Hu
- The First Bethune Clinical Medical College of Ji Lin University, Changchun, Jilin, People’s Republic of China
| | - Changhe Shi
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, 450000, People’s Republic of China
- NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, Zhengzhou, Henan, People’s Republic of China
| | - Yusheng Li
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan, 450000, People’s Republic of China
- NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, Zhengzhou, Henan, People’s Republic of China
- Henan Neurological Function Detection and Regulation Center, Zhengzhou, Henan, 450000, People’s Republic of China
| |
Collapse
|
5
|
Chen YC, Tsai YY, Huang WM, Zhao CG, Hwang IS. Age-Related Topological Organization of Phase-Amplitude Coupling Between Postural Fluctuations and Scalp EEG During Unsteady Stance. IEEE Trans Neural Syst Rehabil Eng 2024; 32:3231-3239. [PMID: 39196741 DOI: 10.1109/tnsre.2024.3451023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/30/2024]
Abstract
Through phase-amplitude analysis, this study investigated how low-frequency postural fluctuations interact with high-frequency scalp electroencephalography (EEG) amplitudes, shedding light on age-related mechanic differences in balance control during uneven surface navigation. Twenty young ( 24.1 ± 1.9 years) and twenty older adults ( 66.2 ± 2.7 years) stood on a training stabilometer with visual guidance, while their scalp EEG and stabilometer plate movements were monitored. In addition to analyzing the dynamics of the postural fluctuation phase, phase-amplitude coupling (PAC) for postural fluctuations below 2 Hz and within EEG sub-bands (theta: 4-7 Hz, alpha: 8-12 Hz, beta: 13-35 Hz) was calculated. The results indicated that older adults exhibited significantly larger postural fluctuation amplitudes(p <0.001) and lower mean frequencies of the postural fluctuation phase ( p = 0.005 ) than young adults. The PAC between postural fluctuation and theta EEG (FCz and bilateral temporal-parietal-occipital area), as well as that between postural fluctuation and alpha EEG oscillation, was lower in older adults than in young adults (p <0.05). In contrast, the PAC between the phase of postural fluctuation and beta EEG oscillation, particularly in C3 ( p=0.006 ), was higher in older adults than in young adults. In summary, the postural fluctuation phase and phase-amplitude coupling between postural fluctuation and EEG are sensitive indicators of the age-related decline in postural adjustments, reflecting less flexible motor state transitions and adaptive changes in error monitoring and visuospatial attention.
Collapse
|
6
|
Duchet B, Bogacz R. How to design optimal brain stimulation to modulate phase-amplitude coupling? J Neural Eng 2024; 21:10.1088/1741-2552/ad5b1a. [PMID: 38985096 PMCID: PMC7616267 DOI: 10.1088/1741-2552/ad5b1a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Accepted: 06/24/2024] [Indexed: 07/11/2024]
Abstract
Objective.Phase-amplitude coupling (PAC), the coupling of the amplitude of a faster brain rhythm to the phase of a slower brain rhythm, plays a significant role in brain activity and has been implicated in various neurological disorders. For example, in Parkinson's disease, PAC between the beta (13-30 Hz) and gamma (30-100 Hz) rhythms in the motor cortex is exaggerated, while in Alzheimer's disease, PAC between the theta (4-8 Hz) and gamma rhythms is diminished. Modulating PAC (i.e. reducing or enhancing PAC) using brain stimulation could therefore open new therapeutic avenues. However, while it has been previously reported that phase-locked stimulation can increase PAC, it is unclear what the optimal stimulation strategy to modulate PAC might be. Here, we provide a theoretical framework to narrow down the experimental optimisation of stimulation aimed at modulating PAC, which would otherwise rely on trial and error.Approach.We make analytical predictions using a Stuart-Landau model, and confirm these predictions in a more realistic model of coupled neural populations.Main results.Our framework specifies the critical Fourier coefficients of the stimulation waveform which should be tuned to optimally modulate PAC. Depending on the characteristics of the amplitude response curve of the fast population, these components may include the slow frequency, the fast frequency, combinations of these, as well as their harmonics. We also show that the optimal balance of energy between these Fourier components depends on the relative strength of the endogenous slow and fast rhythms, and that the alignment of fast components with the fast rhythm should change throughout the slow cycle. Furthermore, we identify the conditions requiring to phase-lock stimulation to the fast and/or slow rhythms.Significance.Together, our theoretical framework lays the foundation for guiding the development of innovative and more effective brain stimulation aimed at modulating PAC for therapeutic benefit.
Collapse
Affiliation(s)
- Benoit Duchet
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United
Kingdom
| | - Rafal Bogacz
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United
Kingdom
| |
Collapse
|
7
|
Mark JI, Riddle J, Gangwani R, Huang B, Fröhlich F, Cassidy JM. Cross-Frequency Coupling as a Biomarker for Early Stroke Recovery. Neurorehabil Neural Repair 2024; 38:506-517. [PMID: 38842027 PMCID: PMC11179969 DOI: 10.1177/15459683241257523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2024]
Abstract
BACKGROUND The application of neuroimaging-based biomarkers in stroke has enriched our understanding of post-stroke recovery mechanisms, including alterations in functional connectivity based on synchronous oscillatory activity across various cortical regions. Phase-amplitude coupling, a type of cross-frequency coupling, may provide additional mechanistic insight. OBJECTIVE To determine how the phase of prefrontal cortex delta (1-3 Hz) oscillatory activity mediates the amplitude of motor cortex beta (13-20 Hz) oscillations in individual's early post-stroke. METHODS Participants admitted to an inpatient rehabilitation facility completed resting and task-based EEG recordings and motor assessments around the time of admission and discharge along with structural neuroimaging. Unimpaired controls completed EEG procedures during a single visit. Mixed-effects linear models were performed to assess within- and between-group differences in delta-beta prefrontomotor coupling. Associations between coupling and motor status and injury were also determined. RESULTS Thirty individuals with stroke and 17 unimpaired controls participated. Coupling was greater during task versus rest conditions for all participants. Though coupling during affected extremity task performance decreased during hospitalization, coupling remained elevated at discharge compared to controls. Greater baseline coupling was associated with better motor status at admission and discharge and positively related to motor recovery. Coupling demonstrated both positive and negative associations with injury involving measures of lesion volume and overlap injury to anterior thalamic radiation, respectively. CONCLUSIONS This work highlights the utility of prefrontomotor cross-frequency coupling as a potential motor status and recovery biomarker in stroke. The frequency- and region-specific neurocircuitry featured in this work may also facilitate novel treatment strategies in stroke.
Collapse
Affiliation(s)
- Jasper I. Mark
- Human Movement Science Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Health Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Justin Riddle
- Department of Psychology, Florida State University, Tallahassee, FL, USA
| | - Rachana Gangwani
- Human Movement Science Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Health Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Benjamin Huang
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Flavio Fröhlich
- Carolina Center for Neurostimulation, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jessica M. Cassidy
- Department of Health Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| |
Collapse
|
8
|
Chen YC, Tsai YY, Huang WM, Zhao CG, Hwang IS. Cross-frequency modulation of postural fluctuations and scalp EEG in older adults: error amplification feedback for rapid balance adjustments. GeroScience 2024:10.1007/s11357-024-01258-1. [PMID: 38910193 DOI: 10.1007/s11357-024-01258-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Accepted: 06/14/2024] [Indexed: 06/25/2024] Open
Abstract
Virtual error amplification (VEA) in visual feedback enhances attentive control over postural stability, although the neural mechanisms are still debated. This study investigated the distinct cortical control of unsteady stance in older adults using VEA through cross-frequency modulation of postural fluctuations and scalp EEG. Thirty-seven community-dwelling older adults (68.1 ± 3.6 years) maintained an upright stance on a stabilometer while receiving either VEA or real error feedback. Along with postural fluctuation dynamics, phase-amplitude coupling (PAC) and amplitude-amplitude coupling (AAC) were analyzed for postural fluctuations under 2 Hz and EEG sub-bands (theta, alpha, and beta). The results revealed a higher mean frequency of the postural fluctuation phase (p = .005) and a greater root mean square of the postural fluctuation amplitude (p = .003) with VEA compared to the control condition. VEA also reduced PAC between the postural fluctuation phase and beta-band EEG in the left frontal (p = .009), sensorimotor (p = .002), and occipital (p = .018) areas. Conversely, VEA increased the AAC of posture fluctuation amplitude and beta-band EEG in FP2 (p = .027). Neither theta nor alpha band PAC or AAC were affected by VEA. VEA optimizes postural strategies in older adults during stabilometer stance by enhancing visuospatial attentive control of postural responses and facilitating the transition of motor states against postural perturbations through a disinhibitory process. Incorporating VEA into virtual reality technology is advocated as a valuable strategy for optimizing therapeutic interventions in postural therapy, particularly to mitigate the risk of falls among older adults.
Collapse
Affiliation(s)
- Yi-Ching Chen
- Department of Physical Therapy, College of Medical Science and Technology, Chung Shan Medical University, Taichung City, Taiwan
- Physical Therapy Room, Chung Shan Medical University Hospital, Taichung City, Taiwan
| | - Yi-Ying Tsai
- Department of Physical Therapy, College of Medicine, National Cheng Kung University, Tainan City, Taiwan
| | - Wei-Min Huang
- Department of Management Information System, National Chung Cheng University, Chiayi, Taiwan
| | - Chen-Guang Zhao
- Department of Physical Therapy, College of Medicine, National Cheng Kung University, Tainan City, Taiwan
| | - Ing-Shiou Hwang
- Department of Physical Therapy, College of Medicine, National Cheng Kung University, Tainan City, Taiwan.
- Institute of Allied Health Sciences, College of Medicine, National Cheng Kung University, Tainan City, Taiwan.
| |
Collapse
|
9
|
Tan H, Zeng X, Ni J, Liang K, Xu C, Zhang Y, Wang J, Li Z, Yang J, Han C, Gao Y, Yu X, Han S, Meng F, Ma Y. Intracranial EEG signals disentangle multi-areal neural dynamics of vicarious pain perception. Nat Commun 2024; 15:5203. [PMID: 38890380 PMCID: PMC11189531 DOI: 10.1038/s41467-024-49541-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 06/07/2024] [Indexed: 06/20/2024] Open
Abstract
Empathy enables understanding and sharing of others' feelings. Human neuroimaging studies have identified critical brain regions supporting empathy for pain, including the anterior insula (AI), anterior cingulate (ACC), amygdala, and inferior frontal gyrus (IFG). However, to date, the precise spatio-temporal profiles of empathic neural responses and inter-regional communications remain elusive. Here, using intracranial electroencephalography, we investigated electrophysiological signatures of vicarious pain perception. Others' pain perception induced early increases in high-gamma activity in IFG, beta power increases in ACC, but decreased beta power in AI and amygdala. Vicarious pain perception also altered the beta-band-coordinated coupling between ACC, AI, and amygdala, as well as increased modulation of IFG high-gamma amplitudes by beta phases of amygdala/AI/ACC. We identified a necessary combination of neural features for decoding vicarious pain perception. These spatio-temporally specific regional activities and inter-regional interactions within the empathy network suggest a neurodynamic model of human pain empathy.
Collapse
Affiliation(s)
- Huixin Tan
- State Key Laboratory of Cognitive Neuroscience and Learning Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
| | - Xiaoyu Zeng
- State Key Laboratory of Cognitive Neuroscience and Learning Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
| | - Jun Ni
- State Key Laboratory of Cognitive Neuroscience and Learning Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
| | - Kun Liang
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Cuiping Xu
- Department of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yanyang Zhang
- Department of Neurosurgery, Chinese PLA General Hospital, Beijing, China
| | - Jiaxin Wang
- State Key Laboratory of Cognitive Neuroscience and Learning Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
| | - Zizhou Li
- State Key Laboratory of Cognitive Neuroscience and Learning Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
| | - Jiaxin Yang
- State Key Laboratory of Cognitive Neuroscience and Learning Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China
| | - Chunlei Han
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yuan Gao
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xinguang Yu
- Department of Neurosurgery, Chinese PLA General Hospital, Beijing, China
| | - Shihui Han
- School of Psychological and Cognitive Sciences, PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing, China
| | - Fangang Meng
- Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
- Chinese Institute for Brain Research, Beijing, China.
| | - Yina Ma
- State Key Laboratory of Cognitive Neuroscience and Learning Beijing Normal University, Beijing, China.
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China.
- Chinese Institute for Brain Research, Beijing, China.
| |
Collapse
|
10
|
Perley AS, Coleman TP. A mutual information measure of phase-amplitude coupling using gamma generalized linear models. Front Comput Neurosci 2024; 18:1392655. [PMID: 38841426 PMCID: PMC11150603 DOI: 10.3389/fncom.2024.1392655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Accepted: 05/06/2024] [Indexed: 06/07/2024] Open
Abstract
Introduction Cross frequency coupling (CFC) between electrophysiological signals in the brain is a long-studied phenomenon and its abnormalities have been observed in conditions such as Parkinson's disease and epilepsy. More recently, CFC has been observed in stomach-brain electrophysiologic studies and thus becomes an enticing possible target for diseases involving aberrations of the gut-brain axis. However, current methods of detecting coupling, specifically phase-amplitude coupling (PAC), do not attempt to capture the phase and amplitude statistical relationships. Methods In this paper, we first demonstrate a method of modeling these joint statistics with a flexible parametric approach, where we model the conditional distribution of amplitude given phase using a gamma distributed generalized linear model (GLM) with a Fourier basis of regressors. We perform model selection with minimum description length (MDL) principle, demonstrate a method for assessing goodness-of-fit (GOF), and showcase the efficacy of this approach in multiple electroencephalography (EEG) datasets. Secondly, we showcase how we can utilize the mutual information, which operates on the joint distribution, as a canonical measure of coupling, as it is non-zero and non-negative if and only if the phase and amplitude are not statistically independent. In addition, we build off of previous work by Martinez-Cancino et al., and Voytek et al., and show that the information density, evaluated using our method along the given sample path, is a promising measure of time-resolved PAC. Results Using synthetically generated gut-brain coupled signals, we demonstrate that our method outperforms the existing gold-standard methods for detectable low-levels of phase-amplitude coupling through receiver operating characteristic (ROC) curve analysis. To validate our method, we test on invasive EEG recordings by generating comodulograms, and compare our method to the gold standard PAC measure, Modulation Index, demonstrating comparable performance in exploratory analysis. Furthermore, to showcase its use in joint gut-brain electrophysiology data, we generate topoplots of simultaneous high-density EEG and electrgastrography recordings and reproduce seminal work by Richter et al. that demonstrated the existence of gut-brain PAC. Using simulated data, we validate our method for different types of time-varying coupling and then demonstrate its performance to track time-varying PAC in sleep spindle EEG and mismatch negativity (MMN) datasets. Conclusions Our new measure of PAC using Gamma GLMs and mutual information demonstrates a promising new way to compute PAC values using the full joint distribution on amplitude and phase. Our measure outperforms the most common existing measures of PAC, and show promising results in identifying time varying PAC in electrophysiological datasets. In addition, we provide for using our method with multiple comparisons and show that our measure potentially has more statistical power in electrophysiologic recordings using simultaneous gut-brain datasets.
Collapse
Affiliation(s)
| | - Todd P. Coleman
- Department of Bioengineering, Stanford University, Stanford, CA, United States
| |
Collapse
|
11
|
Shibata T, Tsuchiya H, Akiyama M, Akiyama T, Kobayashi K. Modulation index predicts the effect of ethosuximide on developmental and epileptic encephalopathy with spike-and-wave activation in sleep. Epilepsy Res 2024; 202:107359. [PMID: 38582072 DOI: 10.1016/j.eplepsyres.2024.107359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 03/27/2024] [Accepted: 04/03/2024] [Indexed: 04/08/2024]
Abstract
PURPOSE In developmental and epileptic encephalopathy with spike-and-wave activation in sleep (DEE-SWAS), the thalamocortical network is suggested to play an important role in the pathophysiology of the progression from focal epilepsy to DEE-SWAS. Ethosuximide (ESM) exerts effects by blocking T-type calcium channels in thalamic neurons. With the thalamocortical network in mind, we studied the prediction of ESM effectiveness in DEE-SWAS treatment using phase-amplitude coupling (PAC) analysis. METHODS We retrospectively enrolled children with DEE-SWAS who had an electroencephalogram (EEG) recorded between January 2009 and September 2022 and were prescribed ESM at Okayama University Hospital. Only patients whose EEG showed continuous spike-and-wave during sleep were included. We extracted 5-min non-rapid eye movement sleep stage N2 segments from EEG recorded before starting ESM. We calculated the modulation index (MI) as the measure of PAC in pair combination comprising one of two fast oscillation types (gamma, 40-80 Hz; ripples, 80-150 Hz) and one of five slow-wave bands (delta, 0.5-1, 1-2, 2-3, and 3-4 Hz; theta, 4-8 Hz), and compared it between ESM responders and non-responders. RESULTS We identified 20 children with a diagnosis of DEE-SWAS who took ESM. Fifteen were ESM responders. Regarding gamma oscillations, significant differences were seen only in MI with 0.5-1 Hz slow waves in the frontal pole and occipital regions. Regarding ripples, ESM responders had significantly higher MI in coupling with all slow waves in the frontal pole region, 0.5-1, 3-4, and 4-8 Hz slow waves in the frontal region, 3-4 Hz slow waves in the parietal region, 0.5-1, 2-3, 3-4, and 4-8 Hz slow waves in the occipital region, and 3-4 Hz slow waves in the anterior-temporal region. SIGNIFICANCE High MI in a wider area of the brain may represent the epileptic network mediated by the thalamus in DEE-SWAS and may be a predictor of ESM effectiveness.
Collapse
Affiliation(s)
- Takashi Shibata
- Department of Child Neurology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences and Okayama University Hospital, Okayama, Japan.
| | - Hiroki Tsuchiya
- Department of Child Neurology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences and Okayama University Hospital, Okayama, Japan
| | - Mari Akiyama
- Department of Child Neurology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences and Okayama University Hospital, Okayama, Japan
| | - Tomoyuki Akiyama
- Department of Child Neurology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences and Okayama University Hospital, Okayama, Japan
| | - Katsuhiro Kobayashi
- Department of Child Neurology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences and Okayama University Hospital, Okayama, Japan
| |
Collapse
|
12
|
Khanjanianpak M, Azimi-Tafreshi N, Valizadeh A. Emergence of complex oscillatory dynamics in the neuronal networks with long activity time of inhibitory synapses. iScience 2024; 27:109401. [PMID: 38532887 PMCID: PMC10963234 DOI: 10.1016/j.isci.2024.109401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 12/30/2023] [Accepted: 02/28/2024] [Indexed: 03/28/2024] Open
Abstract
The brain displays complex dynamics, including collective oscillations, and extensive research has been conducted to understand their generation. However, our understanding of how biological constraints influence these oscillations is incomplete. This study investigates the essential properties of neuronal networks needed to generate oscillations resembling those in the brain. A simple discrete-time model of interconnected excitable elements is developed, capable of closely resembling the complex oscillations observed in biological neural networks. In the model, synaptic connections remain active for a duration exceeding individual neuron activity. We show that the inhibitory synapses must exhibit longer activity than excitatory synapses to produce a diverse range of the dynamical states, including biologically plausible oscillations. Upon meeting this condition, the transition between different dynamical states can be controlled by external stochastic input to the neurons. The study provides a comprehensive explanation for the emergence of distinct dynamical states in neural networks based on specific parameters.
Collapse
Affiliation(s)
- Mozhgan Khanjanianpak
- Physics Department, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan 45137-66731, Iran
- Pasargad Institute for Advanced Innovative Solutions (PIAIS), Tehran 1991633357, Iran
| | - Nahid Azimi-Tafreshi
- Physics Department, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan 45137-66731, Iran
| | - Alireza Valizadeh
- Physics Department, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan 45137-66731, Iran
- Pasargad Institute for Advanced Innovative Solutions (PIAIS), Tehran 1991633357, Iran
| |
Collapse
|
13
|
Keshavarzi M, Mandke K, Macfarlane A, Parvez L, Gabrielczyk F, Wilson A, Goswami U. Atypical beta-band effects in children with dyslexia in response to rhythmic audio-visual speech. Clin Neurophysiol 2024; 160:47-55. [PMID: 38387402 DOI: 10.1016/j.clinph.2024.02.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 01/31/2024] [Accepted: 02/06/2024] [Indexed: 02/24/2024]
Abstract
OBJECTIVE Previous studies have reported atypical delta phase in children with dyslexia, and that delta phase modulates the amplitude of the beta-band response via delta-beta phase-amplitude coupling (PAC). Accordingly, the atypical delta-band effects in children with dyslexia may imply related atypical beta-band effects, particularly regarding delta-beta PAC. Our primary objective was to explore beta-band oscillations in children with and without dyslexia, to explore potentially atypical effects in the beta band in dyslexic children. METHODS We collected EEG data during a rhythmic speech paradigm from 51 children (21 control; 30 dyslexia). We then assessed beta-band phase entrainment, beta-band angular velocity, beta-band power responses and delta-beta PAC. RESULTS We found significant beta-band phase entrainment for control children but not for dyslexic children. Furthermore, children with dyslexia exhibited significantly faster beta-band angular velocity and significantly greater beta-band power. Delta-beta PAC was comparable in both groups. CONCLUSION Atypical beta-band effects were observed in children with dyslexia. However, delta-beta PAC was comparable in both dyslexic and control children. SIGNIFICANCE These findings offer further insights into the neurophysiological basis of atypical rhythmic speech processing by children with dyslexia, suggesting the involvement of a wide range of frequency bands.
Collapse
Affiliation(s)
- Mahmoud Keshavarzi
- Centre for Neuroscience in Education, Department of Psychology, University of Cambridge, Cambridge CB2 3EB, United Kingdom.
| | - Kanad Mandke
- Centre for Neuroscience in Education, Department of Psychology, University of Cambridge, Cambridge CB2 3EB, United Kingdom
| | - Annabel Macfarlane
- Centre for Neuroscience in Education, Department of Psychology, University of Cambridge, Cambridge CB2 3EB, United Kingdom
| | - Lyla Parvez
- Centre for Neuroscience in Education, Department of Psychology, University of Cambridge, Cambridge CB2 3EB, United Kingdom
| | - Fiona Gabrielczyk
- Centre for Neuroscience in Education, Department of Psychology, University of Cambridge, Cambridge CB2 3EB, United Kingdom
| | - Angela Wilson
- Centre for Neuroscience in Education, Department of Psychology, University of Cambridge, Cambridge CB2 3EB, United Kingdom
| | - Usha Goswami
- Centre for Neuroscience in Education, Department of Psychology, University of Cambridge, Cambridge CB2 3EB, United Kingdom
| |
Collapse
|
14
|
Easwaran K, Ramakrishnan K, Jeyabal SN. Classification of cognitive impairment using electroencephalography for clinical inspection. Proc Inst Mech Eng H 2024; 238:358-371. [PMID: 38366360 DOI: 10.1177/09544119241228912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2024]
Abstract
Impairment in cognitive skill though set-in due to various diseases, its progress is based on neuronal degeneration. In general, cognitive impairment (CI) is divided into three stages: mild, moderate and severe. Quantification of CI is important for deciding/changing therapy. Attempted in this work is to quantify electroencephalograph (EEG) signal and group it into four classes (controls and three stages of CI). After acquiring resting state EEG signal from the participants, non-local and local synchrony measures are derived from phase amplitude coupling and phase locking value. This totals to 160 features per individual for each task. Two types of classification networks are constructed. The first one is an artificial neural network (ANN) that takes derived features and gives a maximum accuracy of 85.11%. The second network is convolutional neural network (CNN) for which topographical images constructed from EEG features becomes the input dataset. The network is trained with 60% of data and then tested with remaining 40% of data. This process is performed in 5-fold technique, which yields an average accuracy of 94.75% with only 30 numbers of inputs for every individual. The result of the study shows that CNN outperforms ANN with a relatively lesser number of inputs. From this it can be concluded that this method proposes a simple task for acquiring EEG (which can be done by CI subjects) and quantifies CI stages with no overlapping between control and test group, thus making it possible for identifying early symptoms of CI.
Collapse
Affiliation(s)
- Karuppathal Easwaran
- Department of Biomedical Engineering, Rajalakshmi Engineering College, Chennai, Tamil Nadu, India
| | - Kalpana Ramakrishnan
- Department of Biomedical Engineering, Rajalakshmi Engineering College, Chennai, Tamil Nadu, India
| | | |
Collapse
|
15
|
Vardalakis N, Aussel A, Rougier NP, Wagner FB. A dynamical computational model of theta generation in hippocampal circuits to study theta-gamma oscillations during neurostimulation. eLife 2024; 12:RP87356. [PMID: 38354040 PMCID: PMC10942594 DOI: 10.7554/elife.87356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/16/2024] Open
Abstract
Neurostimulation of the hippocampal formation has shown promising results for modulating memory but the underlying mechanisms remain unclear. In particular, the effects on hippocampal theta-nested gamma oscillations and theta phase reset, which are both crucial for memory processes, are unknown. Moreover, these effects cannot be investigated using current computational models, which consider theta oscillations with a fixed amplitude and phase velocity. Here, we developed a novel computational model that includes the medial septum, represented as a set of abstract Kuramoto oscillators producing a dynamical theta rhythm with phase reset, and the hippocampal formation, composed of biophysically realistic neurons and able to generate theta-nested gamma oscillations under theta drive. We showed that, for theta inputs just below the threshold to induce self-sustained theta-nested gamma oscillations, a single stimulation pulse could switch the network behavior from non-oscillatory to a state producing sustained oscillations. Next, we demonstrated that, for a weaker theta input, pulse train stimulation at the theta frequency could transiently restore seemingly physiological oscillations. Importantly, the presence of phase reset influenced whether these two effects depended on the phase at which stimulation onset was delivered, which has practical implications for designing neurostimulation protocols that are triggered by the phase of ongoing theta oscillations. This novel model opens new avenues for studying the effects of neurostimulation on the hippocampal formation. Furthermore, our hybrid approach that combines different levels of abstraction could be extended in future work to other neural circuits that produce dynamical brain rhythms.
Collapse
Affiliation(s)
- Nikolaos Vardalakis
- University of Bordeaux, CNRS, IMNBordeauxFrance
- University of Bordeaux, INRIA, IMNBordeauxFrance
| | - Amélie Aussel
- University of Bordeaux, CNRS, IMNBordeauxFrance
- University of Bordeaux, INRIA, IMNBordeauxFrance
- University of Bordeaux, CNRS, Bordeaux INPTalenceFrance
| | - Nicolas P Rougier
- University of Bordeaux, CNRS, IMNBordeauxFrance
- University of Bordeaux, INRIA, IMNBordeauxFrance
- University of Bordeaux, CNRS, Bordeaux INPTalenceFrance
| | | |
Collapse
|
16
|
Weiner OM, O'Byrne J, Cross NE, Giraud J, Tarelli L, Yue V, Homer L, Walker K, Carbone R, Dang-Vu TT. Slow oscillation-spindle cross-frequency coupling predicts overnight declarative memory consolidation in older adults. Eur J Neurosci 2024; 59:662-685. [PMID: 37002805 DOI: 10.1111/ejn.15980] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 03/06/2023] [Accepted: 03/24/2023] [Indexed: 04/04/2023]
Abstract
Cross-frequency coupling (CFC) between brain oscillations during non-rapid-eye-movement (NREM) sleep (e.g. slow oscillations [SO] and spindles) may be a neural mechanism of overnight memory consolidation. Declines in CFC across the lifespan might accompany coinciding memory problems with ageing. However, there are few reports of CFC changes during sleep after learning in older adults, controlling for baseline effects. Our objective was to examine NREM CFC in healthy older adults, with an emphasis on spindle activity and SOs from frontal electroencephalogram (EEG), during a learning night after a declarative learning task, as compared to a baseline night without learning. Twenty-five older adults (M [SD] age = 69.12 [5.53] years; 64% female) completed a two-night study, with a pre- and post-sleep word-pair associates task completed on the second night. SO-spindle coupling strength and a measure of coupling phase distance from the SO up-state were both examined for between-night differences and associations with memory consolidation. Coupling strength and phase distance from the up-state peak were both stable between nights. Change in coupling strength between nights was not associated with memory consolidation, but a shift in coupling phase towards (vs. away from) the up-state peak after learning predicted better memory consolidation. Also, an exploratory interaction model suggested that associations between coupling phase closer to the up-state peak and memory consolidation may be moderated by higher (vs. lower) coupling strength. This study supports a role for NREM CFC in sleep-related memory consolidation in older adults.
Collapse
Affiliation(s)
- Oren M Weiner
- PERFORM Centre and Center for Studies in Behavioural Neurobiology, Department of Psychology and Department of Health, Kinesiology, and Applied Physiology, Concordia University, Montréal, Quebec, Canada
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, CIUSSS Centre-Sud-de-l'île-de-Montréal, Montréal, Quebec, Canada
| | - Jordan O'Byrne
- PERFORM Centre and Center for Studies in Behavioural Neurobiology, Department of Psychology and Department of Health, Kinesiology, and Applied Physiology, Concordia University, Montréal, Quebec, Canada
- Department of Psychology, Université de Montréal, Montréal, Quebec, Canada
| | - Nathan E Cross
- PERFORM Centre and Center for Studies in Behavioural Neurobiology, Department of Psychology and Department of Health, Kinesiology, and Applied Physiology, Concordia University, Montréal, Quebec, Canada
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, CIUSSS Centre-Sud-de-l'île-de-Montréal, Montréal, Quebec, Canada
| | - Julia Giraud
- Department of Neurosciences, Université de Montréal, Montréal, Quebec, Canada
| | - Lukia Tarelli
- PERFORM Centre and Center for Studies in Behavioural Neurobiology, Department of Psychology and Department of Health, Kinesiology, and Applied Physiology, Concordia University, Montréal, Quebec, Canada
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, CIUSSS Centre-Sud-de-l'île-de-Montréal, Montréal, Quebec, Canada
| | - Victoria Yue
- PERFORM Centre and Center for Studies in Behavioural Neurobiology, Department of Psychology and Department of Health, Kinesiology, and Applied Physiology, Concordia University, Montréal, Quebec, Canada
| | - Léa Homer
- PERFORM Centre and Center for Studies in Behavioural Neurobiology, Department of Psychology and Department of Health, Kinesiology, and Applied Physiology, Concordia University, Montréal, Quebec, Canada
| | - Katherine Walker
- PERFORM Centre and Center for Studies in Behavioural Neurobiology, Department of Psychology and Department of Health, Kinesiology, and Applied Physiology, Concordia University, Montréal, Quebec, Canada
| | - Roxanne Carbone
- PERFORM Centre and Center for Studies in Behavioural Neurobiology, Department of Psychology and Department of Health, Kinesiology, and Applied Physiology, Concordia University, Montréal, Quebec, Canada
| | - Thien Thanh Dang-Vu
- PERFORM Centre and Center for Studies in Behavioural Neurobiology, Department of Psychology and Department of Health, Kinesiology, and Applied Physiology, Concordia University, Montréal, Quebec, Canada
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, CIUSSS Centre-Sud-de-l'île-de-Montréal, Montréal, Quebec, Canada
- Department of Neurosciences, Université de Montréal, Montréal, Quebec, Canada
| |
Collapse
|
17
|
Li J, Li Z, Wang X, Liu Y, Wang S, Wang X, Li Y, Qin L. The Thalamocortical Mechanism Underlying the Generation and Regulation of the Auditory Steady-State Responses in Awake Mice. J Neurosci 2024; 44:e1166232023. [PMID: 37945348 PMCID: PMC10851679 DOI: 10.1523/jneurosci.1166-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Revised: 09/28/2023] [Accepted: 11/01/2023] [Indexed: 11/12/2023] Open
Abstract
The auditory steady-state response (ASSR) is a cortical oscillation induced by trains of 40 Hz acoustic stimuli. While the ASSR has been widely used in clinic measurement, the underlying neural mechanism remains poorly understood. In this study, we investigated the contribution of different stages of auditory thalamocortical pathway-medial geniculate body (MGB), thalamic reticular nucleus (TRN), and auditory cortex (AC)-to the generation and regulation of 40 Hz ASSR in C57BL/6 mice of both sexes. We found that the neural response synchronizing to 40 Hz sound stimuli was most prominent in the GABAergic neurons in the granular layer of AC and the ventral division of MGB (MGBv), which were regulated by optogenetic manipulation of TRN neurons. Behavioral experiments confirmed that disrupting TRN activity has a detrimental effect on the ability of mice to discriminate 40 Hz sounds. These findings revealed a thalamocortical mechanism helpful to interpret the results of clinical ASSR examinations.Significance Statement Our study contributes to clarifying the thalamocortical mechanisms underlying the generation and regulation of the auditory steady-state response (ASSR), which is commonly used in both clinical and neuroscience research to assess the integrity of auditory function. Combining a series of electrophysiological and optogenetic experiments, we demonstrate that the generation of cortical ASSR is dependent on the lemniscal thalamocortical projections originating from the ventral division of medial geniculate body to the GABAergic interneurons in the granule layer of the auditory cortex. Furthermore, the thalamocortical process for ASSR is strictly regulated by the activity of thalamic reticular nucleus (TRN) neurons. Behavioral experiments confirmed that dysfunction of TRN would cause a disruption of mice's behavioral performance in the auditory discrimination task.
Collapse
Affiliation(s)
- Jinhong Li
- Department of Physiology, China Medical University, Shenyang 110122, People's Republic of China
| | - Zijie Li
- Department of Physiology, China Medical University, Shenyang 110122, People's Republic of China
| | - Xueru Wang
- Department of Physiology, China Medical University, Shenyang 110122, People's Republic of China
| | - Yunhan Liu
- Department of Physiology, China Medical University, Shenyang 110122, People's Republic of China
| | - Shuai Wang
- Department of Physiology, China Medical University, Shenyang 110122, People's Republic of China
| | - Xuejiao Wang
- Department of Physiology, China Medical University, Shenyang 110122, People's Republic of China
| | - Yingna Li
- Department of Physiology, China Medical University, Shenyang 110122, People's Republic of China
| | - Ling Qin
- Department of Physiology, China Medical University, Shenyang 110122, People's Republic of China
| |
Collapse
|
18
|
Schreiner T, Petzka M, Staudigl T, Staresina BP. Respiration modulates sleep oscillations and memory reactivation in humans. Nat Commun 2023; 14:8351. [PMID: 38110418 PMCID: PMC10728072 DOI: 10.1038/s41467-023-43450-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 11/09/2023] [Indexed: 12/20/2023] Open
Abstract
The beneficial effect of sleep on memory consolidation relies on the precise interplay of slow oscillations and spindles. However, whether these rhythms are orchestrated by an underlying pacemaker has remained elusive. Here, we tested the relationship between respiration, which has been shown to impact brain rhythms and cognition during wake, sleep-related oscillations and memory reactivation in humans. We re-analysed an existing dataset, where scalp electroencephalography and respiration were recorded throughout an experiment in which participants (N = 20) acquired associative memories before taking a nap. Our results reveal that respiration modulates the emergence of sleep oscillations. Specifically, slow oscillations, spindles as well as their interplay (i.e., slow-oscillation_spindle complexes) systematically increase towards inhalation peaks. Moreover, the strength of respiration - slow-oscillation_spindle coupling is linked to the extent of memory reactivation (i.e., classifier evidence in favour of the previously learned stimulus category) during slow-oscillation_spindles. Our results identify a clear association between respiration and memory consolidation in humans and highlight the role of brain-body interactions during sleep.
Collapse
Affiliation(s)
- Thomas Schreiner
- Department of Psychology, Ludwig-Maximilians-Universität München, München, Germany.
| | - Marit Petzka
- Max Planck Institute for Human Development, Berlin, Germany
- Institute of Psychology, University of Hamburg, Hamburg, Germany
| | - Tobias Staudigl
- Department of Psychology, Ludwig-Maximilians-Universität München, München, Germany
| | - Bernhard P Staresina
- Department of Experimental Psychology, University of Oxford, Oxford, UK.
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK.
| |
Collapse
|
19
|
Yun R, Rembado I, Perlmutter SI, Rao RPN, Fetz EE. Local field potentials and single unit dynamics in motor cortex of unconstrained macaques during different behavioral states. Front Neurosci 2023; 17:1273627. [PMID: 38075283 PMCID: PMC10702227 DOI: 10.3389/fnins.2023.1273627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Accepted: 11/09/2023] [Indexed: 02/12/2024] Open
Abstract
Different sleep stages have been shown to be vital for a variety of brain functions, including learning, memory, and skill consolidation. However, our understanding of neural dynamics during sleep and the role of prominent LFP frequency bands remain incomplete. To elucidate such dynamics and differences between behavioral states we collected multichannel LFP and spike data in primary motor cortex of unconstrained macaques for up to 24 h using a head-fixed brain-computer interface (Neurochip3). Each 8-s bin of time was classified into awake-moving (Move), awake-resting (Rest), REM sleep (REM), or non-REM sleep (NREM) by using dimensionality reduction and clustering on the average spectral density and the acceleration of the head. LFP power showed high delta during NREM, high theta during REM, and high beta when the animal was awake. Cross-frequency phase-amplitude coupling typically showed higher coupling during NREM between all pairs of frequency bands. Two notable exceptions were high delta-high gamma and theta-high gamma coupling during Move, and high theta-beta coupling during REM. Single units showed decreased firing rate during NREM, though with increased short ISIs compared to other states. Spike-LFP synchrony showed high delta synchrony during Move, and higher coupling with all other frequency bands during NREM. These results altogether reveal potential roles and functions of different LFP bands that have previously been unexplored.
Collapse
Affiliation(s)
- Richy Yun
- Department of Bioengineering, University of Washington, Seattle, WA, United States
- Center for Neurotechnology, University of Washington, Seattle, WA, United States
- Washington National Primate Research Center, University of Washington, Seattle, WA, United States
| | - Irene Rembado
- Washington National Primate Research Center, University of Washington, Seattle, WA, United States
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, United States
| | - Steve I. Perlmutter
- Center for Neurotechnology, University of Washington, Seattle, WA, United States
- Washington National Primate Research Center, University of Washington, Seattle, WA, United States
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, United States
| | - Rajesh P. N. Rao
- Center for Neurotechnology, University of Washington, Seattle, WA, United States
- Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, United States
| | - Eberhard E. Fetz
- Department of Bioengineering, University of Washington, Seattle, WA, United States
- Center for Neurotechnology, University of Washington, Seattle, WA, United States
- Washington National Primate Research Center, University of Washington, Seattle, WA, United States
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, United States
| |
Collapse
|
20
|
Kiani MM, Heidari Beni MH, Aghajan H. Aberrations in temporal dynamics of cognitive processing induced by Parkinson's disease and Levodopa. Sci Rep 2023; 13:20195. [PMID: 37980451 PMCID: PMC10657430 DOI: 10.1038/s41598-023-47410-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 11/10/2023] [Indexed: 11/20/2023] Open
Abstract
The motor symptoms of Parkinson's disease (PD) have been shown to significantly improve by Levodopa. However, despite the widespread adoption of Levodopa as a standard pharmaceutical drug for the treatment of PD, cognitive impairments linked to PD do not show visible improvement with Levodopa treatment. Furthermore, the neuronal and network mechanisms behind the PD-induced cognitive impairments are not clearly understood. In this work, we aim to explain these cognitive impairments, as well as the ones exacerbated by Levodopa, through examining the differential dynamic patterns of the phase-amplitude coupling (PAC) during cognitive functions. EEG data recorded in an auditory oddball task performed by a cohort consisting of controls and a group of PD patients during both on and off periods of Levodopa treatment were analyzed to derive the temporal dynamics of the PAC across the brain. We observed distinguishing patterns in the PAC dynamics, as an indicator of information binding, which can explain the slower cognitive processing associated with PD in the form of a latency in the PAC peak time. Thus, considering the high-level connections between the hippocampus, the posterior and prefrontal cortices established through the dorsal and ventral striatum acting as a modulatory system, we posit that the primary issue with cognitive impairments of PD, as well as Levodopa's cognitive deficit side effects, can be attributed to the changes in temporal dynamics of dopamine release influencing the modulatory function of the striatum.
Collapse
Affiliation(s)
- Mohammad Mahdi Kiani
- Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
| | | | - Hamid Aghajan
- Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran.
| |
Collapse
|
21
|
Ortiz-Barajas MC, Guevara R, Gervain J. Neural oscillations and speech processing at birth. iScience 2023; 26:108187. [PMID: 37965146 PMCID: PMC10641252 DOI: 10.1016/j.isci.2023.108187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 08/29/2023] [Accepted: 10/09/2023] [Indexed: 11/16/2023] Open
Abstract
Are neural oscillations biologically endowed building blocks of the neural architecture for speech processing from birth, or do they require experience to emerge? In adults, delta, theta, and low-gamma oscillations support the simultaneous processing of phrasal, syllabic, and phonemic units in the speech signal, respectively. Using electroencephalography to investigate neural oscillations in the newborn brain we reveal that delta and theta oscillations differ for rhythmically different languages, suggesting that these bands underlie newborns' universal ability to discriminate languages on the basis of rhythm. Additionally, higher theta activity during post-stimulus as compared to pre-stimulus rest suggests that stimulation after-effects are present from birth.
Collapse
Affiliation(s)
- Maria Clemencia Ortiz-Barajas
- Integrative Neuroscience and Cognition Center, CNRS & Université Paris Cité, 45 rue des Saints-Pères, 75006 Paris, France
| | - Ramón Guevara
- Department of Physics and Astronomy, University of Padua, Via Marzolo 8, 35131 Padua, Italy
| | - Judit Gervain
- Integrative Neuroscience and Cognition Center, CNRS & Université Paris Cité, 45 rue des Saints-Pères, 75006 Paris, France
- Department of Developmental and Social Psychology, University of Padua, Via Venezia 8, 35131 Padua, Italy
| |
Collapse
|
22
|
Aiello G, Ledergerber D, Dubcek T, Stieglitz L, Baumann C, Polanìa R, Imbach L. Functional network dynamics between the anterior thalamus and the cortex in deep brain stimulation for epilepsy. Brain 2023; 146:4717-4735. [PMID: 37343140 DOI: 10.1093/brain/awad211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 05/10/2023] [Accepted: 06/08/2023] [Indexed: 06/23/2023] Open
Abstract
Owing to its unique connectivity profile with cortical brain regions, and its suggested role in the subcortical propagation of seizures, the anterior nucleus of the thalamus (ANT) has been proposed as a key deep brain stimulation (DBS) target in drug-resistant epilepsy. However, the spatio-temporal interaction dynamics of this brain structure, and the functional mechanisms underlying ANT DBS in epilepsy remain unknown. Here, we study how the ANT interacts with the neocortex in vivo in humans and provide a detailed neurofunctional characterization of mechanisms underlying the effectiveness of ANT DBS, aiming at defining intraoperative neural biomarkers of responsiveness to therapy, assessed at 6 months post-implantation as the reduction in seizure frequency. A cohort of 15 patients with drug-resistant epilepsy (n = 6 males, age = 41.6 ± 13.79 years) underwent bilateral ANT DBS implantation. Using intraoperative cortical and ANT simultaneous electrophysiological recordings, we found that the ANT is characterized by high amplitude θ (4-8 Hz) oscillations, mostly in its superior part. The strongest functional connectivity between the ANT and the scalp EEG was also found in the θ band in ipsilateral centro-frontal regions. Upon intraoperative stimulation in the ANT, we found a decrease in higher EEG frequencies (20-70 Hz) and a generalized increase in scalp-to-scalp connectivity. Crucially, we observed that responders to ANT DBS treatment were characterized by higher EEG θ oscillations, higher θ power in the ANT, and stronger ANT-to-scalp θ connectivity, highlighting the crucial role of θ oscillations in the dynamical network characterization of these structures. Our study provides a comprehensive characterization of the interaction dynamic between the ANT and the cortex, delivering crucial information to optimize and predict clinical DBS response in patients with drug-resistant epilepsy.
Collapse
Affiliation(s)
- Giovanna Aiello
- Decision Neuroscience Lab, Department of Health Sciences and Technology, ETH Zurich, 8092 Zurich, Switzerland
- Swiss Epilepsy Center (Klinik Lengg), 8008 Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, 8057 Zurich, Switzerland
| | - Debora Ledergerber
- Swiss Epilepsy Center (Klinik Lengg), 8008 Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, 8057 Zurich, Switzerland
| | - Tena Dubcek
- Decision Neuroscience Lab, Department of Health Sciences and Technology, ETH Zurich, 8092 Zurich, Switzerland
- Swiss Epilepsy Center (Klinik Lengg), 8008 Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, 8057 Zurich, Switzerland
| | - Lennart Stieglitz
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Christian Baumann
- Department of Neurology, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Rafael Polanìa
- Decision Neuroscience Lab, Department of Health Sciences and Technology, ETH Zurich, 8092 Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, 8057 Zurich, Switzerland
| | - Lukas Imbach
- Swiss Epilepsy Center (Klinik Lengg), 8008 Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, 8057 Zurich, Switzerland
| |
Collapse
|
23
|
Richter M, Cross ZR, Bornkessel-Schlesewsky I. Individual differences in information processing during sleep and wake predict sleep-based memory consolidation of complex rules. Neurobiol Learn Mem 2023; 205:107842. [PMID: 37848075 DOI: 10.1016/j.nlm.2023.107842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 09/03/2023] [Accepted: 10/13/2023] [Indexed: 10/19/2023]
Abstract
Memory is critical for many cognitive functions, from remembering facts, to learning complex environmental rules. While memory encoding occurs during wake, memory consolidation is associated with sleep-related neural activity. Further, research suggests that individual differences in alpha frequency during wake (∼7 - 13 Hz) modulate memory processes, with higher individual alpha frequency (IAF) associated with greater memory performance. However, the relationship between wake-related EEG individual differences, such as IAF, and sleep-related neural correlates of memory consolidation has been largely unexplored, particularly in a complex rule-based memory context. Here, we aimed to investigate whether wake-derived IAF and sleep neurophysiology interact to influence rule learning in a sample of 35 healthy adults (16 males; mean age = 25.4, range: 18 - 40). Participants learned rules of a modified miniature language prior to either 8hrs of sleep or wake, after which they were tested on their knowledge of the rules in a grammaticality judgement task. Results indicate that sleep neurophysiology and wake-derived IAF do not interact but modulate memory for complex linguistic rules separately. Phase-amplitude coupling between slow oscillations and spindles during non-rapid eye-movement (NREM) sleep also promoted memory for rules that were analogous to the canonical English word order. As an exploratory analysis, we found that rapid eye-movement (REM) sleep theta power at posterior regions interacts with IAF to predict rule learning and proportion of time in REM sleep predicts rule learning differentially depending on grammatical rule type. Taken together, the current study provides behavioural and electrophysiological evidence for a complex role of NREM and REM sleep neurophysiology and wake-derived IAF in the consolidation of rule-based information.
Collapse
Affiliation(s)
- Madison Richter
- Cognitive Neuroscience Laboratory - Australian Research Centre for Interactive and Virtual Environments, University of South Australia, Adelaide, Australia; College of Nursing and Health Sciences, Flinders University, Adelaide, Australia.
| | - Zachariah R Cross
- Cognitive Neuroscience Laboratory - Australian Research Centre for Interactive and Virtual Environments, University of South Australia, Adelaide, Australia; Department of Medical Social Sciences, Northwestern Feinberg School of Medicine, Chicago, IL, United States
| | - Ina Bornkessel-Schlesewsky
- Cognitive Neuroscience Laboratory - Australian Research Centre for Interactive and Virtual Environments, University of South Australia, Adelaide, Australia
| |
Collapse
|
24
|
Wang Z, Huang R, Yan Y, Luo Z, Zhao S, Wang B, Jin J, Xie L, Yin E. An Improved Canonical Correlation Analysis for EEG Inter-Band Correlation Extraction. Bioengineering (Basel) 2023; 10:1200. [PMID: 37892930 PMCID: PMC10604862 DOI: 10.3390/bioengineering10101200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 09/29/2023] [Accepted: 10/05/2023] [Indexed: 10/29/2023] Open
Abstract
(1) Background: Emotion recognition based on EEG signals is a rapidly growing and promising research field in affective computing. However, traditional methods have focused on single-channel features that reflect time-domain or frequency-domain information of the EEG, as well as bi-channel features that reveal channel-wise relationships across brain regions. Despite these efforts, the mechanism of mutual interactions between EEG rhythms under different emotional expressions remains largely unexplored. Currently, the primary form of information interaction between EEG rhythms is phase-amplitude coupling (PAC), which results in computational complexity and high computational cost. (2) Methods: To address this issue, we proposed a method of extracting inter-bands correlation (IBC) features via canonical correlation analysis (CCA) based on differential entropy (DE) features. This approach eliminates the need for surrogate testing and reduces computational complexity. (3) Results: Our experiments verified the effectiveness of IBC features through several tests, demonstrating that the more correlated features between EEG frequency bands contribute more to emotion classification accuracy. We then fused IBC features and traditional DE features at the decision level, which significantly improved the accuracy of emotion recognition on the SEED dataset and the local CUMULATE dataset compared to using a single feature alone. (4) Conclusions: These findings suggest that IBC features are a promising approach to promoting emotion recognition accuracy. By exploring the mutual interactions between EEG rhythms under different emotional expressions, our method can provide valuable insights into the underlying mechanisms of emotion processing and improve the performance of emotion recognition systems.
Collapse
Affiliation(s)
- Zishan Wang
- School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200030, China; (Z.W.); (B.W.); (J.J.)
- Defense Innovation Institute, Academy of Military Sciences (AMS), Beijing 100000, China; (Z.L.); (S.Z.); (L.X.); (E.Y.)
- Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin 300450, China;
| | - Ruqiang Huang
- Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin 300450, China;
| | - Ye Yan
- Defense Innovation Institute, Academy of Military Sciences (AMS), Beijing 100000, China; (Z.L.); (S.Z.); (L.X.); (E.Y.)
- Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin 300450, China;
| | - Zhiguo Luo
- Defense Innovation Institute, Academy of Military Sciences (AMS), Beijing 100000, China; (Z.L.); (S.Z.); (L.X.); (E.Y.)
- Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin 300450, China;
| | - Shaokai Zhao
- Defense Innovation Institute, Academy of Military Sciences (AMS), Beijing 100000, China; (Z.L.); (S.Z.); (L.X.); (E.Y.)
- Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin 300450, China;
| | - Bei Wang
- School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200030, China; (Z.W.); (B.W.); (J.J.)
| | - Jing Jin
- School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200030, China; (Z.W.); (B.W.); (J.J.)
| | - Liang Xie
- Defense Innovation Institute, Academy of Military Sciences (AMS), Beijing 100000, China; (Z.L.); (S.Z.); (L.X.); (E.Y.)
- Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin 300450, China;
| | - Erwei Yin
- Defense Innovation Institute, Academy of Military Sciences (AMS), Beijing 100000, China; (Z.L.); (S.Z.); (L.X.); (E.Y.)
- Tianjin Artificial Intelligence Innovation Center (TAIIC), Tianjin 300450, China;
| |
Collapse
|
25
|
Xu J, Hu L, Qiao R, Hu Y, Tian Y. Music-emotion EEG coupling effects based on representational similarity. J Neurosci Methods 2023; 398:109959. [PMID: 37661055 DOI: 10.1016/j.jneumeth.2023.109959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 08/05/2023] [Accepted: 08/30/2023] [Indexed: 09/05/2023]
Abstract
BACKGROUND Music can evoke intense emotions and music emotion is a complex cognitive process. However, we know little about the cognitive mechanisms underlying these processes, and there are significant individual differences in the emotional responses to the same musical stimuli. NEW METHOD We used the inter-subject representational similarity analysis (IS-RSA) method to investigate the shared music emotion responses across multiple participants. In addition, we extended IS-RSA to estimate the group cross-frequency coupling effects of music emotion. Based on the cross-frequency coupling IS-RSA, we analyzed the differences in cross-frequency coupling patterns under different music emotions using MI. Comparison of existing methods: most current IS-RSA analyses focus on within-frequency band analysis. However, the cognitive processing of music emotion involves not only activation and brain network connections differences within frequency bands but also information communication between frequency bands. RESULTS The results of the within-frequency band IS-RSA analysis showed that the theta and gamma frequency bands play important roles in the inter-participant consistency of music emotion. The inter-frequency band IS-RSA analysis showed that the theta-beta coupling pattern exhibited stronger inter-participant consistency compared to the theta-gamma coupling pattern, and the theta-beta coupling had significant consistent representation across various music conditions. Through the significant regions of cross-frequency coupling representation similarity analysis, we performed phase-amplitude coupling analysis on FC4-C6 and FC4-Pz connections. For the theta-beta coupling pattern, we found that the MI of these two connections exhibited different coupling patterns under different music conditions, and they showed a significant decrease compared to the baseline period.
Collapse
Affiliation(s)
- Jiayang Xu
- School of Bioinformatics, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
| | - Liangliang Hu
- School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China; West China institute of children's brain and cognition, Chongqing university of education, Chongqing 400065, China
| | - Rui Qiao
- School of Bioinformatics, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
| | - Yilin Hu
- School of Bioinformatics, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
| | - Yin Tian
- School of Bioinformatics, Chongqing University of Posts and Telecommunications, Chongqing 400065, China; School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China; Institute for Advanced Sciences,Chongqing University of Posts and Telecommunications, Chongqing 400065, China; Chongqing Institute for Brain and Intelligence, Guangyang Bay Laboratory, Chongqing 400064, China.
| |
Collapse
|
26
|
Iwane F, Sobolewski A, Chavarriaga R, Millán JDR. EEG error-related potentials encode magnitude of errors and individual perceptual thresholds. iScience 2023; 26:107524. [PMID: 37636067 PMCID: PMC10448161 DOI: 10.1016/j.isci.2023.107524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 06/15/2023] [Accepted: 07/28/2023] [Indexed: 08/29/2023] Open
Abstract
Error-related potentials (ErrPs) are a prominent electroencephalogram (EEG) correlate of performance monitoring, and so crucial for learning and adapting our behavior. It is poorly understood whether ErrPs encode further information beyond error awareness. We report an experiment with sixteen participants over three sessions in which occasional visual rotations of varying magnitude occurred during a cursor reaching task. We designed a brain-computer interface (BCI) to detect ErrPs that provided real-time feedback. The individual ErrP-BCI decoders exhibited good transfer across sessions and scalability over the magnitude of errors. A non-linear relationship between the ErrP-BCI output and the magnitude of errors predicts individual perceptual thresholds to detect errors. We also reveal theta-gamma oscillatory coupling that co-varied with the magnitude of the required adjustment. Our findings open new avenues to probe and extend current theories of performance monitoring by incorporating continuous human interaction tasks and analysis of the ErrP complex rather than individual peaks.
Collapse
Affiliation(s)
- Fumiaki Iwane
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX 78712, USA
- Department of Neurology, The University of Texas at Austin, Austin, TX 78712, USA
- Learning Algorithms and Systems Laboratory (LASA), École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Aleksander Sobolewski
- Wyss Center for Bio and Neuroengineering, Campus Biotech, 1202 Genève, Switzerland
- École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, 1202 Genève, Switzerland
| | - Ricardo Chavarriaga
- École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, 1202 Genève, Switzerland
- Centre for Artificial Intelligence, Zurich University of Applied Sciences (ZHAW), 8401 Winterthur, Switzerland
| | - José del R. Millán
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX 78712, USA
- Department of Neurology, The University of Texas at Austin, Austin, TX 78712, USA
- École Polytechnique Fédérale de Lausanne (EPFL), Campus Biotech, 1202 Genève, Switzerland
- Mulva Clinic for the Neurosciences, The University of Texas at Austin, Austin, TX 78712, USA
| |
Collapse
|
27
|
Rodheim K, Kainec K, Noh E, Jones B, Spencer RMC. Emotional memory consolidation during sleep is associated with slow oscillation-spindle coupling strength in young and older adults. Learn Mem 2023; 30:237-244. [PMID: 37770106 PMCID: PMC10547370 DOI: 10.1101/lm.053685.122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Accepted: 08/29/2023] [Indexed: 10/03/2023]
Abstract
Emotional memories are processed during sleep; however, the specific mechanisms are unclear. Understanding such mechanisms may provide critical insight into preventing and treating mood disorders. Consolidation of neutral memories is associated with the coupling of NREM sleep slow oscillations (SOs) and sleep spindles (SPs). Whether SO-SP coupling is likewise involved in emotional memory processing is unknown. Furthermore, there is an age-related emotional valence bias such that sleep consolidates and preserves reactivity to negative but not positive emotional memories in young adults and positive but not negative emotional memories in older adults. If SO-SP coupling contributes to the effect of sleep on emotional memory, then it may selectively support negative memory in young adults and positive memory in older adults. To address these questions, we examined whether emotional memory recognition and overnight change in emotional reactivity were associated with the strength of SO-SP coupling in young (n = 22) and older (n = 32) adults. In younger adults, coupling strength predicted negative but not positive emotional memory performance after sleep. In contrast, coupling strength predicted positive but not negative emotional memory performance after sleep in older adults. Coupling strength was not associated with emotional reactivity in either age group. Our findings suggest that SO-SP coupling may play a mechanistic role in sleep-dependent consolidation of emotional memories.
Collapse
Affiliation(s)
- Katrina Rodheim
- Neuroscience and Behavior Program, University of Massachusetts Amherst, Amherst, Massachusetts 01003, USA
| | - Kyle Kainec
- Neuroscience and Behavior Program, University of Massachusetts Amherst, Amherst, Massachusetts 01003, USA
- Institute for Applied Life Sciences, University of Massachusetts Amherst, Amherst, Massachusetts 01003, USA
| | - Eunsol Noh
- Neuroscience and Behavior Program, University of Massachusetts Amherst, Amherst, Massachusetts 01003, USA
| | - Bethany Jones
- Neuroscience and Behavior Program, University of Massachusetts Amherst, Amherst, Massachusetts 01003, USA
- Institute for Applied Life Sciences, University of Massachusetts Amherst, Amherst, Massachusetts 01003, USA
| | - Rebecca M C Spencer
- Neuroscience and Behavior Program, University of Massachusetts Amherst, Amherst, Massachusetts 01003, USA
- Institute for Applied Life Sciences, University of Massachusetts Amherst, Amherst, Massachusetts 01003, USA
- Developmental Sciences Program, University of Massachusetts Amherst, Amherst, Massachusetts 01003, USA
| |
Collapse
|
28
|
Rustamov N, Souders L, Sheehan L, Carter A, Leuthardt EC. IpsiHand Brain-Computer Interface Therapy Induces Broad Upper Extremity Motor Recovery in Chronic Stroke. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.26.23294320. [PMID: 37693482 PMCID: PMC10491278 DOI: 10.1101/2023.08.26.23294320] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Background and Purpose Chronic hemiparetic stroke patients have very limited benefits from current therapies. Brain-computer interface (BCI) engaging the unaffected hemisphere has emerged as a promising novel therapeutic approach for chronic stroke rehabilitation. This study investigated the effectiveness of the IpsiHand System, a contralesionally-controlled BCI therapy in chronic stroke patients with impaired upper extremity motor function. We further explored neurophysiological features of motor recovery affected by BCI. We hypothesized that BCI therapy would induce a broad motor recovery in the upper extremity (proximal and distal), and there would be corresponding changes in baseline theta and gamma oscillations, which have been shown to be associated with motor recovery. Methods Thirty chronic hemiparetic stroke patients performed a therapeutic BCI task for 12 weeks. Motor function assessment data and resting state electroencephalogram (EEG) signals were acquired before initiating BCI therapy and across BCI therapy sessions. The Upper Extremity Fugl-Meyer assessment (UEFM) served as a primary motor outcome assessment tool. Theta-gamma cross-frequency coupling (CFC) was computed and correlated with motor recovery. Results Chronic stroke patients achieved significant motor improvement with BCI therapy. We found significant improvement in both proximal and distal upper extremity motor function. Importantly, motor function improvement was independent of Botox application. Theta-gamma CFC enhanced bilaterally over the C3 and C4 motor electrodes following BCI therapy. We observed significant positive correlations between motor recovery and theta gamma CFC increase across BCI therapy sessions. Conclusions BCI therapy resulted in significant motor function improvement across the proximal and distal upper extremities of patients. This therapy was significantly correlated with changes in baseline cortical dynamics, specifically theta-gamma CFC increases in both the right and left motor regions. This may represent rhythm-specific cortical oscillatory mechanism for BCI-driven motor rehabilitation in chronic stroke patients.
Collapse
|
29
|
李 凯, 卢 俊, 余 仁, 张 锐, 陈 明. [Alterations of β-γ coupling of scalp electroencephalography during epilepsy]. SHENG WU YI XUE GONG CHENG XUE ZA ZHI = JOURNAL OF BIOMEDICAL ENGINEERING = SHENGWU YIXUE GONGCHENGXUE ZAZHI 2023; 40:700-708. [PMID: 37666760 PMCID: PMC10477402 DOI: 10.7507/1001-5515.202212024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Revised: 05/10/2023] [Indexed: 09/06/2023]
Abstract
Uncovering the alterations of neural interactions within the brain during epilepsy is important for the clinical diagnosis and treatment. Previous studies have shown that the phase-amplitude coupling (PAC) can be used as a potential biomarker for locating epileptic zones and characterizing the transition of epileptic phases. However, in contrast to the θ-γ coupling widely investigated in epilepsy, few studies have paid attention to the β-γ coupling, as well as its potential applications. In the current study, we use the modulation index (MI) to calculate the scalp electroencephalography (EEG)-based β-γ coupling and investigate the corresponding changes during different epileptic phases. The results show that the β-γ coupling of each brain region changes with the evolution of epilepsy, and in several brain regions, the β-γ coupling decreases during the ictal period but increases in the post-ictal period, where the differences are statistically significant. Moreover, the alterations of β-γ coupling between different brain regions can also be observed, and the strength of β-γ coupling increases in the post-ictal period, where the differences are also significant. Taken together, these findings not only contribute to understanding neural interactions within the brain during the evolution of epilepsy, but also provide a new insight into the clinical treatment.
Collapse
Affiliation(s)
- 凯杰 李
- 郑州大学 电气与信息工程学院 河南省脑科学与脑机接口技术重点实验室(郑州 450001)Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, P. R. China
| | - 俊峰 卢
- 郑州大学 电气与信息工程学院 河南省脑科学与脑机接口技术重点实验室(郑州 450001)Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, P. R. China
| | - 仁萍 余
- 郑州大学 电气与信息工程学院 河南省脑科学与脑机接口技术重点实验室(郑州 450001)Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, P. R. China
- 郑州大学 电气与信息工程学院 中医药智能科学与工程技术研究中心(郑州 450001)Research Center for Intelligent Science and Engineering Technology of Traditional Chinese Medicine, School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, P. R. China
| | - 锐 张
- 郑州大学 电气与信息工程学院 河南省脑科学与脑机接口技术重点实验室(郑州 450001)Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, P. R. China
- 郑州大学 电气与信息工程学院 中医药智能科学与工程技术研究中心(郑州 450001)Research Center for Intelligent Science and Engineering Technology of Traditional Chinese Medicine, School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, P. R. China
| | - 明明 陈
- 郑州大学 电气与信息工程学院 河南省脑科学与脑机接口技术重点实验室(郑州 450001)Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, P. R. China
- 郑州大学 电气与信息工程学院 中医药智能科学与工程技术研究中心(郑州 450001)Research Center for Intelligent Science and Engineering Technology of Traditional Chinese Medicine, School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, P. R. China
| |
Collapse
|
30
|
Chen X, Li Y, Li R, Yuan X, Liu M, Zhang W, Li Y. Multiple cross-frequency coupling analysis of resting-state EEG in patients with mild cognitive impairment and Alzheimer's disease. Front Aging Neurosci 2023; 15:1142085. [PMID: 37600515 PMCID: PMC10436577 DOI: 10.3389/fnagi.2023.1142085] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 07/11/2023] [Indexed: 08/22/2023] Open
Abstract
Introduction Electroencephalographic (EEG) abnormalities are seen in patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI) with characteristic features of cognitive impairment. The most common findings of EEG features in AD and MCI patients are increased relative power of slow oscillations (delta and theta rhythms) and decreased relative power of fast oscillations (alpha, beta and gamma rhythms). However, impairments in cognitive processes in AD and MCI are not sufficiently reflected by brain oscillatory activity in a particular frequency band. MCI patients are at high risk of progressing to AD. Cross-frequency coupling (CFC), which refers to coupling between different frequency bands, is a crucial tool for comprehending changes in brain oscillations and cognitive performance. CFC features exhibit some specificity in patients with AD and MCI, but a comparison between CFC features in individuals with these disorders is still lacking. The aim of this study was to explore changes in CFC properties in MCI and AD and to explore the relationship between CFC properties and multiple types of cognitive functional performance. Methods We recorded resting-state EEG (rsEEG) signals in 46 MCI patients, 43 AD patients, and 43 cognitively healthy controls (HCs) and analyzed the changes in CFC as well as the relationship between CFC and scores on clinical tests of cognitive function. Results and discussion Multiple couplings between low-frequency oscillations and high-frequency oscillations were found to be significantly enhanced in AD patients compared to those of HCs and MCI, while delta-gamma as well as theta-gamma couplings in the right temporal and parietal lobes were significantly enhanced in MCI patients compared to HCs. Moreover, theta-gamma coupling in the right temporal lobe tended to be stronger in MCI patients than in HCs, and it was stronger in AD than in MCI. Multiple CFC properties were found to correlate significantly with various cognitive domains, especially the memory function domain. Overall, these findings suggest that AD and MCI patients must use more neural resources to maintain a resting brain state and that alterations in theta-gamma coupling in the temporal lobe become progressively obvious during disease progression and are likely to be a valuable indicator of MCI and AD pathology.
Collapse
Affiliation(s)
- Xi Chen
- School of Communication and Information Engineering, Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, China
| | - Yingjie Li
- College of International Education, Shanghai University, Shanghai, China
- School of Life Science, Institute of Biomedical Engineering, Shanghai University, Shanghai, China
| | - Renren Li
- Department of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Xiao Yuan
- Department of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Meng Liu
- Department of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
- Department of Neurology, Shanghai Changhai Hospital, the Second Military Medical University, Shanghai, China
| | - Wei Zhang
- Department of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Yunxia Li
- Department of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
- Department of Neurology, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, China
| |
Collapse
|
31
|
Jiang X, Liu X, Liu Y, Wang Q, Li B, Zhang L. Epileptic seizures detection and the analysis of optimal seizure prediction horizon based on frequency and phase analysis. Front Neurosci 2023; 17:1191683. [PMID: 37260846 PMCID: PMC10228742 DOI: 10.3389/fnins.2023.1191683] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Accepted: 04/14/2023] [Indexed: 06/02/2023] Open
Abstract
Changes in the frequency composition of the human electroencephalogram are associated with the transitions to epileptic seizures. Cross-frequency coupling (CFC) is a measure of neural oscillations in different frequency bands and brain areas, and specifically phase-amplitude coupling (PAC), a form of CFC, can be used to characterize these dynamic transitions. In this study, we propose a method for seizure detection and prediction based on frequency domain analysis and PAC combined with machine learning. We analyzed two databases, the Siena Scalp EEG database and the CHB-MIT database, and used the frequency features and modulation index (MI) for time-dependent quantification. The extracted features were fed to a random forest classifier for classification and prediction. The seizure prediction horizon (SPH) was also analyzed based on the highest-performing band to maximize the time for intervention and treatment while ensuring the accuracy of the prediction. Under comprehensive consideration, the results demonstrate that better performance could be achieved at an interval length of 5 min with an average accuracy of 85.71% and 95.87% for the Siena Scalp EEG database and the CHB-MIT database, respectively. As for the adult database, the combination of PAC analysis and classification can be of significant help for seizure detection and prediction. It suggests that the rarely used SPH also has a major impact on seizure detection and prediction and further explorations for the application of PAC are needed.
Collapse
Affiliation(s)
- Ximiao Jiang
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China
| | - Xiaotong Liu
- Department of Dynamics and Control, Beihang University, Beijing, China
| | - Youjun Liu
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China
| | - Qingyun Wang
- Department of Dynamics and Control, Beihang University, Beijing, China
| | - Bao Li
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China
| | - Liyuan Zhang
- Department of Biomedical Engineering, Faculty of Environment and Life, Beijing University of Technology, Beijing, China
| |
Collapse
|
32
|
Gauthier-Umaña C, Valderrama M, Múnera A, Nava-Mesa MO. BOARD-FTD-PACC: a graphical user interface for the synaptic and cross-frequency analysis derived from neural signals. Brain Inform 2023; 10:12. [PMID: 37155028 PMCID: PMC10167074 DOI: 10.1186/s40708-023-00191-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 04/01/2023] [Indexed: 05/10/2023] Open
Abstract
In order to understand the link between brain functional states and behavioral/cognitive processes, the information carried in neural oscillations can be retrieved using different analytic techniques. Processing these different bio-signals is a complex, time-consuming, and often non-automatized process that requires customization, due to the type of signal acquired, acquisition method implemented, and the objectives of each individual research group. To this end, a new graphical user interface (GUI), named BOARD-FTD-PACC, was developed and designed to facilitate the visualization, quantification, and analysis of neurophysiological recordings. BOARD-FTD-PACC provides different and customizable tools that facilitate the task of analyzing post-synaptic activity and complex neural oscillatory data, mainly cross-frequency analysis. It is a flexible and user-friendly software that can be used by a wide range of users to extract valuable information from neurophysiological signals such as phase-amplitude coupling and relative power spectral density, among others. BOARD-FTD-PACC allows researchers to select, in the same open-source GUI, different approaches and techniques that will help promote a better understanding of synaptic and oscillatory activity in specific brain structures with or without stimulation.
Collapse
Affiliation(s)
- Cécile Gauthier-Umaña
- Grupo de Investigación en Neurociencias (NeURos), Centro de Neurociencias Neurovitae-UR, Instituto de Medicina Traslacional (IMT), Escuela de Medicina y Ciencias de la Salud, Universidad del Rosario, Bogotá, Colombia
- Department of Systems Engineering, Pontificia Universidad Javeriana, Bogota, Colombia
| | - Mario Valderrama
- Department of Biomedical Engineering, Universidad de Los Andes, Bogotá, Colombia
| | - Alejandro Múnera
- Behavioral Neurophysiology Laboratory, Physiological Sciences Department, School of Medicine, Universidad Nacional de Colombia, Bogotá, Colombia
| | - Mauricio O Nava-Mesa
- Grupo de Investigación en Neurociencias (NeURos), Centro de Neurociencias Neurovitae-UR, Instituto de Medicina Traslacional (IMT), Escuela de Medicina y Ciencias de la Salud, Universidad del Rosario, Bogotá, Colombia.
| |
Collapse
|
33
|
Zakaria L, Desowska A, Berde CB, Cornelissen L. Electroencephalographic delta and alpha oscillations reveal phase-amplitude coupling in paediatric patients undergoing sevoflurane-based general anaesthesia. Br J Anaesth 2023; 130:595-602. [PMID: 36922266 DOI: 10.1016/j.bja.2023.01.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 01/03/2023] [Accepted: 01/28/2023] [Indexed: 03/14/2023] Open
Abstract
BACKGROUND Sevoflurane-induced anaesthesia generates frontal alpha oscillations as early as 6 months of age, whereas strong delta oscillations are present at birth. In adults, delta oscillations and alpha oscillations are coupled: the phase of delta waves modulates the amplitude of alpha oscillations in a phenomenon known as phase-amplitude coupling. We hypothesise that delta-alpha phase-amplitude coupling exists in young children and is a feature of sevoflurane-based general anaesthesia distinct from emergence after anaesthesia. METHODS Electroencephalographic data from 31 paediatric patients aged 10 months to 3 yr undergoing elective surgery with sevoflurane-based anaesthesia were analysed retrospectively. Delta-alpha phase-amplitude coupling was evaluated during maintenance of anaesthesia and during emergence. RESULTS Delta-alpha phase-amplitude coupling was observed in the study population. Strength of phase-amplitude coupling, represented by the delta-alpha mean amplitude vector, was greater during general anaesthesia than during emergence (Wilcoxon paired signed-rank test, Z=3.107, P=0.002). Frontal alpha amplitude during anaesthesia was not uniformly distributed across all delta phases. During general anaesthesia, alpha power was restricted to the positive phase of the delta wave (omnibus circular uniformity, general anaesthesia: P<0.001, mean phase: 114º; 99% confidence interval: 90º-139º; emergence: P=0.35, mean phase 181º, 99% confidence interval: 110º-253º). CONCLUSIONS Sevoflurane-based anaesthesia is associated with delta-alpha phase-amplitude coupling in paediatric patients. These findings improve our understanding of cortical dynamics in children undergoing general anaesthesia, which might improve paediatric intraoperative depth of anaesthesia monitoring techniques.
Collapse
Affiliation(s)
- Luai Zakaria
- Department of Anesthesiology, Perioperative & Pain Medicine, Brigham & Women's Hospital, Boston, USA; Harvard Medical School, Boston, MA, USA; Department of Anesthesiology, Critical Care & Pain Medicine, Boston Children's Hospital, Boston, MA, USA
| | - Adela Desowska
- Harvard Medical School, Boston, MA, USA; Department of Anesthesiology, Critical Care & Pain Medicine, Boston Children's Hospital, Boston, MA, USA
| | - Charles B Berde
- Harvard Medical School, Boston, MA, USA; Department of Anesthesiology, Critical Care & Pain Medicine, Boston Children's Hospital, Boston, MA, USA
| | - Laura Cornelissen
- Harvard Medical School, Boston, MA, USA; Department of Anesthesiology, Critical Care & Pain Medicine, Boston Children's Hospital, Boston, MA, USA.
| |
Collapse
|
34
|
Scherer M, Wang T, Guggenberger R, Milosevic L, Gharabaghi A. Direct modulation index: A measure of phase amplitude coupling for neurophysiology data. Hum Brain Mapp 2023; 44:1862-1867. [PMID: 36579658 PMCID: PMC9980882 DOI: 10.1002/hbm.26190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 11/22/2022] [Accepted: 12/11/2022] [Indexed: 12/30/2022] Open
Abstract
Neural communication across different spatial and temporal scales is a topic of great interest in clinical and basic science. Phase-amplitude coupling (PAC) has attracted particular interest due to its functional role in a wide range of cognitive and motor functions. Here, we introduce a novel measure termed the direct modulation index (dMI). Based on the classical modulation index, dMI provides an estimate of PAC that is (1) bound to an absolute interval between 0 and +1, (2) resistant against noise, and (3) reliable even for small amounts of data. To highlight the properties of this newly-proposed measure, we evaluated dMI by comparing it to the classical modulation index, mean vector length, and phase-locking value using simulated data. We ascertained that dMI provides a more accurate estimate of PAC than the existing methods and that is resilient to varying noise levels and signal lengths. As such, dMI permits a reliable investigation of PAC, which may reveal insights crucial to our understanding of functional brain architecture in key contexts such as behaviour and cognition. A Python toolbox that implements dMI and other measures of PAC is freely available at https://github.com/neurophysiological-analysis/FiNN.
Collapse
Affiliation(s)
- Maximilian Scherer
- Institute for Neuromodulation and NeurotechnologyUniversity Hospital and University of TübingenTübingenGermany
- Krembil Brain InstituteUniversity Health NetworkTorontoCanada
- Institute for Biomedical EngineeringUniversity of TorontoTorontoCanada
| | - Tianlu Wang
- Institute for Neuromodulation and NeurotechnologyUniversity Hospital and University of TübingenTübingenGermany
| | - Robert Guggenberger
- Institute for Neuromodulation and NeurotechnologyUniversity Hospital and University of TübingenTübingenGermany
| | - Luka Milosevic
- Institute for Neuromodulation and NeurotechnologyUniversity Hospital and University of TübingenTübingenGermany
- Krembil Brain InstituteUniversity Health NetworkTorontoCanada
- Institute for Biomedical EngineeringUniversity of TorontoTorontoCanada
| | - Alireza Gharabaghi
- Institute for Neuromodulation and NeurotechnologyUniversity Hospital and University of TübingenTübingenGermany
| |
Collapse
|
35
|
Davis P, Takach K, Maski K, Levin A. A circuit-level biomarker of Rett syndrome based on ectopic phase-amplitude coupling during slow-wave-sleep. Cereb Cortex 2023; 33:2559-2572. [PMID: 35640651 DOI: 10.1093/cercor/bhac226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Revised: 05/01/2022] [Accepted: 05/02/2022] [Indexed: 11/13/2022] Open
Abstract
Rett syndrome (RTT) is a neurodevelopmental disorder characterized by loss of purposeful hand use and spoken language following an initial period of normal development. Although much is known about the genetic and molecular underpinnings of RTT, less is known about the circuit-level etiopathology. Coupling of oscillations during slow-wave-sleep (SWS) underlies important neurocognitive processes in adulthood, yet its emergence has yet to be described in early typical development (TD) or in RTT. We therefore addressed these unknowns by describing SWS cross-frequency coupling in both RTT and early TD using a retrospective study design. We found that in TD, phase-amplitude coupling (PAC) during SWS was dominated by coupling of slow-wave (0.5-2 Hz) phase to theta amplitude (5-8 Hz, "SW:T") as well as slow-wave to spindle-range (12-15 Hz, "SW:S"). Coupling exhibited characteristic vertex-prominent spatial topography, which emerged during an early developmental window. This topography failed to develop in patients with RTT due to persistent ectopic coupling. Furthermore, we found that subtypes of RTT exhibit distinct PAC topographic profiles, and that ectopic PAC correlates with clinical severity. These findings suggest that altered PAC dynamics and spatial organization during SWS may underlie the circuit-level pathophysiology of RTT and suggest that ectopic coupling may contribute to RTT pathogenesis.
Collapse
Affiliation(s)
- Patrick Davis
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - Kyle Takach
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States
- Division of Developmental Medicine, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - Kiran Maski
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - April Levin
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, United States
| |
Collapse
|
36
|
Zhang W, Liu W, Liu S, Su F, Kang X, Ke Y, Ming D. Altered fronto-central theta-gamma coupling in major depressive disorder during auditory steady-state responses. Clin Neurophysiol 2023; 146:65-76. [PMID: 36535093 DOI: 10.1016/j.clinph.2022.11.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Revised: 09/19/2022] [Accepted: 11/27/2022] [Indexed: 12/09/2022]
Abstract
OBJECTIVE Neural oscillations during sensory and cognitive events interact at different frequencies. However, such evidence in major depressive disorder (MDD) remains scarce. We explored the possible abnormal neural oscillations in MDD by analyzing theta-phase/gamma-amplitude coupling (TGC). METHODS Resting-state and auditory steady-state response (ASSR) electroencephalography recordings were obtained from 35 first-episode MDD and 35 healthy controls (HCs). TGC during rest, ASSR stimulation, and ASSR baseline between and within groups were analyzed to evaluate MDD alterations. Receiver operating characteristic (ROC), TGC comparison between MDD severity subgroups (mild, moderate, major), and correlations were investigated to determine the potential use of altered TGC for identifying MDD. RESULTS In MDD, left fronto-central TGC decreased during stimulation, while right fronto-central TGC increased during baseline. The area under ROC curve for altered TGC was 0.863. Furthermore, during stimulation, moderate and major MDD groups exhibited significantly lower TGC than mild group, and fronto-central TGC was negatively correlated with depression scale scores. CONCLUSIONS Our results provided the first evidence for an abnormal TGC response of fronto-central regions in MDD during an ASSR task. Importantly, altered TGC may be promising biomarkers of MDD. SIGNIFICANCE Our findings enhance the understanding of physiological mechanisms underlying MDD and aid in its clinical diagnosis.
Collapse
Affiliation(s)
- Wenquan Zhang
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Wei Liu
- Children's Hospital, Tianjin University, Tianjin, China
| | - Shuang Liu
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.
| | - Fangyue Su
- School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Xianyun Kang
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Yufeng Ke
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Dong Ming
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China; School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| |
Collapse
|
37
|
Gordillo D, Ramos da Cruz J, Moreno D, Garobbio S, Herzog MH. Do we really measure what we think we are measuring? iScience 2023; 26:106017. [PMID: 36844457 PMCID: PMC9947309 DOI: 10.1016/j.isci.2023.106017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 12/18/2022] [Accepted: 01/16/2023] [Indexed: 01/21/2023] Open
Abstract
Tests used in the empirical sciences are often (implicitly) assumed to be representative of a given research question in the sense that similar tests should lead to similar results. Here, we show that this assumption is not always valid. We illustrate our argument with the example of resting-state electroencephalogram (EEG). We used multiple analysis methods, contrary to typical EEG studies where one analysis method is used. We found, first, that many EEG features correlated significantly with cognitive tasks. However, these EEG features correlated weakly with each other. Similarly, in a second analysis, we found that many EEG features were significantly different in older compared to younger participants. When we compared these EEG features pairwise, we did not find strong correlations. In addition, EEG features predicted cognitive tasks poorly as shown by cross-validated regression analysis. We discuss several explanations of these results.
Collapse
Affiliation(s)
- Dario Gordillo
- Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
- Corresponding author
| | - Janir Ramos da Cruz
- Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
- Institute for Systems and Robotics – Lisboa (LARSyS), Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, 1049-001 Lisbon, Portugal
- Wyss Center for Bio and Neuroengineering, CH-1202 Geneva, Switzerland
| | - Dana Moreno
- Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Simona Garobbio
- Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Michael H. Herzog
- Laboratory of Psychophysics, Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| |
Collapse
|
38
|
Ujma PP, Dresler M, Simor P, Fabó D, Ulbert I, Erőss L, Bódizs R. The sleep EEG envelope is a novel, neuronal firing-based human biomarker. Sci Rep 2022; 12:18836. [PMID: 36336717 PMCID: PMC9637727 DOI: 10.1038/s41598-022-22255-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2022] [Accepted: 10/12/2022] [Indexed: 11/08/2022] Open
Abstract
Sleep EEG reflects voltage differences relative to a reference, while its spectrum reflects its composition of various frequencies. In contrast, the envelope of the sleep EEG reflects the instantaneous amplitude of oscillations, while its spectrum reflects the rhythmicity of the occurrence of these oscillations. The sleep EEG spectrum is known to relate to demographic, psychological and clinical characteristics, but the envelope spectrum has been rarely studied. In study 1, we demonstrate in human invasive data from cortex-penetrating microelectrodes and subdural grids that the sleep EEG envelope spectrum reflects neuronal firing. In study 2, we demonstrate that the scalp EEG envelope spectrum is stable within individuals. A multivariate learning algorithm could predict age (r = 0.6) and sex (r = 0.5) from the EEG envelope spectrum. With age, oscillations shifted from a 4-5 s rhythm to faster rhythms. Our results demonstrate that the sleep envelope spectrum is a promising biomarker of demographic and disease-related phenotypes.
Collapse
Affiliation(s)
- Péter P Ujma
- Institute of Behavioural Sciences, Semmelweis University, Budapest, Hungary.
- National Institute of Clinical Neuroscience, Budapest, Hungary.
| | - Martin Dresler
- Radboud University Medical Center, Donders Institute, Nijmegen, The Netherlands
| | - Péter Simor
- Institute of Psychology, ELTE, Eötvös Loránd University, Budapest, Hungary
- UR2NF, Neuropsychology and Functional Neuroimaging Research Unit at CRCN - Center for Research in Cognition and Neurosciences and UNI - ULB Neurosciences Institute, Université Libre de Bruxelles (ULB), Brussels, Belgium
| | - Dániel Fabó
- National Institute of Clinical Neuroscience, Budapest, Hungary
| | - István Ulbert
- Department of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
- Research Centre for Natural Sciences, Institute for Cognitive Neuroscience and Psychology, Budapest, Hungary
| | - Loránd Erőss
- National Institute of Clinical Neuroscience, Budapest, Hungary
| | - Róbert Bódizs
- Institute of Behavioural Sciences, Semmelweis University, Budapest, Hungary
- National Institute of Clinical Neuroscience, Budapest, Hungary
| |
Collapse
|
39
|
Relief of chronic pain associated with increase in midline frontal theta power. Pain Rep 2022; 7:e1040. [PMID: 36247110 PMCID: PMC9555895 DOI: 10.1097/pr9.0000000000001040] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 07/27/2022] [Accepted: 08/11/2022] [Indexed: 11/26/2022] Open
Abstract
Unique electroencephalogram signatures of relief from chronic pain demonstrate theta power increase in the midline frontal cortex. Introduction: Objectives: Methods: Results: Conclusion:
Collapse
|
40
|
Kostoglou K, Müller-Putz GR. Using linear parameter varying autoregressive models to measure cross frequency couplings in EEG signals. Front Hum Neurosci 2022; 16:915815. [PMID: 36188180 PMCID: PMC9525181 DOI: 10.3389/fnhum.2022.915815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Accepted: 08/31/2022] [Indexed: 11/25/2022] Open
Abstract
For years now, phase-amplitude cross frequency coupling (CFC) has been observed across multiple brain regions under different physiological and pathological conditions. It has been suggested that CFC serves as a mechanism that facilitates communication and information transfer between local and spatially separated neuronal populations. In non-invasive brain computer interfaces (BCI), CFC has not been thoroughly explored. In this work, we propose a CFC estimation method based on Linear Parameter Varying Autoregressive (LPV-AR) models and we assess its performance using both synthetic data and electroencephalographic (EEG) data recorded during attempted arm/hand movements of spinal cord injured (SCI) participants. Our results corroborate the potentiality of CFC as a feature for movement attempt decoding and provide evidence of the superiority of our proposed CFC estimation approach compared to other commonly used techniques.
Collapse
Affiliation(s)
- Kyriaki Kostoglou
- Institute of Neural Engineering, Graz University of Technology, Graz, Austria
| | - Gernot R. Müller-Putz
- Institute of Neural Engineering, Graz University of Technology, Graz, Austria
- BioTechMed-Graz, Graz, Austria
| |
Collapse
|
41
|
Riddle J, Frohlich F. Mental Activity as the Bridge between Neural Biomarkers and Symptoms of Psychiatric Illness. Clin EEG Neurosci 2022:15500594221112417. [PMID: 35861807 DOI: 10.1177/15500594221112417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The Research Domain Criteria (RDoC) initiative challenges researchers to build neurobehavioral models of psychiatric illness with the hope that such models identify better targets that will yield more effective treatment. However, a guide for building such models was not provided and symptom heterogeneity within Diagnostic Statistical Manual categories has hampered progress in identifying endophenotypes that underlie mental illness. We propose that the best chance to discover viable biomarkers and treatment targets for psychiatric illness is to investigate a triangle of relationships: severity of a specific psychiatric symptom that correlates to mental activity that correlates to a neural activity signature. We propose that this is the minimal model complexity required to advance the field of psychiatry. With an understanding of how neural activity relates to the experience of the patient, a genuine understanding for how treatment imparts its therapeutic effect is possible. After the discovery of this three-fold relationship, causal testing is required in which the neural activity pattern is directly enhanced or suppressed to provide causal, instead of just correlational, evidence for the biomarker. We suggest using non-invasive brain stimulation (NIBS) as these techniques provide tools to precisely manipulate spatial and temporal activity patterns. We detail how this approach enabled the discovery of two orthogonal electroencephalography (EEG) activity patterns associated with anhedonia and anxiosomatic symptoms in depression that can serve as future treatment targets. Altogether, we propose a systematic approach for building neurobehavioral models for dimensional psychiatry.
Collapse
Affiliation(s)
- Justin Riddle
- Department of Psychiatry, 6797University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Carolina Center for Neurostimulation, 6797University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Flavio Frohlich
- Department of Psychiatry, 6797University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Carolina Center for Neurostimulation, 6797University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Department of Neurology, 6797University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Department of Cell Biology and Physiology, 6797University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Department of Biomedical Engineering, 6797University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Neuroscience Center, 6797University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| |
Collapse
|
42
|
Perley A, Coleman TP. A Mutual Information Measure of Phase-Amplitude Coupling using High Dimensional Sparse Models. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:21-24. [PMID: 36086427 DOI: 10.1109/embc48229.2022.9871816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Cross frequency coupling (CFC) between electrophysiological signals in the brain has been observed and it's abnormalities have been observed in conditions such as Parkinson's disease and epilepsy. More recently, CFC has been observed in stomach-brain electrophysiologic studies and thus becomes an enticing possible target for diseases involving aberrations of the gut-brain axis. However, current methods of detecting coupling do not attempt to capture the underlying statistical relationships that give rise to this coupling. In this paper, we demonstrate a new method of calculating phase amplitude coupling by estimating the mutual information between phase and amplitude, using a flexible parametric modeling approach. Specifically, we develop an exponential generalized linear model (GLM) to model amplitude given phase, using a high dimensional basis of von-Mises function regressors and l1 regularized model selection. Using synthetically generated gut-brain coupled signals, we demonstrate that our method outperforms the existing gold-standard methods for detectable low-levels of phase amplitude coupling through receiver operating characteristic (ROC) curve analysis.
Collapse
|
43
|
Wang X, Liu H, Ortigoza EB, Kota S, Liu Y, Zhang R, Chalak LF. Feasibility of EEG Phase-Amplitude Coupling to Stratify Encephalopathy Severity in Neonatal HIE Using Short Time Window. Brain Sci 2022; 12:brainsci12070854. [PMID: 35884659 PMCID: PMC9313332 DOI: 10.3390/brainsci12070854] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Revised: 06/27/2022] [Accepted: 06/28/2022] [Indexed: 12/02/2022] Open
Abstract
Goal: It is challenging to clinically discern the severity of neonatal hypoxic ischemic encephalopathy (HIE) within hours after birth in time for therapeutic decision-making for hypothermia. The goal of this study was to determine the shortest duration of the EEG based PAC index to provide real-time guidance for clinical decision-making for neonates with HIE. Methods: Neonates were recruited from a single-center Level III NICU between 2017 and 2019. A time-dependent, PAC-frequency-averaged index, tPACm, was calculated to characterize intrinsic coupling between the amplitudes of 12−30 Hz and the phases of 1−2 Hz oscillation from 6-h EEG data at electrode P3 during the first day of life, using different sizes of moving windows including 10 s, 20 s, 1 min, 2 min, 5 min, 10 min, 20 min, 30 min, 60 min, and 120 min. Time-dependent receiver operating characteristic (ROC) curves were generated to examine the performance of the accurate window tPACm as a neurophysiologic biomarker. Results: A total of 33 neonates (mild-HIE, n = 15 and moderate/severe HIE, n = 18) were enrolled. Mixed effects models demonstrated that tPACm between the two groups was significantly different with window time segments of 3−120 min. By observing the estimates of group differences in tPACm across different window sizes, we found 20 min was the shortest window size to optimally distinguish the two groups (p < 0.001). Time-varying ROC showed significant average area-under-the-curve of 0.82. Conclusions: We demonstrated the feasibility of using tPACm with a 20 min EEG time window to differentiate the severity of HIE and facilitate earlier diagnosis and treatment initiation.
Collapse
Affiliation(s)
- Xinlong Wang
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX 75220, USA; (X.W.); (H.L.)
| | - Hanli Liu
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX 75220, USA; (X.W.); (H.L.)
| | - Eric B. Ortigoza
- Division of Neonatal-Perinatal Medicine, Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX 75220, USA;
| | - Srinivas Kota
- Department of Neurosurgery, University of Texas Southwestern Medical Center, Dallas, TX 75220, USA;
| | - Yulun Liu
- Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX 75220, USA;
| | - Rong Zhang
- Departments of Internal Medicine and Neurology, University of Texas Southwestern Medical Center, Dallas, TX 75220, USA;
| | - Lina F. Chalak
- Division of Neonatal-Perinatal Medicine, Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX 75220, USA;
- Correspondence: ; Tel.: +1-214-648-3753; Fax: +1-214-648-2481
| |
Collapse
|
44
|
Rustamov N, Humphries J, Carter A, Leuthardt EC. Theta-gamma coupling as a cortical biomarker of brain-computer interface-mediated motor recovery in chronic stroke. Brain Commun 2022; 4:fcac136. [PMID: 35702730 PMCID: PMC9188323 DOI: 10.1093/braincomms/fcac136] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 03/19/2022] [Accepted: 05/23/2022] [Indexed: 11/15/2022] Open
Abstract
Chronic stroke patients with upper-limb motor disabilities are now beginning to see treatment options that were not previously available. To date, the two options recently approved by the United States Food and Drug Administration include vagus nerve stimulation and brain-computer interface therapy. While the mechanisms for vagus nerve stimulation have been well defined, the mechanisms underlying brain-computer interface-driven motor rehabilitation are largely unknown. Given that cross-frequency coupling has been associated with a wide variety of higher-order functions involved in learning and memory, we hypothesized this rhythm-specific mechanism would correlate with the functional improvements effected by a brain-computer interface. This study investigated whether the motor improvements in chronic stroke patients induced with a brain-computer interface therapy are associated with alterations in phase-amplitude coupling, a type of cross-frequency coupling. Seventeen chronic hemiparetic stroke patients used a robotic hand orthosis controlled with contralesional motor cortical signals measured with EEG. Patients regularly performed a therapeutic brain-computer interface task for 12 weeks. Resting-state EEG recordings and motor function data were acquired before initiating brain-computer interface therapy and once every 4 weeks after the therapy. Changes in phase-amplitude coupling values were assessed and correlated with motor function improvements. To establish whether coupling between two different frequency bands was more functionally important than either of those rhythms alone, we calculated power spectra as well. We found that theta-gamma coupling was enhanced bilaterally at the motor areas and showed significant correlations across brain-computer interface therapy sessions. Importantly, an increase in theta-gamma coupling positively correlated with motor recovery over the course of rehabilitation. The sources of theta-gamma coupling increase following brain-computer interface therapy were mostly located in the hand regions of the primary motor cortex on the left and right cerebral hemispheres. Beta-gamma coupling decreased bilaterally at the frontal areas following the therapy, but these effects did not correlate with motor recovery. Alpha-gamma coupling was not altered by brain-computer interface therapy. Power spectra did not change significantly over the course of the brain-computer interface therapy. The significant functional improvement in chronic stroke patients induced by brain-computer interface therapy was strongly correlated with increased theta-gamma coupling in bihemispheric motor regions. These findings support the notion that specific cross-frequency coupling dynamics in the brain likely play a mechanistic role in mediating motor recovery in the chronic phase of stroke recovery.
Collapse
Affiliation(s)
- Nabi Rustamov
- Department of Neurological Surgery, Washington University School of Medicine, St Louis, MO, USA
- Center for Innovation in Neuroscience and Technology, Washington University School of Medicine, St Louis, MO, USA
| | - Joseph Humphries
- Department of Biomedical Engineering, Washington University in St Louis, St Louis, MO, USA
| | - Alexandre Carter
- Department of Neurology, Washington University in St Louis, St Louis, MO, USA
| | - Eric C. Leuthardt
- Department of Neurological Surgery, Washington University School of Medicine, St Louis, MO, USA
- Center for Innovation in Neuroscience and Technology, Washington University School of Medicine, St Louis, MO, USA
- Department of Biomedical Engineering, Washington University in St Louis, St Louis, MO, USA
- Department of Neuroscience, Washington University School of Medicine, St Louis, MO, USA
- Department of Mechanical Engineering and Materials Science, Washington University in St Louis, St Louis, MO, USA
| |
Collapse
|
45
|
Riddle J, Alexander ML, Schiller CE, Rubinow DR, Frohlich F. Reward-Based Decision-Making Engages Distinct Modes of Cross-Frequency Coupling. Cereb Cortex 2022; 32:2079-2094. [PMID: 34622271 PMCID: PMC9113280 DOI: 10.1093/cercor/bhab336] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 08/18/2021] [Accepted: 08/22/2021] [Indexed: 11/13/2022] Open
Abstract
Prefrontal cortex exerts control over sensory and motor systems via cross-frequency coupling. However, it is unknown whether these signals play a role in reward-based decision-making and whether such dynamic network configuration is altered in a major depressive episode. We recruited men and women with and without depression to perform a streamlined version of the Expenditure of Effort for Reward Task during recording of electroencephalography. Goal-directed behavior was quantified as willingness to exert physical effort to obtain reward, and reward-evaluation was the degree to which the decision to exert effort was modulated by incentive level. We found that the amplitude of frontal-midline theta oscillations was greatest in participants with the greatest reward-evaluation. Furthermore, coupling between frontal theta phase and parieto-occipital gamma amplitude was positively correlated with reward-evaluation. In addition, goal-directed behavior was positively correlated with coupling between frontal delta phase to motor beta amplitude. Finally, we performed a factor analysis to derive 2 symptom dimensions and found that mood symptoms positively tracked with reward-evaluation and motivation symptoms negatively tracked with goal-directed behavior. Altogether, these results provide evidence that 2 aspects of reward-based decision-making are instantiated by different modes of prefrontal top-down control and are modulated in different symptom dimensions of depression.
Collapse
Affiliation(s)
- Justin Riddle
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Carolina Center for Neurostimulation, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Morgan L Alexander
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Carolina Center for Neurostimulation, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Crystal Edler Schiller
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - David R Rubinow
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Flavio Frohlich
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Carolina Center for Neurostimulation, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Biomedical Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| |
Collapse
|
46
|
Gouveris H, Koirala N, Anwar AR, Ding H, Ludwig K, Huppertz T, Matthias C, Groppa S, Muthuraman M. Reduced Cross-Frequency Coupling and Daytime Sleepiness in Obstructive Sleep Apnea Patients. BIOLOGY 2022; 11:biology11050700. [PMID: 35625429 PMCID: PMC9138271 DOI: 10.3390/biology11050700] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 04/10/2022] [Accepted: 04/25/2022] [Indexed: 11/30/2022]
Abstract
Obstructive sleep apnea (OSA) is associated with sleep-stage- and respiratory-event-specific sensorimotor cortico-muscular disconnection. The modulation of phase−amplitude cross-frequency coupling (PACFC) may influence information processing throughout the brain. We investigated whether sleep-stage-specific PACFC is impaired at the sensorimotor areas in OSA patients. C3 and C4 electrode EEG polysomnography recordings of 170 participants were evaluated. Different frequency band combinations were used to compute CFC modulation index (MI) to assess if MI differs between OSA and non-significant OSA patients in distinct sleep stages. We tested if the CFC-MI could predict daytime sleepiness in OSA. Theta−gamma CFC-MI at cortical sensorimotor areas was significantly reduced during all sleep stages; the delta−alpha CFC-MI was significantly reduced during REM and N1 while increasing during N2 in patients with respiratory disturbance index (RDI) > 15/h compared to those with RDI ≤ 15/h. A sleep stage classification using MI values was achieved in both patient groups. Theta−gamma MI during N2 and N3 could predict RDI and Epworth Sleepiness Scale, while delta−alpha MI during REM predicted RDI. This increase in disconnection at the cortical sensorimotor areas with increasing respiratory distress during sleep supports a cortical motor dysfunction in OSA patients. The MI provides an objective marker to quantify subjective sleepiness and respiratory distress in OSA.
Collapse
Affiliation(s)
- Haralampos Gouveris
- Sleep Medicine Center, Department of Otolaryngology, University Medical Center, Johannes Gutenberg University Mainz, 55131 Mainz, Germany; (K.L.); (T.H.); (C.M.)
- Correspondence: ; Tel.: +49-6131-177361
| | - Nabin Koirala
- Haskins Laboratories, Yale University, New Haven, CT 06511, USA;
| | - Abdul Rauf Anwar
- Department of Biomedical Engineering, University of Engineering and Technology (New Campus), Lahore 54890, Pakistan;
| | - Hao Ding
- Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of Johannes Gutenberg University Mainz, 55131 Mainz, Germany; (H.D.); (S.G.); (M.M.)
| | - Katharina Ludwig
- Sleep Medicine Center, Department of Otolaryngology, University Medical Center, Johannes Gutenberg University Mainz, 55131 Mainz, Germany; (K.L.); (T.H.); (C.M.)
| | - Tilman Huppertz
- Sleep Medicine Center, Department of Otolaryngology, University Medical Center, Johannes Gutenberg University Mainz, 55131 Mainz, Germany; (K.L.); (T.H.); (C.M.)
| | - Christoph Matthias
- Sleep Medicine Center, Department of Otolaryngology, University Medical Center, Johannes Gutenberg University Mainz, 55131 Mainz, Germany; (K.L.); (T.H.); (C.M.)
| | - Sergiu Groppa
- Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of Johannes Gutenberg University Mainz, 55131 Mainz, Germany; (H.D.); (S.G.); (M.M.)
| | - Muthuraman Muthuraman
- Movement Disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of Johannes Gutenberg University Mainz, 55131 Mainz, Germany; (H.D.); (S.G.); (M.M.)
| |
Collapse
|
47
|
Theta and gamma oscillatory dynamics in mouse models of Alzheimer's disease: A path to prospective therapeutic intervention. Neurosci Biobehav Rev 2022; 136:104628. [PMID: 35331816 DOI: 10.1016/j.neubiorev.2022.104628] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 03/09/2022] [Accepted: 03/15/2022] [Indexed: 12/26/2022]
Abstract
Understanding the neural basis of cognitive deficits, a key feature of Alzheimer's disease (AD), is imperative for achieving the therapy of the disease. Rhythmic oscillatory activities in neural systems are a fundamental mechanism for diverse brain functions, including cognition. In several neurological conditions like AD, aberrant neural oscillations have been shown to play a central role. Furthermore, manipulation of brain oscillations in animals has confirmed their impact on cognition and disease. In this article, we review the evidence from mouse models that shows how synchronized oscillatory activity is intricately linked to AD machinery. We primarily focus on recent reports showing abnormal oscillatory activities at theta and gamma frequencies in AD condition and their influence on cellular disturbances and cognitive impairments. A thorough comprehension of the role that neuronal oscillations play in AD pathology should pave the way to therapeutic interventions that can curb the disease.
Collapse
|
48
|
Keil A, Bernat EM, Cohen MX, Ding M, Fabiani M, Gratton G, Kappenman ES, Maris E, Mathewson KE, Ward RT, Weisz N. Recommendations and publication guidelines for studies using frequency domain and time-frequency domain analyses of neural time series. Psychophysiology 2022; 59:e14052. [PMID: 35398913 PMCID: PMC9717489 DOI: 10.1111/psyp.14052] [Citation(s) in RCA: 37] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 03/08/2022] [Indexed: 01/29/2023]
Abstract
Since its beginnings in the early 20th century, the psychophysiological study of human brain function has included research into the spectral properties of electrical and magnetic brain signals. Now, dramatic advances in digital signal processing, biophysics, and computer science have enabled increasingly sophisticated methodology for neural time series analysis. Innovations in hardware and recording techniques have further expanded the range of tools available to researchers interested in measuring, quantifying, modeling, and altering the spectral properties of neural time series. These tools are increasingly used in the field, by a growing number of researchers who vary in their training, background, and research interests. Implementation and reporting standards also vary greatly in the published literature, causing challenges for authors, readers, reviewers, and editors alike. The present report addresses this issue by providing recommendations for the use of these methods, with a focus on foundational aspects of frequency domain and time-frequency analyses. It also provides publication guidelines, which aim to (1) foster replication and scientific rigor, (2) assist new researchers who wish to enter the field of brain oscillations, and (3) facilitate communication among authors, reviewers, and editors.
Collapse
Affiliation(s)
- Andreas Keil
- Department and Psychology and Center for the Study of Emotion and Attention, University of Florida, Gainesville, Florida, USA
| | - Edward M. Bernat
- Department of Psychology, University of Maryland, College Park, Maryland, USA
| | - Michael X. Cohen
- Radboud University and University Medical Center, Nijmegen, the Netherlands
| | - Mingzhou Ding
- J Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, Florida, USA
| | - Monica Fabiani
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA,Psychology Department, University of Illinois at Urbana-Champaign, Champaign, Illinois, USA
| | - Gabriele Gratton
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA,Psychology Department, University of Illinois at Urbana-Champaign, Champaign, Illinois, USA
| | - Emily S. Kappenman
- Department of Psychology, San Diego State University, San Diego, California, USA
| | - Eric Maris
- Donders Institute for Brain, Cognition, and Behaviour & Faculty of Social Sciences Radboud University, Nijmegen, the Netherlands
| | - Kyle E. Mathewson
- Department of Psychology, Faculty of Science, University of Alberta, Edmonton, Alberta, Canada
| | - Richard T. Ward
- Department and Psychology and Center for the Study of Emotion and Attention, University of Florida, Gainesville, Florida, USA
| | - Nathan Weisz
- Psychology, University of Salzburg, Salzburg, Austria,Neuroscience Institute, Christian Doppler University Hospital, Paracelsus Medical University, Salzburg, Austria
| |
Collapse
|
49
|
Zhang M, Riecke L, Fraga-González G, Bonte M. Altered brain network topology during speech tracking in developmental dyslexia. Neuroimage 2022; 254:119142. [PMID: 35342007 DOI: 10.1016/j.neuroimage.2022.119142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 03/15/2022] [Accepted: 03/23/2022] [Indexed: 10/18/2022] Open
Abstract
Developmental dyslexia is often accompanied by altered phonological processing of speech. Underlying neural changes have typically been characterized in terms of stimulus- and/or task-related responses within individual brain regions or their functional connectivity. Less is known about potential changes in the more global functional organization of brain networks. Here we recorded electroencephalography (EEG) in typical and dyslexic readers while they listened to (a) a random sequence of syllables and (b) a series of tri-syllabic real words. The network topology of the phase synchronization of evoked cortical oscillations was investigated in four frequency bands (delta, theta, alpha and beta) using minimum spanning tree graphs. We found that, compared to syllable tracking, word tracking triggered a shift toward a more integrated network topology in the theta band in both groups. Importantly, this change was significantly stronger in the dyslexic readers, who also showed increased reliance on a right frontal cluster of electrodes for word tracking. The current findings point towards an altered effect of word-level processing on the functional brain network organization that may be associated with less efficient phonological and reading skills in dyslexia.
Collapse
Affiliation(s)
- Manli Zhang
- Maastricht Brain Imaging Center, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands.
| | - Lars Riecke
- Maastricht Brain Imaging Center, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Gorka Fraga-González
- Department of Child and Adolescent Psychiatry, Faculty of Medicine, University of Zurich, Switzerland
| | - Milene Bonte
- Maastricht Brain Imaging Center, Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| |
Collapse
|
50
|
Gallego-Molina NJ, Ortiz A, Martínez-Murcia FJ, Formoso MA, Giménez A. Complex network modeling of EEG band coupling in dyslexia: An exploratory analysis of auditory processing and diagnosis. Knowl Based Syst 2022. [DOI: 10.1016/j.knosys.2021.108098] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
|