1
|
Choi JW, Malekmohammadi M, Niketeghad S, Cross KA, Ebadi H, Alijanpourotaghsara A, Aron A, Rutishauser U, Pouratian N. Prefrontal-subthalamic theta signaling mediates delayed responses during conflict processing. Prog Neurobiol 2024; 236:102613. [PMID: 38631480 PMCID: PMC11149786 DOI: 10.1016/j.pneurobio.2024.102613] [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: 11/06/2023] [Revised: 02/29/2024] [Accepted: 04/12/2024] [Indexed: 04/19/2024]
Abstract
While medial frontal cortex (MFC) and subthalamic nucleus (STN) have been implicated in conflict monitoring and action inhibition, respectively, an integrated understanding of the spatiotemporal and spectral interaction of these nodes and how they interact with motor cortex (M1) to definitively modify motor behavior during conflict is lacking. We recorded neural signals intracranially across presupplementary motor area (preSMA), M1, STN, and globus pallidus internus (GPi), during a flanker task in 20 patients undergoing deep brain stimulation implantation surgery for Parkinson disease or dystonia. Conflict is associated with sequential and causal increases in local theta power from preSMA to STN to M1 with movement delays directly correlated with increased STN theta power, indicating preSMA is the MFC locus that monitors conflict and signals STN to implement a 'break.' Transmission of theta from STN-to-M1 subsequently results in a transient increase in M1-to-GPi beta flow immediately prior to movement, modulating the motor network to actuate the conflict-related action inhibition (i.e., delayed response). Action regulation during conflict relies on two distinct circuits, the conflict-related theta and movement-related beta networks, that are separated spatially, spectrally, and temporally, but which interact dynamically to mediate motor performance, highlighting complex parallel yet interacting networks regulating movement.
Collapse
Affiliation(s)
- Jeong Woo Choi
- Department of Neurological Surgery, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - Mahsa Malekmohammadi
- Department of Neurosurgery, University of California, Los Angeles, CA 90095, USA
| | - Soroush Niketeghad
- Department of Neurosurgery, University of California, Los Angeles, CA 90095, USA
| | - Katy A Cross
- Department of Neurology, University of California, Los Angeles, CA 90095, USA
| | - Hamasa Ebadi
- Department of Neurological Surgery, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | | | - Adam Aron
- Department of Psychology, University of California, San Diego, CA 92093, USA
| | - Ueli Rutishauser
- Departments of Neurosurgery and Neurology, and Center for Neural Science and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA; Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Nader Pouratian
- Department of Neurological Surgery, UT Southwestern Medical Center, Dallas, TX 75390, USA.
| |
Collapse
|
2
|
Cheron G, Simar C, Cebolla AM. The oscillatory nature of the motor and perceptive kinematics invariants: Comment on "Motor invariants in action execution and perception" by Francesco Torricelli et al. Phys Life Rev 2023; 46:80-84. [PMID: 37327669 DOI: 10.1016/j.plrev.2023.05.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 05/25/2023] [Indexed: 06/18/2023]
Affiliation(s)
- Guy Cheron
- Laboratory of Neurophysiology and Movement Biomechanics, Neuroscience Institute, Université Libre de Bruxelles (ULB), Brussels, Belgium; Laboratory of Electrophysiology, Université de Mons-Hainaut, Mons, Belgium.
| | - Cédric Simar
- Machine Learning Group, Computer Science Department, Faculty of Sciences, Université Libre de Bruxelles (ULB), Brussels, Belgium
| | - Ana Maria Cebolla
- Laboratory of Neurophysiology and Movement Biomechanics, Neuroscience Institute, Université Libre de Bruxelles (ULB), Brussels, Belgium
| |
Collapse
|
3
|
Anand S, Cho H, Adamek M, Burton H, Moran D, Leuthardt E, Brunner P. High gamma coherence between task-responsive sensory-motor cortical regions in a motor reaction-time task. J Neurophysiol 2023; 130:628-639. [PMID: 37584101 PMCID: PMC10648945 DOI: 10.1152/jn.00172.2023] [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: 05/02/2023] [Revised: 07/19/2023] [Accepted: 08/10/2023] [Indexed: 08/17/2023] Open
Abstract
Electrical activity at high gamma frequencies (70-170 Hz) is thought to reflect the activity of small cortical ensembles. For example, high gamma activity (often quantified by spectral power) can increase in sensory-motor cortex in response to sensory stimuli or movement. On the other hand, synchrony of neural activity between cortical areas (often quantified by coherence) has been hypothesized as an important mechanism for inter-areal communication, thereby serving functional roles in cognition and behavior. Currently, high gamma activity has primarily been studied as a local amplitude phenomenon. We investigated the synchronization of high gamma activity within sensory-motor cortex and the extent to which underlying high gamma activity can explain coherence during motor tasks. We characterized high gamma coherence in sensory-motor networks and the relationship between coherence and power by analyzing electrocorticography (ECoG) data from human subjects as they performed a motor response to sensory cues. We found greatly increased high gamma coherence during the motor response compared with the sensory cue. High gamma power poorly predicted high gamma coherence, but the two shared a similar time course. However, high gamma coherence persisted longer than high gamma power. The results of this study suggest that high gamma coherence is a physiologically distinct phenomenon during a sensory-motor task, the emergence of which may require active task participation.NEW & NOTEWORTHY Motor action after auditory stimulus elicits high gamma responses in sensory-motor and auditory cortex, respectively. We show that high gamma coherence reliably and greatly increased during motor response, but not after auditory stimulus. Underlying high gamma power could not explain high gamma coherence. Our results indicate that high gamma coherence is a physiologically distinct sensory-motor phenomenon that may serve as an indicator of increased synaptic communication on short timescales (∼1 s).
Collapse
Affiliation(s)
- Shashank Anand
- Department of Biomedical Engineering, McKelvey School of Engineering, Washington University in St. Louis, St. Louis, Missouri, United States
| | - Hohyun Cho
- Department of Neurosurgery, Washington University in St. Louis School of Medicine, St. Louis, Missouri, United States
- National Center for Adaptive Neurotechnologies, St. Louis, Missouri, United States
| | - Markus Adamek
- National Center for Adaptive Neurotechnologies, St. Louis, Missouri, United States
- Department of Neuroscience, Washington University in St. Louis School of Medicine, St. Louis, Missouri, United States
| | - Harold Burton
- Department of Neuroscience, Washington University in St. Louis School of Medicine, St. Louis, Missouri, United States
| | - Daniel Moran
- Department of Biomedical Engineering, McKelvey School of Engineering, Washington University in St. Louis, St. Louis, Missouri, United States
- Department of Neurosurgery, Washington University in St. Louis School of Medicine, St. Louis, Missouri, United States
- Department of Neuroscience, Washington University in St. Louis School of Medicine, St. Louis, Missouri, United States
| | - Eric Leuthardt
- Department of Biomedical Engineering, McKelvey School of Engineering, Washington University in St. Louis, St. Louis, Missouri, United States
- Department of Neurosurgery, Washington University in St. Louis School of Medicine, St. Louis, Missouri, United States
- National Center for Adaptive Neurotechnologies, St. Louis, Missouri, United States
- Department of Neuroscience, Washington University in St. Louis School of Medicine, St. Louis, Missouri, United States
| | - Peter Brunner
- Department of Biomedical Engineering, McKelvey School of Engineering, Washington University in St. Louis, St. Louis, Missouri, United States
- Department of Neurosurgery, Washington University in St. Louis School of Medicine, St. Louis, Missouri, United States
- National Center for Adaptive Neurotechnologies, St. Louis, Missouri, United States
- Department of Neurology, Albany Medical College, Albany, New York, United States
| |
Collapse
|
4
|
Alhassen W, Alhassen S, Chen J, Monfared RV, Alachkar A. Cilia in the Striatum Mediate Timing-Dependent Functions. Mol Neurobiol 2023; 60:545-565. [PMID: 36322337 PMCID: PMC9849326 DOI: 10.1007/s12035-022-03095-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 10/16/2022] [Indexed: 11/07/2022]
Abstract
Almost all brain cells contain cilia, antennae-like microtubule-based organelles. Yet, the significance of cilia, once considered vestigial organelles, in the higher-order brain functions is unknown. Cilia act as a hub that senses and transduces environmental sensory stimuli to generate an appropriate cellular response. Similarly, the striatum, a brain structure enriched in cilia, functions as a hub that receives and integrates various types of environmental information to drive appropriate motor response. To understand cilia's role in the striatum functions, we used loxP/Cre technology to ablate cilia from the dorsal striatum of male mice and monitored the behavioral consequences. Our results revealed an essential role for striatal cilia in the acquisition and brief storage of information, including learning new motor skills, but not in long-term consolidation of information or maintaining habitual/learned motor skills. A fundamental aspect of all disrupted functions was the "time perception/judgment deficit." Furthermore, the observed behavioral deficits form a cluster pertaining to clinical manifestations overlapping across psychiatric disorders that involve the striatum functions and are known to exhibit timing deficits. Thus, striatal cilia may act as a calibrator of the timing functions of the basal ganglia-cortical circuit by maintaining proper timing perception. Our findings suggest that dysfunctional cilia may contribute to the pathophysiology of neuro-psychiatric disorders, as related to deficits in timing perception.
Collapse
Affiliation(s)
- Wedad Alhassen
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University of California-Irvine, 356A Med Surge II, Irvine, CA 92697-4625 USA
| | - Sammy Alhassen
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University of California-Irvine, 356A Med Surge II, Irvine, CA 92697-4625 USA
| | - Jiaqi Chen
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University of California-Irvine, 356A Med Surge II, Irvine, CA 92697-4625 USA
| | - Roudabeh Vakil Monfared
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University of California-Irvine, 356A Med Surge II, Irvine, CA 92697-4625 USA
| | - Amal Alachkar
- Department of Pharmaceutical Sciences, School of Pharmacy and Pharmaceutical Sciences, University of California-Irvine, 356A Med Surge II, Irvine, CA 92697-4625 USA ,UC Irvine Center for the Neurobiology of Learning and Memory, University of California-Irvine, Irvine, CA 92697 USA ,Institute for Genomics and Bioinformatics, School of Information and Computer Sciences, University of California-Irvine, Irvine, CA 92697 USA
| |
Collapse
|
5
|
Lee LHN, Huang CS, Wang RW, Lai HJ, Chung CC, Yang YC, Kuo CC. Deep brain stimulation rectifies the noisy cortex and irresponsive subthalamus to improve parkinsonian locomotor activities. NPJ Parkinsons Dis 2022; 8:77. [PMID: 35725730 PMCID: PMC9209473 DOI: 10.1038/s41531-022-00343-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 05/31/2022] [Indexed: 11/10/2022] Open
Abstract
The success of deep brain stimulation (DBS) therapy indicates that Parkinson's disease is a brain rhythm disorder. However, the manifestations of the erroneous rhythms corrected by DBS remain to be established. We found that augmentation of α rhythms and α coherence between the motor cortex (MC) and the subthalamic nucleus (STN) is characteristically prokinetic and is decreased in parkinsonian rats. In multi-unit recordings, movement is normally associated with increased changes in spatiotemporal activities rather than overall spike rates in MC. In parkinsonian rats, MC shows higher spike rates at rest but less spatiotemporal activity changes upon movement, and STN burst discharges are more prevalent, longer lasting, and less responsive to MC inputs. DBS at STN rectifies the foregoing pathological MC-STN oscillations and consequently locomotor deficits, yet overstimulation may cause behavioral restlessness. These results indicate that delicate electrophysiological considerations at both cortical and subcortical levels should be exercised for optimal DBS therapy.
Collapse
Affiliation(s)
- Lan-Hsin Nancy Lee
- Department of Physiology, National Taiwan University College of Medicine, Taipei, Taiwan.,Department of Neurology, Fu Jen Catholic University Hospital, New Taipei, Taiwan.,Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan
| | - Chen-Syuan Huang
- Graduate Institute of Biomedical Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Ren-Wei Wang
- Department of Physiology, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Hsing-Jung Lai
- Department of Physiology, National Taiwan University College of Medicine, Taipei, Taiwan.,Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan.,National Taiwan University Hospital, Jin-Shan Branch, New Taipei, Taiwan
| | - Chih-Ching Chung
- Department of Biomedical Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Ya-Chin Yang
- Graduate Institute of Biomedical Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan. .,Department of Biomedical Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan. .,Neuroscience Research Center, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan, Taiwan. .,Department of Psychiatry, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan, Taiwan.
| | - Chung-Chin Kuo
- Department of Physiology, National Taiwan University College of Medicine, Taipei, Taiwan. .,Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan.
| |
Collapse
|
6
|
Merk T, Peterson V, Köhler R, Haufe S, Richardson RM, Neumann WJ. Machine learning based brain signal decoding for intelligent adaptive deep brain stimulation. Exp Neurol 2022; 351:113993. [PMID: 35104499 PMCID: PMC10521329 DOI: 10.1016/j.expneurol.2022.113993] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2021] [Revised: 11/18/2021] [Accepted: 01/22/2022] [Indexed: 12/30/2022]
Abstract
Sensing enabled implantable devices and next-generation neurotechnology allow real-time adjustments of invasive neuromodulation. The identification of symptom and disease-specific biomarkers in invasive brain signal recordings has inspired the idea of demand dependent adaptive deep brain stimulation (aDBS). Expanding the clinical utility of aDBS with machine learning may hold the potential for the next breakthrough in the therapeutic success of clinical brain computer interfaces. To this end, sophisticated machine learning algorithms optimized for decoding of brain states from neural time-series must be developed. To support this venture, this review summarizes the current state of machine learning studies for invasive neurophysiology. After a brief introduction to the machine learning terminology, the transformation of brain recordings into meaningful features for decoding of symptoms and behavior is described. Commonly used machine learning models are explained and analyzed from the perspective of utility for aDBS. This is followed by a critical review on good practices for training and testing to ensure conceptual and practical generalizability for real-time adaptation in clinical settings. Finally, first studies combining machine learning with aDBS are highlighted. This review takes a glimpse into the promising future of intelligent adaptive DBS (iDBS) and concludes by identifying four key ingredients on the road for successful clinical adoption: i) multidisciplinary research teams, ii) publicly available datasets, iii) open-source algorithmic solutions and iv) strong world-wide research collaborations.
Collapse
Affiliation(s)
- Timon Merk
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, Chariteplatz 1, 10117 Berlin, Germany
| | - Victoria Peterson
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, United States
| | - Richard Köhler
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, Chariteplatz 1, 10117 Berlin, Germany
| | - Stefan Haufe
- Berlin Center for Advanced Neuroimaging (BCAN), Charité - Universitätsmedizin Berlin, Chariteplatz 1, 10117 Berlin, Germany
| | - R Mark Richardson
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, United States
| | - Wolf-Julian Neumann
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, Chariteplatz 1, 10117 Berlin, Germany.
| |
Collapse
|
7
|
Karekal A, Miocinovic S, Swann NC. Novel approaches for quantifying beta synchrony in Parkinson's disease. Exp Brain Res 2022; 240:991-1004. [PMID: 35099592 DOI: 10.1007/s00221-022-06308-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 01/12/2022] [Indexed: 11/25/2022]
Abstract
Despite the clinical and financial burden of Parkinson's disease (PD), there is no standardized, reliable biomarker to diagnose and track PD progression. Instead, PD is primarily assessed using subjective clinical rating scales and patient self-report. Such approaches can be imprecise, hindering diagnosis and disease monitoring. An objective biomarker would be beneficial for clinical care, refining diagnosis, and treatment. Due to widespread electrophysiological abnormalities both within and between brain structures in PD, development of electrophysiologic biomarkers may be feasible. Basal ganglia recordings acquired with neurosurgical approaches have revealed elevated power in the beta frequency range (13-30 Hz) in PD, suggesting that beta power could be a putative PD biomarker. However, there are limitations to the use of beta power as a biomarker. Recent advances in analytic approaches have led to novel methods to quantify oscillatory synchrony in the beta frequency range. Here we describe some of these novel approaches in the context of PD and explore how they may serve as electrophysiological biomarkers. These novel signatures include (1) interactions between beta phase and broadband (> 50 Hz, "gamma") amplitude (i.e., phase amplitude coupling, PAC), (2) asymmetries in waveform shape, (3) beta coherence, and (4) beta "bursts." Development of a robust, reliable, and readily accessible electrophysiologic biomarker would represent a major step towards more precise and personalized care in PD.
Collapse
Affiliation(s)
- Apoorva Karekal
- Department of Human Physiology, University of Oregon, Eugene, OR, USA
| | | | - Nicole C Swann
- Department of Human Physiology, University of Oregon, Eugene, OR, USA.
| |
Collapse
|
8
|
Karimi F, Niu J, Gouweleeuw K, Almeida Q, Jiang N. Movement-related EEG signatures associated with freezing of gait in Parkinson's disease: an integrative analysis. Brain Commun 2021; 3:fcab277. [PMID: 34877535 PMCID: PMC8643573 DOI: 10.1093/braincomms/fcab277] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 08/20/2021] [Accepted: 09/28/2021] [Indexed: 01/09/2023] Open
Abstract
Freezing of gait is the most severe gait deficit associated with Parkinson's disease and significantly affects patients' independence and consequently their quality of life. The lack of a clear understanding of its underlying neurophysiological mechanism has resulted in limited effectiveness of the current treatment options. In this study, we investigated EEG features over (pre-)supplementary motor area and primary motor cortex during a simple cue-based ankle dorsiflexion movement. These features include movement-related cortical potentials (0.05-5 Hz) and brain oscillations (1-50 Hz). Electromyogram signal from the tibialis anterior muscle of the dominant foot was used to determine the movement onset. The EEG features before, during and following the onset of the movement were compared among three groups of participants: patients with freezing (N = 14, 11 males), patients without freezing (N = 14, 13 males) and healthy age-matched controls (N = 13, 10 males) with 15 recorded trials for each individual. Additionally, Parkinson's disease patients with freezing of gait were separated into mild (N = 7) and severe cases (N = 5), so that EEG features associated with freezing severity could be investigated. The results indicated significant differences between patients with severe freezing of gait compared to healthy controls and patients without freezing of gait. In addition, patients with mild and severe freezing represented cortical activity differences. For patients with freezing, the initial component of movement-related cortical potential is significantly lower than that of the healthy controls (P = 0.002) and is affected by the severity of freezing. Furthermore, a striking absence of beta frequency band (12-35 Hz) desynchronization was observed in patients with freezing, especially low-beta frequency band over Cz, before the movement, which was also associated with the severity of the freezing of gait. Low-beta (13-20 Hz) and high-beta (21-35 Hz) frequency band activities represented unique features for each group. Beta event-related desynchronization over Cz present in healthy controls prior to movement onset, was partially replaced by the theta band (4-8 Hz) synchrony in patients with freezing. Patients with severe freezing also represented some level of theta band synchronization over contralateral supplementary motor area. This suggests the involvement of cognitive processing over the motor cortex in controlling cue-based voluntary movement as a compensatory mechanism associated with freezing of gait. The EEG features identified in this study are indicative of important freezing of gait clinical characteristics such as severity and contribute to a better understanding of the underlying neurophysiology of the mysterious phenomenon of freezing of gait.
Collapse
Affiliation(s)
- Fatemeh Karimi
- Systems Design Engineering Department, University of Waterloo, Waterloo N2L 3G1, Canada
| | - Jiansheng Niu
- Systems Design Engineering Department, University of Waterloo, Waterloo N2L 3G1, Canada
| | - Kim Gouweleeuw
- Department of Human Media Interaction, University of Twente, 7522 NB Enschede, The Netherlands
| | - Quincy Almeida
- Department of Kinesiology and Physical Education, Wilfrid Laurier University, Waterloo N2L 3C5, Canada
| | - Ning Jiang
- Systems Design Engineering Department, University of Waterloo, Waterloo N2L 3G1, Canada
| |
Collapse
|
9
|
Kazemi A, Mirian MS, Lee S, McKeown MJ. Galvanic Vestibular Stimulation Effects on EEG Biomarkers of Motor Vigor in Parkinson's Disease. Front Neurol 2021; 12:759149. [PMID: 34803892 PMCID: PMC8599939 DOI: 10.3389/fneur.2021.759149] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 10/05/2021] [Indexed: 01/18/2023] Open
Abstract
Background: Impaired motor vigor (MV) is a critical aspect of Parkinson's disease (PD) pathophysiology. While MV is predominantly encoded in the basal ganglia, deriving (cortical) EEG measures of MV may provide valuable targets for modulation via galvanic vestibular stimulation (GVS). Objective: To find EEG features predictive of MV and examine the effects of high-frequency GVS. Methods: Data were collected from 20 healthy control (HC) and 18 PD adults performing 30 trials total of a squeeze bulb task with sham or multi-sine (50-100 Hz "GVS1" or 100-150 Hz "GVS2") stimuli. For each trial, we determined the time to reach maximum force after a "Go" signal, defined MV as the inverse of this time, and used the EEG data 1-sec prior to this time for prediction. We utilized 53 standard EEG features, including relative spectral power, harmonic parameters, and amplitude and phase of bispectrum corresponding to standard EEG bands from each of 27 EEG channels. We then used LASSO regression to select a sparse set of features to predict MV. The regression weights were examined, and separate band-specific models were developed by including only band-specific features (Delta, Theta, Alpha-low, Alpha-high, Beta, Gamma). The correlation between MV prediction and measured MV was used to assess model performance. Results: Models utilizing broadband EEG features were capable of accurately predicting MV (controls: 75%, PD: 81% of the variance). In controls, all EEG bands performed roughly equally in predicting MV, while in the PD group, the model using only beta band features did not predict MV well compared to other bands. Despite having minimal effects on the EEG feature values themselves, both GVS stimuli had significant effects on MV and profound effects on MV predictability via the EEG. With the GVS1 stimulus, beta-band activity in PD subjects became more closely associated with MV compared to the sham condition. With GVS2 stimulus, MV could no longer be accurately predicted from the EEG. Conclusions: EEG features can be a proxy for MV. However, GVS stimuli have profound effects on the relationship between EEG and MV, possibly via direct vestibulo-basal ganglia connections not measurable by the EEG.
Collapse
Affiliation(s)
- Alireza Kazemi
- Center for Mind and Brain, Department of Psychology, University of California, Davis, Davis, CA, United States
| | - Maryam S. Mirian
- Pacific Parkinson's Research Centre, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Soojin Lee
- Pacific Parkinson's Research Centre, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
- Wellcome Centre for Integrative Neuroimaging (FMRIB), University of Oxford, Oxford, United Kingdom
| | - Martin J. McKeown
- Pacific Parkinson's Research Centre, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
- Faculty of Medicine (Neurology), University of British Columbia, Vancouver, BC, Canada
| |
Collapse
|
10
|
Oswal A, Cao C, Yeh CH, Neumann WJ, Gratwicke J, Akram H, Horn A, Li D, Zhan S, Zhang C, Wang Q, Zrinzo L, Foltynie T, Limousin P, Bogacz R, Sun B, Husain M, Brown P, Litvak V. Neural signatures of hyperdirect pathway activity in Parkinson's disease. Nat Commun 2021; 12:5185. [PMID: 34465771 PMCID: PMC8408177 DOI: 10.1038/s41467-021-25366-0] [Citation(s) in RCA: 57] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2020] [Accepted: 08/02/2021] [Indexed: 11/25/2022] Open
Abstract
Parkinson's disease (PD) is characterised by the emergence of beta frequency oscillatory synchronisation across the cortico-basal-ganglia circuit. The relationship between the anatomy of this circuit and oscillatory synchronisation within it remains unclear. We address this by combining recordings from human subthalamic nucleus (STN) and internal globus pallidus (GPi) with magnetoencephalography, tractography and computational modelling. Coherence between supplementary motor area and STN within the high (21-30 Hz) but not low (13-21 Hz) beta frequency range correlated with 'hyperdirect pathway' fibre densities between these structures. Furthermore, supplementary motor area activity drove STN activity selectively at high beta frequencies suggesting that high beta frequencies propagate from the cortex to the basal ganglia via the hyperdirect pathway. Computational modelling revealed that exaggerated high beta hyperdirect pathway activity can provoke the generation of widespread pathological synchrony at lower beta frequencies. These findings suggest a spectral signature and a pathophysiological role for the hyperdirect pathway in PD.
Collapse
Affiliation(s)
- Ashwini Oswal
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK.
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
- The Wellcome Centre for Human Neuroimaging, University College London, London, UK.
| | - Chunyan Cao
- Department of Neurosurgery, Affiliated Ruijin Hospital, School of Medicine, Shanghai JiaoTong University, Shanghai, China
| | - Chien-Hung Yeh
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- School of Information and Electronics Engineering, Beijing Institute of Technology, Beijing, China
| | | | - James Gratwicke
- Department of Clinical and Movement Neurosciences, University College London, London, UK
| | - Harith Akram
- Department of Clinical and Movement Neurosciences, University College London, London, UK
| | - Andreas Horn
- Department of Neurology, Charité University, Berlin, Germany
| | - Dianyou Li
- Department of Neurosurgery, Affiliated Ruijin Hospital, School of Medicine, Shanghai JiaoTong University, Shanghai, China
| | - Shikun Zhan
- Department of Neurosurgery, Affiliated Ruijin Hospital, School of Medicine, Shanghai JiaoTong University, Shanghai, China
| | - Chao Zhang
- Department of Neurosurgery, Affiliated Ruijin Hospital, School of Medicine, Shanghai JiaoTong University, Shanghai, China
| | - Qiang Wang
- Department of Neurology, Charité University, Berlin, Germany
| | - Ludvic Zrinzo
- Department of Clinical and Movement Neurosciences, University College London, London, UK
| | - Tom Foltynie
- Department of Clinical and Movement Neurosciences, University College London, London, UK
| | - Patricia Limousin
- Department of Clinical and Movement Neurosciences, University College London, London, UK
| | - Rafal Bogacz
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Bomin Sun
- Department of Neurosurgery, Affiliated Ruijin Hospital, School of Medicine, Shanghai JiaoTong University, Shanghai, China
| | - Masud Husain
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Peter Brown
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, UK.
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
| | - Vladimir Litvak
- The Wellcome Centre for Human Neuroimaging, University College London, London, UK.
| |
Collapse
|
11
|
Baldi P, Alhassen W, Chen S, Nguyen H, Khoudari M, Alachkar A. Large-scale analysis reveals spatiotemporal circadian patterns of cilia transcriptomes in the primate brain. J Neurosci Res 2021; 99:2610-2624. [PMID: 34310750 DOI: 10.1002/jnr.24919] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 06/08/2021] [Accepted: 06/24/2021] [Indexed: 01/13/2023]
Abstract
Cilia are dynamic subcellular systems, with core structural and functional components operating in a highly coordinated manner. Since many environmental stimuli sensed by cilia are circadian in nature, it is reasonable to speculate that genes encoding cilia structural and functional components follow rhythmic circadian patterns of expression. Using computational methods and the largest spatiotemporal gene expression atlas of primates, we identified and analyzed the circadian rhythmic expression of cilia genes across 22 primate brain areas. We found that around 73% of cilia transcripts exhibited circadian rhythmicity across at least one of 22 brain regions. In 12 brain regions, cilia transcriptomes were significantly enriched with circadian oscillating transcripts, as compared to the rest of the transcriptome. The phase of the cilia circadian transcripts deviated from the phase of the majority of the background circadian transcripts, and transcripts coding for cilia basal body components accounted for the majority of cilia circadian transcripts. In addition, adjacent or functionally connected brain nuclei had large overlapping complements of circadian cilia genes. Most remarkably, cilia circadian transcripts shared across the basal ganglia nuclei and the prefrontal cortex peaked in these structures in sequential fashion that is similar to the sequential order of activation of the basal ganglia-cortical circuitry in connection with movement coordination, albeit on completely different timescales. These findings support a role for the circadian spatiotemporal orchestration of cilia gene expression in the normal physiology of the basal ganglia-cortical circuit and motor control. Studying orchestrated cilia rhythmicity in the basal ganglia-cortical circuits and other brain circuits may help develop better functional models, and shed light on the causal effects cilia functions have on these circuits and on the regulation of movement and other behaviors.
Collapse
Affiliation(s)
- Pierre Baldi
- Department of Computer Science, School of Information and Computer Sciences, University of California-Irvine, Irvine, CA, USA.,Institute for Genomics and Bioinformatics, School of Information and Computer Sciences, University of California-Irvine, Irvine, CA, USA
| | - Wedad Alhassen
- Department of Pharmaceutical Sciences, School of Pharmacy, University of California-Irvine, Irvine, CA, USA
| | - Siwei Chen
- Department of Computer Science, School of Information and Computer Sciences, University of California-Irvine, Irvine, CA, USA.,Institute for Genomics and Bioinformatics, School of Information and Computer Sciences, University of California-Irvine, Irvine, CA, USA
| | - Henry Nguyen
- Department of Pharmaceutical Sciences, School of Pharmacy, University of California-Irvine, Irvine, CA, USA
| | - Mohammad Khoudari
- Department of Pharmaceutical Sciences, School of Pharmacy, University of California-Irvine, Irvine, CA, USA
| | - Amal Alachkar
- Institute for Genomics and Bioinformatics, School of Information and Computer Sciences, University of California-Irvine, Irvine, CA, USA.,Department of Pharmaceutical Sciences, School of Pharmacy, University of California-Irvine, Irvine, CA, USA
| |
Collapse
|
12
|
The causal interaction in human basal ganglia. Sci Rep 2021; 11:12989. [PMID: 34155321 PMCID: PMC8217174 DOI: 10.1038/s41598-021-92490-8] [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: 02/12/2021] [Accepted: 06/03/2021] [Indexed: 02/05/2023] Open
Abstract
The experimental study of the human brain has important restrictions, particularly in the case of basal ganglia, subcortical centers whose activity can be recorded with fMRI methods but cannot be directly modified. Similar restrictions occur in other complex systems such as those studied by Earth system science. The present work studied the cause/effect relationships between human basal ganglia with recently introduced methods to study climate dynamics. Data showed an exhaustive (identifying basal ganglia interactions regardless of their linear, non-linear or complex nature) and selective (avoiding spurious relationships) view of basal ganglia activity, showing a fast functional reconfiguration of their main centers during the execution of voluntary motor tasks. The methodology used here offers a novel view of the human basal ganglia which expands the perspective provided by the classical basal ganglia model and may help to understand BG activity under normal and pathological conditions.
Collapse
|
13
|
Litvak V, Florin E, Tamás G, Groppa S, Muthuraman M. EEG and MEG primers for tracking DBS network effects. Neuroimage 2020; 224:117447. [PMID: 33059051 DOI: 10.1016/j.neuroimage.2020.117447] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 10/08/2020] [Accepted: 10/08/2020] [Indexed: 10/23/2022] Open
Abstract
Deep brain stimulation (DBS) is an effective treatment method for a range of neurological and psychiatric disorders. It involves implantation of stimulating electrodes in a precisely guided fashion into subcortical structures and, at a later stage, chronic stimulation of these structures with an implantable pulse generator. While the DBS surgery makes it possible to both record brain activity and stimulate parts of the brain that are difficult to reach with non-invasive techniques, electroencephalography (EEG) and magnetoencephalography (MEG) provide complementary information from other brain areas, which can be used to characterize brain networks targeted through DBS. This requires, however, the careful consideration of different types of artifacts in the data acquisition and the subsequent analyses. Here, we review both the technical issues associated with EEG/MEG recordings in DBS patients and the experimental findings to date. One major line of research is simultaneous recording of local field potentials (LFPs) from DBS targets and EEG/MEG. These studies revealed a set of cortico-subcortical coherent networks functioning at distinguishable physiological frequencies. Specific network responses were linked to clinical state, task or stimulation parameters. Another experimental approach is mapping of DBS-targeted networks in chronically implanted patients by recording EEG/MEG responses during stimulation. One can track responses evoked by single stimulation pulses or bursts as well as brain state shifts caused by DBS. These studies have the potential to provide biomarkers for network responses that can be adapted to guide stereotactic implantation or optimization of stimulation parameters. This is especially important for diseases where the clinical effect of DBS is delayed or develops slowly over time. The same biomarkers could also potentially be utilized for the online control of DBS network effects in the new generation of closed-loop stimulators that are currently entering clinical use. Through future studies, the use of network biomarkers may facilitate the integration of circuit physiology into clinical decision making.
Collapse
Affiliation(s)
- Vladimir Litvak
- The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, UK
| | - Esther Florin
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Gertrúd Tamás
- Department of Neurology, Semmelweis University, Budapest, Hungary
| | - Sergiu Groppa
- Movement disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of the Johannes Gutenberg University, Langenbeckstrasse 1, 55131 Mainz, Germany
| | - Muthuraman Muthuraman
- Movement disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of the Johannes Gutenberg University, Langenbeckstrasse 1, 55131 Mainz, Germany.
| |
Collapse
|
14
|
Choi JW, Malekmohammadi M, Sparks H, Kashanian A, Cross KA, Bordelon Y, Pouratian N. Altered Pallidocortical Low-Beta Oscillations During Self-Initiated Movements in Parkinson Disease. Front Syst Neurosci 2020; 14:54. [PMID: 32792918 PMCID: PMC7390921 DOI: 10.3389/fnsys.2020.00054] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Accepted: 07/06/2020] [Indexed: 11/20/2022] Open
Abstract
Background Parkinson disease (PD) patients have difficulty with self-initiated (SI) movements, presumably related to basal ganglia thalamocortical (BGTC) circuit dysfunction, while showing less impairment with externally cued (EC) movements. Objectives We investigate the role of BGTC in movement initiation and the neural underpinning of impaired SI compared to EC movements in PD using multifocal intracranial recordings and correlating signals with symptom severity. Methods We compared time-resolved neural activities within and between globus pallidus internus (GPi) and motor cortex during between SI and EC movements recorded invasively in 13 PD patients undergoing deep brain stimulation implantation. We compared cortical (but not subcortical) dynamics with those recorded in 10 essential tremor (ET) patients, who do not have impairments in movement initiation. Results SI movements in PD are associated with greater low-beta (13–20 Hz) power suppression during pre-movement period in GPi and motor cortex compared to EC movements in PD and compared to SI movements in ET (motor cortex only). SI movements in PD are uniquely associated with significant low-beta pallidocortical coherence suppression during movement execution that correlates with bradykinesia severity. In ET, motor cortex neural dynamics during EC movements do not significantly differ from that observed in PD and do not significantly differ between SI and EC movements. Conclusion These findings implicate low beta BGTC oscillations in impaired SI movements in PD. These results provide a physiological basis for the strategy of using EC movements in PD, circumventing diseased neural circuits associated with SI movements and instead engaging circuits that function similarly to those without PD.
Collapse
Affiliation(s)
- Jeong Woo Choi
- Department of Neurosurgery, University of California, Los Angeles, Los Angeles, CA, United States
| | - Mahsa Malekmohammadi
- Department of Neurosurgery, University of California, Los Angeles, Los Angeles, CA, United States
| | - Hiro Sparks
- Department of Neurosurgery, University of California, Los Angeles, Los Angeles, CA, United States
| | - Alon Kashanian
- Department of Neurosurgery, University of California, Los Angeles, Los Angeles, CA, United States
| | - Katy A Cross
- Department of Neurology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Yvette Bordelon
- Department of Neurology, University of California, Los Angeles, Los Angeles, CA, United States
| | - Nader Pouratian
- Department of Neurosurgery, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States.,Brain Research Institute, University of California, Los Angeles, Los Angeles, CA, United States
| |
Collapse
|
15
|
Ramirez Pasos UE, Steigerwald F, Reich MM, Matthies C, Volkmann J, Reese R. Levodopa Modulates Functional Connectivity in the Upper Beta Band Between Subthalamic Nucleus and Muscle Activity in Tonic and Phasic Motor Activity Patterns in Parkinson's Disease. Front Hum Neurosci 2019; 13:223. [PMID: 31312129 PMCID: PMC6614179 DOI: 10.3389/fnhum.2019.00223] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2019] [Accepted: 06/18/2019] [Indexed: 01/10/2023] Open
Abstract
Introduction: Striatal dopamine depletion disrupts basal ganglia function and causes Parkinson's disease (PD). The pathophysiology of the dopamine-dependent relationship between basal ganglia signaling and motor control, however, is not fully understood. We obtained simultaneous recordings of local field potentials (LFPs) from the subthalamic nucleus (STN) and electromyograms (EMGs) in patients with PD to investigate the impact of dopaminergic state and movement on long-range beta functional connectivity between basal ganglia and lower motor neurons. Methods: Eight PD patients were investigated 3 months after implantation of a deep brain stimulation (DBS)-system capable of recording LFPs via chronically-implanted leads (Medtronic, ACTIVA PC+S®). We analyzed STN spectral power and its coherence with EMG in the context of two different movement paradigms (tonic wrist extension vs. alternating wrist extension and flexion) and the effect of levodopa (L-Dopa) intake using an unbiased data-driven approach to determine regions of interest (ROI). Results: Two ROIs capturing prominent coherence within a grand average coherogram were identified. A trend of a dopamine effect was observed for the first ROI (50-150 ms after movement start) with higher STN-EMG coherence in medicated patients. Concerning the second ROI (300-500 ms after movement start), an interaction effect of L-Dopa medication and movement task was observed with higher coherence in the isometric contraction task compared to alternating movements in the medication ON state, a pattern which was reversed in L-Dopa OFF. Discussion: L-Dopa medication may normalize functional connectivity between remote structures of the motor system with increased upper beta coherence reflecting a physiological restriction of the amount of information conveyed between remote structures. This may be necessary to maintain simple movements like isometric contraction. Our study adds dynamic properties to the complex interplay between STN spectral beta power and the nucleus' functional connectivity to remote structures of the motor system as a function of movement and dopaminergic state. This may help to identify markers of neuronal activity relevant for more individualized programming of DBS therapy.
Collapse
Affiliation(s)
| | - Frank Steigerwald
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - Martin M Reich
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - Cordula Matthies
- Department of Neurosurgery, University Hospital Würzburg, Würzburg, Germany
| | - Jens Volkmann
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - René Reese
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany.,Department of Neurology, University of Rostock, Rostock, Germany
| |
Collapse
|
16
|
Middlebrooks EH, Tuna IS, Grewal SS, Almeida L, Heckman MG, Lesser ER, Foote KD, Okun MS, Holanda VM. Segmentation of the Globus Pallidus Internus Using Probabilistic Diffusion Tractography for Deep Brain Stimulation Targeting in Parkinson Disease. AJNR Am J Neuroradiol 2018; 39:1127-1134. [PMID: 29700048 DOI: 10.3174/ajnr.a5641] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2017] [Accepted: 02/24/2018] [Indexed: 01/13/2023]
Abstract
BACKGROUND AND PURPOSE Although globus pallidus internus deep brain stimulation is a widely accepted treatment for Parkinson disease, there is persistent variability in outcomes that is not yet fully understood. In this pilot study, we aimed to investigate the potential role of globus pallidus internus segmentation using probabilistic tractography as a supplement to traditional targeting methods. MATERIALS AND METHODS Eleven patients undergoing globus pallidus internus deep brain stimulation were included in this retrospective analysis. Using multidirection diffusion-weighted MR imaging, we performed probabilistic tractography at all individual globus pallidus internus voxels. Each globus pallidus internus voxel was then assigned to the 1 ROI with the greatest number of propagated paths. On the basis of deep brain stimulation programming settings, the volume of tissue activated was generated for each patient using a finite element method solution. For each patient, the volume of tissue activated within each of the 10 segmented globus pallidus internus regions was calculated and examined for association with a change in the Unified Parkinson Disease Rating Scale, Part III score before and after treatment. RESULTS Increasing volume of tissue activated was most strongly correlated with a change in the Unified Parkinson Disease Rating Scale, Part III score for the primary motor region (Spearman r = 0.74, P = .010), followed by the supplementary motor area/premotor cortex (Spearman r = 0.47, P = .15). CONCLUSIONS In this pilot study, we assessed a novel method of segmentation of the globus pallidus internus based on probabilistic tractography as a supplement to traditional targeting methods. Our results suggest that our method may be an independent predictor of deep brain stimulation outcome, and evaluation of a larger cohort or prospective study is warranted to validate these findings.
Collapse
Affiliation(s)
| | - I S Tuna
- Departments of Radiology (I.S.T.)
| | | | | | - M G Heckman
- Division of Biomedical Statistics and Informatics (M.G.H., E.R.L.), Mayo Clinic, Jacksonville, Florida
| | - E R Lesser
- Division of Biomedical Statistics and Informatics (M.G.H., E.R.L.), Mayo Clinic, Jacksonville, Florida
| | - K D Foote
- Neurosurgery (K.D.F.), University of Florida, Gainesville, Florida
| | | | - V M Holanda
- Center of Neurology and Neurosurgery Associates (V.M.H.), BP-A Beneficência Portuguesa de São Paulo, São Paulo, Brazil
| |
Collapse
|
17
|
Spatio-temporal dynamics of cortical drive to human subthalamic nucleus neurons in Parkinson's disease. Neurobiol Dis 2018; 112:49-62. [PMID: 29307661 PMCID: PMC5821899 DOI: 10.1016/j.nbd.2018.01.001] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2017] [Revised: 11/30/2017] [Accepted: 01/03/2018] [Indexed: 11/24/2022] Open
Abstract
Pathological synchronisation of beta frequency (12–35 Hz) oscillations between the subthalamic nucleus (STN) and cerebral cortex is thought to contribute to motor impairment in Parkinson's disease (PD). For this cortico-subthalamic oscillatory drive to be mechanistically important, it must influence the firing of STN neurons and, consequently, their downstream targets. Here, we examined the dynamics of synchronisation between STN LFPs and units with multiple cortical areas, measured using frontal ECoG, midline EEG and lateral EEG, during rest and movement. STN neurons lagged cortical signals recorded over midline (over premotor cortices) and frontal (over prefrontal cortices) with stable time delays, consistent with strong corticosubthalamic drive, and many neurons maintained these dynamics during movement. In contrast, most STN neurons desynchronised from lateral EEG signals (over primary motor cortices) during movement and those that did not had altered phase relations to the cortical signals. The strength of synchronisation between STN units and midline EEG in the high beta range (25–35 Hz) correlated positively with the severity of akinetic-rigid motor symptoms across patients. Together, these results suggest that sustained synchronisation of STN neurons to premotor-cortical beta oscillations play an important role in disrupting the normal coding of movement in PD. Multi-channel EEG with coincident STN single unit and local field potential recordings Variable time delays between beta oscillations in different cortical areas and STN neurons. Frontal/premotor cortical areas have most stable oscillatory synchronisation with STN neurons. Correlation between cortico-subthalamic beta-frequency synchronisation and clinical scores in PD.
Collapse
|
18
|
Talakoub O, Paiva RR, Milosevic M, Hoexter MQ, Franco R, Alho E, Navarro J, Pereira JF, Popovic MR, Savage C, Lopes AC, Alvarenga P, Damiani D, Teixeira MJ, Miguel EC, Fonoff ET, Batistuzzo MC, Hamani C. Lateral hypothalamic activity indicates hunger and satiety states in humans. Ann Clin Transl Neurol 2017; 4:897-901. [PMID: 29296618 PMCID: PMC5740250 DOI: 10.1002/acn3.466] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2017] [Accepted: 08/09/2017] [Indexed: 12/02/2022] Open
Abstract
Lateral hypothalamic area (LHA) local field potentials (LFPs) were recorded in a Prader–Willi patient undergoing deep brain stimulation (DBS) for obesity. During hunger, exposure to food‐related cues induced an increase in beta/low‐gamma activity. In contrast, recordings during satiety were marked by prominent alpha rhythms. Based on these findings, we have delivered alpha‐frequency DBS prior to and during food intake. Despite reporting an early sensation of fullness, the patient continued to crave food. This suggests that the pattern of activity in LHA may indicate hunger/satiety states in humans but attest to the complexity of conducting neuromodulation studies in obesity.
Collapse
Affiliation(s)
- Omid Talakoub
- Institute of Biomaterials and Biomedical Engineering University of Toronto Toronto Canada
| | - Raquel R Paiva
- Department of Psychiatry Institute of Psychiatry University of São Paulo Medical School São Paulo Brazil
| | - Matija Milosevic
- Institute of Biomaterials and Biomedical Engineering University of Toronto Toronto Canada.,Rehabilitation Engineering Laboratory Toronto Rehabilitation Institute - University Health Network Toronto Canada
| | - Marcelo Q Hoexter
- Department of Psychiatry Institute of Psychiatry University of São Paulo Medical School São Paulo Brazil
| | - Ruth Franco
- Division of Pediatric Endocrinology Children's Institute of Neurology University of São Paulo Medical School São Paulo Brazil
| | - Eduardo Alho
- Division of Functional Neurosurgery of Institute of Psychiatry Department of Neurology University of São Paulo Medical School São Paulo Brazil
| | - Jessie Navarro
- Division of Functional Neurosurgery of Institute of Psychiatry Department of Neurology University of São Paulo Medical School São Paulo Brazil
| | - José F Pereira
- Division of Functional Neurosurgery of Institute of Psychiatry Department of Neurology University of São Paulo Medical School São Paulo Brazil
| | - Milos R Popovic
- Institute of Biomaterials and Biomedical Engineering University of Toronto Toronto Canada.,Rehabilitation Engineering Laboratory Toronto Rehabilitation Institute - University Health Network Toronto Canada
| | - Cary Savage
- Banner Alzheimer's Institute Phoenix United States
| | - Antonio C Lopes
- Department of Psychiatry Institute of Psychiatry University of São Paulo Medical School São Paulo Brazil
| | - Pedro Alvarenga
- Department of Psychiatry Institute of Psychiatry University of São Paulo Medical School São Paulo Brazil
| | - Durval Damiani
- Division of Pediatric Endocrinology Children's Institute of Neurology University of São Paulo Medical School São Paulo Brazil
| | - Manoel J Teixeira
- Division of Functional Neurosurgery of Institute of Psychiatry Department of Neurology University of São Paulo Medical School São Paulo Brazil
| | - Euripides C Miguel
- Department of Psychiatry Institute of Psychiatry University of São Paulo Medical School São Paulo Brazil
| | - Erich T Fonoff
- Division of Functional Neurosurgery of Institute of Psychiatry Department of Neurology University of São Paulo Medical School São Paulo Brazil.,Instituto de Ensino e Pesquisa Hospital Sírio-Libanês Sǎo Paulo Brazil
| | - Marcelo C Batistuzzo
- Department of Psychiatry Institute of Psychiatry University of São Paulo Medical School São Paulo Brazil
| | - Clement Hamani
- Behavioural Neurobiology Laboratory Campbell Family Mental Health Research Institute Centre for Addiction and Mental Health Canada.,Division of Neurosurgery Toronto Western Hospital University of Toronto Canada.,Department of Psychiatry Institute of Psychiatry University of São Paulo Medical School São Paulo Brazil
| |
Collapse
|
19
|
Talakoub O, Marquez-Chin C, Popovic MR, Navarro J, Fonoff ET, Hamani C, Wong W. Reconstruction of reaching movement trajectories using electrocorticographic signals in humans. PLoS One 2017; 12:e0182542. [PMID: 28931054 PMCID: PMC5606933 DOI: 10.1371/journal.pone.0182542] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2016] [Accepted: 07/20/2017] [Indexed: 01/08/2023] Open
Abstract
In this study, we used electrocorticographic (ECoG) signals to extract the onset of arm movement as well as the velocity of the hand as a function of time. ECoG recordings were obtained from three individuals while they performed reaching tasks in the left, right and forward directions. The ECoG electrodes were placed over the motor cortex contralateral to the moving arm. Movement onset was detected from gamma activity with near perfect accuracy (> 98%), and a multiple linear regression model was used to predict the trajectory of the reaching task in three-dimensional space with an accuracy exceeding 85%. An adaptive selection of frequency bands was used for movement classification and prediction. This demonstrates the efficacy of developing a real-time brain-machine interface for arm movements with as few as eight ECoG electrodes.
Collapse
Affiliation(s)
- Omid Talakoub
- Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada
- Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Canada
| | - Cesar Marquez-Chin
- Rehabilitation Engineering Laboratory, Toronto Rehabilitation Institute–University Health Network, Toronto, Canada
- Neural Engineering Laboratory, Toronto Rehabilitation Institute–University Health Network, Toronto, Canada
| | - Milos R. Popovic
- Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Canada
- Rehabilitation Engineering Laboratory, Toronto Rehabilitation Institute–University Health Network, Toronto, Canada
| | - Jessie Navarro
- Division of Functional Neurosurgery of Institute of Psychiatry, Hospital das Clínicas, Department of Neurology, University of Sao Paulo Medical School, São Paulo, Brazil
| | - Erich T. Fonoff
- Division of Functional Neurosurgery of Institute of Psychiatry, Hospital das Clínicas, Department of Neurology, University of Sao Paulo Medical School, São Paulo, Brazil
| | - Clement Hamani
- Toronto Western Research Institute–University Health Network, Toronto, Canada
| | - Willy Wong
- Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada
- Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Canada
- * E-mail:
| |
Collapse
|
20
|
van Wijk BCM, Neumann WJ, Schneider GH, Sander TH, Litvak V, Kühn AA. Low-beta cortico-pallidal coherence decreases during movement and correlates with overall reaction time. Neuroimage 2017; 159:1-8. [PMID: 28712991 PMCID: PMC5678295 DOI: 10.1016/j.neuroimage.2017.07.024] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2017] [Revised: 07/10/2017] [Accepted: 07/12/2017] [Indexed: 01/02/2023] Open
Abstract
Beta band oscillations (13–30 Hz) are a hallmark of cortical and subcortical structures that are part of the motor system. In addition to local population activity, oscillations also provide a means for synchronization of activity between regions. Here we examined the role of beta band coherence between the internal globus pallidus (GPi) and (motor) cortex during a simple reaction time task performed by nine patients with idiopathic dystonia. We recorded local field potentials from deep brain stimulation (DBS) electrodes implanted in bilateral GPi in combination with simultaneous whole-head magneto-encephalography (MEG). Patients responded to visually presented go or stop-signal cues by pressing a button with left or right hand. Although coherence between signals from DBS electrodes and MEG sensors was observed throughout the entire beta band, a significant movement-related decrease prevailed in lower beta frequencies (∼13–21 Hz). In addition, patients' absolute coherence values in this frequency range significantly correlated with their median reaction time during the task (r = 0.89, p = 0.003). These findings corroborate the recent idea of two functionally distinct frequency ranges within the beta band, as well as the anti-kinetic character of beta oscillations. Simultaneous internal pallidum LFP and MEG recordings in dystonia patients. Cortico-pallidal coherence was found throughout the beta frequency range. Predominantly low-beta coherence (13–21 Hz) decreased with movement. Overall level of coherence was indicative of subject's median reaction time. No correlations were found between beta coherence measures and clinical scores.
Collapse
Affiliation(s)
- Bernadette C M van Wijk
- Department of Neurology, Charité - University Medicine Berlin, Germany; Wellcome Trust Centre for Neuroimaging, University College London, UK.
| | | | | | | | - Vladimir Litvak
- Wellcome Trust Centre for Neuroimaging, University College London, UK
| | - Andrea A Kühn
- Department of Neurology, Charité - University Medicine Berlin, Germany; Berlin School of Mind and Brain, Charité - University Medicine Berlin, Germany; NeuroCure, Charité - University Medicine Berlin, Germany
| |
Collapse
|