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Ghazizadeh E, Naseri Z, Deigner HP, Rahimi H, Altintas Z. Approaches of wearable and implantable biosensor towards of developing in precision medicine. Front Med (Lausanne) 2024; 11:1390634. [PMID: 39091290 PMCID: PMC11293309 DOI: 10.3389/fmed.2024.1390634] [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: 02/23/2024] [Accepted: 04/30/2024] [Indexed: 08/04/2024] Open
Abstract
In the relentless pursuit of precision medicine, the intersection of cutting-edge technology and healthcare has given rise to a transformative era. At the forefront of this revolution stands the burgeoning field of wearable and implantable biosensors, promising a paradigm shift in how we monitor, analyze, and tailor medical interventions. As these miniature marvels seamlessly integrate with the human body, they weave a tapestry of real-time health data, offering unprecedented insights into individual physiological landscapes. This log embarks on a journey into the realm of wearable and implantable biosensors, where the convergence of biology and technology heralds a new dawn in personalized healthcare. Here, we explore the intricate web of innovations, challenges, and the immense potential these bioelectronics sentinels hold in sculpting the future of precision medicine.
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Affiliation(s)
- Elham Ghazizadeh
- Department of Bioinspired Materials and Biosensor Technologies, Faculty of Engineering, Institute of Materials Science, Kiel University, Kiel, Germany
- Department of Medical Biotechnology, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Zahra Naseri
- Department of Medical Biotechnology, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Hans-Peter Deigner
- Institute of Precision Medicine, Furtwangen University, Villingen-Schwenningen, Germany
- Fraunhofer Institute IZI (Leipzig), Rostock, Germany
- Faculty of Science, Eberhard-Karls-University Tuebingen, Tuebingen, Germany
| | - Hossein Rahimi
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
| | - Zeynep Altintas
- Department of Bioinspired Materials and Biosensor Technologies, Faculty of Engineering, Institute of Materials Science, Kiel University, Kiel, Germany
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2
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Sihn D, Kim SP. Disruption of alpha oscillation propagation in patients with schizophrenia. Clin Neurophysiol 2024; 162:262-270. [PMID: 38480063 DOI: 10.1016/j.clinph.2024.02.028] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 01/18/2024] [Accepted: 02/17/2024] [Indexed: 05/19/2024]
Abstract
OBJECTIVE Propagation of electroencephalogram (EEG) oscillations, often referred to as traveling waves, reflects the role of brain oscillations in neural information transmission. This propagation can be distorted by brain disorders such as schizophrenia that features disconnection of neural information transmission (i.e., disconnection syndrome). However, this possibility of the disruption of EEG oscillation propagation in patients with schizophrenia remains largely unexplored. METHODS Using a publicly shared dataset (N = 19 and 24; patients with schizophrenia and healthy controls, respectively), we investigated EEG oscillation propagation by analyzing the local phase gradients (LPG) of alpha (8-12 Hz) oscillations in both healthy participants and patients with schizophrenia. RESULTS Our results showed significant directionality in the propagation of alpha oscillations in healthy participants. Specifically, alpha oscillations propagated in an anterior-to-posterior direction along mid-line and a posterior-to-anterior direction laterally. In patients with schizophrenia, some of alpha oscillation propagation were notably disrupted, particularly in the central midline area where alpha oscillations propagated from anterior to posterior areas. CONCLUSION Our finding lends support to the hypothesis of a disconnection syndrome in schizophrenia, underscoring a disruption in the anterior-to-posterior propagation of alpha oscillations. SIGNIFICANCE This study identified disruption of alpha oscillation propagation observed in scalp EEG as a biomarker for schizophrenia.
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Affiliation(s)
- Duho Sihn
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea
| | - Sung-Phil Kim
- Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea.
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3
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Mohan UR, Zhang H, Ermentrout B, Jacobs J. The direction of theta and alpha travelling waves modulates human memory processing. Nat Hum Behav 2024; 8:1124-1135. [PMID: 38459263 DOI: 10.1038/s41562-024-01838-3] [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: 07/14/2023] [Accepted: 01/24/2024] [Indexed: 03/10/2024]
Abstract
To support a range of behaviours, the brain must flexibly coordinate neural activity across widespread brain regions. One potential mechanism for this coordination is a travelling wave, in which a neural oscillation propagates across the brain while organizing the order and timing of activity across regions. Although travelling waves are present across the brain in various species, their potential functional relevance has remained unknown. Here, using rare direct human brain recordings, we demonstrate a distinct functional role for travelling waves of theta- and alpha-band (2-13 Hz) oscillations in the cortex. Travelling waves propagate in different directions during separate cognitive processes. In episodic memory, travelling waves tended to propagate in a posterior-to-anterior direction during successful memory encoding and in an anterior-to-posterior direction during recall. Because travelling waves of oscillations correspond to local neuronal spiking, these patterns indicate that rhythmic pulses of activity move across the brain in different directions for separate behaviours. More broadly, our results suggest a fundamental role for travelling waves and oscillations in dynamically coordinating neural connectivity, by flexibly organizing the timing and directionality of network interactions across the cortex to support cognition and behaviour.
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Affiliation(s)
- Uma R Mohan
- Surgical Neurology Branch, NINDS, National Institutes of Health, Bethesda, MD, USA
| | | | - Bard Ermentrout
- Department of Mathematics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Joshua Jacobs
- Department of Biomedical Engineering, Columbia University, New York City, NY, USA.
- Department of Neurological Surgery, Columbia University, New York City, NY, USA.
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4
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Ramon C, Doud A, Holmes MD. Decrease in phase slip rates and phase cone structures during seizure evolution and epileptogenic activities derived from microgrid ECoG data. CURRENT RESEARCH IN NEUROBIOLOGY 2024; 6:100126. [PMID: 38616959 PMCID: PMC11015059 DOI: 10.1016/j.crneur.2024.100126] [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: 05/18/2023] [Revised: 12/25/2023] [Accepted: 02/03/2024] [Indexed: 04/16/2024] Open
Abstract
Sudden phase changes are related to cortical phase transitions, which likely change in frequency and spatial distribution as epileptogenic activity evolves. A 100 s long section of micro-ECoG data obtained before and during a seizure was selected and analyzed. In addition, nine other short-duration epileptic events were also examined. The data was collected at 420 Hz, imported into MATLAB, downsampled to 200 Hz, and filtered in the 1-50 Hz band. The Hilbert transform was applied to compute the analytic phase, which was then unwrapped, and detrended to look for sudden phase changes. The phase slip rate (counts/s) and its acceleration (counts/s2) were computed with a stepping window of 1-s duration and with a step size of 5 ms. The analysis was performed for theta (3-7 Hz), alpha (7-12 Hz), and beta (12-30 Hz) bands. The phase slip rate on all electrodes in the theta band decreased while it increased for the alpha and beta bands during the seizure period. Similar patterns were observed for isolated epileptogenic events. Spatiotemporal contour plots of the phase slip rates were also constructed using a montage layout of 8 × 8 electrode positions. These plots exhibited dynamic and oscillatory formation of phase cone-like structures which were higher in the theta band and lower in the alpha and beta bands during the seizure period and epileptogenic events. These results indicate that the formation of phase cones might be an excellent biomarker to study the evolution of a seizure and also the cortical dynamics of isolated epileptogenic events.
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Affiliation(s)
- Ceon Ramon
- Department of Electrical & Computer Engineering, University of Washington, Seattle, WA, 98195, USA
- Regional Epilepsy Center, Harborview Medical Center, Department of Neurology, University of Washington, Seattle, WA, 98195, USA
| | - Alexander Doud
- Providence Spokane Neuroscience Institute, 105 West 8th Avenue, Spokane, WA, 99204, USA
| | - Mark D. Holmes
- Regional Epilepsy Center, Harborview Medical Center, Department of Neurology, University of Washington, Seattle, WA, 98195, USA
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Paulk AC, Salami P, Zelmann R, Cash SS. Electrode Development for Epilepsy Diagnosis and Treatment. Neurosurg Clin N Am 2024; 35:135-149. [PMID: 38000837 DOI: 10.1016/j.nec.2023.09.003] [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: 11/26/2023]
Abstract
Recording neural activity has been a critical aspect in the diagnosis and treatment of patients with epilepsy. For those with intractable epilepsy, intracranial neural monitoring has been of substantial importance. Clinically, however, methods for recording neural information have remained essentially unchanged for decades. Over the last decade or so, rapid advances in electrode technology have begun to change this landscape. New systems allow for the observation of neural activity with high spatial resolution and, in some cases, at the level of the activity of individual neurons. These new tools have contributed greatly to our understanding of brain function and dysfunction. Here, the authors review the primary technologies currently in use in humans. The authors discuss other possible systems, some of the challenges which come along with these devices, and how they will become incorporated into the clinical workflow. Ultimately, the expectation is that these new, high-density, high-spatial-resolution recording systems will become a valuable part of the clinical arsenal used in the diagnosis and surgical management of epilepsy.
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Affiliation(s)
- Angelique C Paulk
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, 55 Fruit Street, Boston, MA 02114, USA.
| | - Pariya Salami
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, 55 Fruit Street, Boston, MA 02114, USA
| | - Rina Zelmann
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, 55 Fruit Street, Boston, MA 02114, USA
| | - Sydney S Cash
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, 55 Fruit Street, Boston, MA 02114, USA
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6
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Lee S, Shirinpour S, Alekseichuk I, Perera N, Linn G, Schroeder CE, Falchier AY, Opitz A. Predicting the phase distribution during multi-channel transcranial alternating current stimulation in silico and in vivo. Comput Biol Med 2023; 166:107516. [PMID: 37769460 PMCID: PMC10955626 DOI: 10.1016/j.compbiomed.2023.107516] [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: 06/15/2023] [Revised: 08/22/2023] [Accepted: 09/19/2023] [Indexed: 09/30/2023]
Abstract
BACKGROUND Transcranial alternating current stimulation (tACS) is a widely used noninvasive brain stimulation (NIBS) technique to affect neural activity. TACS experiments have been coupled with computational simulations to predict the electromagnetic fields within the brain. However, existing simulations are focused on the magnitude of the field. As the possibility of inducing the phase gradient in the brain using multiple tACS electrodes arises, a simulation framework is necessary to investigate and predict the phase gradient of electric fields during multi-channel tACS. OBJECTIVE Here, we develop such a framework for phasor simulation using phasor algebra and evaluate its accuracy using in vivo recordings in monkeys. METHODS We extract the phase and amplitude of electric fields from intracranial recordings in two monkeys during multi-channel tACS and compare them to those calculated by phasor analysis using finite element models. RESULTS Our findings demonstrate that simulated phases correspond well to measured phases (r = 0.9). Further, we systematically evaluated the impact of accurate electrode placement on modeling and data agreement. Finally, our framework can predict the amplitude distribution in measurements given calibrated tissues' conductivity. CONCLUSIONS Our validated general framework for simulating multi-phase, multi-electrode tACS provides a streamlined tool for principled planning of multi-channel tACS experiments.
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Affiliation(s)
- Sangjun Lee
- Department of Biomedical Engineering, University of Minnesota, MN, USA.
| | - Sina Shirinpour
- Department of Biomedical Engineering, University of Minnesota, MN, USA
| | - Ivan Alekseichuk
- Department of Biomedical Engineering, University of Minnesota, MN, USA
| | - Nipun Perera
- Department of Biomedical Engineering, University of Minnesota, MN, USA
| | - Gary Linn
- Translational Neuroscience Lab Division, Center for Biomedical Imaging and Neuromodulation, The Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA; Department of Psychiatry NYU Grossman School of Medicine, New York City, NY, USA
| | - Charles E Schroeder
- Translational Neuroscience Lab Division, Center for Biomedical Imaging and Neuromodulation, The Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA; Departments of Neurological Surgery and Psychiatry, Columbia University College of Physicians and Surgeons, NY, USA
| | - Arnaud Y Falchier
- Translational Neuroscience Lab Division, Center for Biomedical Imaging and Neuromodulation, The Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA; Department of Psychiatry NYU Grossman School of Medicine, New York City, NY, USA
| | - Alexander Opitz
- Department of Biomedical Engineering, University of Minnesota, MN, USA.
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7
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Coughlin B, Muñoz W, Kfir Y, Young MJ, Meszéna D, Jamali M, Caprara I, Hardstone R, Khanna A, Mustroph ML, Trautmann EM, Windolf C, Varol E, Soper DJ, Stavisky SD, Welkenhuysen M, Dutta B, Shenoy KV, Hochberg LR, Mark Richardson R, Williams ZM, Cash SS, Paulk AC. Modified Neuropixels probes for recording human neurophysiology in the operating room. Nat Protoc 2023; 18:2927-2953. [PMID: 37697108 DOI: 10.1038/s41596-023-00871-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 06/08/2023] [Indexed: 09/13/2023]
Abstract
Neuropixels are silicon-based electrophysiology-recording probes with high channel count and recording-site density. These probes offer a turnkey platform for measuring neural activity with single-cell resolution and at a scale that is beyond the capabilities of current clinically approved devices. Our team demonstrated the first-in-human use of these probes during resection surgery for epilepsy or tumors and deep brain stimulation electrode placement in patients with Parkinson's disease. Here, we provide a better understanding of the capabilities and challenges of using Neuropixels as a research tool to study human neurophysiology, with the hope that this information may inform future efforts toward regulatory approval of Neuropixels probes as research devices. In perioperative procedures, the major concerns are the initial sterility of the device, maintaining a sterile field during surgery, having multiple referencing and grounding schemes available to de-noise recordings (if necessary), protecting the silicon probe from accidental contact before insertion and obtaining high-quality action potential and local field potential recordings. The research team ensures that the device is fully operational while coordinating with the surgical team to remove sources of electrical noise that could otherwise substantially affect the signals recorded by the sensitive hardware. Prior preparation using the equipment and training in human clinical research and working in operating rooms maximize effective communication within and between the teams, ensuring high recording quality and minimizing the time added to the surgery. The perioperative procedure requires ~4 h, and the entire protocol requires multiple weeks.
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Affiliation(s)
- Brian Coughlin
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - William Muñoz
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Yoav Kfir
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Michael J Young
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Domokos Meszéna
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Mohsen Jamali
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Irene Caprara
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Richard Hardstone
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Arjun Khanna
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Martina L Mustroph
- Department of Neurosurgery, Harvard Medical School and Brigham & Women's Hospital, Boston, MA, USA
| | - Eric M Trautmann
- Department of Neuroscience, Columbia University Medical Center, New York, NY, USA
- Zuckerman Institute, Columbia University, New York, NY, USA
- Grossman Center for the Statistics of Mind, Columbia University Medical Center, New York, NY, USA
| | - Charlie Windolf
- Department of Statistics, Zuckerman Institute, Columbia University, New York, NY, USA
| | - Erdem Varol
- Department of Statistics, Zuckerman Institute, Columbia University, New York, NY, USA
- Department of Computer Science and Engineering, Zuckerman Institute, Columbia University, New York, NY, USA
| | - Dan J Soper
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Sergey D Stavisky
- Department of Neurological Surgery, University of California Davis, Davis, CA, USA
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute and Bio-X Institute, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA
| | | | | | - Krishna V Shenoy
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute and Bio-X Institute, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Department of Neurobiology, Stanford University, Stanford, CA, USA
| | - Leigh R Hochberg
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
- VA RR&D Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Providence VA Medical Center, Providence, RI, USA
- School of Engineering and Carney Institute for Brain Science, Brown University, Providence, RI, USA
| | - R Mark Richardson
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Ziv M Williams
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA.
| | - Sydney S Cash
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
- Department of Neurology, Harvard Medical School, Boston, MA, USA.
| | - Angelique C Paulk
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
- Department of Neurology, Harvard Medical School, Boston, MA, USA.
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Zabeh E, Foley NC, Jacobs J, Gottlieb JP. Beta traveling waves in monkey frontal and parietal areas encode recent reward history. Nat Commun 2023; 14:5428. [PMID: 37669966 PMCID: PMC10480436 DOI: 10.1038/s41467-023-41125-9] [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: 05/16/2022] [Accepted: 08/22/2023] [Indexed: 09/07/2023] Open
Abstract
Brain function depends on neural communication, but the mechanisms of this communication are not well understood. Recent studies suggest that one form of neural communication is through traveling waves (TWs)-patterns of neural oscillations that propagate within and between brain areas. We show that TWs are robust in microarray recordings in frontal and parietal cortex and encode recent reward history. Two adult male monkeys made saccades to obtain probabilistic rewards and were sensitive to the (statistically irrelevant) reward on the previous trial. TWs in frontal and parietal areas were stronger in trials that followed a prior reward versus a lack of reward and, in the frontal lobe, correlated with the monkeys' behavioral sensitivity to the prior reward. The findings suggest that neural communication mediated by TWs within the frontal and parietal lobes contribute to maintaining information about recent reward history and mediating the impact of this history on the monkeys' expectations.
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Affiliation(s)
- Erfan Zabeh
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
| | - Nicholas C Foley
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
| | - Joshua Jacobs
- Department of Biomedical Engineering, Columbia University, New York, NY, USA.
- Department of Neurological Surgery, Columbia University, New York, NY, USA.
| | - Jacqueline P Gottlieb
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA.
- Department of Neuroscience, Columbia University, New York, NY, USA.
- Kavli Institute for Brain Science, Columbia University, New York, NY, USA.
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Wu Y, Chen ZS. Computational models for state-dependent traveling waves in hippocampal formation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.19.541436. [PMID: 37292865 PMCID: PMC10245836 DOI: 10.1101/2023.05.19.541436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Hippocampal theta (4-10 Hz) oscillations have been identified as traveling waves in both rodents and humans. In freely foraging rodents, the theta traveling wave is a planar wave propagating from the dorsal to ventral hippocampus along the septotemporal axis. Motivated from experimental findings, we develop a spiking neural network of excitatory and inhibitory neurons to generate state-dependent hippocampal traveling waves to improve current mechanistic understanding of propagating waves. Model simulations demonstrate the necessary conditions for generating wave propagation and characterize the traveling wave properties with respect to model parameters, running speed and brain state of the animal. Networks with long-range inhibitory connections are more suitable than networks with long-range excitatory connections. We further generalize the spiking neural network to model traveling waves in the medial entorhinal cortex (MEC) and predict that traveling theta waves in the hippocampus and entorhinal cortex are in sink.
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10
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Son S, Moon J, Kim YJ, Kang MS, Lee J. Frontal-to-visual information flow explains predictive motion tracking. Neuroimage 2023; 269:119914. [PMID: 36736637 DOI: 10.1016/j.neuroimage.2023.119914] [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: 11/03/2022] [Revised: 01/28/2023] [Accepted: 01/30/2023] [Indexed: 02/04/2023] Open
Abstract
Predictive tracking demonstrates our ability to maintain a line of vision on moving objects even when they temporarily disappear. Models of smooth pursuit eye movements posit that our brain achieves this ability by directly streamlining motor programming from continuously updated sensory motion information. To test this hypothesis, we obtained sensory motion representation from multivariate electroencephalogram activity while human participants covertly tracked a temporarily occluded moving stimulus with their eyes remaining stationary at the fixation point. The sensory motion representation of the occluded target evolves to its maximum strength at the expected timing of reappearance, suggesting a timely modulation of the internal model of the visual target. We further characterize the spatiotemporal dynamics of the task-relevant motion information by computing the phase gradients of slow oscillations. We discovered a predominant posterior-to-anterior phase gradient immediately after stimulus occlusion; however, at the expected timing of reappearance, the axis reverses the gradient, becoming anterior-to-posterior. The behavioral bias of smooth pursuit eye movements, which is a signature of the predictive process of the pursuit, was correlated with the posterior division of the gradient. These results suggest that the sensory motion area modulated by the prediction signal is involved in updating motor programming.
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Affiliation(s)
- Sangkyu Son
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon 16419, South Korea; Department of Biomedical Engineering, Sungkyunkwan University, Suwon 16419, South Korea
| | - Joonsik Moon
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon 16419, South Korea
| | - Yee-Joon Kim
- Center for Cognition and Sociality, Institute for Basic Science (IBS), Daejeon 34141, South Korea
| | - Min-Suk Kang
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon 16419, South Korea; Department of Psychology, Sungkyunkwan University, Seoul 03063, South Korea.
| | - Joonyeol Lee
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon 16419, South Korea; Department of Biomedical Engineering, Sungkyunkwan University, Suwon 16419, South Korea; Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon 16419, South Korea.
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11
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Chen ZS, Wilson MA. How our understanding of memory replay evolves. J Neurophysiol 2023; 129:552-580. [PMID: 36752404 PMCID: PMC9988534 DOI: 10.1152/jn.00454.2022] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 01/20/2023] [Accepted: 01/20/2023] [Indexed: 02/09/2023] Open
Abstract
Memory reactivations and replay, widely reported in the hippocampus and cortex across species, have been implicated in memory consolidation, planning, and spatial and skill learning. Technological advances in electrophysiology, calcium imaging, and human neuroimaging techniques have enabled neuroscientists to measure large-scale neural activity with increasing spatiotemporal resolution and have provided opportunities for developing robust analytic methods to identify memory replay. In this article, we first review a large body of historically important and representative memory replay studies from the animal and human literature. We then discuss our current understanding of memory replay functions in learning, planning, and memory consolidation and further discuss the progress in computational modeling that has contributed to these improvements. Next, we review past and present analytic methods for replay analyses and discuss their limitations and challenges. Finally, looking ahead, we discuss some promising analytic methods for detecting nonstereotypical, behaviorally nondecodable structures from large-scale neural recordings. We argue that seamless integration of multisite recordings, real-time replay decoding, and closed-loop manipulation experiments will be essential for delineating the role of memory replay in a wide range of cognitive and motor functions.
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Affiliation(s)
- Zhe Sage Chen
- Department of Psychiatry, New York University Grossman School of Medicine, New York, New York, United States
- Department of Neuroscience and Physiology, New York University Grossman School of Medicine, New York, New York, United States
- Neuroscience Institute, New York University Grossman School of Medicine, New York, New York, United States
- Department of Biomedical Engineering, New York University Tandon School of Engineering, Brooklyn, New York, United States
| | - Matthew A Wilson
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
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12
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Functional re-organization of hippocampal-cortical gradients during naturalistic memory processes. Neuroimage 2023; 271:119996. [PMID: 36863548 DOI: 10.1016/j.neuroimage.2023.119996] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 02/12/2023] [Accepted: 02/27/2023] [Indexed: 03/04/2023] Open
Abstract
The functional organization of the hippocampus mirrors that of the cortex, changing smoothly along connectivity gradients and abruptly at inter-areal boundaries. Hippocampal-dependent cognitive processes require flexible integration of these hippocampal gradients into functionally related cortical networks. To understand the cognitive relevance of this functional embedding, we acquired fMRI data while participants viewed brief news clips, either containing or lacking recently familiarized cues. Participants were 188 healthy mid-life adults and 31 adults with mild cognitive impairment (MCI) or Alzheimer's disease (AD). We employed a recently developed technique - connectivity gradientography - to study gradually changing patterns of voxel to whole brain functional connectivity and their sudden transitions. We observed that functional connectivity gradients of the anterior hippocampus map onto connectivity gradients across the default mode network during these naturalistic stimuli. The presence of familiar cues in the news clips accentuates a stepwise transition across the boundary from the anterior to the posterior hippocampus. This functional transition is shifted in the posterior direction in the left hippocampus of individuals with MCI or AD. These findings shed new light on the functional integration of hippocampal connectivity gradients into large-scale cortical networks, how these adapt with memory context and how these change in the presence of neurodegenerative disease.
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Chiang CC, Durand DM. Subthreshold Oscillating Waves in Neural Tissue Propagate by Volume Conduction and Generate Interference. Brain Sci 2022; 13:74. [PMID: 36672054 PMCID: PMC9856930 DOI: 10.3390/brainsci13010074] [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: 11/29/2022] [Revised: 12/21/2022] [Accepted: 12/28/2022] [Indexed: 12/31/2022] Open
Abstract
Subthreshold neural oscillations have been observed in several brain regions and can influence the timing of neural spikes. However, the spatial extent and function of these spontaneous oscillations remain unclear. To study the mechanisms underlying these oscillations, we use optogenetic stimulation to generate oscillating waves in the longitudinal hippocampal slice expressing optopatch proteins. We found that optogenetic stimulation can generate two types of neural activity: suprathreshold neural spikes and subthreshold oscillating waves. Both waves could propagate bidirectionally at similar speeds and go through a transection of the tissue. The propagating speed is independent of the oscillating frequency but increases with increasing amplitudes of the waves. The endogenous electric fields generated by oscillating waves are about 0.6 mV/mm along the dendrites and about 0.3 mV/mm along the cell layer. We also observed that these oscillating waves could interfere with each other. Optical stimulation applied simultaneously at each slice end generated a larger wave in the middle of the tissue (constructive interference) or destructive interference with laser signals in opposite phase. However, the suprathreshold neural spikes were annihilated when they collided. Finally, the waves were not affected by the NMDA blocker (APV) and still propagated in the presence of tetrodotoxin (TTX) but at a significantly lower amplitude. The role of these subthreshold waves in neural function is unknown, but the results show that at low amplitude, the subthreshold propagating waves lack a refractory period allowing a novel analog form of preprocessing of neural activity by interference independent of synaptic transmission.
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Affiliation(s)
| | - Dominique M. Durand
- Neural Engineering Center, Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA
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14
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Liu X, Wang F, Ramakrishna S. Hippocampus-guided engineering of memory prosthesis. CURRENT OPINION IN BIOMEDICAL ENGINEERING 2022. [DOI: 10.1016/j.cobme.2022.100415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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15
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Yener G, Öz D. Innovations in Neurophysiology and Their Use in Neuropsychiatry. Noro Psikiyatr Ars 2022; 59:S67-S74. [PMID: 36578987 PMCID: PMC9767126 DOI: 10.29399/npa.28234] [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: 06/04/2022] [Accepted: 07/31/2022] [Indexed: 12/31/2022] Open
Abstract
Many structural and functional tests are used to explore the nature of neurodevelopmental and neurodegenerative diseases. Cognitive involvement has become more and more remarkable in many neurological and psychiatric diseases. This condition evoked a paradigm shift, and today disorders are addressed from a neuroscientific perspective, including silent symptoms. The spatial resolution of structural studies is lacking and is combined with the unique temporal resolution of EEG methods. In our current clinical practice, EEG does not have definitive diagnostic value in psychiatric disorders, but it helps to make a correct diagnosis by excluding other neurological diseases. However, the use of EEG for research purposes is promising in both groups. In this review; there is up-to-date information on the use of electrophysiological examinations in neurological diseases, especially Alzheimer's disease, Parkinson's disease, Frontotemporal dementia, and psychiatric disorders such as schizophrenia, mood disorders, attention deficit and hyperactivity disorder, and obsessive-compulsive disorder, to define the point we have reached in our journey to understand these disorders.
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Affiliation(s)
- Görsev Yener
- İzmir University of Economics, Faculty of Medicine, Department of Neurology, İzmir, Turkey,İzmir Biomedicine and Genom Center, İzmir, Turkey,Dokuz Eylül University Brain Dynamics Multidisciplinary Research Center, İzmir, Turkey
| | - Didem Öz
- Dokuz Eylül University Brain Dynamics Multidisciplinary Research Center, İzmir, Turkey,Dokuz Eylül University Hospital, Department of Neurology, İzmir, Turkey,Dokuz Eylül University, Medical Science Faculty, Neuroscience Department, İzmir, Turkey,Global Brain Health Institute, San Francisco, USA,Correspondence Address: Didem Öz, Dokuz Eylül Üniversitesi, Tıp Fakültesi, Nöroloji Anabilim Dalı, 15 Temmuz Sağlık ve Sanat Yerleşkesi, İnciraltı 35340, İzmir, Turkey • E-mail:
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16
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Hussin AT, Abbaspoor S, Hoffman KL. Retrosplenial and Hippocampal Synchrony during Retrieval of Old Memories in Macaques. J Neurosci 2022; 42:7947-7956. [PMID: 36261267 PMCID: PMC9617609 DOI: 10.1523/jneurosci.0001-22.2022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2022] [Revised: 06/05/2022] [Accepted: 07/11/2022] [Indexed: 11/21/2022] Open
Abstract
Memory for events from the distant past relies on multiple brain regions, but little is known about the underlying neural dynamics that give rise to such abilities. We recorded neural activity in the hippocampus and retrosplenial cortex of two female rhesus macaques as they visually selected targets in year-old and newly acquired object-scene associations. Whereas hippocampal activity was unchanging with memory age, the retrosplenial cortex responded with greater magnitude alpha oscillations (10-15 Hz) and greater phase locking to memory-guided eye movements during retrieval of old events. A similar old-memory enhancement was observed in the anterior cingulate cortex but in a beta2/gamma band (28-35 Hz). In contrast, remote retrieval was associated with decreased gamma-band synchrony between the hippocampus and each neocortical area. The increasing retrosplenial alpha oscillation and decreasing hippocampocortical synchrony with memory age may signify a shift in frank memory allocation or, alternatively, changes in selection among distributed memory representations in the primate brain.SIGNIFICANCE STATEMENT Memory depends on multiple brain regions, whose involvement is thought to change with time. Here, we recorded neuronal population activity from the hippocampus and retrosplenial cortex as nonhuman primates searched for objects embedded in scenes. These memoranda were either newly presented or a year old. Remembering old material drove stronger oscillations in the retrosplenial cortex and led to a greater locking of neural activity to search movements. Remembering new material revealed stronger oscillatory synchrony between the hippocampus and retrosplenial cortex. These results suggest that with age, memories may come to rely more exclusively on neocortical oscillations for retrieval and search guidance and less on long-range coupling with the hippocampus.
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Affiliation(s)
- Ahmed T Hussin
- Department of Biology, Centre for Vision Research, York University, Toronto Ontario M3J 1P3, Canada
| | | | - Kari L Hoffman
- Department of Biology, Centre for Vision Research, York University, Toronto Ontario M3J 1P3, Canada
- Departments of Psychology
- Biomedical Engineering, Vanderbilt Vision Research Center, Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee 37240
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17
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Schlafly ED, Marshall FA, Merricks EM, Eden UT, Cash SS, Schevon CA, Kramer MA. Multiple Sources of Fast Traveling Waves during Human Seizures: Resolving a Controversy. J Neurosci 2022; 42:6966-6982. [PMID: 35906069 PMCID: PMC9464018 DOI: 10.1523/jneurosci.0338-22.2022] [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: 02/16/2022] [Revised: 05/26/2022] [Accepted: 06/18/2022] [Indexed: 11/21/2022] Open
Abstract
During human seizures, organized waves of voltage activity rapidly sweep across the cortex. Two contradictory theories describe the source of these fast traveling waves: either a slowly advancing narrow region of multiunit activity (an ictal wavefront) or a fixed cortical location. Limited observations and different analyses prevent resolution of these incompatible theories. Here we address this disagreement by combining the methods and microelectrode array recordings (N = 11 patients, 2 females, N = 31 seizures) from previous human studies to analyze the traveling wave source. We find, inconsistent with both existing theories, a transient relationship between the ictal wavefront and traveling waves, and multiple stable directions of traveling waves in many seizures. Using a computational model that combines elements of both existing theories, we show that interactions between an ictal wavefront and fixed source reproduce the traveling wave dynamics observed in vivo We conclude that combining both existing theories can generate the diversity of ictal traveling waves.SIGNIFICANCE STATEMENT The source of voltage discharges that propagate across cortex during human seizures remains unknown. Two candidate theories exist, each proposing a different discharge source. Support for each theory consists of observations from a small number of human subject recordings, analyzed with separately developed methods. How the different, limited data and different analysis methods impact the evidence for each theory is unclear. To resolve these differences, we combine the unique, human microelectrode array recordings collected separately for each theory and analyze these combined data with a unified approach. We show that neither existing theory adequately describes the data. We then propose a new theory that unifies existing proposals and successfully reproduces the voltage discharge dynamics observed in vivo.
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Affiliation(s)
- Emily D Schlafly
- Graduate Program in Neuroscience, Boston University, Boston, Massachusetts 02215
| | - François A Marshall
- Department of Mathematics and Statistics & Center for Systems Neuroscience, Boston University, Boston, Massachusetts 02215
| | - Edward M Merricks
- Department of Neurology, Columbia University, New York, New York 10032
| | - Uri T Eden
- Department of Mathematics and Statistics & Center for Systems Neuroscience, Boston University, Boston, Massachusetts 02215
| | - Sydney S Cash
- Department of Neurology, Massachusetts General Hospital & Harvard Medical School, Boston, Massachusetts 02114
| | | | - Mark A Kramer
- Department of Mathematics and Statistics & Center for Systems Neuroscience, Boston University, Boston, Massachusetts 02215
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18
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Das A, Myers J, Mathura R, Shofty B, Metzger BA, Bijanki K, Wu C, Jacobs J, Sheth SA. Spontaneous neuronal oscillations in the human insula are hierarchically organized traveling waves. eLife 2022; 11:76702. [PMID: 35616527 PMCID: PMC9200407 DOI: 10.7554/elife.76702] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 05/25/2022] [Indexed: 11/16/2022] Open
Abstract
The insula plays a fundamental role in a wide range of adaptive human behaviors, but its electrophysiological dynamics are poorly understood. Here, we used human intracranial electroencephalographic recordings to investigate the electrophysiological properties and hierarchical organization of spontaneous neuronal oscillations within the insula. We analyzed the neuronal oscillations of the insula directly and found that rhythms in the theta and beta frequency oscillations are widespread and spontaneously present. These oscillations are largely organized along the anterior–posterior (AP) axis of the insula. Both the left and right insula showed anterior-to-posterior decreasing gradients for the power of oscillations in the beta frequency band. The left insula also showed a posterior-to-anterior decreasing frequency gradient and an anterior-to-posterior decreasing power gradient in the theta frequency band. In addition to measuring the power of these oscillations, we also examined the phase of these signals across simultaneous recording channels and found that the insula oscillations in the theta and beta bands are traveling waves. The strength of the traveling waves in each frequency was positively correlated with the amplitude of each oscillation. However, the theta and beta traveling waves were uncoupled to each other in terms of phase and amplitude, which suggested that insular traveling waves in the theta and beta bands operate independently. Our findings provide new insights into the spatiotemporal dynamics and hierarchical organization of neuronal oscillations within the insula, which, given its rich connectivity with widespread cortical regions, indicates that oscillations and traveling waves have an important role in intrainsular and interinsular communications.
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Affiliation(s)
- Anup Das
- Department of Biomedical Engineering, Columbia University, New York, United States
| | - John Myers
- Department of Neurosurgery, Baylor College of Medicine, Houston, United States
| | - Raissa Mathura
- Department of Neurosurgery, Baylor College of Medicine, Houston, United States
| | - Ben Shofty
- Department of Neurosurgery, Baylor College of Medicine, Houston, United States
| | - Brian A Metzger
- Department of Neurosurgery, Baylor College of Medicine, Houston, United States
| | - Kelly Bijanki
- Department of Neurosurgery, Baylor College of Medicine, Houston, United States
| | - Chengyuan Wu
- Department of Neurosurgery, Thomas Jefferson University, Philadelphia, United States
| | - Joshua Jacobs
- Department of Biomedical Engineering, Columbia University, New York, United States
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, United States
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19
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Paulk AC, Kfir Y, Khanna AR, Mustroph ML, Trautmann EM, Soper DJ, Stavisky SD, Welkenhuysen M, Dutta B, Shenoy KV, Hochberg LR, Richardson RM, Williams ZM, Cash SS. Large-scale neural recordings with single neuron resolution using Neuropixels probes in human cortex. Nat Neurosci 2022; 25:252-263. [PMID: 35102333 DOI: 10.1038/s41593-021-00997-0] [Citation(s) in RCA: 82] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Accepted: 12/07/2021] [Indexed: 12/20/2022]
Abstract
Recent advances in multi-electrode array technology have made it possible to monitor large neuronal ensembles at cellular resolution in animal models. In humans, however, current approaches restrict recordings to a few neurons per penetrating electrode or combine the signals of thousands of neurons in local field potential (LFP) recordings. Here we describe a new probe variant and set of techniques that enable simultaneous recording from over 200 well-isolated cortical single units in human participants during intraoperative neurosurgical procedures using silicon Neuropixels probes. We characterized a diversity of extracellular waveforms with eight separable single-unit classes, with differing firing rates, locations along the length of the electrode array, waveform spatial spread and modulation by LFP events such as inter-ictal discharges and burst suppression. Although some challenges remain in creating a turnkey recording system, high-density silicon arrays provide a path for studying human-specific cognitive processes and their dysfunction at unprecedented spatiotemporal resolution.
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Affiliation(s)
- Angelique C Paulk
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
- Department of Neurology, Harvard Medical School, Boston, MA, USA.
| | - Yoav Kfir
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Arjun R Khanna
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Martina L Mustroph
- Department of Neurosurgery, Harvard Medical School and Brigham & Women's Hospital, Boston, MA, USA
| | - Eric M Trautmann
- Department of Neuroscience, Columbia University Medical Center, New York City, NY, USA
- Zuckerman Institute, Columbia University, New York City, NY, USA
- Grossman Center for the Statistics of Mind, Columbia University Medical Center, New York City, NY, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute and Bio-X Institute, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA
- Columbia University, New York City, NY, USA
| | - Dan J Soper
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Sergey D Stavisky
- Wu Tsai Neurosciences Institute and Bio-X Institute, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA
- Department of Neurological Surgery, University of California at Davis, Davis, CA, USA
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | | | | | - Krishna V Shenoy
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute and Bio-X Institute, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute at Stanford University, Stanford, CA, USA
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Department of Neurobiology, Stanford University, Stanford, CA, USA
| | - Leigh R Hochberg
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
- VA RR&D Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Providence VA Medical Center, Providence, RI, USA
- School of Engineering and Carney Institute for Brain Science, Brown University, Providence, RI, USA
| | - R Mark Richardson
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA
| | - Ziv M Williams
- Department of Neurosurgery, Harvard Medical School and Massachusetts General Hospital, Boston, MA, USA.
| | - Sydney S Cash
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
- Department of Neurology, Harvard Medical School, Boston, MA, USA.
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