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Jordan FD, Kutter M, Comby JM, Brozzi F, Kurtys E. Open and remotely accessible Neuroplatform for research in wetware computing. Front Artif Intell 2024; 7:1376042. [PMID: 38756757 PMCID: PMC11097343 DOI: 10.3389/frai.2024.1376042] [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: 01/24/2024] [Accepted: 03/11/2024] [Indexed: 05/18/2024] Open
Abstract
Wetware computing and organoid intelligence is an emerging research field at the intersection of electrophysiology and artificial intelligence. The core concept involves using living neurons to perform computations, similar to how Artificial Neural Networks (ANNs) are used today. However, unlike ANNs, where updating digital tensors (weights) can instantly modify network responses, entirely new methods must be developed for neural networks using biological neurons. Discovering these methods is challenging and requires a system capable of conducting numerous experiments, ideally accessible to researchers worldwide. For this reason, we developed a hardware and software system that allows for electrophysiological experiments on an unmatched scale. The Neuroplatform enables researchers to run experiments on neural organoids with a lifetime of even more than 100 days. To do so, we streamlined the experimental process to quickly produce new organoids, monitor action potentials 24/7, and provide electrical stimulations. We also designed a microfluidic system that allows for fully automated medium flow and change, thus reducing the disruptions by physical interventions in the incubator and ensuring stable environmental conditions. Over the past three years, the Neuroplatform was utilized with over 1,000 brain organoids, enabling the collection of more than 18 terabytes of data. A dedicated Application Programming Interface (API) has been developed to conduct remote research directly via our Python library or using interactive compute such as Jupyter Notebooks. In addition to electrophysiological operations, our API also controls pumps, digital cameras and UV lights for molecule uncaging. This allows for the execution of complex 24/7 experiments, including closed-loop strategies and processing using the latest deep learning or reinforcement learning libraries. Furthermore, the infrastructure supports entirely remote use. Currently in 2024, the system is freely available for research purposes, and numerous research groups have begun using it for their experiments. This article outlines the system's architecture and provides specific examples of experiments and results.
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Kagan BJ, Gyngell C, Lysaght T, Cole VM, Sawai T, Savulescu J. The technology, opportunities, and challenges of Synthetic Biological Intelligence. Biotechnol Adv 2023; 68:108233. [PMID: 37558186 PMCID: PMC7615149 DOI: 10.1016/j.biotechadv.2023.108233] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 07/15/2023] [Accepted: 08/05/2023] [Indexed: 08/11/2023]
Abstract
Integrating neural cultures developed through synthetic biology methods with digital computing has enabled the early development of Synthetic Biological Intelligence (SBI). Recently, key studies have emphasized the advantages of biological neural systems in some information processing tasks. However, neither the technology behind this early development, nor the potential ethical opportunities or challenges, have been explored in detail yet. Here, we review the key aspects that facilitate the development of SBI and explore potential applications. Considering these foreseeable use cases, various ethical implications are proposed. Ultimately, this work aims to provide a robust framework to structure ethical considerations to ensure that SBI technology can be both researched and applied responsibly.
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Affiliation(s)
| | - Christopher Gyngell
- Murdoch Children's Research Institute, Melbourne, VIC, Australia; University of Melbourne, Melbourne, VIC, Australia
| | - Tamra Lysaght
- Centre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Victor M Cole
- Centre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Tsutomu Sawai
- Graduate School of Humanities and Social Sciences, Hiroshima University, Hiroshima, Japan; Institute for the Advanced Study of Human Biology (ASHBi), Kyoto University, Kyoto, Japan
| | - Julian Savulescu
- Murdoch Children's Research Institute, Melbourne, VIC, Australia; University of Melbourne, Melbourne, VIC, Australia; Centre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
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3
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Haggie L, Schmid L, Röhrle O, Besier T, McMorland A, Saini H. Linking cortex and contraction-Integrating models along the corticomuscular pathway. Front Physiol 2023; 14:1095260. [PMID: 37234419 PMCID: PMC10206006 DOI: 10.3389/fphys.2023.1095260] [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: 11/11/2022] [Accepted: 04/21/2023] [Indexed: 05/28/2023] Open
Abstract
Computational models of the neuromusculoskeletal system provide a deterministic approach to investigate input-output relationships in the human motor system. Neuromusculoskeletal models are typically used to estimate muscle activations and forces that are consistent with observed motion under healthy and pathological conditions. However, many movement pathologies originate in the brain, including stroke, cerebral palsy, and Parkinson's disease, while most neuromusculoskeletal models deal exclusively with the peripheral nervous system and do not incorporate models of the motor cortex, cerebellum, or spinal cord. An integrated understanding of motor control is necessary to reveal underlying neural-input and motor-output relationships. To facilitate the development of integrated corticomuscular motor pathway models, we provide an overview of the neuromusculoskeletal modelling landscape with a focus on integrating computational models of the motor cortex, spinal cord circuitry, α-motoneurons and skeletal muscle in regard to their role in generating voluntary muscle contraction. Further, we highlight the challenges and opportunities associated with an integrated corticomuscular pathway model, such as challenges in defining neuron connectivities, modelling standardisation, and opportunities in applying models to study emergent behaviour. Integrated corticomuscular pathway models have applications in brain-machine-interaction, education, and our understanding of neurological disease.
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Affiliation(s)
- Lysea Haggie
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Laura Schmid
- Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany
| | - Oliver Röhrle
- Institute for Modelling and Simulation of Biomechanical Systems, University of Stuttgart, Stuttgart, Germany
- Stuttgart Center for Simulation Sciences (SC SimTech), University of Stuttgart, Stuttgart, Germany
| | - Thor Besier
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
| | - Angus McMorland
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
- Department of Exercise Sciences, University of Auckland, Auckland, New Zealand
| | - Harnoor Saini
- Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand
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4
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Abramson CI, Levin M. Behaviorist approaches to investigating memory and learning: A primer for synthetic biology and bioengineering. Commun Integr Biol 2021; 14:230-247. [PMID: 34925687 PMCID: PMC8677006 DOI: 10.1080/19420889.2021.2005863] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022] Open
Abstract
The fields of developmental biology, biomedicine, and artificial life are being revolutionized by advances in synthetic morphology. The next phase of synthetic biology and bioengineering is resulting in the construction of novel organisms (biobots), which exhibit not only morphogenesis and physiology but functional behavior. It is now essential to begin to characterize the behavioral capacity of novel living constructs in terms of their ability to make decisions, form memories, learn from experience, and anticipate future stimuli. These synthetic organisms are highly diverse, and often do not resemble familiar model systems used in behavioral science. Thus, they represent an important context in which to begin to unify and standardize vocabulary and techniques across developmental biology, behavioral ecology, and neuroscience. To facilitate the study of behavior in novel living systems, we present a primer on techniques from the behaviorist tradition that can be used to probe the functions of any organism – natural, chimeric, or synthetic – regardless of the details of their construction or origin. These techniques provide a rich toolkit for advancing the fields of synthetic bioengineering, evolutionary developmental biology, basal cognition, exobiology, and robotics.
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Affiliation(s)
- Charles I Abramson
- Department of Psychology, Laboratory of Comparative Psychology and Behavioral Biology at Oklahoma State University, United States of America
| | - Michael Levin
- Department of Biology, Allen Discovery Center at Tufts University, United States of America
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5
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Farkhondeh Tale Navi F, Heysieattalab S, Ramanathan DS, Raoufy MR, Nazari MA. Closed-loop Modulation of the Self-regulating Brain: A Review on Approaches, Emerging Paradigms, and Experimental Designs. Neuroscience 2021; 483:104-126. [PMID: 34902494 DOI: 10.1016/j.neuroscience.2021.12.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 11/30/2021] [Accepted: 12/06/2021] [Indexed: 11/27/2022]
Abstract
Closed-loop approaches, setups, and experimental designs have been applied within the field of neuroscience to enhance the understanding of basic neurophysiology principles (closed-loop neuroscience; CLNS) and to develop improved procedures for modulating brain circuits and networks for clinical purposes (closed-loop neuromodulation; CLNM). The contents of this review are thus arranged into the following sections. First, we describe basic research findings that have been made using CLNS. Next, we provide an overview of the application, rationale, and therapeutic aspects of CLNM for clinical purposes. Finally, we summarize methodological concerns and critics in clinical practice of neurofeedback and novel applications of closed-loop perspective and techniques to improve and optimize its experiments. Moreover, we outline the theoretical explanations and experimental ideas to test animal models of neurofeedback and discuss technical issues and challenges associated with implementing closed-loop systems. We hope this review is helpful for both basic neuroscientists and clinical/ translationally-oriented scientists interested in applying closed-loop methods to improve mental health and well-being.
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Affiliation(s)
- Farhad Farkhondeh Tale Navi
- Department of Cognitive Neuroscience, Faculty of Education and Psychology, University of Tabriz, Tabriz, Iran
| | - Soomaayeh Heysieattalab
- Department of Cognitive Neuroscience, Faculty of Education and Psychology, University of Tabriz, Tabriz, Iran
| | | | - Mohammad Reza Raoufy
- Department of Physiology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
| | - Mohammad Ali Nazari
- Department of Cognitive Neuroscience, Faculty of Education and Psychology, University of Tabriz, Tabriz, Iran; Department of Neuroscience, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran, Iran.
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6
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Voitiuk K, Geng J, Keefe MG, Parks DF, Sanso SE, Hawthorne N, Freeman DB, Currie R, Mostajo-Radji MA, Pollen AA, Nowakowski TJ, Salama SR, Teodorescu M, Haussler D. Light-weight electrophysiology hardware and software platform for cloud-based neural recording experiments. J Neural Eng 2021; 18:10.1088/1741-2552/ac310a. [PMID: 34666315 PMCID: PMC8667733 DOI: 10.1088/1741-2552/ac310a] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Accepted: 10/19/2021] [Indexed: 11/12/2022]
Abstract
Objective.Neural activity represents a functional readout of neurons that is increasingly important to monitor in a wide range of experiments. Extracellular recordings have emerged as a powerful technique for measuring neural activity because these methods do not lead to the destruction or degradation of the cells being measured. Current approaches to electrophysiology have a low throughput of experiments due to manual supervision and expensive equipment. This bottleneck limits broader inferences that can be achieved with numerous long-term recorded samples.Approach.We developed Piphys, an inexpensive open source neurophysiological recording platform that consists of both hardware and software. It is easily accessed and controlled via a standard web interface through Internet of Things (IoT) protocols.Main results.We used a Raspberry Pi as the primary processing device along with an Intan bioamplifier. We designed a hardware expansion circuit board and software to enable voltage sampling and user interaction. This standalone system was validated with primary human neurons, showing reliability in collecting neural activity in near real-time.Significance.The hardware modules and cloud software allow for remote control of neural recording experiments as well as horizontal scalability, enabling long-term observations of development, organization, and neural activity at scale.
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Affiliation(s)
- Kateryna Voitiuk
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95060, United States of America
| | - Jinghui Geng
- Department of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA 95060, United States of America
| | - Matthew G Keefe
- Department of Anatomy, University of California San Francisco, San Francisco, CA 94143, United States of America
| | - David F Parks
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95060, United States of America
| | - Sebastian E Sanso
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060, United States of America
| | - Nico Hawthorne
- Department of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA 95060, United States of America
| | - Daniel B Freeman
- Universal Audio Inc., Scotts Valley, CA 95066, United States of America
| | - Rob Currie
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060, United States of America
| | - Mohammed A Mostajo-Radji
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco, San Francisco, CA 94143, United States of America
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060, United States of America
- Department of Neurology, University of California San Francisco, San Francisco, CA 94143, United States of America
| | - Alex A Pollen
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco, San Francisco, CA 94143, United States of America
- Department of Neurology, University of California San Francisco, San Francisco, CA 94143, United States of America
| | - Tomasz J Nowakowski
- Department of Anatomy, University of California San Francisco, San Francisco, CA 94143, United States of America
- The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California San Francisco, San Francisco, CA 94143, United States of America
| | - Sofie R Salama
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95060, United States of America
- Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, United States of America
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060, United States of America
| | - Mircea Teodorescu
- Department of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA 95060, United States of America
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060, United States of America
| | - David Haussler
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95060, United States of America
- Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, United States of America
- UC Santa Cruz Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95060, United States of America
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7
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Firfilionis D, Hutchings F, Tamadoni R, Walsh D, Turnbull M, Escobedo-Cousin E, Bailey RG, Gausden J, Patel A, Haci D, Liu Y, LeBeau FEN, Trevelyan A, Constandinou TG, O'Neill A, Kaiser M, Degenaar P, Jackson A. A Closed-Loop Optogenetic Platform. Front Neurosci 2021; 15:718311. [PMID: 34566564 PMCID: PMC8462298 DOI: 10.3389/fnins.2021.718311] [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: 08/31/2021] [Accepted: 08/16/2021] [Indexed: 01/11/2023] Open
Abstract
Neuromodulation is an established treatment for numerous neurological conditions, but to expand the therapeutic scope there is a need to improve the spatial, temporal and cell-type specificity of stimulation. Optogenetics is a promising area of current research, enabling optical stimulation of genetically-defined cell types without interfering with concurrent electrical recording for closed-loop control of neural activity. We are developing an open-source system to provide a platform for closed-loop optogenetic neuromodulation, incorporating custom integrated circuitry for recording and stimulation, real-time closed-loop algorithms running on a microcontroller and experimental control via a PC interface. We include commercial components to validate performance, with the ultimate aim of translating this approach to humans. In the meantime our system is flexible and expandable for use in a variety of preclinical neuroscientific applications. The platform consists of a Controlling Abnormal Network Dynamics using Optogenetics (CANDO) Control System (CS) that interfaces with up to four CANDO headstages responsible for electrical recording and optical stimulation through custom CANDO LED optrodes. Control of the hardware, inbuilt algorithms and data acquisition is enabled via the CANDO GUI (Graphical User Interface). Here we describe the design and implementation of this system, and demonstrate how it can be used to modulate neuronal oscillations in vitro and in vivo.
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Affiliation(s)
- Dimitrios Firfilionis
- Neuroprosthesis Lab, School of Engineering, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Frances Hutchings
- Digital Institute, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Reza Tamadoni
- Neuroprosthesis Lab, School of Engineering, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Darren Walsh
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Mark Turnbull
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Enrique Escobedo-Cousin
- Emerging Technologies and Materials Group, School of Engineering, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Richard G. Bailey
- Emerging Technologies and Materials Group, School of Engineering, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Johannes Gausden
- Emerging Technologies and Materials Group, School of Engineering, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Aaliyah Patel
- Emerging Technologies and Materials Group, School of Engineering, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Dorian Haci
- Department of Electrical and Electronic Engineering, Imperial College London, London, United Kingdom
| | - Yan Liu
- Department of Electrical and Electronic Engineering, Imperial College London, London, United Kingdom
- Department of Micro-Nano Electronics, Shanghai Jiaotong University, Shanghai, China
| | - Fiona E. N. LeBeau
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Andrew Trevelyan
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Timothy G. Constandinou
- Department of Electrical and Electronic Engineering, Imperial College London, London, United Kingdom
- Care Research and Technology Centre, UK Dementia Research Institute, London, United Kingdom
| | - Anthony O'Neill
- Emerging Technologies and Materials Group, School of Engineering, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Marcus Kaiser
- School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
- School of Medicine, University of Nottingham, Nottingham, United Kingdom
- Rui Jin Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Patrick Degenaar
- Neuroprosthesis Lab, School of Engineering, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Andrew Jackson
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
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8
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Shupe LE, Miles FP, Jones G, Yun R, Mishler J, Rembado I, Murphy RL, Perlmutter SI, Fetz EE. Neurochip3: An Autonomous Multichannel Bidirectional Brain-Computer Interface for Closed-Loop Activity-Dependent Stimulation. Front Neurosci 2021; 15:718465. [PMID: 34489634 PMCID: PMC8417105 DOI: 10.3389/fnins.2021.718465] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 07/22/2021] [Indexed: 11/13/2022] Open
Abstract
Toward addressing many neuroprosthetic applications, the Neurochip3 (NC3) is a multichannel bidirectional brain-computer interface that operates autonomously and can support closed-loop activity-dependent stimulation. It consists of four circuit boards populated with off-the-shelf components and is sufficiently compact to be carried on the head of a non-human primate (NHP). NC3 has six main components: (1) an analog front-end with an Intan biophysical signal amplifier (16 differential or 32 single-ended channels) and a 3-axis accelerometer, (2) a digital control system comprised of a Cyclone V FPGA and Atmel SAM4 MCU, (3) a micro SD Card for 128 GB or more storage, (4) a 6-channel differential stimulator with ±60 V compliance, (5) a rechargeable battery pack supporting autonomous operation for up to 24 h and, (6) infrared transceiver and serial ports for communication. The NC3 and earlier versions have been successfully deployed in many closed-loop operations to induce synaptic plasticity and bridge lost biological connections, as well as deliver activity-dependent intracranial reinforcement. These paradigms to strengthen or replace impaired connections have many applications in neuroprosthetics and neurorehabilitation.
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Affiliation(s)
- Larry E Shupe
- Department of Physiology & Biophysics, University of Washington, Seattle, WA, United States.,Washington National Primate Research Center, University of Washington, Seattle, WA, United States
| | - Frank P Miles
- Washington National Primate Research Center, University of Washington, Seattle, WA, United States
| | - Geoff Jones
- Independent Researcher, Seattle, CA, United States
| | - Richy Yun
- Department of Bioengineering, University of Washington, Seattle, WA, United States
| | - Jonathan Mishler
- Department of Bioengineering, University of Washington, Seattle, WA, United States
| | - Irene Rembado
- Department of Physiology & Biophysics, University of Washington, Seattle, WA, United States
| | - R Logan Murphy
- Department of Physiology & Biophysics, University of Washington, Seattle, WA, United States
| | - Steve I Perlmutter
- Department of Physiology & Biophysics, University of Washington, Seattle, WA, United States.,Washington National Primate Research Center, University of Washington, Seattle, WA, United States
| | - Eberhard E Fetz
- Department of Physiology & Biophysics, University of Washington, Seattle, WA, United States.,Washington National Primate Research Center, University of Washington, Seattle, WA, United States.,Department of Bioengineering, University of Washington, Seattle, WA, United States
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9
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Prefrontal Cortical Projection Neurons Targeting Dorsomedial Striatum Control Behavioral Inhibition. Curr Biol 2020; 30:4188-4200.e5. [DOI: 10.1016/j.cub.2020.08.031] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 07/21/2020] [Accepted: 08/07/2020] [Indexed: 01/08/2023]
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10
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Distributed Manufacturing of Open Source Medical Hardware for Pandemics. JOURNAL OF MANUFACTURING AND MATERIALS PROCESSING 2020. [DOI: 10.3390/jmmp4020049] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Distributed digital manufacturing offers a solution to medical supply and technology shortages during pandemics. To prepare for the next pandemic, this study reviews the state-of-the-art of open hardware designs needed in a COVID-19-like pandemic. It evaluates the readiness of the top twenty technologies requested by the Government of India. The results show that the majority of the actual medical products have some open source development, however, only 15% of the supporting technologies required to produce them are freely available. The results show there is still considerable research needed to provide open source paths for the development of all the medical hardware needed during pandemics. Five core areas of future research are discussed, which include (i) technical development of a wide-range of open source solutions for all medical supplies and devices, (ii) policies that protect the productivity of laboratories, makerspaces, and fabrication facilities during a pandemic, as well as (iii) streamlining the regulatory process, (iv) developing Good-Samaritan laws to protect makers and designers of open medical hardware, as well as to compel those with knowledge that will save lives to share it, and (v) requiring all citizen-funded research to be released with free and open source licenses.
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11
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Newman JP, Voigts J, Borius M, Karlsson M, Harnett MT, Wilson MA. Twister3: a simple and fast microwire twister. J Neural Eng 2020; 17:026040. [PMID: 32074512 PMCID: PMC8879418 DOI: 10.1088/1741-2552/ab77fa] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Objective. Twisted wire probes (TWPs, e.g. stereotrodes and tetrodes) provide a cheap and reliable method for obtaining high quality, multiple single-unit neural recordings in freely moving animals. Despite their ubiquity, TWPs are constructed using a tedious procedure consisting of manually folding, turning, and fusing microwire. This imposes a significant labor burden on research personnel who use TWPs in their experiments. Approach. To address this issue, we created Twister3, an open-source microwire twisting machine. This machine features a quick-draw wire feeder that eliminates manual wire folding, an auto-aligning motor attachment mechanism which results in consistently straight probes, and a high speed motor for rapid probe turning. Main results. Twister3 greatly increases the speed and repeatability of constructing twisted microwire probes compared to existing options. Users with less than one hour of experience using the device were able to make ~70 tetrodes per hour, on average. It is cheap, well documented, and all associated designs and source code are open-source. Significance. Twister3 significantly reduces the labor burden of creating high-quality TWPs so electrophysiologists can spend more of their time performing recordings rather than making probes. Therefore, this device is of interest to any lab performing TWP neural recordings, for example, using microdrives.
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Affiliation(s)
- Jonathan P Newman
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, United States of America.,Picower Institute for Learning and Memory, MIT, Cambridge, MA, United States of America.,Open Ephys Inc, Cambridge, MA, United States of America.,Author to whom any correspondence should be addressed
| | - Jakob Voigts
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, United States of America.,McGovern Institute for Brain Research, MIT, Cambridge, MA, United States of America.,Open Ephys Inc, Cambridge, MA, United States of America
| | - Maxim Borius
- SpikeGadgets LLC, San Francisco, CA, United States of America
| | | | - Mark T Harnett
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, United States of America.,McGovern Institute for Brain Research, MIT, Cambridge, MA, United States of America
| | - Matthew A Wilson
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, United States of America.,Picower Institute for Learning and Memory, MIT, Cambridge, MA, United States of America.,Open Ephys Inc, Cambridge, MA, United States of America
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12
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A Systematic Review of Closed-Loop Feedback Techniques in Sleep Studies-Related Issues and Future Directions. SENSORS 2020; 20:s20102770. [PMID: 32414060 PMCID: PMC7285770 DOI: 10.3390/s20102770] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Revised: 04/13/2020] [Accepted: 05/10/2020] [Indexed: 01/09/2023]
Abstract
Advances in computer processing technology have enabled researchers to analyze real-time brain activity and build real-time closed-loop paradigms. In many fields, the effectiveness of these closed-loop protocols has proven to be better than that of the simple open-loop paradigms. Recently, sleep studies have attracted much attention as one possible application of closed-loop paradigms. To date, several studies that used closed-loop paradigms have been reported in the sleep-related literature and recommend a closed-loop feedback system to enhance specific brain activity during sleep, which leads to improvements in sleep's effects, such as memory consolidation. However, to the best of our knowledge, no report has reviewed and discussed the detailed technical issues that arise in designing sleep closed-loop paradigms. In this paper, we reviewed the most recent reports on sleep closed-loop paradigms and offered an in-depth discussion of some of their technical issues. We found 148 journal articles strongly related with 'sleep and stimulation' and reviewed 20 articles on closed-loop feedback sleep studies. We focused on human sleep studies conducting any modality of feedback stimulation. Then we introduced the main component of the closed-loop system and summarized several open-source libraries, which are widely used in closed-loop systems, with step-by-step guidelines for closed-loop system implementation for sleep. Further, we proposed future directions for sleep research with closed-loop feedback systems, which provide some insight into closed-loop feedback systems.
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13
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Vila CH, Williamson RS, Hancock KE, Polley DB. Optimizing optogenetic stimulation protocols in auditory corticofugal neurons based on closed-loop spike feedback. J Neural Eng 2019; 16:066023. [PMID: 31394519 PMCID: PMC6956656 DOI: 10.1088/1741-2552/ab39cf] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
OBJECTIVE Optogenetics provides a means to probe functional connections between brain areas. By activating a set of presynaptic neurons and recording the activity from a downstream brain area, one can establish the sign and strength of a feedforward connection. One challenge is that there are virtually limitless patterns that can be used to stimulate a presynaptic brain area. Functional influences on downstream brain areas can depend not just on whether presynaptic neurons were activated, but how they were activated. Corticofugal axons from the auditory cortex (ACtx) heavily innervate the auditory tectum, the inferior colliculus (IC). Here, we sought to determine whether different modes of corticocollicular activation could titrate the strength of feedforward modulation of sound processing in IC neurons. APPROACH We used multi-channel electrophysiology and optogenetics to record from multiple regions of the IC in awake head-fixed mice while optogenetically stimulating ACtx neurons expressing Chronos, an ultra-fast channelrhodopsin. To identify cortical activation patterns associated with the strongest effects on IC firing rates, we employed a closed-loop evolutionary optimization procedure that tailored the voltage command signal sent to the laser based on spike feedback from single IC neurons. MAIN RESULTS Within minutes, our evolutionary search procedure converged on ACtx stimulation configurations that produced more effective and widespread enhancement of IC unit activity than generic activation parameters. Cortical modulation of midbrain spiking was bi-directional, as the evolutionary search procedure could be programmed to converge on activation patterns that either suppressed or enhanced sound-evoked IC firing rate. SIGNIFICANCE This study introduces a closed-loop optimization procedure to probe functional connections between brain areas. Our findings demonstrate that the influence of descending feedback projections on subcortical sensory processing can vary both in sign and degree depending on how cortical neurons are activated in time.
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Affiliation(s)
- Charles-Henri Vila
- - Eaton-Peabody Laboratories, Massachusetts Eye and Ear Infirmary, Boston MA 02114 USA
- - Bertarelli Fellows Program, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Ross S Williamson
- - Eaton-Peabody Laboratories, Massachusetts Eye and Ear Infirmary, Boston MA 02114 USA
- - Dept. Otolaryngology, Harvard Medical School, Boston MA 02114
| | - Kenneth E Hancock
- - Eaton-Peabody Laboratories, Massachusetts Eye and Ear Infirmary, Boston MA 02114 USA
- - Dept. Otolaryngology, Harvard Medical School, Boston MA 02114
| | - Daniel B Polley
- - Eaton-Peabody Laboratories, Massachusetts Eye and Ear Infirmary, Boston MA 02114 USA
- - Dept. Otolaryngology, Harvard Medical School, Boston MA 02114
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Murphy M, Buccelli S, Bornat Y, Bundy D, Nudo R, Guggenmos D, Chiappalone M. Improving an open-source commercial system to reliably perform activity-dependent stimulation. J Neural Eng 2019; 16:066022. [PMID: 31315090 PMCID: PMC7703379 DOI: 10.1088/1741-2552/ab3319] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Activity-dependent stimulation (ADS) is designed to strengthen the connections between neuronal circuits and therefore may be a promising tool for promoting neurophysiological reorganization following a brain injury. To successfully perform this technique, two criteria must be met: (1) spikes in the extracellular electrical field potential must be detected accurately at one site of interest, and (2) stimulation pulses generated at fixed (<1 ms jitter), low-latency (<10 ms) intervals relative to each detected spike must be delivered reliably to a second site of interest. Here, we aimed to improve noise rejection in a low-cost commercial system to reliably perform ADS in awake, behaving rats, while maintaining latency requirements. APPROACH We implemented a spike detection state machine on a field-programmable gate array (FPGA). Because the accuracy of spike detection can be heavily reduced in awake and behaving animals due to biological artifacts such as movement and chewing, the state machine tracks candidate spike waveforms, checking them against multiple programmable thresholds and rejecting any spikes that fail to meet a programmed threshold criterion. MAIN RESULTS A series of offline analyses showed that our implementation was able to appropriately trigger stimulation during epochs of biological artifacts with an overall accuracy between 72% and 97%, fixed computational latency of 167 µs, and an algorithmic latency of 300 µs to 800 µs. SIGNIFICANCE Our improvements have been made open-source and are freely available to all scientists working on closed-loop neuroprosthetic devices. Importantly, the improvements are easily incorporated into existing workflows that utilize the Intan Stimulation and Recording Controller.
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Affiliation(s)
- Maxwell Murphy
- Department of Rehabilitation Medicine, University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, 66160 KS, United States of America. Bioengineering Graduate Program, University of Kansas, Lawrence, KS, United States of America
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Closed-Loop Systems and In Vitro Neuronal Cultures: Overview and Applications. ADVANCES IN NEUROBIOLOGY 2019; 22:351-387. [DOI: 10.1007/978-3-030-11135-9_15] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
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16
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Seu GP, Angotzi GN, Boi F, Raffo L, Berdondini L, Meloni P. Exploiting All Programmable SoCs in Neural Signal Analysis: A Closed-Loop Control for Large-Scale CMOS Multielectrode Arrays. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2018; 12:839-850. [PMID: 29993584 DOI: 10.1109/tbcas.2018.2830659] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Microelectrode array (MEA) systems with up to several thousands of recording electrodes and electrical or optical stimulation capabilities are commercially available or described in the literature. By exploiting their submillisecond and micrometric temporal and spatial resolutions to record bioelectrical signals, such emerging MEA systems are increasingly used in neuroscience to study the complex dynamics of neuronal networks and brain circuits. However, they typically lack the capability of implementing real-time feedback between the detection of neuronal spiking events and stimulation, thus restricting large-scale neural interfacing to open-loop conditions. In order to exploit the potential of such large-scale recording systems and stimulation, we designed and validated a fully reconfigurable FPGA-based processing system for closed-loop multichannel control. By adopting a Xilinx Zynq-all-programmable system on chip that integrates reconfigurable logic and a dual-core ARM-based processor on the same device, the proposed platform permits low-latency preprocessing (filtering and detection) of spikes acquired simultaneously from several thousands of electrode sites. To demonstrate the proposed platform, we tested its performances through ex vivo experiments on the mice retina using a state-of-the-art planar high-density MEA that samples 4096 electrodes at 18 kHz and record light-evoked spikes from several thousands of retinal ganglion cells simultaneously. Results demonstrate that the platform is able to provide a total latency from whole-array data acquisition to stimulus generation below 2 ms. This opens the opportunity to design closed-loop experiments on neural systems and biomedical applications using emerging generations of planar or implantable large-scale MEA systems.
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Siegle JH, López AC, Patel YA, Abramov K, Ohayon S, Voigts J. Open Ephys: an open-source, plugin-based platform for multichannel electrophysiology. J Neural Eng 2018; 14:045003. [PMID: 28169219 DOI: 10.1088/1741-2552/aa5eea] [Citation(s) in RCA: 251] [Impact Index Per Article: 41.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Closed-loop experiments, in which causal interventions are conditioned on the state of the system under investigation, have become increasingly common in neuroscience. Such experiments can have a high degree of explanatory power, but they require a precise implementation that can be difficult to replicate across laboratories. We sought to overcome this limitation by building open-source software that makes it easier to develop and share algorithms for closed-loop control. APPROACH We created the Open Ephys GUI, an open-source platform for multichannel electrophysiology experiments. In addition to the standard 'open-loop' visualization and recording functionality, the GUI also includes modules for delivering feedback in response to events detected in the incoming data stream. Importantly, these modules can be built and shared as plugins, which makes it possible for users to extend the functionality of the GUI through a simple API, without having to understand the inner workings of the entire application. MAIN RESULTS In combination with low-cost, open-source hardware for amplifying and digitizing neural signals, the GUI has been used for closed-loop experiments that perturb the hippocampal theta rhythm in a phase-specific manner. SIGNIFICANCE The Open Ephys GUI is the first widely used application for multichannel electrophysiology that leverages a plugin-based workflow. We hope that it will lower the barrier to entry for electrophysiologists who wish to incorporate real-time feedback into their research.
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Affiliation(s)
- Joshua H Siegle
- Allen Institute for Brain Science, 615 Westlake Ave N, Seattle, WA 98109, United States of America, jsiegle on GitHub
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Ciliberti D, Kloosterman F. Falcon: a highly flexible open-source software for closed-loop neuroscience. J Neural Eng 2018; 14:045004. [PMID: 28548044 DOI: 10.1088/1741-2552/aa7526] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
OBJECTIVE Closed-loop experiments provide unique insights into brain dynamics and function. To facilitate a wide range of closed-loop experiments, we created an open-source software platform that enables high-performance real-time processing of streaming experimental data. APPROACH We wrote Falcon, a C++ multi-threaded software in which the user can load and execute an arbitrary processing graph. Each node of a Falcon graph is mapped to a single thread and nodes communicate with each other through thread-safe buffers. The framework allows for easy implementation of new processing nodes and data types. Falcon was tested both on a 32-core and a 4-core workstation. Streaming data was read from either a commercial acquisition system (Neuralynx) or the open-source Open Ephys hardware, while closed-loop TTL pulses were generated with a USB module for digital output. We characterized the round-trip latency of our Falcon-based closed-loop system, as well as the specific latency contribution of the software architecture, by testing processing graphs with up to 32 parallel pipelines and eight serial stages. We finally deployed Falcon in a task of real-time detection of population bursts recorded live from the hippocampus of a freely moving rat. MAIN RESULTS On Neuralynx hardware, round-trip latency was well below 1 ms and stable for at least 1 h, while on Open Ephys hardware latencies were below 15 ms. The latency contribution of the software was below 0.5 ms. Round-trip and software latencies were similar on both 32- and 4-core workstations. Falcon was used successfully to detect population bursts online with ~40 ms average latency. SIGNIFICANCE Falcon is a novel open-source software for closed-loop neuroscience. It has sub-millisecond intrinsic latency and gives the experimenter direct control of CPU resources. We envisage Falcon to be a useful tool to the neuroscientific community for implementing a wide variety of closed-loop experiments, including those requiring use of complex data structures and real-time execution of computationally intensive algorithms, such as population neural decoding/encoding from large cell assemblies.
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Affiliation(s)
- Davide Ciliberti
- Neuro-Electronic Research Flanders (NERF), Leuven, Belgium. Brain & Cognition Research Unit, KU Leuven, Belgium. VIB, Leuven, Belgium
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Hazan H, Ziv NE. Closed Loop Experiment Manager (CLEM)-An Open and Inexpensive Solution for Multichannel Electrophysiological Recordings and Closed Loop Experiments. Front Neurosci 2017; 11:579. [PMID: 29093659 PMCID: PMC5651259 DOI: 10.3389/fnins.2017.00579] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2017] [Accepted: 10/03/2017] [Indexed: 11/13/2022] Open
Abstract
There is growing need for multichannel electrophysiological systems that record from and interact with neuronal systems in near real-time. Such systems are needed, for example, for closed loop, multichannel electrophysiological/optogenetic experimentation in vivo and in a variety of other neuronal preparations, or for developing and testing neuro-prosthetic devices, to name a few. Furthermore, there is a need for such systems to be inexpensive, reliable, user friendly, easy to set-up, open and expandable, and possess long life cycles in face of rapidly changing computing environments. Finally, they should provide powerful, yet reasonably easy to implement facilities for developing closed-loop protocols for interacting with neuronal systems. Here, we survey commercial and open source systems that address these needs to varying degrees. We then present our own solution, which we refer to as Closed Loop Experiments Manager (CLEM). CLEM is an open source, soft real-time, Microsoft Windows desktop application that is based on a single generic personal computer (PC) and an inexpensive, general-purpose data acquisition board. CLEM provides a fully functional, user-friendly graphical interface, possesses facilities for recording, presenting and logging electrophysiological data from up to 64 analog channels, and facilities for controlling external devices, such as stimulators, through digital and analog interfaces. Importantly, it includes facilities for running closed-loop protocols written in any programming language that can generate dynamic link libraries (DLLs). We describe the application, its architecture and facilities. We then demonstrate, using networks of cortical neurons growing on multielectrode arrays (MEA) that despite its reliance on generic hardware, its performance is appropriate for flexible, closed-loop experimentation at the neuronal network level.
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Affiliation(s)
- Hananel Hazan
- Faculty of Medicine, Technion, Haifa, Israel.,Network Biology Research Laboratories, Lorry Lokey Center for Life Sciences and Engineering, Technion, Haifa, Israel
| | - Noam E Ziv
- Faculty of Medicine, Technion, Haifa, Israel.,Network Biology Research Laboratories, Lorry Lokey Center for Life Sciences and Engineering, Technion, Haifa, Israel
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20
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Closed-Loop Characterization of Neuronal Activation Using Electrical Stimulation and Optical Imaging. Processes (Basel) 2017. [DOI: 10.3390/pr5020030] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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21
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Patel YA, George A, Dorval AD, White JA, Christini DJ, Butera RJ. Hard real-time closed-loop electrophysiology with the Real-Time eXperiment Interface (RTXI). PLoS Comput Biol 2017; 13:e1005430. [PMID: 28557998 PMCID: PMC5469488 DOI: 10.1371/journal.pcbi.1005430] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2016] [Revised: 06/13/2017] [Accepted: 02/10/2017] [Indexed: 01/24/2023] Open
Abstract
The ability to experimentally perturb biological systems has traditionally been limited to static pre-programmed or operator-controlled protocols. In contrast, real-time control allows dynamic probing of biological systems with perturbations that are computed on-the-fly during experimentation. Real-time control applications for biological research are available; however, these systems are costly and often restrict the flexibility and customization of experimental protocols. The Real-Time eXperiment Interface (RTXI) is an open source software platform for achieving hard real-time data acquisition and closed-loop control in biological experiments while retaining the flexibility needed for experimental settings. RTXI has enabled users to implement complex custom closed-loop protocols in single cell, cell network, animal, and human electrophysiology studies. RTXI is also used as a free and open source, customizable electrophysiology platform in open-loop studies requiring online data acquisition, processing, and visualization. RTXI is easy to install, can be used with an extensive range of external experimentation and data acquisition hardware, and includes standard modules for implementing common electrophysiology protocols.
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Affiliation(s)
- Yogi A. Patel
- Bioengineering Graduate Program, Georgia Institute of Technology, Atlanta, Georgia, United States of America
- Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, United States of America
| | - Ansel George
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, United States of America
| | - Alan D. Dorval
- Department of Bioengineering, University of Utah, Salt Lake City, Utah, United States of America
| | - John A. White
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts, United States of America
| | - David J. Christini
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, United States of America
- * E-mail: (DJC); (RJB)
| | - Robert J. Butera
- Bioengineering Graduate Program, Georgia Institute of Technology, Atlanta, Georgia, United States of America
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, United States of America
- * E-mail: (DJC); (RJB)
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22
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Targeted Stimulation Using Differences in Activation Probability across the Strength–Duration Space. Processes (Basel) 2017. [DOI: 10.3390/pr5020014] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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23
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Vlachos I, Deniz T, Aertsen A, Kumar A. Recovery of Dynamics and Function in Spiking Neural Networks with Closed-Loop Control. PLoS Comput Biol 2016; 12:e1004720. [PMID: 26829673 PMCID: PMC4734620 DOI: 10.1371/journal.pcbi.1004720] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2015] [Accepted: 12/18/2015] [Indexed: 11/30/2022] Open
Abstract
There is a growing interest in developing novel brain stimulation methods to control disease-related aberrant neural activity and to address basic neuroscience questions. Conventional methods for manipulating brain activity rely on open-loop approaches that usually lead to excessive stimulation and, crucially, do not restore the original computations performed by the network. Thus, they are often accompanied by undesired side-effects. Here, we introduce delayed feedback control (DFC), a conceptually simple but effective method, to control pathological oscillations in spiking neural networks (SNNs). Using mathematical analysis and numerical simulations we show that DFC can restore a wide range of aberrant network dynamics either by suppressing or enhancing synchronous irregular activity. Importantly, DFC, besides steering the system back to a healthy state, also recovers the computations performed by the underlying network. Finally, using our theory we identify the role of single neuron and synapse properties in determining the stability of the closed-loop system. Brain stimulation is being used to ease symptoms in several neurological disorders in cases where pharmacological treatment is not effective (anymore). The most common way for stimulation so far has been to apply a fixed, predetermined stimulus irrespective of the actual state of the brain or the condition of the patient. Recently, alternative strategies such as event-triggered stimulation protocols have attracted the interest of researchers. In these protocols the state of the affected brain area is continuously monitored, but the stimulus is only applied if certain criteria are met. Here we go one step further and present a truly closed-loop stimulation protocol. That is, a stimulus is being continuously provided and the magnitude of the stimulus depends, at any point in time, on the ongoing neural activity dynamics of the affected brain area. This results not only in suppression of the pathological activity, but also in a partial recovery of the transfer function of the activity dynamics. Thus, the ability of the lesioned brain area to carry out relevant computations is restored up to a point as well.
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Affiliation(s)
- Ioannis Vlachos
- Bernstein Center Freiburg and Faculty of Biology, University of Freiburg, Freiburg, Germany
- * E-mail: (IV); (AK)
| | - Taşkin Deniz
- Bernstein Center Freiburg and Faculty of Biology, University of Freiburg, Freiburg, Germany
| | - Ad Aertsen
- Bernstein Center Freiburg and Faculty of Biology, University of Freiburg, Freiburg, Germany
| | - Arvind Kumar
- Bernstein Center Freiburg and Faculty of Biology, University of Freiburg, Freiburg, Germany
- Department of Computational Science and Technology, School of Computer Science and Communication, KTH Royal Institute of Technology, Stockholm, Sweden
- * E-mail: (IV); (AK)
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Greenwald E, Masters MR, Thakor NV. Erratum to: Implantable neurotechnologies: bidirectional neural interfaces--applications and VLSI circuit implementations. Med Biol Eng Comput 2016; 54:19-22. [PMID: 26924780 PMCID: PMC4955539 DOI: 10.1007/s11517-016-1452-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Affiliation(s)
- Elliot Greenwald
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
| | - Matthew R Masters
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Nitish V Thakor
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
- Singapore Institute for Neurotechnology (SINAPSE), National University of Singapore, Singapore, Singapore.
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Greenwald E, Masters MR, Thakor NV. Implantable neurotechnologies: bidirectional neural interfaces--applications and VLSI circuit implementations. Med Biol Eng Comput 2016; 54:1-17. [PMID: 26753776 PMCID: PMC4839984 DOI: 10.1007/s11517-015-1429-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2015] [Accepted: 12/10/2015] [Indexed: 12/20/2022]
Abstract
A bidirectional neural interface is a device that transfers information into and out of the nervous system. This class of devices has potential to improve treatment and therapy in several patient populations. Progress in very large-scale integration has advanced the design of complex integrated circuits. System-on-chip devices are capable of recording neural electrical activity and altering natural activity with electrical stimulation. Often, these devices include wireless powering and telemetry functions. This review presents the state of the art of bidirectional circuits as applied to neuroprosthetic, neurorepair, and neurotherapeutic systems.
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Affiliation(s)
- Elliot Greenwald
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
| | - Matthew R Masters
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Nitish V Thakor
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
- Singapore Institute for Neurotechnology (SINAPSE), National University of Singapore, Singapore, Singapore.
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Tung JK, Gutekunst CA, Gross RE. Inhibitory luminopsins: genetically-encoded bioluminescent opsins for versatile, scalable, and hardware-independent optogenetic inhibition. Sci Rep 2015; 5:14366. [PMID: 26399324 PMCID: PMC4585826 DOI: 10.1038/srep14366] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2015] [Accepted: 08/25/2015] [Indexed: 01/11/2023] Open
Abstract
Optogenetic techniques provide an unprecedented ability to precisely manipulate neural activity in the context of complex neural circuitry. Although the toolbox of optogenetic probes continues to expand at a rapid pace with more efficient and responsive reagents, hardware-based light delivery is still a major hurdle that limits its practical use in vivo. We have bypassed the challenges of external light delivery by directly coupling a bioluminescent light source (a genetically encoded luciferase) to an inhibitory opsin, which we term an inhibitory luminopsin (iLMO). iLMO was shown to suppress action potential firing and synchronous bursting activity in vitro in response to both external light and luciferase substrate. iLMO was further shown to suppress single-unit firing rate and local field potentials in the hippocampus of anesthetized rats. Finally, expression of iLMO was scaled up to multiple structures of the basal ganglia to modulate rotational behavior of freely moving animals in a hardware-independent fashion. This novel class of optogenetic probes demonstrates how non-invasive inhibition of neural activity can be achieved, which adds to the versatility, scalability, and practicality of optogenetic applications in freely behaving animals.
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Affiliation(s)
- Jack K. Tung
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA
- Department of Neurosurgery, Emory University, Atlanta, GA
| | | | - Robert E. Gross
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA
- Department of Neurosurgery, Emory University, Atlanta, GA
- Department of Neurology, Emory University, Atlanta, GA
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27
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Desai SA, Rolston JD, McCracken CE, Potter SM, Gross RE. Asynchronous Distributed Multielectrode Microstimulation Reduces Seizures in the Dorsal Tetanus Toxin Model of Temporal Lobe Epilepsy. Brain Stimul 2015; 9:86-100. [PMID: 26607483 DOI: 10.1016/j.brs.2015.08.008] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2014] [Revised: 08/09/2015] [Accepted: 08/14/2015] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Electrical brain stimulation has shown promise for reducing seizures in drug-resistant epilepsy, but the electrical stimulation parameter space remains largely unexplored. New stimulation parameters, electrode types, and stimulation targets may be more effective in controlling seizures compared to currently available options. HYPOTHESIS We hypothesized that a novel electrical stimulation approach involving distributed multielectrode microstimulation at the epileptic focus would reduce seizure frequency in the tetanus toxin model of temporal lobe epilepsy. METHODS We explored a distributed multielectrode microstimulation (DMM) approach in which electrical stimulation was delivered through 15 33-µm-diameter electrodes implanted at the epileptic focus (dorsal hippocampus) in the rat tetanus toxin model of temporal lobe epilepsy. RESULTS We show that hippocampal theta (6-12 Hz brain oscillations) is decreased in this animal model during awake behaving conditions compared to control animals (p < 10(-4)). DMM with biphasic, theta-range (6-12 Hz/electrode) pulses delivered asynchronously on the 15 microelectrodes was effective in reducing seizures by 46% (p < 0.05). When theta pulses or sinusoidal stimulation was delivered synchronously and continuously on the 15 microelectrodes, or through a single macroelectrode, no effects on seizure frequency were observed. High frequency stimulation (>16.66 Hz/per electrode), in contrast, had a tendency to increase seizure frequency. CONCLUSIONS These results indicate that DMM could be a new effective approach to therapeutic brain stimulation for reducing seizures in epilepsy.
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Affiliation(s)
- Sharanya Arcot Desai
- The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, USA; Laboratory for Neuroengineering, Georgia Institute of Technology, Atlanta, USA
| | - John D Rolston
- Department of Neurological Surgery, University of California, San Francisco, USA
| | | | - Steve M Potter
- The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, USA; Laboratory for Neuroengineering, Georgia Institute of Technology, Atlanta, USA
| | - Robert E Gross
- The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, USA; Department of Neurosurgery, Emory University School of Medicine, Atlanta, USA.
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Kocaturk M, Gulcur HO, Canbeyli R. Toward Building Hybrid Biological/in silico Neural Networks for Motor Neuroprosthetic Control. Front Neurorobot 2015; 9:8. [PMID: 26321943 PMCID: PMC4531252 DOI: 10.3389/fnbot.2015.00008] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2015] [Accepted: 07/15/2015] [Indexed: 11/13/2022] Open
Abstract
In this article, we introduce the Bioinspired Neuroprosthetic Design Environment (BNDE) as a practical platform for the development of novel brain–machine interface (BMI) controllers, which are based on spiking model neurons. We built the BNDE around a hard real-time system so that it is capable of creating simulated synapses from extracellularly recorded neurons to model neurons. In order to evaluate the practicality of the BNDE for neuroprosthetic control experiments, a novel, adaptive BMI controller was developed and tested using real-time closed-loop simulations. The present controller consists of two in silico medium spiny neurons, which receive simulated synaptic inputs from recorded motor cortical neurons. In the closed-loop simulations, the recordings from the cortical neurons were imitated using an external, hardware-based neural signal synthesizer. By implementing a reward-modulated spike timing-dependent plasticity rule, the controller achieved perfect target reach accuracy for a two-target reaching task in one-dimensional space. The BNDE combines the flexibility of software-based spiking neural network (SNN) simulations with powerful online data visualization tools and is a low-cost, PC-based, and all-in-one solution for developing neurally inspired BMI controllers. We believe that the BNDE is the first implementation, which is capable of creating hybrid biological/in silico neural networks for motor neuroprosthetic control and utilizes multiple CPU cores for computationally intensive real-time SNN simulations.
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Affiliation(s)
- Mehmet Kocaturk
- Institute of Biomedical Engineering, Bogazici University , Istanbul , Turkey ; Department of Biomedical Engineering, Istanbul Medipol University , Istanbul , Turkey
| | - Halil Ozcan Gulcur
- Institute of Biomedical Engineering, Bogazici University , Istanbul , Turkey
| | - Resit Canbeyli
- Department of Psychology, Bogazici University , Istanbul , Turkey
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Newman JP, Fong MF, Millard DC, Whitmire CJ, Stanley GB, Potter SM. Optogenetic feedback control of neural activity. eLife 2015; 4:e07192. [PMID: 26140329 PMCID: PMC4490717 DOI: 10.7554/elife.07192] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2015] [Accepted: 05/28/2015] [Indexed: 12/22/2022] Open
Abstract
Optogenetic techniques enable precise excitation and inhibition of firing in specified neuronal populations and artifact-free recording of firing activity. Several studies have suggested that optical stimulation provides the precision and dynamic range requisite for closed-loop neuronal control, but no approach yet permits feedback control of neuronal firing. Here we present the ‘optoclamp’, a feedback control technology that provides continuous, real-time adjustments of bidirectional optical stimulation in order to lock spiking activity at specified targets over timescales ranging from seconds to days. We demonstrate how this system can be used to decouple neuronal firing levels from ongoing changes in network excitability due to multi-hour periods of glutamatergic or GABAergic neurotransmission blockade in vitro as well as impinging vibrissal sensory drive in vivo. This technology enables continuous, precise optical control of firing in neuronal populations in order to disentangle causally related variables of circuit activation in a physiologically and ethologically relevant manner. DOI:http://dx.doi.org/10.7554/eLife.07192.001 Cells called neurons use electrical signals to rapidly carry information around the body. When a neuron is activated, it generates (or ‘fires’) a short electrical impulse that travels along the cell to relay a message to other neurons, muscles or organs. Optogenetics is a technique that allows scientists to genetically modify neurons to produce proteins that make them light sensitive. One of the most commonly used light-sensitive proteins is called channelrhodopsin-2. It is activated by blue light and increases the electrical activity of neurons. Another protein is called halorhodopsin, which responds to yellow light and inhibits the firing of neurons. By shining light of particular colors onto neurons that produce these and other light-sensitive proteins, it is possible to manipulate the activity of large populations of neurons. Most previous optogenetic experiments have involved altering the activity of neurons and then observing the outcome at a later point in time. However, it would be very useful to be able to alter the amount of optical stimulation to achieve particular levels of neuron activity in real time. To achieve this, the level of neuron activity at any point in time would need to be quickly compared to the desired level, so that optogenetics could be used to increase or decrease the firing of neurons as appropriate. Newman et al. have now developed an optogenetic system called ‘optoclamp’ that can control the activity of neurons in real time. In neurons grown in cell culture, the optoclamp is able to hold the level of neuron activity at particular values for periods of time ranging from 60 seconds to 24 hours. It can be used to restore and maintain the baseline level of neuron activity in the presence of drugs that would otherwise produce large increases or decreases in the firing of neurons. Moreover, in anaesthetized rats, the optoclamp can prevent some neurons from being activated even when the rats' whiskers move, which would normally change their firing level. Newman et al.'s findings open the door to a new type of neuroscience experiment where it is possible to manipulate activity patterns as they are produced by the brain. This will help researchers to understand how particular patterns of brain activity are linked to learning, memory, and behavior. DOI:http://dx.doi.org/10.7554/eLife.07192.002
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Affiliation(s)
- Jonathan P Newman
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, United States
| | - Ming-fai Fong
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, United States
| | - Daniel C Millard
- Laboratory for Neuroengineering, Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, United States
| | - Clarissa J Whitmire
- Laboratory for Neuroengineering, Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, United States
| | - Garrett B Stanley
- Laboratory for Neuroengineering, Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, United States
| | - Steve M Potter
- Laboratory for Neuroengineering, Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, United States
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Biró I, Giugliano M. A reconfigurable visual-programming library for real-time closed-loop cellular electrophysiology. Front Neuroinform 2015; 9:17. [PMID: 26157385 PMCID: PMC4477165 DOI: 10.3389/fninf.2015.00017] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2014] [Accepted: 06/09/2015] [Indexed: 12/04/2022] Open
Abstract
Most of the software platforms for cellular electrophysiology are limited in terms of flexibility, hardware support, ease of use, or re-configuration and adaptation for non-expert users. Moreover, advanced experimental protocols requiring real-time closed-loop operation to investigate excitability, plasticity, dynamics, are largely inaccessible to users without moderate to substantial computer proficiency. Here we present an approach based on MATLAB/Simulink, exploiting the benefits of LEGO-like visual programming and configuration, combined to a small, but easily extendible library of functional software components. We provide and validate several examples, implementing conventional and more sophisticated experimental protocols such as dynamic-clamp or the combined use of intracellular and extracellular methods, involving closed-loop real-time control. The functionality of each of these examples is demonstrated with relevant experiments. These can be used as a starting point to create and support a larger variety of electrophysiological tools and methods, hopefully extending the range of default techniques and protocols currently employed in experimental labs across the world.
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Affiliation(s)
- István Biró
- Theoretical Neurobiology and Neuroengineering, University of AntwerpAntwerpen, Belgium
| | - Michele Giugliano
- Theoretical Neurobiology and Neuroengineering, University of AntwerpAntwerpen, Belgium
- Department of Computer Science, University of SheffieldSheffield, UK
- Laboratory for Neural Microcircuitry, Brain Mind Institute, École Polytechnique Fédérale de LausanneLausanne, Switzerland
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Wu H, Ghekiere H, Beeckmans D, Tambuyzer T, van Kuyck K, Aerts JM, Nuttin B. Conceptualization and validation of an open-source closed-loop deep brain stimulation system in rat. Sci Rep 2015; 4:9921. [PMID: 25897892 PMCID: PMC4404680 DOI: 10.1038/srep09921] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2014] [Accepted: 03/20/2015] [Indexed: 11/24/2022] Open
Abstract
Conventional deep brain stimulation (DBS) applies constant electrical stimulation to specific brain regions to treat neurological disorders. Closed-loop DBS with real-time feedback is gaining attention in recent years, after proved more effective than conventional DBS in terms of pathological symptom control clinically. Here we demonstrate the conceptualization and validation of a closed-loop DBS system using open-source hardware. We used hippocampal theta oscillations as system input, and electrical stimulation in the mesencephalic reticular formation (mRt) as controller output. It is well documented that hippocampal theta oscillations are highly related to locomotion, while electrical stimulation in the mRt induces freezing. We used an Arduino open-source microcontroller between input and output sources. This allowed us to use hippocampal local field potentials (LFPs) to steer electrical stimulation in the mRt. Our results showed that closed-loop DBS significantly suppressed locomotion compared to no stimulation, and required on average only 56% of the stimulation used in open-loop DBS to reach similar effects. The main advantages of open-source hardware include wide selection and availability, high customizability, and affordability. Our open-source closed-loop DBS system is effective, and warrants further research using open-source hardware for closed-loop neuromodulation.
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Affiliation(s)
- Hemmings Wu
- Research Group Experimental Neurosurgery and Neuroanatomy, KU Leuven, Leuven, Belgium
| | - Hartwin Ghekiere
- Department of Biosystems, M3-BIORES: Measure, Model & Manage Bioresponses, KU Leuven, Leuven, Belgium
| | - Dorien Beeckmans
- Research Group Experimental Neurosurgery and Neuroanatomy, KU Leuven, Leuven, Belgium
| | - Tim Tambuyzer
- Department of Biosystems, M3-BIORES: Measure, Model & Manage Bioresponses, KU Leuven, Leuven, Belgium
| | - Kris van Kuyck
- Research Group Experimental Neurosurgery and Neuroanatomy, KU Leuven, Leuven, Belgium
| | - Jean-Marie Aerts
- Department of Biosystems, M3-BIORES: Measure, Model & Manage Bioresponses, KU Leuven, Leuven, Belgium
| | - Bart Nuttin
- Research Group Experimental Neurosurgery and Neuroanatomy, KU Leuven, Leuven, Belgium.,Department of Neurosurgery, University Hospitals Leuven, Leuven, Belgium
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Upward synaptic scaling is dependent on neurotransmission rather than spiking. Nat Commun 2015; 6:6339. [PMID: 25751516 PMCID: PMC4355957 DOI: 10.1038/ncomms7339] [Citation(s) in RCA: 61] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2014] [Accepted: 01/21/2015] [Indexed: 01/10/2023] Open
Abstract
Homeostatic plasticity encompasses a set of mechanisms that are thought to stabilize firing rates in neural circuits. The most widely studied form of homeostatic plasticity is upward synaptic scaling (upscaling), characterized by a multiplicative increase in the strength of excitatory synaptic inputs to a neuron as a compensatory response to chronic reductions in firing rate. While reduced spiking is thought to trigger upscaling, an alternative possibility is that reduced glutamatergic transmission generates this plasticity directly. However, spiking and neurotransmission are tightly coupled, so it has been difficult to determine their independent roles in the scaling process. Here we combined chronic multielectrode recording, closed-loop optogenetic stimulation, and pharmacology to show that reduced glutamatergic transmission directly triggers cell-wide synaptic upscaling. This work highlights the importance of synaptic activity in initiating signalling cascades that mediate upscaling. Moreover, our findings challenge the prevailing view that upscaling functions to homeostatically stabilize firing rates.
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Neural ensemble communities: open-source approaches to hardware for large-scale electrophysiology. Curr Opin Neurobiol 2014; 32:53-9. [PMID: 25528614 DOI: 10.1016/j.conb.2014.11.004] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2014] [Revised: 11/04/2014] [Accepted: 11/08/2014] [Indexed: 01/19/2023]
Abstract
One often-overlooked factor when selecting a platform for large-scale electrophysiology is whether or not a particular data acquisition system is 'open' or 'closed': that is, whether or not the system's schematics and source code are available to end users. Open systems have a reputation for being difficult to acquire, poorly documented, and hard to maintain. With the arrival of more powerful and compact integrated circuits, rapid prototyping services, and web-based tools for collaborative development, these stereotypes must be reconsidered. We discuss some of the reasons why multichannel extracellular electrophysiology could benefit from open-source approaches and describe examples of successful community-driven tool development within this field. In order to promote the adoption of open-source hardware and to reduce the need for redundant development efforts, we advocate a move toward standardized interfaces that connect each element of the data processing pipeline. This will give researchers the flexibility to modify their tools when necessary, while allowing them to continue to benefit from the high-quality products and expertise provided by commercial vendors.
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Sanders JI, Kepecs A. A low-cost programmable pulse generator for physiology and behavior. FRONTIERS IN NEUROENGINEERING 2014; 7:43. [PMID: 25566051 PMCID: PMC4263096 DOI: 10.3389/fneng.2014.00043] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/17/2014] [Accepted: 11/25/2014] [Indexed: 11/13/2022]
Abstract
Precisely timed experimental manipulations of the brain and its sensory environment are often employed to reveal principles of brain function. While complex and reliable pulse trains for temporal stimulus control can be generated with commercial instruments, contemporary options remain expensive and proprietary. We have developed Pulse Pal, an open source device that allows users to create and trigger software-defined trains of voltage pulses with high temporal precision. Here we describe Pulse Pal’s circuitry and firmware, and characterize its precision and reliability. In addition, we supply online documentation with instructions for assembling, testing and installing Pulse Pal. While the device can be operated as a stand-alone instrument, we also provide application programming interfaces in several programming languages. As an inexpensive, flexible and open solution for temporal control, we anticipate that Pulse Pal will be used to address a wide range of instrumentation timing challenges in neuroscience research.
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Affiliation(s)
- Joshua I Sanders
- Neuroscience, Cold Spring Harbor Laboratory, Kepecs Lab, Cold Spring Harbor NY, USA
| | - Adam Kepecs
- Neuroscience, Cold Spring Harbor Laboratory, Kepecs Lab, Cold Spring Harbor NY, USA
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Laxpati NG, Mahmoudi B, Gutekunst CA, Newman JP, Zeller-Townson R, Gross RE. Real-time in vivo optogenetic neuromodulation and multielectrode electrophysiologic recording with NeuroRighter. FRONTIERS IN NEUROENGINEERING 2014; 7:40. [PMID: 25404915 PMCID: PMC4217045 DOI: 10.3389/fneng.2014.00040] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/15/2014] [Accepted: 10/08/2014] [Indexed: 12/02/2022]
Abstract
Optogenetic channels have greatly expanded neuroscience’s experimental capabilities, enabling precise genetic targeting and manipulation of neuron subpopulations in awake and behaving animals. However, many barriers to entry remain for this technology – including low-cost and effective hardware for combined optical stimulation and electrophysiologic recording. To address this, we adapted the open-source NeuroRighter multichannel electrophysiology platform for use in awake and behaving rodents in both open and closed-loop stimulation experiments. Here, we present these cost-effective adaptations, including commercially available LED light sources; custom-made optical ferrules; 3D printed ferrule hardware and software to calibrate and standardize output intensity; and modifications to commercially available electrode arrays enabling stimulation proximally and distally to the recording target. We then demonstrate the capabilities and versatility of these adaptations in several open and closed-loop experiments, demonstrate spectrographic methods of analyzing the results, as well as discuss artifacts of stimulation.
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Affiliation(s)
- Nealen G Laxpati
- Translational Neuroengineering Group, Department of Biomedical Engineering, Georgia Institute of Technology and Emory University School of Medicine Atlanta, GA, USA ; Department of Neurosurgery, Emory University School of Medicine Atlanta, GA, USA
| | - Babak Mahmoudi
- Translational Neuroengineering Group, Department of Biomedical Engineering, Georgia Institute of Technology and Emory University School of Medicine Atlanta, GA, USA ; Department of Neurosurgery, Emory University School of Medicine Atlanta, GA, USA
| | - Claire-Anne Gutekunst
- Translational Neuroengineering Group, Department of Biomedical Engineering, Georgia Institute of Technology and Emory University School of Medicine Atlanta, GA, USA ; Department of Neurosurgery, Emory University School of Medicine Atlanta, GA, USA
| | - Jonathan P Newman
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology Cambridge, MA, USA
| | - Riley Zeller-Townson
- Laboratory for Neuroengineering, Department of Biomedical Engineering, Georgia Institute of Technology and Emory University School of Medicine Atlanta, GA, USA
| | - Robert E Gross
- Translational Neuroengineering Group, Department of Biomedical Engineering, Georgia Institute of Technology and Emory University School of Medicine Atlanta, GA, USA ; Department of Neurosurgery, Emory University School of Medicine Atlanta, GA, USA ; Department of Neurology, Emory University School of Medicine Atlanta, GA, USA
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36
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Kaufman M, Reinartz S, Ziv NE. Adaptation to prolonged neuromodulation in cortical cultures: an invariable return to network synchrony. BMC Biol 2014; 12:83. [PMID: 25339462 PMCID: PMC4237737 DOI: 10.1186/s12915-014-0083-3] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2014] [Accepted: 09/29/2014] [Indexed: 11/17/2022] Open
Abstract
Background Prolonged neuromodulatory regimes, such as those critically involved in promoting arousal and suppressing sleep-associated synchronous activity patterns, might be expected to trigger adaptation processes and, consequently, a decline in neuromodulator-driven effects. This possibility, however, has rarely been addressed. Results Using networks of cultured cortical neurons, acetylcholine microinjections and a novel closed-loop ‘synchrony-clamp’ system, we found that acetylcholine pulses strongly suppressed network synchrony. Over the course of many hours, however, synchrony invariably reemerged, even when feedback was used to compensate for declining cholinergic efficacy. Network synchrony also reemerged following its initial suppression by noradrenaline, but this did not occlude the suppression of synchrony or its gradual reemergence following subsequent cholinergic input. Importantly, cholinergic efficacy could be restored and preserved over extended time scales by periodically withdrawing cholinergic input. Conclusions These findings indicate that the capacity of neuromodulators to suppress network synchrony is constrained by slow-acting, reactive processes. A multiplicity of neuromodulators and ultimately neuromodulator withdrawal periods might thus be necessary to cope with an inevitable reemergence of network synchrony. Electronic supplementary material The online version of this article (doi:10.1186/s12915-014-0083-3) contains supplementary material, which is available to authorized users.
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37
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Tateno T, Nishikawa J. A CMOS IC-based multisite measuring system for stimulation and recording in neural preparations in vitro. FRONTIERS IN NEUROENGINEERING 2014; 7:39. [PMID: 25346683 PMCID: PMC4193337 DOI: 10.3389/fneng.2014.00039] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2014] [Accepted: 09/15/2014] [Indexed: 11/13/2022]
Abstract
In this report, we describe the system integration of a complementary metal oxide semiconductor (CMOS) integrated circuit (IC) chip, capable of both stimulation and recording of neurons or neural tissues, to investigate electrical signal propagation within cellular networks in vitro. The overall system consisted of three major subunits: a 5.0 × 5.0 mm CMOS IC chip, a reconfigurable logic device (field-programmable gate array, FPGA), and a PC. To test the system, microelectrode arrays (MEAs) were used to extracellularly measure the activity of cultured rat cortical neurons and mouse cortical slices. The MEA had 64 bidirectional (stimulation and recording) electrodes. In addition, the CMOS IC chip was equipped with dedicated analog filters, amplification stages, and a stimulation buffer. Signals from the electrodes were sampled at 15.6 kHz with 16-bit resolution. The measured input-referred circuitry noise was 10.1 μ V root mean square (10 Hz to 100 kHz), which allowed reliable detection of neural signals ranging from several millivolts down to approximately 33 μ Vpp. Experiments were performed involving the stimulation of neurons with several spatiotemporal patterns and the recording of the triggered activity. An advantage over current MEAs, as demonstrated by our experiments, includes the ability to stimulate (voltage stimulation, 5-bit resolution) spatiotemporal patterns in arbitrary subsets of electrodes. Furthermore, the fast stimulation reset mechanism allowed us to record neuronal signals from a stimulating electrode around 3 ms after stimulation. We demonstrate that the system can be directly applied to, for example, auditory neural prostheses in conjunction with an acoustic sensor and a sound processing system.
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Affiliation(s)
- Takashi Tateno
- Special Research Promotion Group, Graduate School of Frontier Biosciences, Osaka University Osaka, Japan ; Bioengineering and Bioinformatics, Graduate School of Information Science and Technology, Hokkaido University Sapporo, Japan
| | - Jun Nishikawa
- Bioengineering and Bioinformatics, Graduate School of Information Science and Technology, Hokkaido University Sapporo, Japan
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Potter SM, El Hady A, Fetz EE. Closed-loop neuroscience and neuroengineering. Front Neural Circuits 2014; 8:115. [PMID: 25294988 PMCID: PMC4171982 DOI: 10.3389/fncir.2014.00115] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2013] [Accepted: 09/01/2014] [Indexed: 01/18/2023] Open
Affiliation(s)
- Steve M Potter
- Laboratory for Neuroengineering, Coulter Department of Biomedical Engineering, Georgia Institute of Technology Atlanta, GA, USA
| | - Ahmed El Hady
- Department of Non Linear Dynamics, Max Planck Institute for Dynamics and Self Organization Goettingen, Germany
| | - Eberhard E Fetz
- Departments of Physiology and Biophysics and Bioengineering, Washington National Primate Research Center, University of Washington Seattle, WA, USA
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Siegle JH, Wilson MA. Enhancement of encoding and retrieval functions through theta phase-specific manipulation of hippocampus. eLife 2014; 3:e03061. [PMID: 25073927 PMCID: PMC4384761 DOI: 10.7554/elife.03061] [Citation(s) in RCA: 158] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Assessing the behavioral relevance of the hippocampal theta rhythm has proven
difficult, due to a shortage of experiments that selectively manipulate
phase-specific information processing. Using closed-loop stimulation, we triggered
inhibition of dorsal CA1 at specific phases of the endogenous theta rhythm in freely
behaving mice. This intervention enhanced performance on a spatial navigation task
that requires the encoding and retrieval of information related to reward location on
every trial. In agreement with prior models of hippocampal function, the behavioral
effects depended on both the phase of theta and the task segment at which we
stimulated. Stimulation in the encoding segment enhanced performance when inhibition
was triggered by the peak of theta. Conversely, stimulation in the retrieval segment
enhanced performance when inhibition was triggered by the trough of theta. These
results suggest that processes related to the encoding and retrieval of task-relevant
information are preferentially active at distinct phases of theta. DOI:http://dx.doi.org/10.7554/eLife.03061.001 Around 15 years ago, an imaging study compared the brains of London taxi
drivers—who need to know their way around one of the biggest cities in the
world—with those of the general public, and found that a structure called the
hippocampus was routinely larger in the taxi drivers. This finding was consistent
with previous studies from rats, which showed that anatomical changes occur in the
hippocampus after animals learn to navigate through various mazes. Together, these
results suggest that the hippocampus is important for spatial awareness in both
humans and rodents. The hippocampus—which takes its name from the Greek for
‘seahorse’ due to its shape—consists mostly of cells called
pyramidal neurons, which communicate with one other using an excitatory molecule
called glutamate. However, it also contains cells that suppress the activity of the
pyramidal neurons, using an inhibitory molecule called GABA. When electrodes are used
to record the combined electrical activity of many cells in the
hippocampus—including both excitatory and inhibitory cells—the
resulting pattern resembles a wave with peaks and troughs that repeat roughly eight
times per second. Although this activity, known as the theta rhythm or cycle, has
been observed in countless experiments, it has been difficult to pin down how it is
relevant to behavior. Siegle and Wilson now show that the theta cycle may help the brain to keep incoming
information separate from information stored in memory. This conclusion is based on
the results of experiments on mice with hippocampi that had been modified to make
them sensitive to light: in particular, light was needed to activate the neurons that
suppress the activity of the pyramidal neurons. This meant that it was possible to
reduce the overall level of activity in the hippocampus by shining light on certain
neurons. The mice were trained to perform a spatial memory task that consisted of an encoding
stage—where they learned the location of a reward—and a retrieval
stage, in which they recalled this location from memory. On certain trials, pulses of
light could be delivered to the brain at specific points in the theta cycle.
Delivering light near the peak of the cycle during the encoding stage resulted in
improved memory performance, as did delivering light near the trough of the cycle
during the retrieval stage. These results suggest that the hippocampus preferentially encodes and retrieves
information at different stages of the theta cycle. Specifically, activity just after
the peak of the theta cycle is biased towards retrieval, meaning that reducing
hippocampal activity at this time point will make it easier to form new memories. By
contrast, reducing activity just after the trough of the theta cycle—when the
hippocampus is biased towards encoding—will enhance memory retrieval. DOI:http://dx.doi.org/10.7554/eLife.03061.002
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Affiliation(s)
- Joshua H Siegle
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, United States Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, United States
| | - Matthew A Wilson
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, United States Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, United States
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40
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Arcot Desai S, Gutekunst CA, Potter SM, Gross RE. Deep brain stimulation macroelectrodes compared to multiple microelectrodes in rat hippocampus. FRONTIERS IN NEUROENGINEERING 2014; 7:16. [PMID: 24971060 PMCID: PMC4054883 DOI: 10.3389/fneng.2014.00016] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/12/2013] [Accepted: 05/19/2014] [Indexed: 01/02/2023]
Abstract
Microelectrode arrays (wire diameter <50 μm) were compared to traditional macroelectrodes for deep brain stimulation (DBS). Understanding the neuronal activation volume may help solve some of the mysteries associated with DBS, e.g., its mechanisms of action. We used c-fos immunohistochemistry to investigate neuronal activation in the rat hippocampus caused by multi-micro- and macroelectrode stimulation. At ± 1V stimulation at 25 Hz, microelectrodes (33 μm diameter) had a radius of activation of 100 μm, which is 50% of that seen with 150 μm diameter macroelectrode stimulation. Macroelectrodes activated about 5.8 times more neurons than a single microelectrode, but displaced ~20 times more neural tissue. The sphere of influence of stimulating electrodes can be significantly increased by reducing their impedance. By ultrasonic electroplating (sonicoplating) the microelectrodes with platinum to increase their surface area and reduce their impedance by an order of magnitude, the radius of activation increased by 50 μm and more than twice the number of neurons were activated within this increased radius compared to unplated microelectrodes. We suggest that a new approach to DBS, one that uses multiple high-surface area microelectrodes, may be more therapeutically effective due to increased neuronal activation.
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Affiliation(s)
- Sharanya Arcot Desai
- Laboratory for Neuroengineering, Georgia Institute of Technology, Atlanta GA, USA ; The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta GA, USA
| | | | - Steve M Potter
- Laboratory for Neuroengineering, Georgia Institute of Technology, Atlanta GA, USA ; The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta GA, USA
| | - Robert E Gross
- The Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta GA, USA ; Department of Neurosurgery, Emory University School of Medicine, Atlanta GA, USA
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Abstract
Technological innovations have driven the advancement of the surgical treatment of movement disorders, from the invention of the stereotactic frame to the adaptation of deep brain stimulation (DBS). Along these lines, this review will describe recent advances in inserting neuromodulation modalities, including DBS, to the target, and in the delivery of therapy at the target. Recent radiological advances are altering the way that DBS leads are targeted and inserted, by refining the ability to visualize the subcortical targets using high-field strength magnetic resonance imaging and other innovations, such as diffusion tensor imaging, and the development of novel targeting devices enabling purely anatomical implantations without the need for neurophysiological monitoring. New portable computed tomography scanners also are facilitating lead implantation without monitoring, as well as improving radiological verification of DBS lead location. Advances in neurophysiological mapping include efforts to develop automatic target verification algorithms, and probabilistic maps to guide target selection. The delivery of therapy at the target is being improved by the development of the next generation of internal pulse generators (IPGs). These include constant current devices that mitigate the variability introduced by impedance changes of the stimulated tissue and, in the near future, devices that deliver novel stimulation patterns with improved efficiency. Closed-loop adaptive IPGs are being tested, which may tailor stimulation to ongoing changes in the nervous system, reflected in biomarkers continuously recorded by the devices. Finer-grained DBS leads, in conjunction with new IPGs and advanced programming tools, may offer improved outcomes via current steering algorithms. Finally, even thermocoagulation-essentially replaced by DBS-is being advanced by new minimally-invasive approaches that may improve this therapy for selected patients in whom it may be preferred. Functional neurosurgery has a history of being driven by technological innovation, a tradition that continues into its future.
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Affiliation(s)
- Robert E Gross
- Department of Neurosurgery, Emory University School of Medicine, 1365 Clifton Road, NE Suite 6200, Atlanta, GA 30322, USA.
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DiMattina C, Zhang K. Adaptive stimulus optimization for sensory systems neuroscience. Front Neural Circuits 2013; 7:101. [PMID: 23761737 PMCID: PMC3674314 DOI: 10.3389/fncir.2013.00101] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2012] [Accepted: 05/08/2013] [Indexed: 11/24/2022] Open
Abstract
In this paper, we review several lines of recent work aimed at developing practical methods for adaptive on-line stimulus generation for sensory neurophysiology. We consider various experimental paradigms where on-line stimulus optimization is utilized, including the classical optimal stimulus paradigm where the goal of experiments is to identify a stimulus which maximizes neural responses, the iso-response paradigm which finds sets of stimuli giving rise to constant responses, and the system identification paradigm where the experimental goal is to estimate and possibly compare sensory processing models. We discuss various theoretical and practical aspects of adaptive firing rate optimization, including optimization with stimulus space constraints, firing rate adaptation, and possible network constraints on the optimal stimulus. We consider the problem of system identification, and show how accurate estimation of non-linear models can be highly dependent on the stimulus set used to probe the network. We suggest that optimizing stimuli for accurate model estimation may make it possible to successfully identify non-linear models which are otherwise intractable, and summarize several recent studies of this type. Finally, we present a two-stage stimulus design procedure which combines the dual goals of model estimation and model comparison and may be especially useful for system identification experiments where the appropriate model is unknown beforehand. We propose that fast, on-line stimulus optimization enabled by increasing computer power can make it practical to move sensory neuroscience away from a descriptive paradigm and toward a new paradigm of real-time model estimation and comparison.
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Affiliation(s)
| | - Kechen Zhang
- Department of Biomedical Engineering, The Johns Hopkins University School of MedicineBaltimore, MD, USA
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Englitz B, David SV, Sorenson MD, Shamma SA. MANTA--an open-source, high density electrophysiology recording suite for MATLAB. Front Neural Circuits 2013; 7:69. [PMID: 23653593 PMCID: PMC3644699 DOI: 10.3389/fncir.2013.00069] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2012] [Accepted: 03/30/2013] [Indexed: 12/01/2022] Open
Abstract
The distributed nature of nervous systems makes it necessary to record from a large number of sites in order to decipher the neural code, whether single cell, local field potential (LFP), micro-electrocorticograms (μECoG), electroencephalographic (EEG), magnetoencephalographic (MEG) or in vitro micro-electrode array (MEA) data are considered. High channel-count recordings also optimize the yield of a preparation and the efficiency of time invested by the researcher. Currently, data acquisition (DAQ) systems with high channel counts (>100) can be purchased from a limited number of companies at considerable prices. These systems are typically closed-source and thus prohibit custom extensions or improvements by end users. We have developed MANTA, an open-source MATLAB-based DAQ system, as an alternative to existing options. MANTA combines high channel counts (up to 1440 channels/PC), usage of analog or digital headstages, low per channel cost (<$90/channel), feature-rich display and filtering, a user-friendly interface, and a modular design permitting easy addition of new features. MANTA is licensed under the GPL and free of charge. The system has been tested by daily use in multiple setups for >1 year, recording reliably from 128 channels. It offers a growing list of features, including integrated spike sorting, PSTH and CSD display and fully customizable electrode array geometry (including 3D arrays), some of which are not available in commercial systems. MANTA runs on a typical PC and communicates via TCP/IP and can thus be easily integrated with existing stimulus generation/control systems in a lab at a fraction of the cost of commercial systems. With modern neuroscience developing rapidly, MANTA provides a flexible platform that can be rapidly adapted to the needs of new analyses and questions. Being open-source, the development of MANTA can outpace commercial solutions in functionality, while maintaining a low price-point.
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Affiliation(s)
- B Englitz
- Neural Systems Laboratory, Institute for Systems Research, University of Maryland College Park, MD, USA ; Equipe Audition, Département d'études cognitives, Ecole Normale Superieure Paris, France
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