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Tang BL. Debates on humanization of human-animal brain chimeras - are we putting the cart before the horses? MEDICINE, HEALTH CARE, AND PHILOSOPHY 2024; 27:359-366. [PMID: 38797779 DOI: 10.1007/s11019-024-10209-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 05/04/2024] [Indexed: 05/29/2024]
Abstract
Research on human-animal chimeras have elicited alarms and prompted debates. Those involving the generation of chimeric brains, in which human brain cells become anatomically and functionally intertwined with their animal counterparts in varying ratios, either via xenografts or embryonic co-development, have been considered the most problematic. The moral issues stem from a potential for "humanization" of the animal brain, as well as speculative changes to the host animals' consciousness or sentience, with consequential alteration in the animal hosts' moral status. However, critical background knowledge appears to be missing to resolve these debates. Firstly, there is no consensus on animal sentience vis-à-vis that of humans, and no established methodology that would allow a wholesome and objective assessment of changes in animal sentience resulting from the introduction of human brain cells. Knowledge in interspecies comparative neuropsychology that could allow effective demarcation of a state of "humanization" is also lacking. Secondly, moral status as a philosophical construct has no scientific and objective points of reference. Either changes in sentience or humanization effects would remain unclear unless there are some neuroscientific research grounding. For a bioethical stance based on moral status of human-animal brain chimera to make meaningful contributions to regulatory policies, it might first need to be adequately informed by, and with its arguments constructed, in a manner that are factually in line with the science. In may be prudent for approved research projects involving the generation of human-animal brain chimera to have a mandatory component of assessing plausible changes in sentience.
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Affiliation(s)
- Bor Luen Tang
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University Health System, National University of Singapore, 8 Medical Dr, Singapore, 117596, Singapore.
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2
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Conroy G. AI made of jelly 'learns' to play Pong - and improves with practice. Nature 2024:10.1038/d41586-024-02704-y. [PMID: 39174775 DOI: 10.1038/d41586-024-02704-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/24/2024]
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3
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Nishimura K, Osaki H, Tezuka K, Nakashima D, Numata S, Masamizu Y. Recent advances and applications of human brain models. Front Neural Circuits 2024; 18:1453958. [PMID: 39161368 PMCID: PMC11330844 DOI: 10.3389/fncir.2024.1453958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2024] [Accepted: 07/25/2024] [Indexed: 08/21/2024] Open
Abstract
Recent advances in human pluripotent stem cell (hPSC) technologies have prompted the emergence of new research fields and applications for human neurons and brain organoids. Brain organoids have gained attention as an in vitro model system that recapitulates the higher structure, cellular diversity and function of the brain to explore brain development, disease modeling, drug screening, and regenerative medicine. This progress has been accelerated by abundant interactions of brain organoid technology with various research fields. A cross-disciplinary approach with human brain organoid technology offers a higher-ordered advance for more accurately understanding the human brain. In this review, we summarize the status of neural induction in two- and three-dimensional culture systems from hPSCs and the modeling of neurodegenerative diseases using brain organoids. We also highlight the latest bioengineered technologies for the assembly of spatially higher-ordered neural tissues and prospects of brain organoid technology toward the understanding of the potential and abilities of the human brain.
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Affiliation(s)
- Kaneyasu Nishimura
- Laboratory of Functional Brain Circuit Construction, Graduate School of Brain Science, Doshisha University, Kyotanabe, Japan
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4
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Vallejo-Mancero B, Faci-Lázaro S, Zapata M, Soriano J, Madrenas J. Real-time hardware emulation of neural cultures: A comparative study of in vitro, in silico and in duris silico models. Neural Netw 2024; 179:106593. [PMID: 39142177 DOI: 10.1016/j.neunet.2024.106593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 06/20/2024] [Accepted: 07/31/2024] [Indexed: 08/16/2024]
Abstract
Biological neural networks are well known for their capacity to process information with extremely low power consumption. Fields such as Artificial Intelligence, with high computational costs, are seeking for alternatives inspired in biological systems. An inspiring alternative is to implement hardware architectures that replicate the behavior of biological neurons but with the flexibility in programming capabilities of an electronic device, all combined with a relatively low operational cost. To advance in this quest, here we analyze the capacity of the HEENS hardware architecture to operate in a similar manner as an in vitro neuronal network grown in the laboratory. For that, we considered data of spontaneous activity in living neuronal cultures of about 400 neurons and compared their collective dynamics and functional behavior with those obtained from direct numerical simulations (in silico) and hardware implementations (in duris silico). The results show that HEENS is capable to mimic both the in vitro and in silico systems with high efficient-cost ratio, and on different network topological designs. Our work shows that compact low-cost hardware implementations are feasible, opening new avenues for future, highly efficient neuromorphic devices and advanced human-machine interfacing.
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Affiliation(s)
- Bernardo Vallejo-Mancero
- Department of Electronic Engineering, Universitat Politecnica de Catalunya, Jordi Girona, 1-3, edif. C4, Barcelona, 08034, Catalunya, Spain.
| | - Sergio Faci-Lázaro
- Department of Condensed Matter Physics, University of Zaragoza, C. de Pedro Cerbuna, 12, Zaragoza, 50009, Spain; GOTHAM Lab, Institute of Biocomputation and Physics of Complex Systems, University of Zaragoza, C. de Pedro Cerbuna, 12, Zaragoza, 50009, Spain
| | - Mireya Zapata
- Department of Electronic Engineering, Universitat Politecnica de Catalunya, Jordi Girona, 1-3, edif. C4, Barcelona, 08034, Catalunya, Spain; Centro de Investigación en Mecatrónica y Sistemas Interactivos - MIST, Universidad Indoamérica, Machala y Sabanilla, Quito, 170103, Ecuador
| | - Jordi Soriano
- Departament de Física de la Matèria Condensada, Universitat de Barcelona, Martíi Franquès 1, Barcelona, 08028, Spain; Universitat de Barcelona Institute of Complex Systems (UBICS), Gran Via Corts Catalanes 585, Barcelona, 08007, Spain
| | - Jordi Madrenas
- Department of Electronic Engineering, Universitat Politecnica de Catalunya, Jordi Girona, 1-3, edif. C4, Barcelona, 08034, Catalunya, Spain
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5
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Niewinski NE, Hernandez D, Colicos MA. Detection of Memory Engrams in Mammalian Neuronal Circuits. eNeuro 2024; 11:ENEURO.0450-23.2024. [PMID: 38997146 PMCID: PMC11307552 DOI: 10.1523/eneuro.0450-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 06/06/2024] [Accepted: 07/04/2024] [Indexed: 07/14/2024] Open
Abstract
It has long been assumed that activity patterns persist in neuronal circuits after they are first experienced, as part of the process of information processing and storage by the brain. However, these "reverberations" of current activity have not been directly observed on a single-neuron level in a mammalian system. Here we demonstrate that specific induced activity patterns are retained in mature cultured hippocampal neuronal networks. Neurons within the network are induced to fire at a single frequency or in a more complex pattern containing two distinct frequencies. After the stimulation was stopped, the subsequent neuronal activity of hundreds of neurons in the network was monitored. In the case of single-frequency stimulation, it was observed that many of the neurons continue to fire at the same frequency that they were stimulated to fire at. Using a recurrent neural network trained to detect specific, more complex patterns, we found that the multiple-frequency stimulation patterns were also retained within the neuronal network. Moreover, it appears that the component frequencies of the more complex patterns are stored in different populations of neurons and neuron subtypes.
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Affiliation(s)
- Nicole E Niewinski
- Department of Physiology and Pharmacology, Cumming School of Medicine, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta T2N 4N1, Canada
| | - Deyanell Hernandez
- Department of Physiology and Pharmacology, Cumming School of Medicine, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta T2N 4N1, Canada
| | - Michael A Colicos
- Department of Physiology and Pharmacology, Cumming School of Medicine, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta T2N 4N1, Canada
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6
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Falandays JB, Yoshimi J, Warren WH, Spivey MJ. A potential mechanism for Gibsonian resonance: behavioral entrainment emerges from local homeostasis in an unsupervised reservoir network. Cogn Neurodyn 2024; 18:1811-1834. [PMID: 39104666 PMCID: PMC11297877 DOI: 10.1007/s11571-023-09988-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 06/15/2023] [Accepted: 06/25/2023] [Indexed: 08/07/2024] Open
Abstract
While the cognitivist school of thought holds that the mind is analogous to a computer, performing logical operations over internal representations, the tradition of ecological psychology contends that organisms can directly "resonate" to information for action and perception without the need for a representational intermediary. The concept of resonance has played an important role in ecological psychology, but it remains a metaphor. Supplying a mechanistic account of resonance requires a non-representational account of central nervous system (CNS) dynamics. Towards this, we present a series of simple models in which a reservoir network with homeostatic nodes is used to control a simple agent embedded in an environment. This network spontaneously produces behaviors that are adaptive in each context, including (1) visually tracking a moving object, (2) substantially above-chance performance in the arcade game Pong, (2) and avoiding walls while controlling a mobile agent. Upon analyzing the dynamics of the networks, we find that behavioral stability can be maintained without the formation of stable or recurring patterns of network activity that could be identified as neural representations. These results may represent a useful step towards a mechanistic grounding of resonance and a view of the CNS that is compatible with ecological psychology.
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Affiliation(s)
| | - Jeffrey Yoshimi
- Department of Cognitive and Information Sciences, University of California, Merced, Merced, USA
| | - William H. Warren
- Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, USA
| | - Michael J. Spivey
- Department of Cognitive and Information Sciences, University of California, Merced, Merced, USA
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Patel D, Shetty S, Acha C, Pantoja IEM, Zhao A, George D, Gracias DH. Microinstrumentation for Brain Organoids. Adv Healthc Mater 2024; 13:e2302456. [PMID: 38217546 DOI: 10.1002/adhm.202302456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Revised: 12/10/2023] [Indexed: 01/15/2024]
Abstract
Brain organoids are three-dimensional aggregates of self-organized differentiated stem cells that mimic the structure and function of human brain regions. Organoids bridge the gaps between conventional drug screening models such as planar mammalian cell culture, animal studies, and clinical trials. They can revolutionize the fields of developmental biology, neuroscience, toxicology, and computer engineering. Conventional microinstrumentation for conventional cellular engineering, such as planar microfluidic chips; microelectrode arrays (MEAs); and optical, magnetic, and acoustic techniques, has limitations when applied to three-dimensional (3D) organoids, primarily due to their limits with inherently two-dimensional geometry and interfacing. Hence, there is an urgent need to develop new instrumentation compatible with live cell culture techniques and with scalable 3D formats relevant to organoids. This review discusses conventional planar approaches and emerging 3D microinstrumentation necessary for advanced organoid-machine interfaces. Specifically, this article surveys recently developed microinstrumentation, including 3D printed and curved microfluidics, 3D and fast-scan optical techniques, buckling and self-folding MEAs, 3D interfaces for electrochemical measurements, and 3D spatially controllable magnetic and acoustic technologies relevant to two-way information transfer with brain organoids. This article highlights key challenges that must be addressed for robust organoid culture and reliable 3D spatiotemporal information transfer.
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Affiliation(s)
- Devan Patel
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Saniya Shetty
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Chris Acha
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Itzy E Morales Pantoja
- Center for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, 21205, USA
| | - Alice Zhao
- Department of Biology, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Derosh George
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - David H Gracias
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
- Department of Chemistry, Johns Hopkins University, Baltimore, MD, 21218, USA
- Department of Materials Science and Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
- Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD, 21218, USA
- Sidney Kimmel Comprehensive Cancer Center (SKCCC), Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
- Center for MicroPhysiological Systems (MPS), Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
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8
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Smirnova L, Hartung T. The Promise and Potential of Brain Organoids. Adv Healthc Mater 2024; 13:e2302745. [PMID: 38252094 DOI: 10.1002/adhm.202302745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Revised: 12/22/2023] [Indexed: 01/23/2024]
Abstract
Brain organoids are 3D in vitro culture systems derived from human pluripotent stem cells that self-organize to model features of the (developing) human brain. This review examines the techniques behind organoid generation, their current and potential applications, and future directions for the field. Brain organoids possess complex architecture containing various neural cell types, synapses, and myelination. They have been utilized for toxicology testing, disease modeling, infection studies, personalized medicine, and gene-environment interaction studies. An emerging concept termed Organoid Intelligence (OI) combines organoids with artificial intelligence systems to generate learning and memory, with the goals of modeling cognition and enabling biological computing applications. Brain organoids allow neuroscience studies not previously achievable with traditional techniques, and have the potential to transform disease modeling, drug development, and the understanding of human brain development and disorders. The aspirational vision of OI parallels the origins of artificial intelligence, and efforts are underway to map a roadmap toward its realization. In summary, brain organoids constitute a disruptive technology that is rapidly advancing and gaining traction across multiple disciplines.
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Affiliation(s)
- Lena Smirnova
- Center for Alternatives to Animal Testing (CAAT), Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, 615 N Wolfe St, Baltimore, MD, 21205, USA
| | - Thomas Hartung
- Center for Alternatives to Animal Testing (CAAT), Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, 615 N Wolfe St, Baltimore, MD, 21205, USA
- CAAT-Europe, University of Konstanz, Universitätsstr. 10, 78464, Konstanz, BW, Germany
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9
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Hamburg S, Jimenez Rodriguez A, Htet A, Di Nuovo A. Active Inference for Learning and Development in Embodied Neuromorphic Agents. ENTROPY (BASEL, SWITZERLAND) 2024; 26:582. [PMID: 39056944 PMCID: PMC11276484 DOI: 10.3390/e26070582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/27/2024] [Revised: 06/23/2024] [Accepted: 06/27/2024] [Indexed: 07/28/2024]
Abstract
Taking inspiration from humans can help catalyse embodied AI solutions for important real-world applications. Current human-inspired tools include neuromorphic systems and the developmental approach to learning. However, this developmental neurorobotics approach is currently lacking important frameworks for human-like computation and learning. We propose that human-like computation is inherently embodied, with its interface to the world being neuromorphic, and its learning processes operating across different timescales. These constraints necessitate a unified framework: active inference, underpinned by the free energy principle (FEP). Herein, we describe theoretical and empirical support for leveraging this framework in embodied neuromorphic agents with autonomous mental development. We additionally outline current implementation approaches (including toolboxes) and challenges, and we provide suggestions for next steps to catalyse this important field.
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Affiliation(s)
- Sarah Hamburg
- Department of Computing, Sheffield Hallam University, Sheffield S1 1WB, UK; (A.J.R.); (A.H.); (A.D.N.)
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10
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Kataoka M, Lee TL, Sawai T. Human Brain Organoid Research and Applications: Where and How to Meet Legal Challenges? JOURNAL OF BIOETHICAL INQUIRY 2024:10.1007/s11673-024-10349-9. [PMID: 38969917 DOI: 10.1007/s11673-024-10349-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 02/23/2024] [Indexed: 07/07/2024]
Abstract
An ethical and legal framework is needed to regulate the rapidly developing human brain organoid research field properly. However, considering the legal issues involved in human brain organoid research remains underdeveloped and scattered. This article reviews the legal issues of human brain organoid research, grouping them into the following five broad themes: (1) consciousness, (2) legal status, (3) consent, (4) ownership, and (5) transplantation. The issues in each topic include both the urgent (e.g., appropriate forms of consent) and the speculative (e.g., protection of conscious human brain organoids). Therefore, we have attempted to be as explicit as possible about the timescale within which each issue will be realized and to prioritize each. Examining these issues has revealed legal issues specific to human brain organoid research and issues common to research in other fields. Further discussion of human brain organoid research from a legal perspective is needed in the future, considering discussions in related fields.
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Affiliation(s)
- M Kataoka
- Graduate School of Humanities and Social Sciences, Hiroshima University, Higashi-Hiroshima, Japan
| | - T-L Lee
- Graduate Institute of Health and Biotechnology Law, Taipei Medical University, Taipei, Taiwan
| | - T Sawai
- Graduate School of Humanities and Social Sciences, Hiroshima University, Higashi-Hiroshima, Japan.
- Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto, Japan.
- Centre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
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Zhang K, Deng Y, Liu Y, Luo J, Glidle A, Cooper JM, Xu S, Yang Y, Lv S, Xu Z, Wu Y, Sha L, Xu Q, Yin H, Cai X. Investigating Communication Dynamics in Neuronal Network using 3D Gold Microelectrode Arrays. ACS NANO 2024; 18:17162-17174. [PMID: 38902594 DOI: 10.1021/acsnano.4c03983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/22/2024]
Abstract
Although in vitro neuronal network models hold great potential for advancing neuroscience research, with the capacity to provide fundamental insights into mechanisms underlying neuronal functions, the dynamics of cell communication within such networks remain poorly understood. Here, we develop a customizable, polymer modified three-dimensional gold microelectrode array with sufficient stability for high signal-to-noise, long-term, neuronal recording of cultured networks. By using directed spatial and temporal patterns of electrical stimulation of cells to explore synaptic-based communication, we monitored cell network dynamics over 3 weeks, quantifying communication capability using correlation heatmaps and mutual information networks. Analysis of synaptic delay and signal speed between cells enabled us to establish a communication connectivity model. We anticipate that our discoveries of the dynamic changes in communication across the neuronal network will provide a valuable tool for future studies in understanding health and disease as well as in developing effective platforms for evaluating therapies.
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Affiliation(s)
- Kui Zhang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute,, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yu Deng
- State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100005, China
| | - Yaoyao Liu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute,, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jinping Luo
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute,, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Andrew Glidle
- James Watt School of Engineering, University of Glasgow, Glasgow G12 8LT, United Kingdom
| | - Jonathan M Cooper
- James Watt School of Engineering, University of Glasgow, Glasgow G12 8LT, United Kingdom
| | - Shihong Xu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute,, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yan Yang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute,, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shiya Lv
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute,, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhaojie Xu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute,, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yirong Wu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute,, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Longzhe Sha
- State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100005, China
| | - Qi Xu
- State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100005, China
| | - Huabing Yin
- James Watt School of Engineering, University of Glasgow, Glasgow G12 8LT, United Kingdom
| | - Xinxia Cai
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute,, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
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12
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Berjaoui C, Kachouh C, Joumaa S, Hussein Ghayyad M, Abate Bekele B, Ajirenike R, Al Maaz Z, Awde S, Wojtara M, Nazir A, Uwishema O. Neuroinflammation-on-a-chip for multiple sclerosis research: a narrative review. Ann Med Surg (Lond) 2024; 86:4053-4059. [PMID: 38989179 PMCID: PMC11230822 DOI: 10.1097/ms9.0000000000002231] [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: 09/26/2023] [Accepted: 05/19/2024] [Indexed: 07/12/2024] Open
Abstract
Introduction Multiple sclerosis (MS) is a chronic inflammatory condition that impacts the central nervous system. It is distinguished by processes like demyelination, gliosis, neuro-axonal harm, and inflammation. The prevailing theory suggests that MS originates from an immune response directed against the body's own antigens within the central nervous system. Aim The main aim of this research paper "Neuroinflammation-on-a-Chip" for studying multiple sclerosis is to enhance our comprehension of MS development, demonstrate the application of cutting-edge technology, and potentially provide valuable insights for therapeutic approaches. Methods The available literature for this Narrative Review was searched on various bibliographic databases, PubMed, NCBI, and many other medical references using an individually verified, prespecified approach. Studies regarding the significance of MS and its neuroinflammatory pathogenesis in addition to the development and optimization of neuroinflammatory-on-a-chip and the advancement in innovations in this field have been reviewed in this research for a better understanding of "Neuroinflammation-on-a-chip for multiple sclerosis". The level of evidence of the included studies was considered as per the Centre for Evidence-Based Medicine recommendations. Results Several studies have indicated that the brain-chip model closely mimics cortical brain tissue compared to commonly used conventional cell culture methods like the Transwell culture system. Additionally, these studies have clearly demonstrated that further research using brain chips has the potential to enhance our understanding of the molecular mechanisms and roles of blood-brain barrier (BBB) transporters in both normal and disease conditions. Conclusion Understanding neuroinflammation processes remains essential to establish new MS treatments approaches. The utilization of brain chips promises to advance our understanding of the molecular processes involving BBB transporters, both in normal and diseased states. Further research needs to be addressed in order to enhance the performance and understanding of neuroinflammation on a chip, hence aiming to provide more effective treatments for all CNS diseases.
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Affiliation(s)
- Christin Berjaoui
- Oli Health Magazine Organization, Research, and Education, Kigali, Rwanda
- Faculty of Medicine, Beirut Arab University
| | - Charbel Kachouh
- Oli Health Magazine Organization, Research, and Education, Kigali, Rwanda
- Faculty of Medicine, Saint-Joseph University
| | - Safaa Joumaa
- Oli Health Magazine Organization, Research, and Education, Kigali, Rwanda
- Faculty of Medical Science, Lebanese University, Beirut, Lebanon
| | - Mohammad Hussein Ghayyad
- Oli Health Magazine Organization, Research, and Education, Kigali, Rwanda
- Faculty of Medicine, Beirut Arab University
| | - Bisrat Abate Bekele
- Oli Health Magazine Organization, Research, and Education, Kigali, Rwanda
- College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia
| | - Rita Ajirenike
- Oli Health Magazine Organization, Research, and Education, Kigali, Rwanda
- Department of Internal Medicine, Rivers State University Teaching Hospital, Rivers State, Nigeria
| | - Zeina Al Maaz
- Oli Health Magazine Organization, Research, and Education, Kigali, Rwanda
- Faculty of Medicine, Beirut Arab University
| | - Sara Awde
- Oli Health Magazine Organization, Research, and Education, Kigali, Rwanda
- Faculty of Medicine, Beirut Arab University
| | - Magda Wojtara
- Oli Health Magazine Organization, Research, and Education, Kigali, Rwanda
- University of Michigan Medical School, Ann Arbor, MI
| | - Abubakar Nazir
- Oli Health Magazine Organization, Research, and Education, Kigali, Rwanda
- Department of Medicine, King Edward Medical University, Lahore, Pakistan
| | - Olivier Uwishema
- Oli Health Magazine Organization, Research, and Education, Kigali, Rwanda
- Clinton Global Initiative University, New York, NY, USA
- Faculty of Medicine, Karadeniz Technical University, Trabzon, Turkey
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13
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Wyle Y, Lu N, Hepfer J, Sayal R, Martinez T, Wang A. The Role of Biophysical Factors in Organ Development: Insights from Current Organoid Models. Bioengineering (Basel) 2024; 11:619. [PMID: 38927855 PMCID: PMC11200479 DOI: 10.3390/bioengineering11060619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Revised: 05/26/2024] [Accepted: 06/12/2024] [Indexed: 06/28/2024] Open
Abstract
Biophysical factors play a fundamental role in human embryonic development. Traditional in vitro models of organogenesis focused on the biochemical environment and did not consider the effects of mechanical forces on developing tissue. While most human tissue has a Young's modulus in the low kilopascal range, the standard cell culture substrate, plasma-treated polystyrene, has a Young's modulus of 3 gigapascals, making it 10,000-100,000 times stiffer than native tissues. Modern in vitro approaches attempt to recapitulate the biophysical niche of native organs and have yielded more clinically relevant models of human tissues. Since Clevers' conception of intestinal organoids in 2009, the field has expanded rapidly, generating stem-cell derived structures, which are transcriptionally similar to fetal tissues, for nearly every organ system in the human body. For this reason, we conjecture that organoids will make their first clinical impact in fetal regenerative medicine as the structures generated ex vivo will better match native fetal tissues. Moreover, autologously sourced transplanted tissues would be able to grow with the developing embryo in a dynamic, fetal environment. As organoid technologies evolve, the resultant tissues will approach the structure and function of adult human organs and may help bridge the gap between preclinical drug candidates and clinically approved therapeutics. In this review, we discuss roles of tissue stiffness, viscoelasticity, and shear forces in organ formation and disease development, suggesting that these physical parameters should be further integrated into organoid models to improve their physiological relevance and therapeutic applicability. It also points to the mechanotransductive Hippo-YAP/TAZ signaling pathway as a key player in the interplay between extracellular matrix stiffness, cellular mechanics, and biochemical pathways. We conclude by highlighting how frontiers in physics can be applied to biology, for example, how quantum entanglement may be applied to better predict spontaneous DNA mutations. In the future, contemporary physical theories may be leveraged to better understand seemingly stochastic events during organogenesis.
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Affiliation(s)
- Yofiel Wyle
- Department of Surgery, School of Medicine, University of California-Davis, Sacramento, CA 95817, USA; (Y.W.); (N.L.); (J.H.); (R.S.); (T.M.)
- Institute for Pediatric Regenerative Medicine, Shriners Children’s, Sacramento, CA 95817, USA
| | - Nathan Lu
- Department of Surgery, School of Medicine, University of California-Davis, Sacramento, CA 95817, USA; (Y.W.); (N.L.); (J.H.); (R.S.); (T.M.)
| | - Jason Hepfer
- Department of Surgery, School of Medicine, University of California-Davis, Sacramento, CA 95817, USA; (Y.W.); (N.L.); (J.H.); (R.S.); (T.M.)
| | - Rahul Sayal
- Department of Surgery, School of Medicine, University of California-Davis, Sacramento, CA 95817, USA; (Y.W.); (N.L.); (J.H.); (R.S.); (T.M.)
| | - Taylor Martinez
- Department of Surgery, School of Medicine, University of California-Davis, Sacramento, CA 95817, USA; (Y.W.); (N.L.); (J.H.); (R.S.); (T.M.)
| | - Aijun Wang
- Department of Surgery, School of Medicine, University of California-Davis, Sacramento, CA 95817, USA; (Y.W.); (N.L.); (J.H.); (R.S.); (T.M.)
- Institute for Pediatric Regenerative Medicine, Shriners Children’s, Sacramento, CA 95817, USA
- Department of Biomedical Engineering, University of California-Davis, Davis, CA 95616, USA
- Center for Surgical Bioengineering, Department of Surgery, School of Medicine, University of California, Davis, 4625 2nd Ave., Research II, Suite 3005, Sacramento, CA 95817, USA
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14
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Kelly AR, Glover DJ. Information Transmission through Biotic-Abiotic Interfaces to Restore or Enhance Human Function. ACS APPLIED BIO MATERIALS 2024; 7:3605-3628. [PMID: 38729914 DOI: 10.1021/acsabm.4c00435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/12/2024]
Abstract
Advancements in reliable information transfer across biotic-abiotic interfaces have enabled the restoration of lost human function. For example, communication between neuronal cells and electrical devices restores the ability to walk to a tetraplegic patient and vision to patients blinded by retinal disease. These impactful medical achievements are aided by tailored biotic-abiotic interfaces that maximize information transfer fidelity by considering the physical properties of the underlying biological and synthetic components. This Review develops a modular framework to define and describe the engineering of biotic and abiotic components as well as the design of interfaces to facilitate biotic-abiotic information transfer using light or electricity. Delineating the properties of the biotic, interface, and abiotic components that enable communication can serve as a guide for future research in this highly interdisciplinary field. Application of synthetic biology to engineer light-sensitive proteins has facilitated the control of neural signaling and the restoration of rudimentary vision after retinal blindness. Electrophysiological methodologies that use brain-computer interfaces and stimulating implants to bypass spinal column injuries have led to the rehabilitation of limb movement and walking ability. Cellular interfacing methodologies and on-chip learning capability have been made possible by organic transistors that mimic the information processing capacity of neurons. The collaboration of molecular biologists, material scientists, and electrical engineers in the emerging field of biotic-abiotic interfacing will lead to the development of prosthetics capable of responding to thought and experiencing touch sensation via direct integration into the human nervous system. Further interdisciplinary research will improve electrical and optical interfacing technologies for the restoration of vision, offering greater visual acuity and potentially color vision in the near future.
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Affiliation(s)
- Alexander R Kelly
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW 2052, Australia
| | - Dominic J Glover
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW 2052, Australia
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15
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Ratwatte A, Somathilaka S, Balasubramaniam S, Gilad AA. Nonlinear classifiers for wet-neuromorphic computing using gene regulatory neural network. BIOPHYSICAL REPORTS 2024; 4:100158. [PMID: 38848994 PMCID: PMC11231448 DOI: 10.1016/j.bpr.2024.100158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 03/20/2024] [Accepted: 05/31/2024] [Indexed: 06/09/2024]
Abstract
The gene regulatory network (GRN) of biological cells governs a number of key functionalities that enable them to adapt and survive through different environmental conditions. Close observation of the GRN shows that the structure and operational principles resemble an artificial neural network (ANN), which can pave the way for the development of wet-neuromorphic computing systems. Genes are integrated into gene-perceptrons with transcription factors (TFs) as input, where the TF concentration relative to half-maximal RNA concentration and gene product copy number influences transcription and translation via weighted multiplication before undergoing a nonlinear activation function. This process yields protein concentration as the output, effectively turning the entire GRN into a gene regulatory neural network (GRNN). In this paper, we establish nonlinear classifiers for molecular machine learning using the inherent sigmoidal nonlinear behavior of gene expression. The eigenvalue-based stability analysis, tailored to system parameters, confirms maximum-stable concentration levels, minimizing concentration fluctuations and computational errors. Given the significance of the stabilization phase in GRNN computing and the dynamic nature of the GRN, alongside potential changes in system parameters, we utilize the Lyapunov stability theorem for temporal stability analysis. Based on this GRN-to-GRNN mapping and stability analysis, three classifiers are developed utilizing two generic multilayer sub-GRNNs and a sub-GRNN extracted from the Escherichia coli GRN. Our findings also reveal the adaptability of different sub-GRNNs to suit different application requirements.
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Affiliation(s)
- Adrian Ratwatte
- School of Computing, University of Nebraska-Lincoln, 104 Schorr Center, Lincoln, Nebraska, USA.
| | - Samitha Somathilaka
- School of Computing, University of Nebraska-Lincoln, 104 Schorr Center, Lincoln, Nebraska, USA; VistaMilk Research Centre, Walton Institute for Information and Communication Systems Science, South East Technological University, Waterford, Ireland
| | | | - Assaf A Gilad
- Department of Chemical Engineering and Materials Science, Michigan State University, East Lansing, Michigan, USA; Department of Radiology, Michigan State University, East Lansing, Michigan, USA
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16
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Sun Y, Xiao Z, Chen B, Zhao Y, Dai J. Advances in Material-Assisted Electromagnetic Neural Stimulation. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2400346. [PMID: 38594598 DOI: 10.1002/adma.202400346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 03/26/2024] [Indexed: 04/11/2024]
Abstract
Bioelectricity plays a crucial role in organisms, being closely connected to neural activity and physiological processes. Disruptions in the nervous system can lead to chaotic ionic currents at the injured site, causing disturbances in the local cellular microenvironment, impairing biological pathways, and resulting in a loss of neural functions. Electromagnetic stimulation has the ability to generate internal currents, which can be utilized to counter tissue damage and aid in the restoration of movement in paralyzed limbs. By incorporating implanted materials, electromagnetic stimulation can be targeted more accurately, thereby significantly improving the effectiveness and safety of such interventions. Currently, there have been significant advancements in the development of numerous promising electromagnetic stimulation strategies with diverse materials. This review provides a comprehensive summary of the fundamental theories, neural stimulation modulating materials, material application strategies, and pre-clinical therapeutic effects associated with electromagnetic stimulation for neural repair. It offers a thorough analysis of current techniques that employ materials to enhance electromagnetic stimulation, as well as potential therapeutic strategies for future applications.
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Affiliation(s)
- Yuting Sun
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhifeng Xiao
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Bing Chen
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Yannan Zhao
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Jianwu Dai
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Tianjin Key Laboratory of Biomedical Materials, Institute of Biomedical Engineering, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, 300192, China
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17
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Hoffmann C, Cho E, Zalesky A, Di Biase MA. From pixels to connections: exploring in vitro neuron reconstruction software for network graph generation. Commun Biol 2024; 7:571. [PMID: 38750282 PMCID: PMC11096190 DOI: 10.1038/s42003-024-06264-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 04/29/2024] [Indexed: 05/18/2024] Open
Abstract
Digital reconstruction has been instrumental in deciphering how in vitro neuron architecture shapes information flow. Emerging approaches reconstruct neural systems as networks with the aim of understanding their organization through graph theory. Computational tools dedicated to this objective build models of nodes and edges based on key cellular features such as somata, axons, and dendrites. Fully automatic implementations of these tools are readily available, but they may also be purpose-built from specialized algorithms in the form of multi-step pipelines. Here we review software tools informing the construction of network models, spanning from noise reduction and segmentation to full network reconstruction. The scope and core specifications of each tool are explicitly defined to assist bench scientists in selecting the most suitable option for their microscopy dataset. Existing tools provide a foundation for complete network reconstruction, however more progress is needed in establishing morphological bases for directed/weighted connectivity and in software validation.
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Affiliation(s)
- Cassandra Hoffmann
- Systems Neuroscience Lab, Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Parkville, Australia.
| | - Ellie Cho
- Biological Optical Microscopy Platform, University of Melbourne, Parkville, Australia
| | - Andrew Zalesky
- Systems Neuroscience Lab, Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Parkville, Australia
- Department of Biomedical Engineering, The University of Melbourne, Parkville, Australia
| | - Maria A Di Biase
- Systems Neuroscience Lab, Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Parkville, Australia
- Stem Cell Disease Modelling Lab, Department of Anatomy and Physiology, The University of Melbourne, Parkville, Australia
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
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18
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Han X, Cai C, Deng W, Shi Y, Li L, Wang C, Zhang J, Rong M, Liu J, Fang B, He H, Liu X, Deng C, He X, Cao X. Landscape of human organoids: Ideal model in clinics and research. Innovation (N Y) 2024; 5:100620. [PMID: 38706954 PMCID: PMC11066475 DOI: 10.1016/j.xinn.2024.100620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 03/29/2024] [Indexed: 05/07/2024] Open
Abstract
In the last decade, organoid research has entered a golden era, signifying a pivotal shift in the biomedical landscape. The year 2023 marked a milestone with the publication of thousands of papers in this arena, reflecting exponential growth. However, amid this burgeoning expansion, a comprehensive and accurate overview of the field has been conspicuously absent. Our review is intended to bridge this gap, providing a panoramic view of the rapidly evolving organoid landscape. We meticulously analyze the organoid field from eight distinctive vantage points, harnessing our rich experience in academic research, industrial application, and clinical practice. We present a deep exploration of the advances in organoid technology, underpinned by our long-standing involvement in this arena. Our narrative traverses the historical genesis of organoids and their transformative impact across various biomedical sectors, including oncology, toxicology, and drug development. We delve into the synergy between organoids and avant-garde technologies such as synthetic biology and single-cell omics and discuss their pivotal role in tailoring personalized medicine, enhancing high-throughput drug screening, and constructing physiologically pertinent disease models. Our comprehensive analysis and reflective discourse provide a deep dive into the existing landscape and emerging trends in organoid technology. We spotlight technological innovations, methodological evolution, and the broadening spectrum of applications, emphasizing the revolutionary influence of organoids in personalized medicine, oncology, drug discovery, and other fields. Looking ahead, we cautiously anticipate future developments in the field of organoid research, especially its potential implications for personalized patient care, new avenues of drug discovery, and clinical research. We trust that our comprehensive review will be an asset for researchers, clinicians, and patients with keen interest in personalized medical strategies. We offer a broad view of the present and prospective capabilities of organoid technology, encompassing a wide range of current and future applications. In summary, in this review we attempt a comprehensive exploration of the organoid field. We offer reflections, summaries, and projections that might be useful for current researchers and clinicians, and we hope to contribute to shaping the evolving trajectory of this dynamic and rapidly advancing field.
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Affiliation(s)
- Xinxin Han
- Organ Regeneration X Lab, Lisheng East China Institute of Biotechnology, Peking University, Jiangsu 226200, China
- Shanghai Lisheng Biotech, Shanghai 200092, China
| | - Chunhui Cai
- Shanghai Lisheng Biotech, Shanghai 200092, China
| | - Wei Deng
- LongHua Hospital, Shanghai University of Traditional Chinese Medicine, 725 Wanping South Road, Xuhui District, Shanghai 200032, China
- Department of Oncology, Shanghai Ninth People’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200125, China
| | - Yanghua Shi
- Shanghai Lisheng Biotech, Shanghai 200092, China
| | - Lanyang Li
- Shanghai Lisheng Biotech, Shanghai 200092, China
| | - Chen Wang
- Shanghai Lisheng Biotech, Shanghai 200092, China
| | - Jian Zhang
- Shanghai Lisheng Biotech, Shanghai 200092, China
| | - Mingjie Rong
- Shanghai Lisheng Biotech, Shanghai 200092, China
| | - Jiping Liu
- Shanghai Lisheng Biotech, Shanghai 200092, China
| | - Bangjiang Fang
- LongHua Hospital, Shanghai University of Traditional Chinese Medicine, 725 Wanping South Road, Xuhui District, Shanghai 200032, China
| | - Hua He
- Department of Neurosurgery, Third Affiliated Hospital, Naval Medical University, Shanghai 200438, China
| | - Xiling Liu
- Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, Shanghai 200063, China
| | - Chuxia Deng
- Cancer Center, Faculty of Health Sciences, University of Macau, Taipa, Macau SAR, China
- Ministry of Education Frontiers Science Center for Precision Oncology, University of Macau, Taipa, Macau SAR 999078, China
| | - Xiao He
- CAS Key Lab for Biomedical Effects of Nanomaterials and Nanosafety, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049, China
| | - Xin Cao
- Zhongshan Hospital Institute of Clinical Science, Fudan University Shanghai Medical College, Shanghai 200032, China
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19
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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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20
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Cerneckis J, Cai H, Shi Y. Induced pluripotent stem cells (iPSCs): molecular mechanisms of induction and applications. Signal Transduct Target Ther 2024; 9:112. [PMID: 38670977 PMCID: PMC11053163 DOI: 10.1038/s41392-024-01809-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 03/09/2024] [Accepted: 03/17/2024] [Indexed: 04/28/2024] Open
Abstract
The induced pluripotent stem cell (iPSC) technology has transformed in vitro research and holds great promise to advance regenerative medicine. iPSCs have the capacity for an almost unlimited expansion, are amenable to genetic engineering, and can be differentiated into most somatic cell types. iPSCs have been widely applied to model human development and diseases, perform drug screening, and develop cell therapies. In this review, we outline key developments in the iPSC field and highlight the immense versatility of the iPSC technology for in vitro modeling and therapeutic applications. We begin by discussing the pivotal discoveries that revealed the potential of a somatic cell nucleus for reprogramming and led to successful generation of iPSCs. We consider the molecular mechanisms and dynamics of somatic cell reprogramming as well as the numerous methods available to induce pluripotency. Subsequently, we discuss various iPSC-based cellular models, from mono-cultures of a single cell type to complex three-dimensional organoids, and how these models can be applied to elucidate the mechanisms of human development and diseases. We use examples of neurological disorders, coronavirus disease 2019 (COVID-19), and cancer to highlight the diversity of disease-specific phenotypes that can be modeled using iPSC-derived cells. We also consider how iPSC-derived cellular models can be used in high-throughput drug screening and drug toxicity studies. Finally, we discuss the process of developing autologous and allogeneic iPSC-based cell therapies and their potential to alleviate human diseases.
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Affiliation(s)
- Jonas Cerneckis
- Department of Neurodegenerative Diseases, Beckman Research Institute of City of Hope, Duarte, CA, 91010, USA
- Irell & Manella Graduate School of Biological Sciences, Beckman Research Institute of City of Hope, Duarte, CA, 91010, USA
| | - Hongxia Cai
- Department of Neurodegenerative Diseases, Beckman Research Institute of City of Hope, Duarte, CA, 91010, USA
| | - Yanhong Shi
- Department of Neurodegenerative Diseases, Beckman Research Institute of City of Hope, Duarte, CA, 91010, USA.
- Irell & Manella Graduate School of Biological Sciences, Beckman Research Institute of City of Hope, Duarte, CA, 91010, USA.
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21
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Zhang Z, Xu F. An Overview of the Free Energy Principle and Related Research. Neural Comput 2024; 36:963-1021. [PMID: 38457757 DOI: 10.1162/neco_a_01642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 11/20/2023] [Indexed: 03/10/2024]
Abstract
The free energy principle and its corollary, the active inference framework, serve as theoretical foundations in the domain of neuroscience, explaining the genesis of intelligent behavior. This principle states that the processes of perception, learning, and decision making-within an agent-are all driven by the objective of "minimizing free energy," evincing the following behaviors: learning and employing a generative model of the environment to interpret observations, thereby achieving perception, and selecting actions to maintain a stable preferred state and minimize the uncertainty about the environment, thereby achieving decision making. This fundamental principle can be used to explain how the brain processes perceptual information, learns about the environment, and selects actions. Two pivotal tenets are that the agent employs a generative model for perception and planning and that interaction with the world (and other agents) enhances the performance of the generative model and augments perception. With the evolution of control theory and deep learning tools, agents based on the FEP have been instantiated in various ways across different domains, guiding the design of a multitude of generative models and decision-making algorithms. This letter first introduces the basic concepts of the FEP, followed by its historical development and connections with other theories of intelligence, and then delves into the specific application of the FEP to perception and decision making, encompassing both low-dimensional simple situations and high-dimensional complex situations. It compares the FEP with model-based reinforcement learning to show that the FEP provides a better objective function. We illustrate this using numerical studies of Dreamer3 by adding expected information gain into the standard objective function. In a complementary fashion, existing reinforcement learning, and deep learning algorithms can also help implement the FEP-based agents. Finally, we discuss the various capabilities that agents need to possess in complex environments and state that the FEP can aid agents in acquiring these capabilities.
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Affiliation(s)
- Zhengquan Zhang
- Key Laboratory of Information Science of Electromagnetic Waves, Fudan University, Shanghai, P.R.C.
| | - Feng Xu
- Key Laboratory of Information Science of Electromagnetic Waves, Fudan University, Shanghai, P.R.C.
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22
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Mencattini A, Daprati E, Della-Morte D, Guadagni F, Sangiuolo F, Martinelli E. Assembloid learning: opportunities and challenges for personalized approaches to brain functioning in health and disease. Front Artif Intell 2024; 7:1385871. [PMID: 38708094 PMCID: PMC11066156 DOI: 10.3389/frai.2024.1385871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Accepted: 04/08/2024] [Indexed: 05/07/2024] Open
Affiliation(s)
- Arianna Mencattini
- Department of Electronic Engineering, University of Rome Tor Vergata, Rome, Italy
- Interdisciplinary Center of Advanced Study of Organ-on-Chip and Lab-on-Chip Applications (IC-LOC), University of Rome Tor Vergata, Rome, Italy
| | - Elena Daprati
- Department of System Medicine and Centro di Biomedicina Spaziale (CBMS), University of Rome Tor Vergata, Rome, Italy
| | - David Della-Morte
- Interdisciplinary Center of Advanced Study of Organ-on-Chip and Lab-on-Chip Applications (IC-LOC), University of Rome Tor Vergata, Rome, Italy
- San Raffaele Rome University, Rome, Italy
| | - Fiorella Guadagni
- San Raffaele Rome University, Rome, Italy
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) San Raffaele, Rome, Italy
| | - Federica Sangiuolo
- Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy
| | - Eugenio Martinelli
- Department of Electronic Engineering, University of Rome Tor Vergata, Rome, Italy
- Interdisciplinary Center of Advanced Study of Organ-on-Chip and Lab-on-Chip Applications (IC-LOC), University of Rome Tor Vergata, Rome, Italy
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23
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Kagan BJ, Loeffler A, Boyd JL, Savulescu J. Embodied Neural Systems Can Enable Iterative Investigations of Morally Relevant States. J Neurosci 2024; 44:e0431242024. [PMID: 38599798 PMCID: PMC11007307 DOI: 10.1523/jneurosci.0431-24.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2024] [Accepted: 03/07/2024] [Indexed: 04/12/2024] Open
Affiliation(s)
- Brett J Kagan
- Cortical Labs, Melbourne, 3000 Victoria, Australia
- Department of Biochemistry and Pharmacology, University of Melbourne, Parkville, 3010 Victoria, Australia
| | | | - J Lomax Boyd
- Berman Institute of Bioethics, Johns Hopkins University, Baltimore, Maryland 21205
| | - Julian Savulescu
- Murdoch Children's Research Institute, Melbourne, 3052 Victoria, Australia
- Melbourne Law School, University of Melbourne, Melbourne, 3053 Victoria, Australia
- Centre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119210, Singapore
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24
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Li G, LeFebre R, Starman A, Chappell P, Mugler A, Sun B. The collective dynamics of frustrated biological neuron networks. RESEARCH SQUARE 2024:rs.3.rs-4006823. [PMID: 38645115 PMCID: PMC11030517 DOI: 10.21203/rs.3.rs-4006823/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
To maintain normal functionality, it is necessary for a multicellular organism to generate robust responses to external temporal signals. However, the underlying mechanisms to coordinate the collective dynamics of cells remain poorly understood. Here we study the calcium activity of micropatterned biological neuron networks excited by periodic ATP stimuli. Combining quantitative experiments, physical and biological manipulation of cells, as well as mathematical modeling, we show that isolated cells in a network become more synchronized at longer period of stimuli through noise cancellation. However, slowly varying external signal also increases gap junction coupling between connected nodes in the network; and gap junction mediated communication may destroy network synchronization due to special nonlinear bifurcations exhibited by the excitable dynamics of neuronal cells. Based on our results, we propose that a biological neuron network supported by gap junctional communication encodes external temporal signals in its network dynamics. A sparely connected network approaches synchronization as input signal slows down, whereas a highly connected network enters dynamic frustration in the same situation.
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Affiliation(s)
- Guanyu Li
- Oregon State University, Department of Physics, Corvallis, 97331, USA
| | - Ryan LeFebre
- Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA 15260
| | - Alia Starman
- Department of Biomedical Sciences, Carlson College of Veterinary Medicine, Oregon State University, Corvallis, OR 97331
| | - Patrick Chappell
- Department of Biomedical Sciences, Carlson College of Veterinary Medicine, Oregon State University, Corvallis, OR 97331
| | - Andrew Mugler
- Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, PA 15260
| | - Bo Sun
- Oregon State University, Department of Physics, Corvallis, 97331, USA
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25
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Boyd JL. Moral considerability of brain organoids from the perspective of computational architecture. OXFORD OPEN NEUROSCIENCE 2024; 3:kvae004. [PMID: 38595940 PMCID: PMC10995847 DOI: 10.1093/oons/kvae004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 02/06/2024] [Accepted: 02/27/2024] [Indexed: 04/11/2024]
Abstract
Human brain organoids equipped with complex cytoarchitecture and closed-loop feedback from virtual environments could provide insights into neural mechanisms underlying cognition. Yet organoids with certain cognitive capacities might also merit moral consideration. A precautionary approach has been proposed to address these ethical concerns by focusing on the epistemological question of whether organoids possess neural structures for morally-relevant capacities that bear resemblance to those found in human brains. Critics challenge this similarity approach on philosophical, scientific, and practical grounds but do so without a suitable alternative. Here, I introduce an architectural approach that infers the potential for cognitive-like processing in brain organoids based on the pattern of information flow through the system. The kind of computational architecture acquired by an organoid then informs the kind of cognitive capacities that could, theoretically, be supported and empirically investigated. The implications of this approach for the moral considerability of brain organoids are discussed.
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Affiliation(s)
- J Lomax Boyd
- Berman Institute of Bioethics, Johns Hopkins University, 1809 Ashland Ave, Baltimore, MD 21205, USA
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Li Y, Wang J, Song SR, Lv SQ, Qin JH, Yu SC. Models for evaluating glioblastoma invasion along white matter tracts. Trends Biotechnol 2024; 42:293-309. [PMID: 37806896 DOI: 10.1016/j.tibtech.2023.09.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 08/31/2023] [Accepted: 09/18/2023] [Indexed: 10/10/2023]
Abstract
White matter tracts (WMs) are one of the main invasion paths of glioblastoma multiforme (GBM). The lack of ideal research models hinders our understanding of the details and mechanisms of GBM invasion along WMs. To date, many potential in vitro models have been reported; nerve fiber culture models and nanomaterial models are biocompatible, and the former have electrically active neurons. Brain slice culture models, organoid models, and microfluidic chip models can simulate the real brain and tumor microenvironment (TME), which contains a variety of cell types. These models are closer to the real in vivo environment and are helpful for further studying not only invasion along WMs by GBM, but also perineural invasion and brain metastasis by solid tumors.
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Affiliation(s)
- Yao Li
- Department of Stem Cell and Regenerative Medicine, Institute of Pathology and Southwest Cancer Center, Southwest Hospital, Chongqing 400038, China; International Joint Research Center for Precision Biotherapy, Ministry of Science and Technology, Chongqing 400038, China; Key Laboratory of Cancer Immunopathology, Ministry of Education, Chongqing 400038, China; Department of Neurosurgery, Xinqiao Hospital, Chongqing 400037, China
| | - Jun Wang
- Department of Stem Cell and Regenerative Medicine, Institute of Pathology and Southwest Cancer Center, Southwest Hospital, Chongqing 400038, China; International Joint Research Center for Precision Biotherapy, Ministry of Science and Technology, Chongqing 400038, China; Key Laboratory of Cancer Immunopathology, Ministry of Education, Chongqing 400038, China; Jin-feng Laboratory, Chongqing 401329, China
| | - Si-Rong Song
- Department of Stem Cell and Regenerative Medicine, Institute of Pathology and Southwest Cancer Center, Southwest Hospital, Chongqing 400038, China; International Joint Research Center for Precision Biotherapy, Ministry of Science and Technology, Chongqing 400038, China; Key Laboratory of Cancer Immunopathology, Ministry of Education, Chongqing 400038, China
| | - Sheng-Qing Lv
- Department of Neurosurgery, Xinqiao Hospital, Chongqing 400037, China
| | - Jian-Hua Qin
- Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Niaoning 116023, China.
| | - Shi-Cang Yu
- Department of Stem Cell and Regenerative Medicine, Institute of Pathology and Southwest Cancer Center, Southwest Hospital, Chongqing 400038, China; International Joint Research Center for Precision Biotherapy, Ministry of Science and Technology, Chongqing 400038, China; Key Laboratory of Cancer Immunopathology, Ministry of Education, Chongqing 400038, China; Jin-feng Laboratory, Chongqing 401329, China.
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Ades C, Abd MA, Hutchinson DT, Tognoli E, Du E, Wei J, Engeberg ED. Biohybrid Robotic Hand to Investigate Tactile Encoding and Sensorimotor Integration. Biomimetics (Basel) 2024; 9:78. [PMID: 38392124 PMCID: PMC10886511 DOI: 10.3390/biomimetics9020078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 01/19/2024] [Accepted: 01/22/2024] [Indexed: 02/24/2024] Open
Abstract
For people who have experienced a spinal cord injury or an amputation, the recovery of sensation and motor control could be incomplete despite noteworthy advances with invasive neural interfaces. Our objective is to explore the feasibility of a novel biohybrid robotic hand model to investigate aspects of tactile sensation and sensorimotor integration with a pre-clinical research platform. Our new biohybrid model couples an artificial hand with biological neural networks (BNN) cultured in a multichannel microelectrode array (MEA). We decoded neural activity to control a finger of the artificial hand that was outfitted with a tactile sensor. The fingertip sensations were encoded into rapidly adapting (RA) or slowly adapting (SA) mechanoreceptor firing patterns that were used to electrically stimulate the BNN. We classified the coherence between afferent and efferent electrodes in the MEA with a convolutional neural network (CNN) using a transfer learning approach. The BNN exhibited the capacity for functional specialization with the RA and SA patterns, represented by significantly different robotic behavior of the biohybrid hand with respect to the tactile encoding method. Furthermore, the CNN was able to distinguish between RA and SA encoding methods with 97.84% ± 0.65% accuracy when the BNN was provided tactile feedback, averaged across three days in vitro (DIV). This novel biohybrid research platform demonstrates that BNNs are sensitive to tactile encoding methods and can integrate robotic tactile sensations with the motor control of an artificial hand. This opens the possibility of using biohybrid research platforms in the future to study aspects of neural interfaces with minimal human risk.
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Affiliation(s)
- Craig Ades
- Department of Ocean and Mechanical Engineering, Florida Atlantic University, Boca Raton, FL 33431, USA
| | - Moaed A Abd
- Department of Ocean and Mechanical Engineering, Florida Atlantic University, Boca Raton, FL 33431, USA
| | | | - Emmanuelle Tognoli
- Center for Complex Systems and Brain Sciences, Florida Atlantic University, Boca Raton, FL 33431, USA
| | - E Du
- Department of Ocean and Mechanical Engineering, Florida Atlantic University, Boca Raton, FL 33431, USA
- Department of Biomedical Engineering, Florida Atlantic University, Boca Raton, FL 33431, USA
| | - Jianning Wei
- Center for Complex Systems and Brain Sciences, Florida Atlantic University, Boca Raton, FL 33431, USA
- Department of Biomedical Science, Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, FL 33431, USA
| | - Erik D Engeberg
- Department of Ocean and Mechanical Engineering, Florida Atlantic University, Boca Raton, FL 33431, USA
- Center for Complex Systems and Brain Sciences, Florida Atlantic University, Boca Raton, FL 33431, USA
- Department of Biomedical Engineering, Florida Atlantic University, Boca Raton, FL 33431, USA
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28
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Hartung T, Morales Pantoja IE, Smirnova L. Brain organoids and organoid intelligence from ethical, legal, and social points of view. Front Artif Intell 2024; 6:1307613. [PMID: 38249793 PMCID: PMC10796793 DOI: 10.3389/frai.2023.1307613] [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: 10/04/2023] [Accepted: 12/07/2023] [Indexed: 01/23/2024] Open
Abstract
Human brain organoids, aka cerebral organoids or earlier "mini-brains", are 3D cellular models that recapitulate aspects of the developing human brain. They show tremendous promise for advancing our understanding of neurodevelopment and neurological disorders. However, the unprecedented ability to model human brain development and function in vitro also raises complex ethical, legal, and social challenges. Organoid Intelligence (OI) describes the ongoing movement to combine such organoids with Artificial Intelligence to establish basic forms of memory and learning. This article discusses key issues regarding the scientific status and prospects of brain organoids and OI, conceptualizations of consciousness and the mind-brain relationship, ethical and legal dimensions, including moral status, human-animal chimeras, informed consent, and governance matters, such as oversight and regulation. A balanced framework is needed to allow vital research while addressing public perceptions and ethical concerns. Interdisciplinary perspectives and proactive engagement among scientists, ethicists, policymakers, and the public can enable responsible translational pathways for organoid technology. A thoughtful, proactive governance framework might be needed to ensure ethically responsible progress in this promising field.
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Affiliation(s)
- Thomas Hartung
- Center for Alternatives to Animal Testing (CAAT), Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States
- CAAT-Europe, University of Konstanz, Konstanz, Germany
| | - Itzy E. Morales Pantoja
- Center for Alternatives to Animal Testing (CAAT), Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Lena Smirnova
- Center for Alternatives to Animal Testing (CAAT), Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States
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29
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Idei H, Yamashita Y. Elucidating multifinal and equifinal pathways to developmental disorders by constructing real-world neurorobotic models. Neural Netw 2024; 169:57-74. [PMID: 37857173 DOI: 10.1016/j.neunet.2023.10.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 10/04/2023] [Accepted: 10/05/2023] [Indexed: 10/21/2023]
Abstract
Vigorous research has been conducted to accumulate biological and theoretical knowledge about neurodevelopmental disorders, including molecular, neural, computational, and behavioral characteristics; however, these findings remain fragmentary and do not elucidate integrated mechanisms. An obstacle is the heterogeneity of developmental pathways causing clinical phenotypes. Additionally, in symptom formations, the primary causes and consequences of developmental learning processes are often indistinguishable. Herein, we review developmental neurorobotic experiments tackling problems related to the dynamic and complex properties of neurodevelopmental disorders. Specifically, we focus on neurorobotic models under predictive processing lens for the study of developmental disorders. By constructing neurorobotic models with predictive processing mechanisms of learning, perception, and action, we can simulate formations of integrated causal relationships among neurodynamical, computational, and behavioral characteristics in the robot agents while considering developmental learning processes. This framework has the potential to bind neurobiological hypotheses (excitation-inhibition imbalance and functional disconnection), computational accounts (unusual encoding of uncertainty), and clinical symptoms. Developmental neurorobotic approaches may serve as a complementary research framework for integrating fragmented knowledge and overcoming the heterogeneity of neurodevelopmental disorders.
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Affiliation(s)
- Hayato Idei
- Department of Information Medicine, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo 187-8502, Japan
| | - Yuichi Yamashita
- Department of Information Medicine, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo 187-8502, Japan.
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30
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Lavazza A, Chinaia AA. Human brain organoids and their ethical issues : Navigating the moral and social challenges between hype and underestimation. EMBO Rep 2024; 25:13-16. [PMID: 38177904 PMCID: PMC10897434 DOI: 10.1038/s44319-023-00007-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Accepted: 11/10/2023] [Indexed: 01/06/2024] Open
Abstract
Recent advancements in the field are forcing scientists and neuroethicists to balance opposite concerns. Some see no risks at all while some waive red flags.
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Affiliation(s)
- Andrea Lavazza
- Department of Brain and Behavioral Sciences, University of Pavia, Piazza Botta 11, 27100, Pavia, Italy.
| | - Alice Andrea Chinaia
- MInD-MoMiLab, IMT School for Advanced Studies, Piazza San Francesco 19, 55100, Lucca, Italy
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31
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van Till SAL, Bunnik EM. The End of Personification: The Mereological Fallacy in Science Communication on Brain Organoids. THE AMERICAN JOURNAL OF BIOETHICS : AJOB 2024; 24:51-54. [PMID: 38236882 PMCID: PMC10805020 DOI: 10.1080/15265161.2023.2278564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/23/2024]
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32
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Lavekar SS, Patel MD, Montalvo-Parra MD, Krencik R. Asteroid impact: the potential of astrocytes to modulate human neural networks within organoids. Front Neurosci 2023; 17:1305921. [PMID: 38075269 PMCID: PMC10702564 DOI: 10.3389/fnins.2023.1305921] [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: 10/02/2023] [Accepted: 11/08/2023] [Indexed: 02/12/2024] Open
Abstract
Astrocytes are a vital cellular component of the central nervous system that impact neuronal function in both healthy and pathological states. This includes intercellular signals to neurons and non-neuronal cells during development, maturation, and aging that can modulate neural network formation, plasticity, and maintenance. Recently, human pluripotent stem cell-derived neural aggregate cultures, known as neurospheres or organoids, have emerged as improved experimental platforms for basic and pre-clinical neuroscience compared to traditional approaches. Here, we summarize the potential capability of using organoids to further understand the mechanistic role of astrocytes upon neural networks, including the production of extracellular matrix components and reactive signaling cues. Additionally, we discuss the application of organoid models to investigate the astrocyte-dependent aspects of neuropathological diseases and to test astrocyte-inspired technologies. We examine the shortcomings of organoid-based experimental platforms and plausible improvements made possible by cutting-edge neuroengineering technologies. These advancements are expected to enable the development of improved diagnostic strategies and high-throughput translational applications regarding neuroregeneration.
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Affiliation(s)
| | | | | | - R. Krencik
- Department of Neurosurgery, Center for Neuroregeneration, Houston Methodist Research Institute, Houston, TX, United States
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33
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Lv S, He E, Luo J, Liu Y, Liang W, Xu S, Zhang K, Yang Y, Wang M, Song Y, Wu Y, Cai X. Using Human-Induced Pluripotent Stem Cell Derived Neurons on Microelectrode Arrays to Model Neurological Disease: A Review. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2301828. [PMID: 37863819 PMCID: PMC10667858 DOI: 10.1002/advs.202301828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 09/04/2023] [Indexed: 10/22/2023]
Abstract
In situ physiological signals of in vitro neural disease models are essential for studying pathogenesis and drug screening. Currently, an increasing number of in vitro neural disease models are established using human-induced pluripotent stem cell (hiPSC) derived neurons (hiPSC-DNs) to overcome interspecific gene expression differences. Microelectrode arrays (MEAs) can be readily interfaced with two-dimensional (2D), and more recently, three-dimensional (3D) neural stem cell-derived in vitro models of the human brain to monitor their physiological activity in real time. Therefore, MEAs are emerging and useful tools to model neurological disorders and disease in vitro using human iPSCs. This is enabling a real-time window into neuronal signaling at the network scale from patient derived. This paper provides a comprehensive review of MEA's role in analyzing neural disease models established by hiPSC-DNs. It covers the significance of MEA fabrication, surface structure and modification schemes for hiPSC-DNs culturing and signal detection. Additionally, this review discusses advances in the development and use of MEA technology to study in vitro neural disease models, including epilepsy, autism spectrum developmental disorder (ASD), and others established using hiPSC-DNs. The paper also highlights the application of MEAs combined with hiPSC-DNs in detecting in vitro neurotoxic substances. Finally, the future development and outlook of multifunctional and integrated devices for in vitro medical diagnostics and treatment are discussed.
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Affiliation(s)
- Shiya Lv
- State Key Laboratory of Transducer TechnologyAerospace Information Research InstituteChinese Academy of SciencesBeijing100190China
- University of Chinese Academy of SciencesBeijing100049China
| | - Enhui He
- State Key Laboratory of Transducer TechnologyAerospace Information Research InstituteChinese Academy of SciencesBeijing100190China
- University of Chinese Academy of SciencesBeijing100049China
- The State Key Lab of Brain‐Machine IntelligenceZhejiang UniversityHangzhou321100China
| | - Jinping Luo
- State Key Laboratory of Transducer TechnologyAerospace Information Research InstituteChinese Academy of SciencesBeijing100190China
- University of Chinese Academy of SciencesBeijing100049China
| | - Yaoyao Liu
- State Key Laboratory of Transducer TechnologyAerospace Information Research InstituteChinese Academy of SciencesBeijing100190China
- University of Chinese Academy of SciencesBeijing100049China
| | - Wei Liang
- State Key Laboratory of Transducer TechnologyAerospace Information Research InstituteChinese Academy of SciencesBeijing100190China
- University of Chinese Academy of SciencesBeijing100049China
| | - Shihong Xu
- State Key Laboratory of Transducer TechnologyAerospace Information Research InstituteChinese Academy of SciencesBeijing100190China
- University of Chinese Academy of SciencesBeijing100049China
| | - Kui Zhang
- State Key Laboratory of Transducer TechnologyAerospace Information Research InstituteChinese Academy of SciencesBeijing100190China
- University of Chinese Academy of SciencesBeijing100049China
| | - Yan Yang
- State Key Laboratory of Transducer TechnologyAerospace Information Research InstituteChinese Academy of SciencesBeijing100190China
- University of Chinese Academy of SciencesBeijing100049China
| | - Mixia Wang
- State Key Laboratory of Transducer TechnologyAerospace Information Research InstituteChinese Academy of SciencesBeijing100190China
- University of Chinese Academy of SciencesBeijing100049China
| | - Yilin Song
- State Key Laboratory of Transducer TechnologyAerospace Information Research InstituteChinese Academy of SciencesBeijing100190China
- University of Chinese Academy of SciencesBeijing100049China
| | - Yirong Wu
- State Key Laboratory of Transducer TechnologyAerospace Information Research InstituteChinese Academy of SciencesBeijing100190China
- University of Chinese Academy of SciencesBeijing100049China
| | - Xinxia Cai
- State Key Laboratory of Transducer TechnologyAerospace Information Research InstituteChinese Academy of SciencesBeijing100190China
- University of Chinese Academy of SciencesBeijing100049China
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34
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Duru J, Maurer B, Giles Doran C, Jelitto R, Küchler J, Ihle SJ, Ruff T, John R, Genocchi B, Vörös J. Investigation of the input-output relationship of engineered neural networks using high-density microelectrode arrays. Biosens Bioelectron 2023; 239:115591. [PMID: 37634421 DOI: 10.1016/j.bios.2023.115591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 07/25/2023] [Accepted: 08/10/2023] [Indexed: 08/29/2023]
Abstract
Bottom-up neuroscience utilizes small, engineered biological neural networks to study neuronal activity in systems of reduced complexity. We present a platform that establishes up to six independent networks formed by primary rat neurons on planar complementary metal-oxide-semiconductor (CMOS) microelectrode arrays (MEAs). We introduce an approach that allows repetitive stimulation and recording of network activity at any of the over 700 electrodes underlying a network. We demonstrate that the continuous application of a repetitive super-threshold stimulus yields a reproducible network answer within a 15 ms post-stimulus window. This response can be tracked with high spatiotemporal resolution across the whole extent of the network. Moreover, we show that the location of the stimulation plays a significant role in the networks' early response to the stimulus. By applying a stimulation pattern to all network-underlying electrodes in sequence, the sensitivity of the whole network to the stimulus can be visualized. We demonstrate that microchannels reduce the voltage stimulation threshold and induce the strongest network response. By varying the stimulation amplitude and frequency we reveal discrete network transition points. Finally, we introduce vector fields to follow stimulation-induced spike propagation pathways within the network. Overall we show that our defined neural networks on CMOS MEAs enable us to elicit highly reproducible activity patterns that can be precisely modulated by stimulation amplitude, stimulation frequency and the site of stimulation.
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Affiliation(s)
- Jens Duru
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| | - Benedikt Maurer
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| | - Ciara Giles Doran
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| | - Robert Jelitto
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| | - Joël Küchler
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| | - Stephan J Ihle
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| | - Tobias Ruff
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| | - Robert John
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| | - Barbara Genocchi
- Computational Biophysics and Imaging Group, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.
| | - János Vörös
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
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Baltieri M, Iizuka H, Witkowski O, Sinapayen L, Suzuki K. Hybrid Life: Integrating biological, artificial, and cognitive systems. WILEY INTERDISCIPLINARY REVIEWS. COGNITIVE SCIENCE 2023; 14:e1662. [PMID: 37403661 DOI: 10.1002/wcs.1662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 05/22/2023] [Accepted: 05/30/2023] [Indexed: 07/06/2023]
Abstract
Artificial life is a research field studying what processes and properties define life, based on a multidisciplinary approach spanning the physical, natural, and computational sciences. Artificial life aims to foster a comprehensive study of life beyond "life as we know it" and toward "life as it could be," with theoretical, synthetic, and empirical models of the fundamental properties of living systems. While still a relatively young field, artificial life has flourished as an environment for researchers with different backgrounds, welcoming ideas, and contributions from a wide range of subjects. Hybrid Life brings our attention to some of the most recent developments within the artificial life community, rooted in more traditional artificial life studies but looking at new challenges emerging from interactions with other fields. Hybrid Life aims to cover studies that can lead to an understanding, from first principles, of what systems are and how biological and artificial systems can interact and integrate to form new kinds of hybrid (living) systems, individuals, and societies. To do so, it focuses on three complementary perspectives: theories of systems and agents, hybrid augmentation, and hybrid interaction. Theories of systems and agents are used to define systems, how they differ (e.g., biological or artificial, autonomous, or nonautonomous), and how multiple systems relate in order to form new hybrid systems. Hybrid augmentation focuses on implementations of systems so tightly connected that they act as a single, integrated one. Hybrid interaction is centered around interactions within a heterogeneous group of distinct living and nonliving systems. After discussing some of the major sources of inspiration for these themes, we will focus on an overview of the works that appeared in Hybrid Life special sessions, hosted by the annual Artificial Life Conference between 2018 and 2022. This article is categorized under: Neuroscience > Cognition Philosophy > Artificial Intelligence Computer Science and Robotics > Robotics.
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Affiliation(s)
- Manuel Baltieri
- Araya Inc., Tokyo, Japan
- Department of Informatics, University of Sussex, Brighton, UK
| | - Hiroyuki Iizuka
- Faculty of Information Science and Technology, Hokkaido University, Sapporo, Japan
- Center for Human Nature, Artificial Intelligence and Neuroscience (CHAIN), Hokkaido University, Sapporo, Japan
| | - Olaf Witkowski
- Center for Human Nature, Artificial Intelligence and Neuroscience (CHAIN), Hokkaido University, Sapporo, Japan
- Cross Labs, Cross Compass, Kyoto, Japan
- College of Arts and Sciences, University of Tokyo, Tokyo, Japan
| | - Lana Sinapayen
- Sony Computer Science Laboratories, Kyoto, Japan
- National Institute for Basic Biology, Okazaki, Japan
| | - Keisuke Suzuki
- Center for Human Nature, Artificial Intelligence and Neuroscience (CHAIN), Hokkaido University, Sapporo, Japan
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36
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Rouleau N, Levin M. The Multiple Realizability of Sentience in Living Systems and Beyond. eNeuro 2023; 10:ENEURO.0375-23.2023. [PMID: 37963652 PMCID: PMC10646883 DOI: 10.1523/eneuro.0375-23.2023] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2023] [Accepted: 10/23/2023] [Indexed: 11/16/2023] Open
Affiliation(s)
- Nicolas Rouleau
- Department of Health Sciences, Wilfrid Laurier University, Waterloo, Ontario N2L 3C5, Canada
- Department of Biomedical Engineering, Tufts University, Medford, MA 02155
- Allen Discovery Center at, Tufts University, Medford, MA 02155
| | - Michael Levin
- Allen Discovery Center at, Tufts University, Medford, MA 02155
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02215
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37
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Milford SR, Shaw D, Starke G. Playing Brains: The Ethical Challenges Posed by Silicon Sentience and Hybrid Intelligence in DishBrain. SCIENCE AND ENGINEERING ETHICS 2023; 29:38. [PMID: 37882881 PMCID: PMC10602981 DOI: 10.1007/s11948-023-00457-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 09/28/2023] [Indexed: 10/27/2023]
Abstract
The convergence of human and artificial intelligence is currently receiving considerable scholarly attention. Much debate about the resulting Hybrid Minds focuses on the integration of artificial intelligence into the human brain through intelligent brain-computer interfaces as they enter clinical use. In this contribution we discuss a complementary development: the integration of a functional in vitro network of human neurons into an in silico computing environment.To do so, we draw on a recent experiment reporting the creation of silico-biological intelligence as a case study (Kagan et al., 2022b). In this experiment, multielectrode arrays were plated with stem cell-derived human neurons, creating a system which the authors call DishBrain. By embedding the system into a virtual game-world, neural clusters were able to receive electrical input signals from the game-world and to respond appropriately with output signals from pre-assigned motor regions. Using this design, the authors demonstrate how the DishBrain self-organises and successfully learns to play the computer game 'Pong', exhibiting 'sentient' and intelligent behaviour in its virtual environment.The creation of such hybrid, silico-biological intelligence raises numerous ethical challenges. Following the neuroscientific framework embraced by the authors themselves, we discuss the arising ethical challenges in the context of Karl Friston's Free Energy Principle, focusing on the risk of creating synthetic phenomenology. Following the DishBrain's creator's neuroscientific assumptions, we highlight how DishBrain's design may risk bringing about artificial suffering and argue for a congruently cautious approach to such synthetic biological intelligence.
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Affiliation(s)
- Stephen R Milford
- Department of Theology, North-West University, Potchefstroom, South Africa.
- Institute for Biomedical Ethics, Basel University, Basel, Switzerland.
| | - David Shaw
- Institute for Biomedical Ethics, Basel University, Basel, Switzerland
- Maastricht University, Maastricht, Netherlands
| | - Georg Starke
- College of Humanities, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Institute for History and Ethics of Medicine, Technical University of Munich, Munich, Germany
- Munich School of Philosophy, Munich, Germany
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Stiefel KM, Coggan JS. The energy challenges of artificial superintelligence. Front Artif Intell 2023; 6:1240653. [PMID: 37941679 PMCID: PMC10629395 DOI: 10.3389/frai.2023.1240653] [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: 06/15/2023] [Accepted: 10/05/2023] [Indexed: 11/10/2023] Open
Abstract
We argue here that contemporary semiconductor computing technology poses a significant if not insurmountable barrier to the emergence of any artificial general intelligence system, let alone one anticipated by many to be "superintelligent". This limit on artificial superintelligence (ASI) emerges from the energy requirements of a system that would be more intelligent but orders of magnitude less efficient in energy use than human brains. An ASI would have to supersede not only a single brain but a large population given the effects of collective behavior on the advancement of societies, further multiplying the energy requirement. A hypothetical ASI would likely consume orders of magnitude more energy than what is available in highly-industrialized nations. We estimate the energy use of ASI with an equation we term the "Erasi equation", for the Energy Requirement for Artificial SuperIntelligence. Additional efficiency consequences will emerge from the current unfocussed and scattered developmental trajectory of AI research. Taken together, these arguments suggest that the emergence of an ASI is highly unlikely in the foreseeable future based on current computer architectures, primarily due to energy constraints, with biomimicry or other new technologies being possible solutions.
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Affiliation(s)
| | - Jay S. Coggan
- NeuroLinx Research Institute, La Jolla, CA, United States
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Owen M, Huang Z, Duclos C, Lavazza A, Grasso M, Hudetz AG. Theoretical Neurobiology of Consciousness Applied to Human Cerebral Organoids. Camb Q Healthc Ethics 2023:1-21. [PMID: 37850471 DOI: 10.1017/s0963180123000543] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2023]
Abstract
Organoids and specifically human cerebral organoids (HCOs) are one of the most relevant novelties in the field of biomedical research. Grown either from embryonic or induced pluripotent stem cells, HCOs can be used as in vitro three-dimensional models, mimicking the developmental process and organization of the developing human brain. Based on that, and despite their current limitations, it cannot be assumed that they will never at any stage of development manifest some rudimentary form of consciousness. In the absence of behavioral indicators of consciousness, the theoretical neurobiology of consciousness being applied to unresponsive brain-injured patients can be considered with respect to HCOs. In clinical neurology, it is difficult to discern a capacity for consciousness in unresponsive brain-injured patients who provide no behavioral indicators of consciousness. In such scenarios, a validated neurobiological theory of consciousness, which tells us what the neural mechanisms of consciousness are, could be used to identify a capacity for consciousness. Like the unresponsive patients that provide a diagnostic difficulty for neurologists, HCOs provide no behavioral indicators of consciousness. Therefore, this article discusses how three prominent neurobiological theories of consciousness apply to human cerebral organoids. From the perspective of the Temporal Circuit Hypothesis, the Global Neuronal Workspace Theory, and the Integrated Information Theory, we discuss what neuronal structures and functions might indicate that cerebral organoids have a neurobiological capacity to be conscious.
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Affiliation(s)
- Matthew Owen
- Philosophy Department, Yakima Valley College, Yakima, WA, USA
- Center for Consciousness Science, University of Michigan, Ann Arbor, MI, USA
| | - Zirui Huang
- Center for Consciousness Science, University of Michigan, Ann Arbor, MI, USA
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA
| | - Catherine Duclos
- Department of Anesthesiology and Pain Medicine, Université de Montréal, Montréal, QC, Canada
- Department of Neuroscience, Université de Montréal, Montréal, QC, Canada
- Centre for Advanced Research in Sleep Medicine, Centre intégré universitaire de santé et de services sociaux (CIUSSS) du Nord-de-l'île-de-Montréal, Montréal, QC, Canada
- CIFAR Azrieli Global Scholars Program, Toronto, ON, Canada
| | - Andrea Lavazza
- Centro Universitario Internazionale, Arezzo, Italy
- University of Pavia, Pavia, Italy
| | - Matteo Grasso
- Center for Sleep and Consciousness, University of Wisconsin-Madison, Madison, WI, USA
| | - Anthony G Hudetz
- Center for Consciousness Science, University of Michigan, Ann Arbor, MI, USA
- Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA
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40
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Gentili PL, Stano P. Tracing a new path in the field of AI and robotics: mimicking human intelligence through chemistry. Part II: systems chemistry. Front Robot AI 2023; 10:1266011. [PMID: 37915426 PMCID: PMC10616823 DOI: 10.3389/frobt.2023.1266011] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 10/09/2023] [Indexed: 11/03/2023] Open
Abstract
Inspired by some traits of human intelligence, it is proposed that wetware approaches based on molecular, supramolecular, and systems chemistry can provide valuable models and tools for novel forms of robotics and AI, being constituted by soft matter and fluid states as the human nervous system and, more generally, life, is. Bottom-up mimicries of intelligence range from the molecular world to the multicellular level, i.e., from the Ångström (10 - 10 meters) to the micrometer scales (10 - 6 meters), and allows the development of unconventional chemical robotics. Whereas conventional robotics lets humans explore and colonise otherwise inaccessible environments, such as the deep oceanic abysses and other solar system planets, chemical robots will permit us to inspect and control the microscopic molecular and cellular worlds. This article suggests that systems made of properly chosen molecular compounds can implement all those modules that are the fundamental ingredients of every living being: sensory, processing, actuating, and metabolic networks. Autonomous chemical robotics will be within reach when such modules are compartmentalised and assembled. The design of a strongly intertwined web of chemical robots, with or without the involvement of living matter, will give rise to collective forms of intelligence that will probably reproduce, on a minimal scale, some sophisticated performances of the human intellect and will implement forms of "general AI." These remarkable achievements will require a productive interdisciplinary collaboration among chemists, biotechnologists, computer scientists, engineers, physicists, neuroscientists, cognitive scientists, and philosophers to be achieved. The principal purpose of this paper is to spark this revolutionary collaborative scientific endeavour.
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Affiliation(s)
- Pier Luigi Gentili
- Department of Chemistry, Biology, and Biotechnology, Università degli Studi di Perugia, Perugia, Italy
| | - Pasquale Stano
- Department of Biological and Environmental Sciences and Technologies (DISTeBA), University of Salento, Lecce, Italy
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41
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Tabor A, Constant A. Lifeworlds in pain: a principled method for investigation and intervention. Neurosci Conscious 2023; 2023:niad021. [PMID: 37711314 PMCID: PMC10499064 DOI: 10.1093/nc/niad021] [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: 04/06/2023] [Revised: 08/03/2023] [Accepted: 08/23/2023] [Indexed: 09/16/2023] Open
Abstract
The experience of pain spans biological, psychological and sociocultural realms, both basic and complex, it is by turns necessary and devastating. Despite an extensive knowledge of the constituents of pain, the ability to translate this into effective intervention remains limited. It is suggested that current, multiscale, medical approaches, largely informed by the biopsychosocial (BPS) model, attempt to integrate knowledge but are undermined by an epistemological obligation, one that necessitates a prior isolation of the constituent parts. To overcome this impasse, we propose that an anthropological stance needs to be taken, underpinned by a Bayesian apparatus situated in computational psychiatry. Here, pain is presented within the context of lifeworlds, where attention is shifted away from the constituents of experience (e.g. nociception, reward processing and fear-avoidance), towards the dynamic affiliation that occurs between these processes over time. We argue that one can derive a principled method of investigation and intervention for pain from modelling approaches in computational psychiatry. We suggest that these modelling methods provide the necessary apparatus to navigate multiscale ontology and epistemology of pain. Finally, a unified approach to the experience of pain is presented, where the relational, inter-subjective phenomenology of pain is brought into contact with a principled method of translation; in so doing, revealing the conditions and possibilities of lifeworlds in pain.
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Affiliation(s)
- Abby Tabor
- Faculty of Health and Applied Sciences, University of the West of England, Frenchay Campus, Coldharbour Ln, Stoke Gifford, Bristol BS16 1QY, UK
- Centre for Pain Research, University of Bath, Claverton Down, Bath BA2 7AY, UK
| | - Axel Constant
- Department of Engineering and Informatics, The University of Sussex, Chichester 1 Room 002, Falmer, Brighton BN1 9QJ, UK
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42
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Montoya I, Montoya D. What Is It like to Be a Brain Organoid? Phenomenal Consciousness in a Biological Neural Network. ENTROPY (BASEL, SWITZERLAND) 2023; 25:1328. [PMID: 37761627 PMCID: PMC10529514 DOI: 10.3390/e25091328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 09/04/2023] [Accepted: 09/11/2023] [Indexed: 09/29/2023]
Abstract
It has been shown that three-dimensional self-assembled multicellular structures derived from human pluripotent stem cells show electrical activity similar to EEG. More recently, neurons were successfully embedded in digital game worlds. The biologically inspired neural network (BNN), expressing human cortical cells, was able to show internal modification and learn the task at hand (predicting the trajectory of a digital ball while moving a digital paddle). In other words, the system allowed to read motor information and write sensory data into cell cultures. In this article, we discuss Neural Correlates of Consciousness (NCC) theories, and their capacity to predict or even allow for consciousness in a BNN. We found that Information Integration Theory (IIT) is the only NCC that offers the possibility for a BNN to show consciousness, since the Φ value in the BNN is >0. In other words, the recording of real-time neural activity responding to environmental stimuli. IIT argues that any system capable of integrating information will have some degree of phenomenal consciousness. We argue that the pattern of activity appearing in the BNN, with increased density of sensory information leading to better performance, implies that the BNN could be conscious. This may have profound implications from a psychological, philosophical, and ethical perspective.
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Affiliation(s)
| | - Daniel Montoya
- Department of Psychology, Fayetteville State University, Fayetteville, NC 28301, USA;
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43
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Lagasse E, Levin M. Future medicine: from molecular pathways to the collective intelligence of the body. Trends Mol Med 2023; 29:687-710. [PMID: 37481382 PMCID: PMC10527237 DOI: 10.1016/j.molmed.2023.06.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 06/20/2023] [Accepted: 06/22/2023] [Indexed: 07/24/2023]
Abstract
The remarkable anatomical homeostasis exhibited by complex living organisms suggests that they are inherently reprogrammable information-processing systems that offer numerous interfaces to their physiological and anatomical problem-solving capacities. We briefly review data suggesting that the multiscale competency of living forms affords a new path for biomedicine that exploits the innate collective intelligence of tissues and organs. The concept of tissue-level allostatic goal-directedness is already bearing fruit in clinical practice. We sketch a roadmap towards 'somatic psychiatry' by using advances in bioelectricity and behavioral neuroscience to design methods that induce self-repair of structure and function. Relaxing the assumption that cellular control mechanisms are static, exploiting powerful concepts from cybernetics, behavioral science, and developmental biology may spark definitive solutions to current biomedical challenges.
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Affiliation(s)
- Eric Lagasse
- McGowan Institute for Regenerative Medicine and Department of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Michael Levin
- Allen Discovery Center, Tufts University, Medford, MA, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.
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44
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Habibollahi F, Kagan BJ, Burkitt AN, French C. Critical dynamics arise during structured information presentation within embodied in vitro neuronal networks. Nat Commun 2023; 14:5287. [PMID: 37648737 PMCID: PMC10469171 DOI: 10.1038/s41467-023-41020-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Accepted: 08/17/2023] [Indexed: 09/01/2023] Open
Abstract
Understanding how brains process information is an incredibly difficult task. Amongst the metrics characterising information processing in the brain, observations of dynamic near-critical states have generated significant interest. However, theoretical and experimental limitations associated with human and animal models have precluded a definite answer about when and why neural criticality arises with links from attention, to cognition, and even to consciousness. To explore this topic, we used an in vitro neural network of cortical neurons that was trained to play a simplified game of 'Pong' to demonstrate Synthetic Biological Intelligence (SBI). We demonstrate that critical dynamics emerge when neural networks receive task-related structured sensory input, reorganizing the system to a near-critical state. Additionally, better task performance correlated with proximity to critical dynamics. However, criticality alone is insufficient for a neuronal network to demonstrate learning in the absence of additional information regarding the consequences of previous actions. These findings offer compelling support that neural criticality arises as a base feature of incoming structured information processing without the need for higher order cognition.
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Affiliation(s)
- Forough Habibollahi
- Cortical Labs Pty Ltd, Melbourne, 3056, VIC, Australia
- Biomedical Engineering Department, University of Melbourne, Parkville, 3010, VIC, Australia
- Neural Dynamics Laboratory, Department of Medicine, University of Melbourne, Parkville, 3010, VIC, Australia
| | - Brett J Kagan
- Cortical Labs Pty Ltd, Melbourne, 3056, VIC, Australia.
| | - Anthony N Burkitt
- Biomedical Engineering Department, University of Melbourne, Parkville, 3010, VIC, Australia
| | - Chris French
- Neural Dynamics Laboratory, Department of Medicine, University of Melbourne, Parkville, 3010, VIC, Australia
- Neurology Department, Royal Melbourne Hospital, Melbourne, Australia
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45
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LeDoux J, Birch J, Andrews K, Clayton NS, Daw ND, Frith C, Lau H, Peters MAK, Schneider S, Seth A, Suddendorf T, Vandekerckhove MMP. Consciousness beyond the human case. Curr Biol 2023; 33:R832-R840. [PMID: 37607474 DOI: 10.1016/j.cub.2023.06.067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
There is growing interest in the relationship been AI and consciousness. Joseph LeDoux and Jonathan Birch thought it would be a good moment to put some of the big questions in this area to some leading experts. The challenge of addressing the questions they raised was taken up by Kristin Andrews, Nicky Clayton, Nathaniel Daw, Chris Frith, Hakwan Lau, Megan Peters, Susan Schneider, Anil Seth, Thomas Suddendorf, and Marie Vanderkerckhoeve.
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46
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Isomura T, Kotani K, Jimbo Y, Friston KJ. Experimental validation of the free-energy principle with in vitro neural networks. Nat Commun 2023; 14:4547. [PMID: 37550277 PMCID: PMC10406890 DOI: 10.1038/s41467-023-40141-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 07/13/2023] [Indexed: 08/09/2023] Open
Abstract
Empirical applications of the free-energy principle are not straightforward because they entail a commitment to a particular process theory, especially at the cellular and synaptic levels. Using a recently established reverse engineering technique, we confirm the quantitative predictions of the free-energy principle using in vitro networks of rat cortical neurons that perform causal inference. Upon receiving electrical stimuli-generated by mixing two hidden sources-neurons self-organised to selectively encode the two sources. Pharmacological up- and downregulation of network excitability disrupted the ensuing inference, consistent with changes in prior beliefs about hidden sources. As predicted, changes in effective synaptic connectivity reduced variational free energy, where the connection strengths encoded parameters of the generative model. In short, we show that variational free energy minimisation can quantitatively predict the self-organisation of neuronal networks, in terms of their responses and plasticity. These results demonstrate the applicability of the free-energy principle to in vitro neural networks and establish its predictive validity in this setting.
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Affiliation(s)
- Takuya Isomura
- Brain Intelligence Theory Unit, RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama, 351-0198, Japan.
| | - Kiyoshi Kotani
- Research Center for Advanced Science and Technology, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, Tokyo, 153-8904, Japan
| | - Yasuhiko Jimbo
- Department of Precision Engineering, School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan
| | - Karl J Friston
- Wellcome Centre for Human Neuroimaging, Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
- VERSES AI Research Lab, Los Angeles, CA, 90016, USA
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Akita D, Suwa E, Ikeda N, Takahashi H. Neural Activity and Information Processing Capacity of Neuronal Culture. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38083492 DOI: 10.1109/embc40787.2023.10340168] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Whether artificial or living, neural networks perform tremendously diverse kinds of information processing, such as visual feature extraction, speech recognition, motor control, and so on. Some studies have evaluated the computational ability of living neural networks based on the performances of specific tasks, yet could not comprehensively grasp the versatile ability. In this study, we investigated dissociated culture of neurons as a physical reservoir, which generates diverse outputs through linear regression, or readout, of the dynamical states. Based on the theory of reservoir computing, the potential computational capabilities of neuronal culture were evaluated by the information processing capacity (IPC), which indicates how a target function can be achieved from the given dynamics. As a result, we found that the neuronal culture exhibited significant IPC and that IPC varied with the inter-step interval (ISI), the time step of reservoir computing. The cultures exhibited a memory capacity of 10 time steps for computation, and this memory capacity decayed at an ISI of 5 ms or shorter. In addition, the IPC had a significant positive correlation with the intensity of the evoked response relative to spontaneous activity. The multiple regression model with evoked response and ISI showed the positive effect of evoked response and 30 ms as the best ISI for IPC. These results suggest that the distinct evoked response and the optimal time step to interact with the neuronal culture are key factors to uncover computational resources from the neuronal system.
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48
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Balasubramaniam S, Somathilaka S, Sun S, Ratwatte A, Pierobon M. Realizing Molecular Machine Learning through Communications for Biological AI: Future Directions and Challenges. IEEE NANOTECHNOLOGY MAGAZINE 2023; 17:10-20. [PMID: 38855043 PMCID: PMC11160936 DOI: 10.1109/mnano.2023.3262099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Artificial Intelligence (AI) and Machine Learning (ML) are weaving their way into the fabric of society, where they are playing a crucial role in numerous facets of our lives. As we witness the increased deployment of AI and ML in various types of devices, we benefit from their use into energy-efficient algorithms for low powered devices. In this paper, we investigate a scale and medium that is far smaller than conventional devices as we move towards molecular systems that can be utilized to perform machine learning functions, i.e., Molecular Machine Learning (MML). Fundamental to the operation of MML is the transport, processing, and interpretation of information propagated by molecules through chemical reactions. We begin by reviewing the current approaches that have been developed for MML, before we move towards potential new directions that rely on gene regulatory networks inside biological organisms as well as their population interactions to create neural networks. We then investigate mechanisms for training machine learning structures in biological cells based on calcium signaling and demonstrate their application to build an Analog to Digital Converter (ADC). Lastly, we look at potential future directions as well as challenges that this area could solve.
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Affiliation(s)
| | - Samitha Somathilaka
- School of Computing, University of Nebraska-Lincoln, NE, USA
- Walton Institute, South East Technological University, Ireland
| | - Sehee Sun
- School of Computing, University of Nebraska-Lincoln, NE, USA
| | - Adrian Ratwatte
- School of Computing, University of Nebraska-Lincoln, NE, USA
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49
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Iyer V, Issadore DA, Aflatouni F. The next generation of hybrid microfluidic/integrated circuit chips: recent and upcoming advances in high-speed, high-throughput, and multifunctional lab-on-IC systems. LAB ON A CHIP 2023; 23:2553-2576. [PMID: 37114950 DOI: 10.1039/d2lc01163h] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
Since the field's inception, pioneers in microfluidics have made significant progress towards realizing complete lab-on-chip systems capable of sophisticated sample analysis and processing. One avenue towards this goal has been to join forces with the related field of microelectronics, using integrated circuits (ICs) to perform on-chip actuation and sensing. While early demonstrations focused on using microfluidic-IC hybrid chips to miniaturize benchtop instruments, steady advancements in the field have enabled a new generation of devices that expand past miniaturization into high-performance applications that would not be possible without IC hybrid integration. In this review, we identify recent examples of labs-on-chip that use high-resolution, high-speed, and multifunctional electronic and photonic chips to expand the capabilities of conventional sample analysis. We focus on three particularly active areas: a) high-throughput integrated flow cytometers; b) large-scale microelectrode arrays for stimulation and multimodal sensing of cells over a wide field of view; c) high-speed biosensors for studying molecules with high temporal resolution. We also discuss recent advancements in IC technology, including on-chip data processing techniques and lens-free optics based on integrated photonics, that are poised to further advance microfluidic-IC hybrid chips.
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Affiliation(s)
- Vasant Iyer
- Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
| | - David A Issadore
- Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Firooz Aflatouni
- Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
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50
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Fingelkurts AA, Fingelkurts AA. Patients with Disorders of Consciousness: Are They Nonconscious, Unconscious, or Subconscious? Expanding the Discussion. Brain Sci 2023; 13:brainsci13050814. [PMID: 37239286 DOI: 10.3390/brainsci13050814] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 05/14/2023] [Accepted: 05/16/2023] [Indexed: 05/28/2023] Open
Abstract
Unprecedented advancements in the diagnosis and treatment of patients with disorders of consciousness (DoC) have given rise to ethical questions about how to recognize and respect autonomy and a sense of agency of the personhood when those capacities are themselves disordered, as they typically are in patients with DoC. At the intersection of these questions rests the distinction between consciousness and unconsciousness. Indeed, evaluations of consciousness levels and capacity for recovery have a significant impact on decisions regarding whether to discontinue or prolong life-sustaining therapy for DoC patients. However, in the unconsciousness domain, there is the confusing array of terms that are regularly used interchangeably, making it quite challenging to comprehend what unconsciousness is and how it might be empirically grounded. In this opinion paper, we will provide a brief overview of the state of the field of unconsciousness and show how a rapidly evolving electroencephalogram (EEG) neuroimaging technique may offer empirical, theoretical, and practical tools to approach unconsciousness and to improve our ability to distinguish consciousness from unconsciousness and also nonconsciousness with greater precision, particularly in cases that are borderline (as is typical in patients with DoC). Furthermore, we will provide a clear description of three distant notions of (un)consciousness (unconsciousness, nonconsciousness, and subconsciousness) and discuss how they relate to the experiential selfhood which is essential for comprehending the moral significance of what makes life worth living.
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