1
|
González-González MA, Conde SV, Latorre R, Thébault SC, Pratelli M, Spitzer NC, Verkhratsky A, Tremblay MÈ, Akcora CG, Hernández-Reynoso AG, Ecker M, Coates J, Vincent KL, Ma B. Bioelectronic Medicine: a multidisciplinary roadmap from biophysics to precision therapies. Front Integr Neurosci 2024; 18:1321872. [PMID: 38440417 PMCID: PMC10911101 DOI: 10.3389/fnint.2024.1321872] [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: 10/16/2023] [Accepted: 01/10/2024] [Indexed: 03/06/2024] Open
Abstract
Bioelectronic Medicine stands as an emerging field that rapidly evolves and offers distinctive clinical benefits, alongside unique challenges. It consists of the modulation of the nervous system by precise delivery of electrical current for the treatment of clinical conditions, such as post-stroke movement recovery or drug-resistant disorders. The unquestionable clinical impact of Bioelectronic Medicine is underscored by the successful translation to humans in the last decades, and the long list of preclinical studies. Given the emergency of accelerating the progress in new neuromodulation treatments (i.e., drug-resistant hypertension, autoimmune and degenerative diseases), collaboration between multiple fields is imperative. This work intends to foster multidisciplinary work and bring together different fields to provide the fundamental basis underlying Bioelectronic Medicine. In this review we will go from the biophysics of the cell membrane, which we consider the inner core of neuromodulation, to patient care. We will discuss the recently discovered mechanism of neurotransmission switching and how it will impact neuromodulation design, and we will provide an update on neuronal and glial basis in health and disease. The advances in biomedical technology have facilitated the collection of large amounts of data, thereby introducing new challenges in data analysis. We will discuss the current approaches and challenges in high throughput data analysis, encompassing big data, networks, artificial intelligence, and internet of things. Emphasis will be placed on understanding the electrochemical properties of neural interfaces, along with the integration of biocompatible and reliable materials and compliance with biomedical regulations for translational applications. Preclinical validation is foundational to the translational process, and we will discuss the critical aspects of such animal studies. Finally, we will focus on the patient point-of-care and challenges in neuromodulation as the ultimate goal of bioelectronic medicine. This review is a call to scientists from different fields to work together with a common endeavor: accelerate the decoding and modulation of the nervous system in a new era of therapeutic possibilities.
Collapse
Affiliation(s)
- María Alejandra González-González
- Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, Houston, TX, United States
- Department of Pediatric Neurology, Baylor College of Medicine, Houston, TX, United States
| | - Silvia V. Conde
- iNOVA4Health, NOVA Medical School, Faculdade de Ciências Médicas, NOVA University, Lisbon, Portugal
| | - Ramon Latorre
- Centro Interdisciplinario de Neurociencia de Valparaíso, Facultad de Ciencias, Universidad de Valparaíso, Valparaíso, Chile
| | - Stéphanie C. Thébault
- Laboratorio de Investigación Traslacional en salud visual (D-13), Instituto de Neurobiología, Universidad Nacional Autónoma de México (UNAM), Querétaro, Mexico
| | - Marta Pratelli
- Neurobiology Department, Kavli Institute for Brain and Mind, UC San Diego, La Jolla, CA, United States
| | - Nicholas C. Spitzer
- Neurobiology Department, Kavli Institute for Brain and Mind, UC San Diego, La Jolla, CA, United States
| | - Alexei Verkhratsky
- Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom
- Achucarro Centre for Neuroscience, IKERBASQUE, Basque Foundation for Science, Bilbao, Spain
- Department of Forensic Analytical Toxicology, School of Forensic Medicine, China Medical University, Shenyang, China
- International Collaborative Center on Big Science Plan for Purinergic Signaling, Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Department of Stem Cell Biology, State Research Institute Centre for Innovative Medicine, Vilnius, Lithuania
| | - Marie-Ève Tremblay
- Division of Medical Sciences, University of Victoria, Victoria, BC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
- Department of Molecular Medicine, Université Laval, Québec City, QC, Canada
- Department of Biochemistry and Molecular Biology, The University of British Columbia, Vancouver, BC, Canada
| | - Cuneyt G. Akcora
- Department of Computer Science, University of Central Florida, Orlando, FL, United States
| | | | - Melanie Ecker
- Department of Biomedical Engineering, University of North Texas, Denton, TX, United States
| | | | - Kathleen L. Vincent
- Department of Obstetrics and Gynecology, University of Texas Medical Branch, Galveston, TX, United States
| | - Brandy Ma
- Stanley H. Appel Department of Neurology, Houston Methodist Hospital, Houston, TX, United States
| |
Collapse
|
2
|
Merchant H, Mendoza G, Pérez O, Betancourt A, García-Saldivar P, Prado L. Diverse Time Encoding Strategies Within the Medial Premotor Areas of the Primate. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2024; 1455:117-140. [PMID: 38918349 DOI: 10.1007/978-3-031-60183-5_7] [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: 06/27/2024]
Abstract
The measurement of time in the subsecond scale is critical for many sophisticated behaviors, yet its neural underpinnings are largely unknown. Recent neurophysiological experiments from our laboratory have shown that the neural activity in the medial premotor areas (MPC) of macaques can represent different aspects of temporal processing. During single interval categorization, we found that preSMA encodes a subjective category limit by reaching a peak of activity at a time that divides the set of test intervals into short and long. We also observed neural signals associated with the category selected by the subjects and the reward outcomes of the perceptual decision. On the other hand, we have studied the behavioral and neurophysiological basis of rhythmic timing. First, we have shown in different tapping tasks that macaques are able to produce predictively and accurately intervals that are cued by auditory or visual metronomes or when intervals are produced internally without sensory guidance. In addition, we found that the rhythmic timing mechanism in MPC is governed by different layers of neural clocks. Next, the instantaneous activity of single cells shows ramping activity that encodes the elapsed or remaining time for a tapping movement. In addition, we found MPC neurons that build neural sequences, forming dynamic patterns of activation that flexibly cover all the produced interval depending on the tapping tempo. This rhythmic neural clock resets on every interval providing an internal representation of pulse. Furthermore, the MPC cells show mixed selectivity, encoding not only elapsed time, but also the tempo of the tapping and the serial order element in the rhythmic sequence. Hence, MPC can map different task parameters, including the passage of time, using different cell populations. Finally, the projection of the time varying activity of MPC hundreds of cells into a low dimensional state space showed circular neural trajectories whose geometry represented the internal pulse and the tapping tempo. Overall, these findings support the notion that MPC is part of the core timing mechanism for both single interval and rhythmic timing, using neural clocks with different encoding principles, probably to flexibly encode and mix the timing representation with other task parameters.
Collapse
Affiliation(s)
- Hugo Merchant
- Instituto de Neurobiología, UNAM, Campus Juriquilla, Querétaro, Mexico.
| | - Germán Mendoza
- Instituto de Neurobiología, UNAM, Campus Juriquilla, Querétaro, Mexico
| | - Oswaldo Pérez
- Instituto de Neurobiología, UNAM, Campus Juriquilla, Querétaro, Mexico
| | | | | | - Luis Prado
- Instituto de Neurobiología, UNAM, Campus Juriquilla, Querétaro, Mexico
| |
Collapse
|
3
|
Zhang W, Zhou J, Su H, Zhang X, Song W, Wang Z, Tang C, Uludağ K, Zhao M, Xiong ZQ, Zhai R, Jiang H. Repeated methamphetamine exposure decreases plasma brain-derived neurotrophic factor levels in rhesus monkeys. Gen Psychiatr 2023; 36:e101127. [PMID: 37920406 PMCID: PMC10618972 DOI: 10.1136/gpsych-2023-101127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Accepted: 09/03/2023] [Indexed: 11/04/2023] Open
Abstract
Background Brain-derived neurotrophic factor (BDNF) is known to prevent methamphetamine (METH)-induced neurotoxicity and plays a role in various stages of METH addiction. However, there is a lack of research with longitudinal design on changes in plasma BDNF levels in active METH-dependent individuals. Aims The aim of the study was to investigate changes in BDNF levels during METH self-administration in monkeys. Methods This study measured plasma BDNF levels in three male rhesus monkeys with continuous METH exposure and four male control rhesus monkeys without METH exposure. Changes in plasma BDNF levels were then assessed longitudinally during 40 sessions of METH self-administration in the three monkeys. Results Repeated METH exposure decreased plasma BDNF levels. Additionally, plasma BDNF decreased with long-term rather than short-term accumulation of METH during METH self-administration. Conclusions These findings may indicate that the changes in peripheral BDNF may reflect the quantity of accumulative METH intake during a frequent drug use period.
Collapse
Affiliation(s)
- Wenlei Zhang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jiahui Zhou
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hang Su
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | | | - Weichen Song
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zijing Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chengjie Tang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Kadir Uludağ
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Min Zhao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Lingang Laboratory, Shanghai, China
- CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Sciences, Shanghai, China
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai, China
| | - Zhi-Qi Xiong
- Lingang Laboratory, Shanghai, China
- CAS Center for Excellence in Brain Science and Intelligence Technology (CEBSIT), Chinese Academy of Sciences, Shanghai, China
| | | | - Haifeng Jiang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai, China
| |
Collapse
|
4
|
Debracque C, Gruber T, Lacoste R, Meguerditchian A, Grandjean D. Cerebral Activity in Female Baboons ( Papio anubis) During the Perception of Conspecific and Heterospecific Agonistic Vocalizations: a Functional Near Infrared Spectroscopy Study. AFFECTIVE SCIENCE 2022; 3:783-791. [PMID: 36519140 PMCID: PMC9743891 DOI: 10.1007/s42761-022-00164-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2022] [Accepted: 10/27/2022] [Indexed: 05/02/2023]
Abstract
UNLABELLED The "voice areas" in the superior temporal cortex have been identified in both humans and non-human primates as selective to conspecific vocalizations only (i.e., expressed by members of our own species), suggesting its old evolutionary roots across the primate lineage. With respect to non-human primate species, it remains unclear whether the listening of vocal emotions from conspecifics leads to similar or different cerebral activations when compared to heterospecific calls (i.e., expressed by another primate species) triggered by the same emotion. Using a neuroimaging technique rarely employed in monkeys so far, functional Near Infrared Spectroscopy, the present study investigated in three lightly anesthetized female baboons (Papio anubis), temporal cortex activities during exposure to agonistic vocalizations from conspecifics and from other primates (chimpanzees-Pan troglodytes), and energy matched white noises in order to control for this low-level acoustic feature. Permutation test analyses on the extracted OxyHemoglobin signal revealed great inter-individual differences on how conspecific and heterospecific vocal stimuli were processed in baboon brains with a cortical response recorded either in the right or the left temporal cortex. No difference was found between emotional vocalizations and their energy-matched white noises. Despite the phylogenetic gap between Homo sapiens and African monkeys, modern humans and baboons both showed a highly heterogeneous brain process for the perception of vocal and emotional stimuli. The results of this study do not exclude that old evolutionary mechanisms for vocal emotional processing may be shared and inherited from our common ancestor. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s42761-022-00164-z.
Collapse
Affiliation(s)
- Coralie Debracque
- Neuroscience of Emotion and Affective Dynamics Lab, Faculty of Psychology and Educational Sciences and Swiss Center for Affective Sciences, University of Geneva, Campus Biotech, Chemin Des Mines 9, 1202 Geneva, Switzerland
| | - Thibaud Gruber
- Neuroscience of Emotion and Affective Dynamics Lab, Faculty of Psychology and Educational Sciences and Swiss Center for Affective Sciences, University of Geneva, Campus Biotech, Chemin Des Mines 9, 1202 Geneva, Switzerland
| | - Romain Lacoste
- Station de Primatologie-Celphedia, CNRS UARS846, Rousset-Sur-Arc, France
| | - Adrien Meguerditchian
- Station de Primatologie-Celphedia, CNRS UARS846, Rousset-Sur-Arc, France
- Laboratoire de Psychologie Cognitive UMR7290, CNRS, Université Aix-Marseille, Marseille, France
| | - Didier Grandjean
- Neuroscience of Emotion and Affective Dynamics Lab, Faculty of Psychology and Educational Sciences and Swiss Center for Affective Sciences, University of Geneva, Campus Biotech, Chemin Des Mines 9, 1202 Geneva, Switzerland
| |
Collapse
|
5
|
Miller JA, Tambini A, Kiyonaga A, D'Esposito M. Long-term learning transforms prefrontal cortex representations during working memory. Neuron 2022; 110:3805-3819.e6. [PMID: 36240768 PMCID: PMC9768795 DOI: 10.1016/j.neuron.2022.09.019] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 06/28/2022] [Accepted: 09/14/2022] [Indexed: 11/06/2022]
Abstract
The role of the lateral prefrontal cortex (lPFC) in working memory (WM) is debated. Non-human primate (NHP) electrophysiology shows that the lPFC stores WM representations, but human neuroimaging suggests that the lPFC controls WM content in sensory cortices. These accounts are confounded by differences in task training and stimulus exposure. We tested whether long-term training alters lPFC function by densely sampling WM activity using functional MRI. Over 3 months, participants trained on both a WM and serial reaction time (SRT) task, wherein fractal stimuli were embedded within sequences. WM performance improved for trained (but not novel) fractals and, neurally, delay activity increased in distributed lPFC voxels across learning. Item-level WM representations became detectable within lPFC patterns, and lPFC activity reflected sequence relationships from the SRT task. These findings demonstrate that human lPFC develops stimulus-selective responses with learning, and WM representations are shaped by long-term experience, which could reconcile competing accounts of WM functioning.
Collapse
Affiliation(s)
- Jacob A Miller
- Wu Tsai Institute, Department of Psychiatry, Yale University, New Haven, CT, USA.
| | - Arielle Tambini
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Anastasia Kiyonaga
- Department of Cognitive Science, University of California, San Diego, CA, USA
| | - Mark D'Esposito
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA; Department of Psychology, University of California, Berkeley, CA, USA
| |
Collapse
|
6
|
Devika K, Mahapatra D, Subramanian R, Ramana Murthy Oruganti V. Dense Attentive GAN-based One-Class Model for Detection of Autism and ADHD. JOURNAL OF KING SAUD UNIVERSITY - COMPUTER AND INFORMATION SCIENCES 2022. [DOI: 10.1016/j.jksuci.2022.11.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
|
7
|
The neurobiology of drug addiction: cross-species insights into the dysfunction and recovery of the prefrontal cortex. Neuropsychopharmacology 2022; 47:276-291. [PMID: 34408275 PMCID: PMC8617203 DOI: 10.1038/s41386-021-01153-9] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 08/02/2021] [Accepted: 08/06/2021] [Indexed: 01/03/2023]
Abstract
A growing preclinical and clinical body of work on the effects of chronic drug use and drug addiction has extended the scope of inquiry from the putative reward-related subcortical mechanisms to higher-order executive functions as regulated by the prefrontal cortex. Here we review the neuroimaging evidence in humans and non-human primates to demonstrate the involvement of the prefrontal cortex in emotional, cognitive, and behavioral alterations in drug addiction, with particular attention to the impaired response inhibition and salience attribution (iRISA) framework. In support of iRISA, functional and structural neuroimaging studies document a role for the prefrontal cortex in assigning excessive salience to drug over non-drug-related processes with concomitant lapses in self-control, and deficits in reward-related decision-making and insight into illness. Importantly, converging insights from human and non-human primate studies suggest a causal relationship between drug addiction and prefrontal insult, indicating that chronic drug use causes the prefrontal cortex damage that underlies iRISA while changes with abstinence and recovery with treatment suggest plasticity of these same brain regions and functions. We further dissect the overlapping and distinct characteristics of drug classes, potential biomarkers that inform vulnerability and resilience, and advancements in cutting-edge psychological and neuromodulatory treatment strategies, providing a comprehensive landscape of the human and non-human primate drug addiction literature as it relates to the prefrontal cortex.
Collapse
|
8
|
Zhong T, Wei J, Wu K, Chen L, Zhao F, Pei Y, Wang Y, Zhang H, Wu Z, Huang Y, Li T, Wang L, Chen Y, Ji W, Zhang Y, Li G, Niu Y. Longitudinal brain atlases of early developing cynomolgus macaques from birth to 48 months of age. Neuroimage 2021; 247:118799. [PMID: 34896583 DOI: 10.1016/j.neuroimage.2021.118799] [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: 09/01/2021] [Revised: 11/05/2021] [Accepted: 12/08/2021] [Indexed: 10/19/2022] Open
Abstract
Longitudinal brain imaging atlases with densely sampled time-points and ancillary anatomical information are of fundamental importance in studying early developmental characteristics of human and non-human primate brains during infancy, which feature extremely dynamic imaging appearance, brain shape and size. However, for non-human primates, which are highly valuable animal models for understanding human brains, the existing brain atlases are mainly developed based on adults or adolescents, denoting a notable lack of temporally densely-sampled atlases covering the dynamic early brain development. To fill this critical gap, in this paper, we construct a comprehensive set of longitudinal brain atlases and associated tissue probability maps (gray matter, white matter, and cerebrospinal fluid) with totally 12 time-points from birth to 4 years of age (i.e., 1, 2, 3, 4, 5, 6, 9, 12, 18, 24, 36, and 48 months of age) based on 175 longitudinal structural MRI scans from 39 typically-developing cynomolgus macaques, by leveraging state-of-the-art computational techniques tailored for early developing brains. Furthermore, to facilitate region-based analysis using our atlases, we also provide two popular hierarchy parcellations, i.e., cortical hierarchy maps (6 levels) and subcortical hierarchy maps (6 levels), on our longitudinal macaque brain atlases. These early developing atlases, which have the densest time-points during infancy (to the best of our knowledge), will greatly facilitate the studies of macaque brain development.
Collapse
Affiliation(s)
- Tao Zhong
- Department of Radiology and BRIC, University of North Carolina Chapel Hill, USA; Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Jingkuan Wei
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, China
| | - Kunhua Wu
- Department of MRI, the First People's Hospital of Yunnan Province, Kunming, China
| | - Liangjun Chen
- Department of Radiology and BRIC, University of North Carolina Chapel Hill, USA
| | - Fenqiang Zhao
- Department of Radiology and BRIC, University of North Carolina Chapel Hill, USA
| | - Yuchen Pei
- Department of Radiology and BRIC, University of North Carolina Chapel Hill, USA
| | - Ya Wang
- Department of Radiology and BRIC, University of North Carolina Chapel Hill, USA
| | - Hongjiang Zhang
- Department of MRI, the First People's Hospital of Yunnan Province, Kunming, China
| | - Zhengwang Wu
- Department of Radiology and BRIC, University of North Carolina Chapel Hill, USA
| | - Ying Huang
- Department of Radiology and BRIC, University of North Carolina Chapel Hill, USA
| | - Tengfei Li
- Department of Radiology and BRIC, University of North Carolina Chapel Hill, USA
| | - Li Wang
- Department of Radiology and BRIC, University of North Carolina Chapel Hill, USA
| | - Yongchang Chen
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, China
| | - Weizhi Ji
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, China
| | - Yu Zhang
- Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Gang Li
- Department of Radiology and BRIC, University of North Carolina Chapel Hill, USA.
| | - Yuyu Niu
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China; Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, China.
| |
Collapse
|