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Ochoa JÁ, Gonzalez-Burgos I, Nicolás MJ, Valencia M. Open Hardware Implementation of Real-Time Phase and Amplitude Estimation for Neurophysiologic Signals. Bioengineering (Basel) 2023; 10:1350. [PMID: 38135941 PMCID: PMC10740741 DOI: 10.3390/bioengineering10121350] [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: 10/10/2023] [Revised: 11/16/2023] [Accepted: 11/21/2023] [Indexed: 12/24/2023] Open
Abstract
Adaptive deep brain stimulation (aDBS) is a promising concept in the field of DBS that consists of delivering electrical stimulation in response to specific events. Dynamic adaptivity arises when stimulation targets dynamically changing states, which often calls for a reliable and fast causal estimation of the phase and amplitude of the signals. Here, we present an open-hardware implementation that exploits the concepts of resonators and Hilbert filters embedded in an open-hardware platform. To emulate real-world scenarios, we built a hardware setup that included a system to replay and process different types of physiological signals and test the accuracy of the instantaneous phase and amplitude estimates. The results show that the system can provide a precise and reliable estimation of the phase even in the challenging scenario of dealing with high-frequency oscillations (~250 Hz) in real-time. The framework might be adopted in neuromodulation studies to quickly test biomarkers in clinical and preclinical settings, supporting the advancement of aDBS.
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Affiliation(s)
- José Ángel Ochoa
- Biomedical Engineering Program, Physiological Monitoring and Control Laboratory, CIMA, Universidad de Navarra, Avda Pio XII 55, 31080 Pamplona, Spain; (J.Á.O.); (I.G.-B.); (M.J.N.)
- IdiSNA, Navarra Institute for Health Research, C/Irunlarrea, 31008 Pamplona, Spain
| | - Irene Gonzalez-Burgos
- Biomedical Engineering Program, Physiological Monitoring and Control Laboratory, CIMA, Universidad de Navarra, Avda Pio XII 55, 31080 Pamplona, Spain; (J.Á.O.); (I.G.-B.); (M.J.N.)
- IdiSNA, Navarra Institute for Health Research, C/Irunlarrea, 31008 Pamplona, Spain
| | - María Jesús Nicolás
- Biomedical Engineering Program, Physiological Monitoring and Control Laboratory, CIMA, Universidad de Navarra, Avda Pio XII 55, 31080 Pamplona, Spain; (J.Á.O.); (I.G.-B.); (M.J.N.)
- IdiSNA, Navarra Institute for Health Research, C/Irunlarrea, 31008 Pamplona, Spain
| | - Miguel Valencia
- Biomedical Engineering Program, Physiological Monitoring and Control Laboratory, CIMA, Universidad de Navarra, Avda Pio XII 55, 31080 Pamplona, Spain; (J.Á.O.); (I.G.-B.); (M.J.N.)
- IdiSNA, Navarra Institute for Health Research, C/Irunlarrea, 31008 Pamplona, Spain
- Institute of Data Science and Artificial Intelligence, Universidad de Navarra, Campus Universitario, 31009 Pamplona, Spain
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Jovanova M, Cosme D, Doré B, Kang Y, Stanoi O, Cooper N, Helion C, Lomax S, McGowan AL, Boyd ZM, Bassett DS, Mucha PJ, Ochsner KN, Lydon-Staley DM, Falk EB. Psychological distance intervention reminders reduce alcohol consumption frequency in daily life. Sci Rep 2023; 13:12045. [PMID: 37491371 PMCID: PMC10368637 DOI: 10.1038/s41598-023-38478-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 07/09/2023] [Indexed: 07/27/2023] Open
Abstract
Modifying behaviors, such as alcohol consumption, is difficult. Creating psychological distance between unhealthy triggers and one's present experience can encourage change. Using two multisite, randomized experiments, we examine whether theory-driven strategies to create psychological distance-mindfulness and perspective-taking-can change drinking behaviors among young adults without alcohol dependence via a 28-day smartphone intervention (Study 1, N = 108 participants, 5492 observations; Study 2, N = 218 participants, 9994 observations). Study 2 presents a close replication with a fully remote delivery during the COVID-19 pandemic. During weeks when they received twice-a-day intervention reminders, individuals in the distancing interventions reported drinking less frequently than on control weeks-directionally in Study 1, and significantly in Study 2. Intervention reminders reduced drinking frequency but did not impact amount. We find that smartphone-based mindfulness and perspective-taking interventions, aimed to create psychological distance, can change behavior. This approach requires repeated reminders, which can be delivered via smartphones.
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Affiliation(s)
- Mia Jovanova
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, USA.
| | - Danielle Cosme
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, USA
| | - Bruce Doré
- Desautels Faculty of Management, McGill University, Montreal, Canada
| | - Yoona Kang
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, USA
| | - Ovidia Stanoi
- Department of Psychology, Columbia University, New York, USA
| | - Nicole Cooper
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, USA
| | - Chelsea Helion
- Department of Psychology, Temple University, Philadelphia, USA
| | - Silicia Lomax
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, USA
| | - Amanda L McGowan
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, USA
| | - Zachary M Boyd
- Mathematics Department, Brigham Young University, Provo, USA
| | - Dani S Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, USA
- Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, USA
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, USA
- Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, USA
- The Santa Fe Institute, Santa Fe, USA
| | - Peter J Mucha
- Department of Mathematics, Dartmouth College, Hanover, USA
| | - Kevin N Ochsner
- Department of Psychology, Columbia University, New York, USA
| | - David M Lydon-Staley
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, USA
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, USA
| | - Emily B Falk
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, USA.
- Department of Psychology, University of Pennsylvania, Philadelphia, USA.
- Wharton Marketing Department, University of Pennsylvania, Philadelphia, USA.
- Wharton Operations, Information and Decisions Department, University of Pennsylvania, Philadelphia, USA.
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Zhou D, Kang Y, Cosme D, Jovanova M, He X, Mahadevan A, Ahn J, Stanoi O, Brynildsen JK, Cooper N, Cornblath EJ, Parkes L, Mucha PJ, Ochsner KN, Lydon-Staley DM, Falk EB, Bassett DS. Mindful attention promotes control of brain network dynamics for self-regulation and discontinues the past from the present. Proc Natl Acad Sci U S A 2023; 120:e2201074119. [PMID: 36595675 PMCID: PMC9926276 DOI: 10.1073/pnas.2201074119] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Accepted: 10/17/2022] [Indexed: 01/05/2023] Open
Abstract
Mindful attention is characterized by acknowledging the present experience as a transient mental event. Early stages of mindfulness practice may require greater neural effort for later efficiency. Early effort may self-regulate behavior and focalize the present, but this understanding lacks a computational explanation. Here we used network control theory as a model of how external control inputs-operationalizing effort-distribute changes in neural activity evoked during mindful attention across the white matter network. We hypothesized that individuals with greater network controllability, thereby efficiently distributing control inputs, effectively self-regulate behavior. We further hypothesized that brain regions that utilize greater control input exhibit shorter intrinsic timescales of neural activity. Shorter timescales characterize quickly discontinuing past processing to focalize the present. We tested these hypotheses in a randomized controlled study that primed participants to either mindfully respond or naturally react to alcohol cues during fMRI and administered text reminders and measurements of alcohol consumption during 4 wk postscan. We found that participants with greater network controllability moderated alcohol consumption. Mindful regulation of alcohol cues, compared to one's own natural reactions, reduced craving, but craving did not differ from the baseline group. Mindful regulation of alcohol cues, compared to the natural reactions of the baseline group, involved more-effortful control of neural dynamics across cognitive control and attention subnetworks. This effort persisted in the natural reactions of the mindful group compared to the baseline group. More-effortful neural states had shorter timescales than less effortful states, offering an explanation for how mindful attention promotes being present.
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Affiliation(s)
- Dale Zhou
- Neuroscience Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
| | - Yoona Kang
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA 19104
| | - Danielle Cosme
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA 19104
| | - Mia Jovanova
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA 19104
| | - Xiaosong He
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104
- Department of Psychology, School of Humanities and Social Sciences, University of Science and Technology of China, 230026 Hefei, People’s Republic of China
| | - Arun Mahadevan
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104
| | - Jeesung Ahn
- Department of Psychology, University of Pennsylvania, Philadelphia, PA 19104
| | - Ovidia Stanoi
- Department of Psychology, Columbia University, New York, NY 19104
| | - Julia K. Brynildsen
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104
| | - Nicole Cooper
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA 19104
| | - Eli J. Cornblath
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104
| | - Linden Parkes
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104
| | - Peter J. Mucha
- Department of Mathematics, Dartmouth College, Hanover, NH 03755
| | - Kevin N. Ochsner
- Department of Psychology, Columbia University, New York, NY 19104
| | - David M. Lydon-Staley
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA 19104
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA 19104
| | - Emily B. Falk
- Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA 19104
- Department of Psychology, University of Pennsylvania, Philadelphia, PA 19104
- Marketing Department, Wharton School, University of Pennsylvania, Philadelphia, PA 19104
| | - Dani S. Bassett
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104
- Department of Physics & Astronomy, College of Arts and Sciences, University of Pennsylvania, Philadelphia, PA 19104
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
- Department of Electrical & Systems Engineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
- Santa Fe Institute, Santa Fe, NM 87501
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Raj A, Verma P, Nagarajan S. Structure-function models of temporal, spatial, and spectral characteristics of non-invasive whole brain functional imaging. Front Neurosci 2022; 16:959557. [PMID: 36110093 PMCID: PMC9468900 DOI: 10.3389/fnins.2022.959557] [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] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 07/27/2022] [Indexed: 11/29/2022] Open
Abstract
We review recent advances in using mathematical models of the relationship between the brain structure and function that capture features of brain dynamics. We argue the need for models that can jointly capture temporal, spatial, and spectral features of brain functional activity. We present recent work on spectral graph theory based models that can accurately capture spectral as well as spatial patterns across multiple frequencies in MEG reconstructions.
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Affiliation(s)
- Ashish Raj
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
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