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Matsui R, Aoyama T, Kato K, Hasegawa Y. Real-time motion force-feedback system with predictive-vision for improving motor accuracy. Sci Rep 2024; 14:2168. [PMID: 38272970 PMCID: PMC10810826 DOI: 10.1038/s41598-024-52811-z] [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: 05/29/2023] [Accepted: 01/23/2024] [Indexed: 01/27/2024] Open
Abstract
Many haptic guidance systems have been studied over the years; however, most of them have been limited to predefined guidance methods. Calculating guidance according to the operator's motion is important for efficient human motor adaptation and learning. In this study, we developed a system that haptically provides guidance trajectory by sequential weighting between the operator's trajectory and the ideal trajectory calculated from a predictive-vision system. We investigated whether motion completion with a predictive-vision system affects human motor accuracy and adaptation in time-constrained goal-directed reaching and ball-hitting tasks through subject experiments. The experiment was conducted with 12 healthy participants, and all participants performed ball-hitting tasks. Half of the participants get forceful guidance from the proposed system in the middle of the experiment. We found that the use of the proposed system improved the operator's motor performance. Furthermore, we observed a trend in which the improvement in motor performance using this system correlated with that after the washout of this system. These results suggest that the predictive-vision system effectively enhances motor accuracy to the target error in dynamic and time-constrained reaching and hitting tasks and may contribute to facilitating motor learning.
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Affiliation(s)
- Ryo Matsui
- The Development of Micro-Nano Mechanical Science and Engineering, Nagoya University, Nagoya, Aichi, 464-8603, Japan
| | - Tadayoshi Aoyama
- The Development of Micro-Nano Mechanical Science and Engineering, Nagoya University, Nagoya, Aichi, 464-8603, Japan.
| | - Kenji Kato
- Assistive Robot Center, National Center for Geriatrics and Gerontology, Obu, Aichi, 474-8511, Japan.
| | - Yasuhisa Hasegawa
- The Development of Micro-Nano Mechanical Science and Engineering, Nagoya University, Nagoya, Aichi, 464-8603, Japan
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Walhovd KB, Bråthen ACS, Panizzon MS, Mowinckel AM, Sørensen Ø, de Lange AMG, Krogsrud SK, Håberg A, Franz CE, Kremen WS, Fjell AM. Within-session verbal learning slope is predictive of lifespan delayed recall, hippocampal volume, and memory training benefit, and is heritable. Sci Rep 2020; 10:21158. [PMID: 33273630 PMCID: PMC7713377 DOI: 10.1038/s41598-020-78225-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2019] [Accepted: 11/12/2020] [Indexed: 11/09/2022] Open
Abstract
Memory performance results from plasticity, the ability to change with experience. We show that benefit from practice over a few trials, learning slope, is predictive of long-term recall and hippocampal volume across a broad age range and a long period of time, relates to memory training benefit, and is heritable. First, in a healthy lifespan sample (n = 1825, age 4-93 years), comprising 3483 occasions of combined magnetic resonance imaging (MRI) scans and memory tests over a period of up to 11 years, learning slope across 5 trials was uniquely related to performance on a delayed free recall test, as well as hippocampal volume, independent from first trial memory or total memory performance across the five learning trials. Second, learning slope was predictive of benefit from memory training across ten weeks in an experimental subsample of adults (n = 155). Finally, in an independent sample of male twins (n = 1240, age 51-50 years), learning slope showed significant heritability. Within-session learning slope may be a useful marker beyond performance per se, being heritable and having unique predictive value for long-term memory function, hippocampal volume and training benefit across the human lifespan.
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Affiliation(s)
- Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, POB 1094, 0317, Oslo, Norway.
- Division of Radiology and Nuclear Medicine, Oslo University Hospital, Rikshospitalet, Norway.
| | - Anne Cecilie Sjøli Bråthen
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, POB 1094, 0317, Oslo, Norway
| | - Matthew S Panizzon
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California, San Diego, USA
| | - Athanasia M Mowinckel
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, POB 1094, 0317, Oslo, Norway
| | - Øystein Sørensen
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, POB 1094, 0317, Oslo, Norway
| | - Ann-Marie G de Lange
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, POB 1094, 0317, Oslo, Norway
- Department of Psychiatry, University of Oxford, Oxford, UK
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Stine Kleppe Krogsrud
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, POB 1094, 0317, Oslo, Norway
| | - Asta Håberg
- Department of Neuroscience, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Carol E Franz
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California, San Diego, USA
| | - William S Kremen
- Department of Psychiatry and Center for Behavior Genetics of Aging, University of California, San Diego, USA
| | - Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, POB 1094, 0317, Oslo, Norway
- Division of Radiology and Nuclear Medicine, Oslo University Hospital, Rikshospitalet, Norway
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Flores-Lázaro JC, Salgado Soruco MA, Stepanov II. Children and adolescents' performance on a medium-length/nonsemantic word-list test. APPLIED NEUROPSYCHOLOGY. CHILD 2017; 6:95-105. [PMID: 28375761 DOI: 10.1080/21622965.2015.1033099] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Word-list learning tasks are among the most important and frequently used tests for declarative memory evaluation. For example, the California Verbal Learning Test-Children's Version (CVLT-C) and Rey Auditory Verbal Learning Test provide important information about different cognitive-neuropsychological processes. However, the impact of test length (i.e., number of words) and semantic organization (i.e., type of words) on children's and adolescents' memory performance remains to be clarified, especially during this developmental stage. To explore whether a medium-length non-semantically organized test can produce the typical curvilinear performance that semantically organized tests produce, reflecting executive control, we studied and compared the cognitive performance of normal children and adolescents by utilizing mathematical modeling. The model is based on the first-order system transfer function and has been successfully applied to learning curves for the CVLT-C (15 words, semantically organized paradigm). Results indicate that learning nine semantically unrelated words produces typical curvilinear (executive function) performance in children and younger adolescents and that performance could be effectively analyzed with the mathematical model. This indicates that the exponential increase (curvilinear performance) of correctly learned words does not solely depend on semantic and/or length features. This type of test controls semantic and length effects and may represent complementary tools for executive function evaluation in clinical populations in which semantic and/or length processing are affected.
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Affiliation(s)
- Julio César Flores-Lázaro
- a Child Psychiatry Hospital, DJNN-National Institutes of Health-México, and Psychology Faculty , National Autonomous University of México , Mexico City , Mexico
| | | | - Igor I Stepanov
- c Department of Neuropharmacology , Institute for Experimental Medicine , St. Petersburg , Russia
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The First Order Transfer Function in the Analysis of Agrochemical Data in Honey Bees (Apis Mellifera L.): Proboscis Extension Reflex (PER) Studies. INSECTS 2014; 5:167-98. [PMID: 26462584 PMCID: PMC4592627 DOI: 10.3390/insects5010167] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 10/14/2013] [Revised: 11/04/2013] [Accepted: 12/23/2013] [Indexed: 11/17/2022]
Abstract
This paper describes a mathematical model of the learning process suitable for studies of conditioning using the proboscis extension reflex (PER) in honey bees when bees are exposed to agrochemicals. Although procedural variations exist in the way laboratories use the PER paradigm, proboscis conditioning is widely used to investigate the influence of pesticides and repellents on honey bee learning. Despite the availability of several mathematical models of the learning process, no attempts have been made to apply a mathematical model to the learning curve in honey bees exposed to agrochemicals. Our model is based on the standard transfer function in the form Y = B3e−B2 (X−1) + B4 (1−e−B2 (X−1)) where X is the trial number, Y is the proportion of correct responses, B2 is the learning rate, B3 is readiness to learn, and B4 is ability to learn. We reanalyze previously published data on the effect of several classes of agrochemicals including: (1) those that are considered harmless to bees (e.g., pymetrozine, essential oils, dicofol); (2) sublethal exposure to pesticides known to harm honey bees (e.g., coumaphos, cyfluthrin, fluvalinate, permethrin); and (3) putative repellents of honey bees (e.g., butyric acid, citronella). The model revealed additional effects not detected with standard statistical tests of significance.
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Stepanov II, Abramson CI, Hoogs M, Benedict RHB. Overall Memory Impairment Identification with Mathematical Modeling of the CVLT-II Learning Curve in Multiple Sclerosis. Mult Scler Int 2012; 2012:312503. [PMID: 22745911 PMCID: PMC3382211 DOI: 10.1155/2012/312503] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2011] [Revised: 03/04/2012] [Accepted: 04/13/2012] [Indexed: 11/17/2022] Open
Abstract
The CVLT-II provides standardized scores for each of the List A five learning trials, so that the clinician can compare the patient's raw trials 1-5 scores with standardized ones. However, frequently, a patient's raw scores fluctuate making a proper interpretation difficult. The CVLT-II does not offer any other methods for classifying a patient's learning and memory status on the background of the learning curve. The main objective of this research is to illustrate that discriminant analysis provides an accurate assessment of the learning curve, if suitable predictor variables are selected. Normal controls were ninety-eight healthy volunteers (78 females and 20 males). A group of MS patients included 365 patients (266 females and 99 males) with clinically defined multiple sclerosis. We show that the best predictor variables are coefficients B3 and B4 of our mathematical model B3 ∗ exp(-B2 ∗ (X - 1)) + B4 ∗ (1 - exp(-B2 ∗ (X - 1))) because discriminant functions, calculated separately for B3 and B4, allow nearly 100% correct classification. These predictors allow identification of separate impairment of readiness to learn or ability to learn, or both.
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Affiliation(s)
- Igor I. Stepanov
- Department of Neuropharmacology, Institute for Experimental Medicine, The Russian Academy of Medical Sciences, Acad. Pavlov Street 12, 197376 St. Petersburg, Russia
| | - Charles I. Abramson
- Department of Psychology, Oklahoma State University, 116 N. Murray, Stillwater, OK 74078, USA
| | - Marietta Hoogs
- The Jacobs Neurological Institute, Buffalo General Hospital, 100 High Street, Buffalo, NY 14203, USA
| | - Ralph H. B. Benedict
- The Jacobs Neurological Institute, Buffalo General Hospital, 100 High Street, Buffalo, NY 14203, USA
- Department of Neurology, State University of New York (SUNY) at Buffalo, Buffalo General Hospital, Suite D6, 100 High Street, Buffalo, NY 14203, USA
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Abramson CI, Stepanov II. The use of the first order system transfer function in the analysis of proboscis extension learning of honey bees, Apis mellifera L., exposed to pesticides. BULLETIN OF ENVIRONMENTAL CONTAMINATION AND TOXICOLOGY 2012; 88:559-562. [PMID: 22218746 DOI: 10.1007/s00128-011-0512-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2011] [Accepted: 12/28/2011] [Indexed: 05/31/2023]
Abstract
No attempts have been made to apply a mathematical model to the learning curve in honey bees exposed to pesticides. We applied a standard transfer function in the form Y = B3*exp(- B2 * (X - 1)) + B4 * (1 - exp(- B2 * (X - 1))), where X is the trial number; Y is proportion of correct responses, B2 is the learning rate, B3 is readiness to learn and B4 is ability to learn. Reanalyzing previously published data on the effect of insect growth regulators tebufenozide and diflubenzuron on the classical conditioning of proboscis extension, the model revealed additional effects not detected with standard statistical tests of significance.
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Affiliation(s)
- Charles I Abramson
- Department of Psychology, Oklahoma State University, 116 N. Murray, Stillwater, OK 74078, USA.
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