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作者： Bergsman, Kristen Clapper Weber, Jill Lynn Chudler, Eric H. Center for Sensorimotor Neural Engineering University of Washington United States Center for Research and Learning United States

The Research Experience for Teachers (RET) program, supported by the National Science Foundation, engages pre-college teachers in authentic research experiences in university-based laboratories across the country. Some RET program sites engage science teachers in engineering research. With A Framework for K-12 Science and engineering Education [1] and the Next Generation Science Standards [2] calling for the integration of engineering practices into science classes, K-12 teachers need support in being prepared to bring engineering design to their students. The center for sensorimotor neural engineering at the University of Washington has hosted a RET program for secondary science teachers since 2012, engaging a total of 22 teachers. This seven-week RET summer program was designed to provide science teachers with authentic research experiences in neural engineering labs and insights into the practices of professional engineers. The program also supports participating teachers as they design, implement, and revise engineering curriculum materials for their classrooms and for broad dissemination to other educators. over 2,862 students have participated in activities from the RET curriculum units. In this paper, we describe the design of the RET program, the program evaluation methods implemented by an external evaluator, and our evaluation findings. We report yearly evaluation findings as well as trends over the program's six year history. By sharing information on program design and longitudinal evaluation findings, RET program coordinators at other sites may benefit from our lessons learned and the best practices we have developed over the program's history. © American Society for engineering Education, 2018.

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Transformational sparse coding

arXiv

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arXiv 2017年

作者： Gklezakos, Dimitrios C. Rao, Rajesh P.N. Department of Computer Science Center for Sensorimotor Neural Engineering University of Washington SeattleWA98105 United States

A fundamental problem faced by object recognition systems is that objects and their features can appear in different locations, scales and orientations. Current deep learning methods attempt to achieve invariance to local translations via pooling, discarding the locations of features in the process. Other approaches explicitly learn transformed versions of the same feature, leading to representations that quickly explode in size. Instead of discarding the rich and useful information about feature transformations to achieve invariance, we argue that models should learn object features conjointly with their transformations to achieve equivariance. We propose a new model of unsupervised learning based on sparse coding that can learn object features jointly with their affine transformations directly from images. Results based on learning from natural images indicate that our approach matches the reconstruction quality of traditional sparse coding but with significantly fewer degrees of freedom while simultaneously learning transformations from data. These results open the door to scaling up unsupervised learning to allow deep feature+transformation learning in a manner consistent with the ventral+dorsal stream architecture of the primate visual cortex. Copyright © 2017, The Authors. All rights reserved.

关键词： Degrees of freedom (mechanics)

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In Vivo Dopamine Detection and Single Unit Recordings Using Intracortical Glassy Carbon Microelectrode Arrays

In Vivo Dopamine Detection and Single Unit Recordings Using ...

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MRS Advances

作者： Castagnola, Elisa Winchester Vahidi, Nasim Nimbalkar, Surabhi Rudraraju, Srihita Thielk, Marvin Zucchini, Elena Cea, Claudia Carli, Stefano Gentner, Timothy Q. Ricci, Davide Fadiga, Luciano Kassegne, Sam MEMS Research Lab. Department of Mechanical Engineering College of Engineering San Diego State University 5500 Campanile Drive San DiegoCA92182-1323 United States Center for Sensorimotor Neural Engineering Box 37 1414 NE 42nd St SeattleWA98105-6271 United States Dept. of Electrical Engineering University of California San Diego San DiegoCA92093 United States Neurosciences Graduate Program University of California San Diego 9500 Gilman Dr San DiegoCA United States Department of Bioengineering University of California San Diego San DiegoCA United States Center for Translational Neurophysiology of Speech and Communication Istituto Italiano di Tecnologia Via Fossato di Mortara 17/19 Ferrara44121 Italy Department of Human Physiology University of Ferrara Via Fossato di Mortara 17/19 Ferrara44121 Italy

In this study, we present a 4-channel intracortical glassy carbon (GC) microelectrode array on a flexible substrate for the simultaneous in vivo neural activity recording and dopamine (DA) concentration measurement at four different brain locations (220m vertical spacing). The ability of GC microelectrodes to detect DA was firstly assessed in vitro in phosphate-buffered saline solution and then validated in vivo measuring spontaneous DA concentration in the Striatum of European Starling songbird through fast scan cyclic voltammetry(FSCV). The capability of GC microelectrode arrays and commercial penetrating metal microelectrode arrays to record neural activity from the Caudomedial Neostriatum of European starling songbird was compared. Preliminary results demonstrated the ability of GC microelectrodes in detecting neurotransmitters release and recording neural activity in vivo. GC microelectrodes array may, therefore, offer a new opportunity to understand the intimate relations linking electrophysiological parameters with neurotransmitters release. © 2018 Materials Research Society.

关键词： Microelectrodes Amines Birds Brain Carbon Cyclic voltammetry Electrophysiology Glass Glassy carbon Microelectronics Neurons Sensors Carbon microelectrodes Concentration Measurement devices Fast scan cyclic voltammetry Microelectrode array Microelectrodes arrays Phosphate buffered saline solutions Single unit recordings

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Staying in the Loop: Relational Agency and Identity in Next-Generation DBS for Psychiatry

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AJOB Neuroscience 2017年第2期8卷 59-70页

作者： Goering, Sara Klein, Eran Dougherty, Darin D. Widge, Alik S. University of Washington Center for Sensorimotor Neural Engineering United States University of Washington Center for Sensorimotor Neural Engineering Oregon Health and Science University United States Massachusetts General Hospital Harvard Medical School United States Massachusetts General Hospital Harvard Medical School Massachusetts Institute of Technology United States

In this article, we explore how deep brain stimulation (DBS) devices designed to “close the loop”—to automatically adjust stimulation levels based on computational algorithms—may risk taking the individual agent “out of the loop” of control in areas where (at least apparent) conscious control is a hallmark of our agency. This is of particular concern in the area of psychiatric disorders, where closed-loop DBS is attracting increasing attention as a therapy. Using a relational model of identity and agency, we consider whether DBS designed for psychiatric regulation may require special attention to agency. To do this, we draw on philosophical work on relational identity and agency, connecting it with reports from people using first-generation DBS devices for depression and obsessive-compulsive disorder. We suggest a way to extend a notion of relational agency to encompass neural devices. © 2017, Copyright © Taylor & Francis Group, LLC.

关键词： brain–computer interfaces deep brain stimulation depression mental health neuromodulation personal identity

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Correction to: Deflating the “DBS causes personality changes” bubble

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Neuroethics 2018年第1期14卷 21-21页

作者： Gilbert, Frederic Viaña, J. N. M. Ineichen, C. Center for Sensorimotor Neural Engineering Department of Philosophy University of Washington Seattle USA CALE School of Humanities University of Tasmania Hobart Australia Department of Psychiatry Psychotherapy and Psychosomatics Psychiatric Hospital Zurich Zurich Switzerland Institute of Biomedical Ethics and History of Medicine University of Zurich Zurich Switzerland

The article Deflating the "DBS causes personality changes" bubble, written by Frederic Gilbert, J. N. M. Viaña and C. Ineichen, was originally published electronically on the publisher’s internet porta...

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Erratum to 'Fast Electrophysiological Mapping of Rat Cortical Motor Representation on a Time Scale of Minutes during Skin Stimulation' [Neuroscience 414C (2019) 245-254]

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Neuroscience 2019年 416卷 294页

作者： Akito Kosugi Elisa Castagnola Stefano Carli Davide Ricci Luciano Fadiga Miki Taoka Atsushi Iriki Junichi Ushiba Graduate School of Science and Technology Keio University Kanagawa Japan Laboratory for Symbolic Cognitive Development RIKEN Brain Science Institute Saitama Japan Laboratory for Symbolic Cognitive Development RIKEN Center for Biosystems Dynamics Research Saitama Japan. Center for Translational Neurophysiology of Speech and Communication Istituto Italiano di Tecnologia Ferrara Italy Center for Sensorimotor Neural Engineering San Diego State University San Diego CA United States. Center for Translational Neurophysiology of Speech and Communication Istituto Italiano di Tecnologia Ferrara Italy. Section of Human Physiology University of Ferrara Ferrara Italy. Department of Bioscience and Informatics Faculty of Science and Technology Keio University Kanagawa Japan Keio Institute of Pure and Applied Sciences Keio University Kanagawa Japan. Electronic address: ushiba@brain.bio.keio.ac.jp.

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Personal responsibility in the age of user-controlled neuroprosthetics

Personal responsibility in the age of user-controlled neurop...

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IEEE International Symposium on Ethics in Science, Technology and engineering

作者： Timothy Brown Patrick Moore Jeffrey Herron Margaret Thompson Tamara Bonaci Howard Chizeck Sara Goering Center for Sensorimotor Neural Engineering University of Washington Seattle Department of Philosophy School of Law Department of Electrical Engineering Department of Bioengineering

Deep-brain stimulation systems are an accepted and clinically effective form of neuroprosthetic treatment for a variety of common and debilitating neurological movement disorders: Essential Tremor, Parkinson's, and others. Most current implementations of DBS are "open-loop:" they remain active continuously, whether or not the user is experiencing symptoms. Recent research suggests that it is possible to devise more advanced systems where stimulation is delivered on demand. Their research offers a proof-of-concept for a Brain-Computer Interface-triggered DBS (BCI-DBS) system capable of detecting either signs of tremor or the user's neural commands through an additional set of co-implanted sensors. The system then delivers stimulation to meet the user's needs or demands. These technologies, however, come with a set of moral problems - in particular, problems for personal responsibility. This paper investigates whether giving users moment-to-moment neural control over their DBS system is ethically responsible given that users can make bad choices and thus harm others. We also ask what responsibilities medical professionals have have to support users as they learn to adapt to neuroprosthetic use. We guide our exploration of these issues through a series of hypothetical scenarios that BCI-DBS users may face.

关键词： Satellite broadcasting Sensor systems Parkinson's disease Implants Real-time systems

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Application of multivariate empirical mode decomposition and canonical correlation analysis for EEG motion artifact removal

Application of multivariate empirical mode decomposition and...

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Conference on Advances in Signal Processing (CASP)

作者： Siddhi Tavildar Ashkan Ashrafi Center for Sensorimotor Neural Engineering San Diego State University Department of Electrical and Computer Engineering San Diego State University

ISBN: (纸本)9781509008506

Electroencephalogram (EEG) is a tool to record the electrical activity of brain. It often records artifacts which are the electrical activities originating from sites other than brain. The presence of artifacts is undesirable as it increases the probability of misinterpretation that may result in adverse clinical consequences. In this paper, we present a novel method of motion artifact removal from the EEG signals. The proposed method employs multivariate empirical mode decomposition (MEMD) with canonical correlation analysis (CCA) for the removal of motion artifacts from EEG signal. The mode alignment property of the multivariate empirical mode decomposition is used in EEG signal analysis where a similarity between different channels is the key to decode the signals. When compared with the results of existing methods for motion artifacts removal on the same data set, the MEMD-CCA is shown to perform better with 16 % increase in the percent artifact removal. Unlike the other competing methods, this method is totally algorithmic and does not require any manual intervention.

关键词： Electroencephalography Correlation Electrodes Accelerometers Empirical mode decomposition Algorithm design and analysis

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