Pub Date : 2015-03-04DOI: 10.1103/PhysRevApplied.4.024001
J. S. Ho, Y. Tanabe, S. Iyer, A. Christensen, L. Grosenick, K. Deisseroth, S. Delp, A. Poon
Optical or electrical stimulation of neural circuits in mice during natural behavior is an important paradigm for studying brain function. Conventional systems for optogenetics and electrical microstimulation require tethers or large head-mounted devices that disrupt animal behavior. We report a method for wireless powering of small-scale implanted devices based on the strong localization of energy that occurs during resonant interaction between a radio-frequency cavity and intrinsic modes in mice. The system features self-tracking over a wide (16 cm diameter) operational area, and is used to demonstrate wireless activation of cortical neurons with miniaturized stimulators (10 mm$^{3}$, 20 mg) fully implanted under the skin.
{"title":"Self-tracking Energy Transfer for Neural Stimulation in Untethered Mice","authors":"J. S. Ho, Y. Tanabe, S. Iyer, A. Christensen, L. Grosenick, K. Deisseroth, S. Delp, A. Poon","doi":"10.1103/PhysRevApplied.4.024001","DOIUrl":"https://doi.org/10.1103/PhysRevApplied.4.024001","url":null,"abstract":"Optical or electrical stimulation of neural circuits in mice during natural behavior is an important paradigm for studying brain function. Conventional systems for optogenetics and electrical microstimulation require tethers or large head-mounted devices that disrupt animal behavior. We report a method for wireless powering of small-scale implanted devices based on the strong localization of energy that occurs during resonant interaction between a radio-frequency cavity and intrinsic modes in mice. The system features self-tracking over a wide (16 cm diameter) operational area, and is used to demonstrate wireless activation of cortical neurons with miniaturized stimulators (10 mm$^{3}$, 20 mg) fully implanted under the skin.","PeriodicalId":298664,"journal":{"name":"arXiv: Neurons and Cognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128302993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-01-08DOI: 10.1007/978-1-4614-7320-6_280-1
S. Schultz, Robin A. A. Ince, S. Panzeri
{"title":"Applications of Information Theory to Analysis of Neural Data","authors":"S. Schultz, Robin A. A. Ince, S. Panzeri","doi":"10.1007/978-1-4614-7320-6_280-1","DOIUrl":"https://doi.org/10.1007/978-1-4614-7320-6_280-1","url":null,"abstract":"","PeriodicalId":298664,"journal":{"name":"arXiv: Neurons and Cognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128388591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-01-08DOI: 10.1007/978-1-4614-7320-6_306-1
Robin A. A. Ince, S. Panzeri, S. Schultz
{"title":"Summary of Information Theoretic Quantities","authors":"Robin A. A. Ince, S. Panzeri, S. Schultz","doi":"10.1007/978-1-4614-7320-6_306-1","DOIUrl":"https://doi.org/10.1007/978-1-4614-7320-6_306-1","url":null,"abstract":"","PeriodicalId":298664,"journal":{"name":"arXiv: Neurons and Cognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132473809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-01-08DOI: 10.1007/978-1-4614-7320-6_140-1
Robin A. A. Ince, S. Schultz, S. Panzeri
{"title":"Estimating Information-Theoretic Quantities","authors":"Robin A. A. Ince, S. Schultz, S. Panzeri","doi":"10.1007/978-1-4614-7320-6_140-1","DOIUrl":"https://doi.org/10.1007/978-1-4614-7320-6_140-1","url":null,"abstract":"","PeriodicalId":298664,"journal":{"name":"arXiv: Neurons and Cognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116610609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-01-07DOI: 10.7287/peerj.preprints.777v3
Apoorvagiri, M. S. Nagananda
The aim of this study is to quantize mental stress by integrating different physiological markers like reaction time, photoplethysmograph (PPG), heart rate variability (HRV) and subjective markers like questionnaire. The study included 10 subjects of age between 22 and 26 years. Study materials included the results of PSS questionnaire, simple reaction time, PPG data, and HRV data during a stress inducing stroop test. The study suggests that mental stress can be quantized when stress is induced acquisitively and more accurate quantification of stress can be achieved by integrating many physiological parameters.
{"title":"Quantization of mental stress using various physiological markers","authors":"Apoorvagiri, M. S. Nagananda","doi":"10.7287/peerj.preprints.777v3","DOIUrl":"https://doi.org/10.7287/peerj.preprints.777v3","url":null,"abstract":"The aim of this study is to quantize mental stress by integrating different physiological markers like reaction time, photoplethysmograph (PPG), heart rate variability (HRV) and subjective markers like questionnaire. The study included 10 subjects of age between 22 and 26 years. Study materials included the results of PSS questionnaire, simple reaction time, PPG data, and HRV data during a stress inducing stroop test. The study suggests that mental stress can be quantized when stress is induced acquisitively and more accurate quantification of stress can be achieved by integrating many physiological parameters.","PeriodicalId":298664,"journal":{"name":"arXiv: Neurons and Cognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128961890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Pascual-Marqui, D. Lehmann, P. Faber, P. Milz, K. Kochi, M. Yoshimura, K. Nishida, T. Isotani, T. Kinoshita
A brain microstate is characterized by a unique, fixed spatial distribution of electrically active neurons with time varying amplitude. It is hypothesized that a microstate implements a functional/physiological state of the brain during which specific neural computations are performed. Based on this hypothesis, brain electrical activity is modeled as a time sequence of non-overlapping microstates with variable, finite durations (Lehmann and Skrandies 1980, 1984; Lehmann et al 1987). In this study, EEG recordings from 109 participants during eyes closed resting condition are modeled with four microstates. In a first part, a new confirmatory statistics method is introduced for the determination of the cortical distributions of electric neuronal activity that generate each microstate. All microstates have common posterior cingulate generators, while three microstates additionally include activity in the left occipital/parietal, right occipital/parietal, and anterior cingulate cortices. This appears to be a fragmented version of the metabolically (PET/fMRI) computed default mode network (DMN), supporting the notion that these four regions activate sequentially at high time resolution, and that slow metabolic imaging corresponds to a low-pass filtered version. In the second part of this study, the microstate amplitude time series are used as the basis for estimating the strength, directionality, and spectral characteristics (i.e., which oscillations are preferentially transmitted) of the connections that are mediated by the microstate transitions. The results show that the posterior cingulate is an important hub, sending alpha and beta oscillatory information to all other microstate generator regions. Interestingly, beyond alpha, beta oscillations are essential in the maintenance of the brain during resting state.
脑微状态的特征是具有时变振幅的电活动神经元具有独特的、固定的空间分布。假设微状态实现了大脑的功能/生理状态，在此期间执行特定的神经计算。基于这一假设，脑电活动被建模为具有可变、有限持续时间的非重叠微观状态的时间序列(Lehmann和Skrandies 1980, 1984;Lehmann et al . 1987)。在本研究中，109名参与者在闭眼休息状态下的脑电图记录被建模为四种微观状态。在第一部分中，介绍了一种新的验证性统计方法，用于确定产生每种微状态的电神经元活动的皮层分布。所有微状态都有共同的后扣带产生器，而另外三种微状态包括左枕/顶叶皮层、右枕/顶叶皮层和前扣带皮层的活动。这似乎是代谢(PET/fMRI)计算的默认模式网络(DMN)的碎片化版本，支持这四个区域在高时间分辨率下顺序激活的概念，而慢代谢成像对应于低通滤波版本。在本研究的第二部分中，将微态振幅时间序列作为估计由微态转换介导的连接的强度、方向性和频谱特征(即哪些振荡优先传播)的基础。结果表明，后扣带是一个重要的中枢，将α和β振荡信息发送到所有其他微态产生区域。有趣的是，除了α振荡外，β振荡对大脑在静息状态下的维持也是必不可少的。
{"title":"The resting microstate networks (RMN): cortical distributions, dynamics, and frequency specific information flow","authors":"R. Pascual-Marqui, D. Lehmann, P. Faber, P. Milz, K. Kochi, M. Yoshimura, K. Nishida, T. Isotani, T. Kinoshita","doi":"10.5167/UZH-100596","DOIUrl":"https://doi.org/10.5167/UZH-100596","url":null,"abstract":"A brain microstate is characterized by a unique, fixed spatial distribution of electrically active neurons with time varying amplitude. It is hypothesized that a microstate implements a functional/physiological state of the brain during which specific neural computations are performed. Based on this hypothesis, brain electrical activity is modeled as a time sequence of non-overlapping microstates with variable, finite durations (Lehmann and Skrandies 1980, 1984; Lehmann et al 1987). In this study, EEG recordings from 109 participants during eyes closed resting condition are modeled with four microstates. In a first part, a new confirmatory statistics method is introduced for the determination of the cortical distributions of electric neuronal activity that generate each microstate. All microstates have common posterior cingulate generators, while three microstates additionally include activity in the left occipital/parietal, right occipital/parietal, and anterior cingulate cortices. This appears to be a fragmented version of the metabolically (PET/fMRI) computed default mode network (DMN), supporting the notion that these four regions activate sequentially at high time resolution, and that slow metabolic imaging corresponds to a low-pass filtered version. In the second part of this study, the microstate amplitude time series are used as the basis for estimating the strength, directionality, and spectral characteristics (i.e., which oscillations are preferentially transmitted) of the connections that are mediated by the microstate transitions. The results show that the posterior cingulate is an important hub, sending alpha and beta oscillatory information to all other microstate generator regions. Interestingly, beyond alpha, beta oscillations are essential in the maintenance of the brain during resting state.","PeriodicalId":298664,"journal":{"name":"arXiv: Neurons and Cognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124429742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
There are significant analogies between the issues related to real-time event selection in HEP, and the issues faced by the human visual system. In fact, the visual system needs to extract rapidly the most important elements of the external world from a large flux of information, for survival purposes. A rapid and reliable detection of visual stimuli is essential for triggering autonomic responses to emotive stimuli, for initiating adaptive behaviors and for orienting towards potentially interesting/ dangerous stimuli. The speed of visual processing can be as fast as 20 ms, about only 20 times the duration of the elementary information exchanges by the action potential. The limitations to the brain capacity to process visual information, imposed by intrinsic energetic costs of neuronal activity, and ecological limits to the size of the skull, require a strong data reduction at an early stage, by creating a compact summary of relevant information, the so called "primal sketch", to be handled by further levels of processing. This is quite similar to the problem of experimental HEP of providing fast data reduction at a reasonable monetary cost, and with a practical device size. As a result of a joint effort of HEP physicists and practicing vision scientists, we recently proposed that not only the problems are similar, but the solutions adopted in the two cases also have strong similarities, and their parallel study can actually shed light on each other. Modeling the visual system as a trigger processor leads to a deeper understanding, and even very specific predictions of its functionality. Conversely, the insights gained from this new approach to vision, can lead to new ideas for enhancing the capabilities of artificial vision systems, and HEP trigger systems as well.
{"title":"The brain as a trigger system","authors":"M. D. Viva, G. Punzi","doi":"10.22323/1.213.0252","DOIUrl":"https://doi.org/10.22323/1.213.0252","url":null,"abstract":"There are significant analogies between the issues related to real-time event selection in HEP, and the issues faced by the human visual system. In fact, the visual system needs to extract rapidly the most important elements of the external world from a large flux of information, for survival purposes. A rapid and reliable detection of visual stimuli is essential for triggering autonomic responses to emotive stimuli, for initiating adaptive behaviors and for orienting towards potentially interesting/ dangerous stimuli. The speed of visual processing can be as fast as 20 ms, about only 20 times the duration of the elementary information exchanges by the action potential. The limitations to the brain capacity to process visual information, imposed by intrinsic energetic costs of neuronal activity, and ecological limits to the size of the skull, require a strong data reduction at an early stage, by creating a compact summary of relevant information, the so called \"primal sketch\", to be handled by further levels of processing. This is quite similar to the problem of experimental HEP of providing fast data reduction at a reasonable monetary cost, and with a practical device size. As a result of a joint effort of HEP physicists and practicing vision scientists, we recently proposed that not only the problems are similar, but the solutions adopted in the two cases also have strong similarities, and their parallel study can actually shed light on each other. Modeling the visual system as a trigger processor leads to a deeper understanding, and even very specific predictions of its functionality. Conversely, the insights gained from this new approach to vision, can lead to new ideas for enhancing the capabilities of artificial vision systems, and HEP trigger systems as well.","PeriodicalId":298664,"journal":{"name":"arXiv: Neurons and Cognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123396029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
After doing away with the evolutionary scaffold for BVSR, what remains is a notion of "blindness" that does not distinguish BVSR from other theories of creativity, and an assumption that creativity can be understood by treating ideas as discrete, countable entities, as opposed to different external manifestations of a singular gradually solidifying internal conception. Uprooted from Darwinian theory, BVSR lacks a scientific framework that can be called upon to generate hypotheses and test them. In lieu of such a framework, hypotheses appear to be generated on the basis of previous data--they are not theory-driven. The paper does not explain how the hypothesis that creativity is enhanced by engagement in a "network of enterprises" is derived from BVSR; this hypothesis is more compatible with competing conceptions of creativity. The notion that creativity involves backtracking conflates evidence for backtracking with respect to the external output with evidence for backtracking of the conception of the invention. The first does not imply the second; a creator can set aside a creative output but cannot go back to the conception of the task he/she had prior to generating that output. The notion that creativity entails superfluity (i.e., many ideas have "zero usefulness") is misguided; usefulness is context-dependent, moreover, the usefulness of an idea may reside in its being a critical stepping-stone to a subsequent idea.
{"title":"Probing the Mind Behind the (Literal and Figurative) Lightbulb","authors":"L. Gabora","doi":"10.1037/A0038075","DOIUrl":"https://doi.org/10.1037/A0038075","url":null,"abstract":"After doing away with the evolutionary scaffold for BVSR, what remains is a notion of \"blindness\" that does not distinguish BVSR from other theories of creativity, and an assumption that creativity can be understood by treating ideas as discrete, countable entities, as opposed to different external manifestations of a singular gradually solidifying internal conception. Uprooted from Darwinian theory, BVSR lacks a scientific framework that can be called upon to generate hypotheses and test them. In lieu of such a framework, hypotheses appear to be generated on the basis of previous data--they are not theory-driven. The paper does not explain how the hypothesis that creativity is enhanced by engagement in a \"network of enterprises\" is derived from BVSR; this hypothesis is more compatible with competing conceptions of creativity. The notion that creativity involves backtracking conflates evidence for backtracking with respect to the external output with evidence for backtracking of the conception of the invention. The first does not imply the second; a creator can set aside a creative output but cannot go back to the conception of the task he/she had prior to generating that output. The notion that creativity entails superfluity (i.e., many ideas have \"zero usefulness\") is misguided; usefulness is context-dependent, moreover, the usefulness of an idea may reside in its being a critical stepping-stone to a subsequent idea.","PeriodicalId":298664,"journal":{"name":"arXiv: Neurons and Cognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134167126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Inter-subject registration of cortical areas is necessary in functional imaging (fMRI) studies for making inferences about equivalent brain function across a population. However, many high-level visual brain areas are defined as peaks of functional contrasts whose cortical position is highly variable. As such, most alignment methods fail to accurately map functional regions of interest (ROIs) across participants. To address this problem, we propose a locally optimized registration method that directly predicts the location of a seed ROI on a separate target cortical sheet by maximizing the functional correlation between their time courses, while simultaneously allowing for non-smooth local deformations in region topology. Our method outperforms the two most commonly used alternatives (anatomical landmark-based AFNI alignment and cortical convexity-based FreeSurfer alignment) in overlap between predicted region and functionally-defined LOC. Furthermore, the maps obtained using our method are more consistent across subjects than both baseline measures. Critically, our method represents an important step forward towards predicting brain regions without explicit localizer scans and deciphering the poorly understood relationship between the location of functional regions, their anatomical extent, and the consistency of computations those regions perform across people.
{"title":"Locally-Optimized Inter-Subject Alignment of Functional Cortical Regions","authors":"M. C. Iordan, Armand Joulin, D. Beck, Li Fei-Fei","doi":"10.1167/14.10.714","DOIUrl":"https://doi.org/10.1167/14.10.714","url":null,"abstract":"Inter-subject registration of cortical areas is necessary in functional imaging (fMRI) studies for making inferences about equivalent brain function across a population. However, many high-level visual brain areas are defined as peaks of functional contrasts whose cortical position is highly variable. As such, most alignment methods fail to accurately map functional regions of interest (ROIs) across participants. To address this problem, we propose a locally optimized registration method that directly predicts the location of a seed ROI on a separate target cortical sheet by maximizing the functional correlation between their time courses, while simultaneously allowing for non-smooth local deformations in region topology. Our method outperforms the two most commonly used alternatives (anatomical landmark-based AFNI alignment and cortical convexity-based FreeSurfer alignment) in overlap between predicted region and functionally-defined LOC. Furthermore, the maps obtained using our method are more consistent across subjects than both baseline measures. Critically, our method represents an important step forward towards predicting brain regions without explicit localizer scans and deciphering the poorly understood relationship between the location of functional regions, their anatomical extent, and the consistency of computations those regions perform across people.","PeriodicalId":298664,"journal":{"name":"arXiv: Neurons and Cognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124141386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-05-20DOI: 10.1007/978-3-319-08672-9_38
I. Goychuk
{"title":"Stochastic Modeling of Excitable Dynamics: Improved Langevin Model for Mesoscopic Channel Noise","authors":"I. Goychuk","doi":"10.1007/978-3-319-08672-9_38","DOIUrl":"https://doi.org/10.1007/978-3-319-08672-9_38","url":null,"abstract":"","PeriodicalId":298664,"journal":{"name":"arXiv: Neurons and Cognition","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115363015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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