Bibliografie tematiche / Brain

Letteratura scientifica selezionata sul tema "Brain"

Autore: Grafiati
Pubblicato: 4 giugno 2021
Ultima modifica: 29 luglio 2024

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Articoli di riviste sul tema "Brain"

1

Scull, A. "Left brain, right brain: One brain, two brains". Brain 133, n. 10 (25 settembre 2010): 3153–56. http://dx.doi.org/10.1093/brain/awq255.

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Vadza, Kejal Chintan. "Brain Gate & Brain Computer Interface". International Journal of Scientific Research 2, n. 5 (1 giugno 2012): 45–49. http://dx.doi.org/10.15373/22778179/may2013/19.

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Gowda, Ashmitha. "Brain Fingerprinting". International Journal of Research Publication and Reviews 4, n. 5 (4 maggio 2023): 1707–10. http://dx.doi.org/10.55248/gengpi.234.5.40436.

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4

Goodman, G., R. R. Poznanski, L. Cacha e D. Bercovich. "The Two-Brains Hypothesis: Towards a guide for brain–brain and brain–machine interfaces". Journal of Integrative Neuroscience 14, n. 03 (settembre 2015): 281–93. http://dx.doi.org/10.1142/s0219635215500235.

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Tsibu, George. "The Child Brain". Clinical Medical Reviews and Reports 2, n. 02 (24 febbraio 2020): 01. http://dx.doi.org/10.31579/2690-8794/011.

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The brain is an organ is a part of the central nervous system created for responses and impulse of the movement of charges and information across the whole body.It is the major organ because it is the first portion to start growing immediately the zygote is form after fertilization .The weight of the brain is fully grown when the child reaches 15years.Boy did you fight your way through, that is unheard of,The embryo of male generative fluid is responsible for the characteristic of the kind of brain a child will have,The growing brain is having a shock recognisable in it shell,vast growth occurs in the next Seven month.
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Pinheiro, Renato Serquiz E., Yanny Cinara T. Ernesto e Irami Araújo-Filho. "Bleeding Brain Intraparenchymal". International Journal of Trend in Scientific Research and Development Volume-3, Issue-3 (30 aprile 2019): 1719–24. http://dx.doi.org/10.31142/ijtsrd23500.

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7

R. Suryawanshi, Chandani, e Vinod Nayyar. "BLUE BRAIN". INTERNATIONAL JOURNAL OF MANAGEMENT & INFORMATION TECHNOLOGY 7, n. 2 (30 novembre 2013): 1009–17. http://dx.doi.org/10.24297/ijmit.v7i2.3294.

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Today scientists are in research to create an artificial brain that can think, respond, take decision, and keep anything in memory. The main aim is to upload human brain into machine. So that man can think, take decision without any effort. After the death of the body, the virtual brain will act as the man. So, even after the death of a person we will not loose the knowledge, intelligence, personalities, feelings and memories of that man, that can be used for the development of the human society. Technology is growing faster than every thing. IBM is now in research to create a virtual brain, called Blue brain. If possible, this would be the first virtual brain of the world. IBM, in partnership with scientists at Switzerlands Ecole Polytech- nique Federale de Lausannes (EPFL) Brain and Mind Institute will begin simulating the brains biological systems and output the data as a working 3-dimensional model that will recreate the high-speed electrochemical interactions that take place within the brains interior. These include cognitive functions such as language, learning, perception and memory in addition to brain malfunction such as psychiatric disorders like depression and autism. From there, the modeling will expand to other regions of the brain and, if successful, shed light on the relationships between genetic, molecular and cognitive functions of the brain.
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R, Divya. "Instagramification of the Brain". Neurology & Neurotherapy Open Access Journal 4, n. 1 (2019): 1–2. http://dx.doi.org/10.23880/nnoaj-16000133.

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Internet usage is the most widespread technological advancement in the history of humanity. It plays a major role in search for information, entertainment area, and management of social networks and relationships in day - to - day life. In a recent research conducted by a team of international researchers from various universities across th e globe found that the Internet usage resulted in acute and sustained modifications in cognition, attention span, memory and social interactions in users
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Markou, Athina, Theodora Duka e Gordana Prelevic. "Estrogens and brain function". HORMONES 4, n. 1 (15 gennaio 2005): 9–17. http://dx.doi.org/10.14310/horm.2002.11138.

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Salami, A., M. Ajani, I. Orhorho, G. Ogun, A. Adeoye, C. Okolo, A. Oluwasola e J. Ogunbiyi. "Brain weights in adult africans". Journal of Morphological Sciences 34, n. 04 (ottobre 2017): 223–25. http://dx.doi.org/10.4322/jms.106316.

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Abstract Introduction: The average brain weight of adult humans, using Caucasian figures, is said to be between 1300g to 1400g. Few studies have however been done to make actual evaluations of brain weights in adult Africans. This study seeks to examine the weight of brains from people of African descent with respect to variations in sex and age in decades using autopsy specimens. Materials and Methods: Analysis of the weight of brains removed from both male and female adult patients during fresh autopsy of their bodies in our center over a ten year period was done. The study criteria required non-involvement of the central nervous system in the cause of death. The brains were grouped based on age in decades and further grouped into early, middle and late age groups. Descriptive statistical analysis was done using SPSS 20 statistics software. Results: A total of one hundred and sixteen brains were included in the study and the mean brain weight was 1280g with a range between 1015g to 1590g. There was no statistically significant difference in the mean brain weight of the different age groups. The average male brain was heavier than those of females and the difference was statistically signiicant. Conclusion: The brain weight of adult Africans in our study is similar to that seen in Caucasians. There is no statistically significant difference in the brain weight of adults from early adulthood to the elderly adults. Male adults have statistically heavier brains than the females.
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Tesi sul tema "Brain"

1

Wolburg, Martin. "On brain drain, brain gain, and brain exchange within Europe /". Baden-Baden : Nomos Verlagsgesellschaft, 2001. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=015306300&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.

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Sebastián, Romagosa Marc. "Brain computer interfaces for brain acquired damage". Doctoral thesis, Universitat Autònoma de Barcelona, 2020. http://hdl.handle.net/10803/670835.

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El terme Interfície Cervell-Ordinador (ICC), va sorgir als anys 70 pel Dr. Jacques J. Vidal, que mitjançant l’ús de l’electroencefalografia (EEG) fou el primer a intentar proporcionar una sortida alternativa als senyals cerebrals per controlar un dispositiu extern. L’objectiu principal d’aquesta fita era ajudar als pacients amb problemes de moviment i comunicació a relacionar-se amb el seu entorn. Des de llavors, molts neurocientífics han emprat aquesta idea i han intentat posar-la en pràctica utilitzant diferents mètodes d’adquisició i processament del senyal, nous dispositius d’interacció, noves metes i objectius. Tot això ha facilitat l’aplicació d’aquesta tecnologia en moltes àrees, i actualment les ICC s’utilitzen per jugar a videojocs, moure cadires de rodes, facilitar l’escriptura en persones sense mobilitat, definir criteris i preferències en el món del comerç i el consum, o inclús poden servir com a detector de mentides. Tot i així, el sector que presenta un major avenç en el desenvolupament de les ICC, és el sector biomèdic. A grans trets, podem utilitzar les ICC amb dues finalitats diferents dins de la neurorehabilitació; substituint una funció perduda o induint canvis en la plasticitat neuronal amb l’objectiu de restaurar o compensar la funció perduda. Existeixen diferents principis per al registre dels senyals del cervell; de manera invasiva, col·locant els elèctrodes de registre dintre de la cavitat cranial, o de manera no invasiva, col·locant els elèctrodes de registre fora de la cavitat cranial. El mètode més conegut i difós és l’EEG. El seu ús és molt adequat en entorns clínics, té una resolució temporal molt precisa i és possible obtenir una retroalimentació en temps real que pot induir la plasticitat cortical i el restabliment de la funció motora normal. En aquesta tesi presentem tres objectius diferents: (1) avaluar els afectes clínics de la rehabilitació mitjançant les ICC en pacients amb ictus, ja sigui realitzant un meta-anàlisi dels estudis publicats o avaluant els canvis funcionals dels pacients amb ictus després de la teràpia d’ICC; (2) explorar paràmetres alternatius per quantificar els efectes de les ICC en pacients amb ictus, avaluant diferents biomarcadors de l’EEG en pacients amb aquesta patologia i correlacionant aquests marcadors amb els resultats de les escales funcionals; (3) optimitzar el sistema ICC mitjançant la gamificació d’un avatar.
El término Interfaz Cerebro-Computadora (ICC) surgió en los años 70 por el Dr. Jacques J. Vidal, que mediante el uso de la electroencefalografía (EEG) trató de dar una salida alternativa a las señales del cerebro para controlar un dispositivo externo. El objetivo principal de esta hazaña era ayudar a los pacientes con problemas de movimiento o comunicación a relacionarse con el entorno. Desde entonces, muchos neurocientíficos han utilizado esta idea y han tratado de ponerla en práctica utilizando diferentes métodos de adquisición y procesamiento de señales, nuevos dispositivos de interacción y nuevas metas y objetivos. Todo ello ha facilitado la aplicación de esta tecnología en muchas áreas y actualmente las ICC se utilizan para jugar a videojuegos, mover sillas de ruedas, facilitar la escritura en personas sin movilidad, establecer criterios y preferencias de compra en el mundo del comercio y el consumo, o incluso pueden servir como detector de mentiras. Sin embargo, el sector que presenta un mayor avance y desarrollo de las ICC es el sector biomédico. A grandes rasgos podemos utilizar las ICC con dos finalidades distintas dentro de la neurorehabilitación; sustituir una función perdida o inducir cambios en la plasticidad neuronal con el objetivo de restaurar o compensar dicha función perdida. Hay diferentes principios para el registro de las señales del cerebro; de forma invasiva, colocando los electrodos de registro dentro de la cavidad craneal, o no invasiva, colocando los electrodos de registro fuera de la cavidad craneal. El método más conocido y difundido es la EEG. Su uso es adecuado para entornos clínicos, tiene una resolución temporal muy precisa y su retroalimentación en tiempo real puede inducir la plasticidad cortical y el restablecimiento de la función motora normal. En esta tesis presentamos tres objetivos diferentes: (1) evaluar los efectos clínicos de la rehabilitación mediante las ICC en pacientes con ictus, ya sea realizando un meta-análisis de los estudios publicados o evaluando los cambios funcionales en los pacientes con ictus después de la terapia de ICC; (2) explorar parámetros alternativos para cuantificar los efectos de las ICC en pacientes con ictus, evaluando diferentes biomarcadores de electroencefalografía en pacientes con esta patología y correlacionando los posibles cambios en estos parámetros con los resultados en las escalas funcionales; (3) optimizar el sistema ICC utilizando mediante la gamificación de un avatar.
The term Brain Computer Interface (BCI) emerged in the 70's by Dr. Jacques J Vidal, who by using electroencephalography (EEG) tried to give an alternative output to the brain signals in order to control an external device. The main objective of this feat was to help patients with impaired movement or communication to relate themselves to the environment. Since then many neuroscientists have used this idea and have tried to implement it using different methods of signal acquisition and processing, new interaction devices, new goals and objectives. All this has facilitated the implementation of this technology in many areas and currently BCI is used to play video games, move wheelchairs, facilitate writing in people without mobility, establish criteria and purchase preferences in the world of marketing and consumption, or even serve as a lie detector. However, the sector that presents the most marked progress and development of BCI is the biomedical sector. In rough outlines we can use BCI with two different purposes within the neurorehabilitation; to substitute a lost function or to induce neural plasticity changes with the aim to restore or compensate the lost function. To restore a lost function by inducing neuroplastic changes in the brain is undoubtedly a challenging strategy but a feasible goal through BCI technology. This type of intervention requires that the patient invests time and effort in a therapy based on the practice of motor image and feedback mechanisms in real time. There are different principles to record the brain signals; invasively, placing the recording electrodes inside the cranial cavity, or non-invasive, placing the recording electrodes outside of the cranial cavity. The best known and most widespread one is EEG, since they are suitable for clinical environments, have a highly accurate temporal resolution and their real-time feedback can induce cortical plasticity and the restoration of normal motor function. On this thesis we present three different objectives: (1) to evaluate the clinical effects of rehabilitation based on BCI system in stroke patients, either by performing a meta-analysis of published studies or by evaluating functional changes in stroke patients after BCI training; (2) to explore alternative parameters to quantify effects of BCI in stroke patients, by evaluating different electroencephalography biomarkers in stroke patients and correlating potential changes in these parameters with functional scales; (3) to optimize the BCI system by using a new gamified avatar.
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Liu, Mianxin. "The brain at criticality : variability of brain spontaneous activity and relevance to brain functions". HKBU Institutional Repository, 2020. https://repository.hkbu.edu.hk/etd_oa/809.

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The brain activities are characterized by spontaneous and persistent irregular fluctuations in space and time. Criticality theory from statistical physics has been proposed as a principle to explain the variability in normal brain spontaneous activity and has suggested the functional benefits of variability, such as maximized dynamic range of response to stimuli and information capacity. In parallel, the brains show variability in other aspects, such as the structural heterogeneity across brain regions, the intra-individual variability across experimental trials, and the behavior difference across groups and individuals. The associations between the variability of spontaneous activities and these different types of structural, intra and inter-individual variabilities remain elusive. My doctoral study thus aimed to bridge the brain variability and the above-mentioned variations based on criticality theory and analysis of empirical data. As a preparatory analysis, we first collected evidence to prove criticality in human functional magnetic resonance imaging (fMRI) data. The advanced statistical criteria were used to exclude potential artefacts that can induce power-law scaling without the mechanism of criticality. In the first part of the study, we addressed methodological issue and tested whether several measures of either spatial or temporal complexity due to experimental limitations could be reliable proxy of spatiotemporal variability (related to criticality) in vivo. The high spatiotemporal resolutions of whole-cortex optical voltage imaging in mice brain during the waking up from anesthesia enabled simultaneous investigation of functional connectivity (FC), Multi-Scale Entropy (MSE, measure of temporal variability), Regional Entropy (RE, quantity of spatiotemporal variability) and the interdependency among them under different brain states. The results suggested that MSE and FC could be effective measures to capture spatiotemporal variability under limitation of imaging modalities applicable to human subjects. This study also lays methodological basis for the third study in this thesis. In the second study, we explored the interaction between spontaneous activity and evoked activity from mice brain imaging under whisker stimulus. The whisker stimulus will first evoke the local activation in sensory cortex and then trigger whole-cortex activity with variable patterns in different experimental trials. This trial-to-trial variability in the cortical evoked component was then attributed to the changes of ongoing activity state at stimulus onset. The study links ongoing activity variability and evoked activity variability, which further consolidates the association between ongoing activity and brain functions. In the third study, we measured the signal variability of the whole brain from resting state fMRI, and developed the multivariate pattern of cortical entropy, called entropy profile, as reliable and interpretable biomarker of individual difference in cognitive ability. We showed that the whole cortical entropy profile from resting- state fMRI is a robust personalized measure. We tested the predictive power for general and specific cognitive abilities based on cortical entropy profiles with out- of-sample prediction. Furthermore, we revealed the anatomical features underlying cross-region and cross-individual variations in cortical entropy profiles. This study provides new potential biomarker based on brain spontaneous variability which could benefit the applications in psychology and psychiatry studies. The whole study laid a foundation for brain criticality-/variability-based studies and applications and broadened our understanding of the associations between neural structures, functional dynamics and cognitive ability
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Dave, Nimita D. "Brain/Brain Tumor Pharmacokinetics and Pharmacodynamics of Letrozole". University of Cincinnati / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1368013158.

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Woody, Christine Buchanan. "Right-brain/left-brain communication in the church". Theological Research Exchange Network (TREN), 2007. http://www.tren.com/search.cfm?p064-0137.

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Álvarez, Fernández Jorge Luis, Segura Claudia Alejandra Muñoz, Apolaya Juan José Polack e Bautista Karina Rodríguez. "Brain Freeze". Bachelor's thesis, Universidad Peruana de Ciencias Aplicadas (UPC), 2018. http://hdl.handle.net/10757/625355.

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El presente trabajo de investigación tiene como principal propósito el desarrollar un modelo de negocio innovador, a partir de la creación de un helado, hecho a base de Polifenol, el cual posee como valor agregado el no derretirse con facilidad. “Brain Freeze” conforma una propuesta innovadora para el mercado de los helados en la actualidad, debido a su principal ventaja competitiva y comparativa frente a la competencia existente en el mercado. Asimismo, a partir del presente documento escrito, se desarrollan todos los principales aspectos para la correcta y eficiente realización del presente proyecto y su pronta ejecución en Lima Metropolitana; así como también todos los detalles financieros requeridos para su evaluación y pronta inversión en el modelo de negocio. Con la finalidad de poder establecer una planificación que permita estimaciones de mercado reales, la presente investigación tomó en cuenta la información respectiva y actualizada del segmento de mercado al cual se espera atender. El concepto de “Brain Freeze” propone el desarrollo de cinco módulos de ventas en cinco de los principales centros comerciales, con la finalidad de poder abarcar a la mayor afluencia de clientes, los cuales recurren a los principales centros comerciales de Lima Metropolitana y convertirse así en una marca Top of Mind, dentro de un plazo de cinco años desde su lanzamiento.
The main purpose of this paper is to develop an innovative business model, based on the creation of an ice cream made from Polyphenol, which has the added value of not melting easily. "Brain Freeze" forms an innovative proposal for the ice cream market at present, due to its main competitive and comparative advantage over the existing competition in the market. Likewise, from this written document, all the main aspects are developed for the correct and efficient realization of this project and its prompt execution in Metropolitan Lima; as well as all the financial details required for its evaluation and prompt investment in the business model. With the purpose of being able to establish a planning that allows real market estimations, the present investigation took into account the respective and updated information of the market segment to which it is expected to attend. The concept of "Brain Freeze" proposes the development of five sales modules in five of the main shopping centers, in order to cover the largest number of customers, who turn to the main shopping centers in Metropolitan Lima and thus become in a Top of Mind brand, within five years of its launch.
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Подолкова, Світлана Віталіївна, Светлана Витальевна Подолкова, Svitlana Vitaliivna Podolkova e I. Strizhakov. "Human brain". Thesis, Вид-во СумДУ, 2011. http://essuir.sumdu.edu.ua/handle/123456789/22106.

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Sylenko, E. V. "Brain-computer". Thesis, Sumy State University, 2016. http://essuir.sumdu.edu.ua/handle/123456789/45871.

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The development of different variants of the interface ―brain-computer‖ (BCI) in recent years ceased to be an experimental direction and finds its practical application. What were the expectations like, what works now and what to expect from this technology in the future?
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Watson, Charles. "Brain mapping". Thesis, The University of Sydney, 2011. https://hdl.handle.net/2123/28840.

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These publications are a summary of work I have completed in brain mapping over many years. The work includes one book (The Rat Brain in Stereotaxic Coordinates, 6th compact edition), ten articles on hindbrain and spinal cord anatomy published in peer reviewed journals between 1975 to 2011, and five published chapters on spinal cord anatomy, including two spinal cord atlases. Over my career I have published 15 books on the anatomy of the brain and spinal cord of experimental animals. I am first author or equal co-author of ten of these books. The most successful of these books, "The Rat Brain in Stereotaxic Coordinates" (Paxinos and Watson, l 982, 1986, 1996, 1998, 2005, 2007), has earned over 50,000 citations since it was first published in 1982. The second edition alone is ranked 32 in the Thomson ISI 50 most cited publications of all time, having been cited 17,093 times up to January 2006. Dr George Paxinos and l are equal contributors to this work; the order of authors was decided on alphabetical precedence.
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Babalola, Karolyn Olatubosun. "Brain-computer interfaces for inducing brain plasticity and motor learning: implications for brain-injury rehabilitation". Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/41164.

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The goal of this investigation was to explore the efficacy of implementing a rehabilitation robot controlled by a noninvasive brain-computer interface (BCI) to influence brain plasticity and facilitate motor learning. The motivation of this project stemmed from the need to address the population of stroke survivors who have few or no options for therapy. A stroke occurs every 40 seconds in the United States and it is the leading cause of long-term disability [1-3]. In a country where the elderly population is growing at an astounding rate, one in six persons above the age of 55 is at risk of having a stroke. Internationally, the rates of strokes and stroke-induced disabilities are comparable to those of the United States [1, 4-6]. Approximately half of all stroke survivors suffer from immediate unilateral paralysis or weakness, 30-60% of which never regain function [1, 6-9]. Many individuals who survive stroke will be forced to seek institutional care or long-term assistance. Clinicians have typically implemented stroke rehabilitative treatment using active training techniques such as constraint induced movement therapy (CIMT) and robotic therapy [10-12]. Such techniques restore motor activity by forcing the movement of weakened limbs. That active engagement of the weakened limb movement stimulates neural pathways and activates the motor cortex, thus inducing brain plasticity and motor learning. Several studies have demonstrated that active training does in fact have an effect on the way the brain restores itself and leads to faster rehabilitation [10, 13-15]. In addition, studies involving mental practice, another form of rehabilitation, have shown that mental imagery directly stimulates the brain, but is not effective unless implemented as a supplemental to active training [16, 17]. Only stroke survivors retaining residual motor ability are able to undergo active rehabilitative training; the current selection of therapies has overlooked the significant population of stroke survivors suffering from severe control loss or complete paralysis [6, 10]. A BCI is a system or device that detects minute changes in brain signals to facilitate communication or control. In this investigation, the BCI was implemented through an electroencephalograph (EEG) device. EEG devices detect electrical brain signals transmitted through the scalp that corresponded with imagined motor activity. Within the BCI, a linear transformation algorithm converted EEG spectral features into control commands for an upper-limb rehabilitative robot, thus implementing a closed-looped feedback-control training system. The concept of the BCI-robot system implemented in this investigation may provide an alternative to current therapies by demonstrating the results of bypassing motor activity using brain signals to facilitate robotic therapy. In this study, 24 able-bodied volunteers were divided into two study groups; one group trained to use sensorimotor rhythms (SMRs) (produced by imagining motor activity) to control the movement of a robot and the other group performed the 'guided-imagery' task of watching the robot move without control. This investigation looked for contrasts between the two groups that showed that the training involved with controlling the BCI-robot system had an effect on brain plasticity and motor learning. To analyze brain plasticity and motor learning, EEG data corresponding to imagined arm movement and motor learning were acquired before, during, and after training. Features extracted from the EEG data consisted of frequencies in the 5-35Hz range, which produced amplitude fluctuations that were measurably significant during reaching. Motor learning data consisted of arm displacement measures (error) produced during an motor adaptation task performed daily by all subjects. The results of the brain plasticity analysis showed persistent reductions in beta activity for subjects in the BCI group. The analysis also showed that subjects in the Non-BCI group had significant reductions in mu activity; however, these results were likely due to the fact that different EEG caps were used in each stage of the study. These results were promising but require further investigation. The motor learning data showed that the BCI group out-performed non-BCI group in all measures of motor learning. These findings were significant because this was the first time a BCI had been applied to a motor learning protocol and the findings suggested that BCI had an influence on the speed at which subjects adapted to a motor learning task. Additional findings suggested that BCI subjects who were in the 40 and over age group had greater decreases in error after the learning phase of motor assessment. These finding suggests that BCI could have positive long term effects on individuals who are more likely to suffer from a stroke and possibly could be beneficial for chronic stroke patients. In addition to exploring the effects of BCI training on brain plasticity and motor learning this investigation sought to detect whether the EEG features produced during guided-imagery could differentiate between reaching direction. While the analysis presented in this project produced classification accuracies no greater than ~77%, it formed the basis of future studies that would incorporate different pattern recognition techniques. The results of this study show the potential for developing new rehabilitation therapies and motor learning protocols that incorporate BCI.
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Più fonti

Libri sul tema "Brain"

1

Dalton, A. J. Brain beats brawn every time. Liverpool: Liverpool Libraries & Arts, 1995.

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2

Georg, Deutsch, a cura di. Left brain, right brain. 4a ed. New York: W.H. Freeman, 1993.

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3

Georg, Deutsch, a cura di. Left brain, right brain. New York: W.H. Freeman and Company, 1989.

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4

Georg, Deutsch, a cura di. Left brain, right brain. New York: W.H. Freeman, 1985.

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5

Helge, Refsum, Sulg Ilmar A. 1919- e Rasmussen Knut, a cura di. Heart & brain, brain & heart. Berlin: Springer-Verlag, 1989.

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6

Springer, Sally P. Left brain, right brain. 3a ed. New York: W.H. Freeman, 1989.

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7

1950-, Fawcett James W., Rosser Anne E e Dunnett S. B, a cura di. Brain damage, brain repair. Oxford: Oxford University Press, 2001.

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8

Comics Collection (University of Pennsylvania), a cura di. The tiger-eater: Brain beats brawn. Mumbai: Amar Chitra Katha, ACK Media, 2011.

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I, Templer Donald, Hartlage Lawrence C e Cannon W. Gary, a cura di. Preventable brain damage: Brain vulnerability and brain health. New York: Springer Pub. Co., 1992.

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Caster, Shannon. Brain. New York: PowerKids Press, 2010.

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Capitoli di libri sul tema "Brain"

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Poon, Jessie P. H., e Wei Yin. "Brawn to brain". In In The Post-Urban World, 109–28. Abingdon, Oxon ; New York, NY : Routledge, 2018.: Routledge, 2017. http://dx.doi.org/10.4324/9781315672168-9.

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Aboitiz, Francisco. "Monkey Brain, Human Brain". In A Brain for Speech, 249–85. London: Palgrave Macmillan UK, 2017. http://dx.doi.org/10.1057/978-1-137-54060-7_7.

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Campagnole-Santos, Maria Jose, Mariela M. Gironacci e Marco Antônio Peliky Fontes. "Brain". In Angiotensin-(1-7), 55–71. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22696-1_4.

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Merrick, Malcolm V. "Brain". In Essentials of Nuclear Medicine, 221–44. London: Springer London, 1998. http://dx.doi.org/10.1007/978-1-4471-0907-5_9.

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Gedroyc, Wladyslaw, e Sheila Rankin. "Brain". In Practical CT Techniques, 26–29. London: Springer London, 1992. http://dx.doi.org/10.1007/978-1-4471-3275-2_8.

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Santiago, Jonas Francisco Y. "Brain". In Positron Emission Tomography with Computed Tomography (PET/CT), 3–12. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05518-3_2.

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Hecht, Silke. "Brain". In Veterinary Computed Tomography, 185–95. West Sussex, UK: John Wiley & Sons, Ltd., 2013. http://dx.doi.org/10.1002/9781118785676.ch19.

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Crispino, Mario, e Emanuela Crispino. "Brain". In Atlas of Imaging Anatomy, 1–27. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10750-9_1.

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Wideman, Timothy H., Michael J. L. Sullivan, Shuji Inada, David McIntyre, Masayoshi Kumagai, Naoya Yahagi, J. Rick Turner et al. "Brain". In Encyclopedia of Behavioral Medicine, 251. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1005-9_1098.

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Wallis, Jennifer. "Brain". In Investigating the Body in the Victorian Asylum, 141–79. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56714-3_5.

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Atti di convegni sul tema "Brain"

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Hu, Hao, William S. Rosenberg e Adnan H. Nayfeh. "Modeling Human Brain Movability Effect on Brain Response During Impact". In ASME 1998 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1998. http://dx.doi.org/10.1115/imece1998-0980.

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Abstract Brain responses due to its movability during impact was investigated by using sliding interface approach. A new 3D 50th percentile human head finite element model has been generated in which sliding interfaces totally separate the brains and cerebrospinal fluid (CSF)/cranium. So, the brains can move to some extent. It becomes an equivalent one to most widely used brain/CSF (cranium) coupled models by switching interface type from sliding to tied. The model was partially validated by using available experimental and computed data in frontal impact. Compared with brain/CSF (cranium) coupled models, the new model predicts higher brain stress levels at sites such as corpus callosum, brain stem, and the vicinity of the ventricles etc. and more realistic deformation patterns. The results suggest that a fluid-solid interaction approach should be used to better model brain movement during impact to correctly interpret the brain injuries and to evaluate proposed head injury mechanisms.
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Wands, Bruce. "Right brain/left brain". In ACM SIGGRAPH 2006 Educators program. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1179295.1179326.

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Guo, Ruipeng, e Rajesh Menon. "Computational cannula-based microscopy for brain imaging". In Computational Optical Sensing and Imaging. Washington, D.C.: Optica Publishing Group, 2022. http://dx.doi.org/10.1364/cosi.2022.ctu5f.3.

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With Machine Learning (ML) algorithms, we experimentally demonstrated deep imaging inside mice brains with cellular-level resolution using computational cannula microscopy. Multi-ANNs were used for the prediction of brain images.
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Min, Byoung-Kyong. "Eeg/sonication-based brain-brain interfacing". In 2013 International Winter Workshop on Brain-Computer Interface (BCI). IEEE, 2013. http://dx.doi.org/10.1109/iww-bci.2013.6506614.

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Roula, Mohammed Ali, Sriharsha Ramaraju e Peter McCarthy. "Brain Stimulation and Brain Computer Interfacing". In Proceedings of the 32nd International BCS Human Computer Interaction Conference. BCS Learning & Development, 2018. http://dx.doi.org/10.14236/ewic/hci2018.231.

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Valentino, D. J., J. C. Mazziotta e H. K. Huang. "Mapping Brain Function To Brain Anatomy". In Medical Imaging II, a cura di Roger H. Schneider e Samuel J. Dwyer III. SPIE, 1988. http://dx.doi.org/10.1117/12.968665.

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Alkan, Sarper, e Fatos T. Yarman-Vural. "Ensembling brain regions for brain decoding". In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2015. http://dx.doi.org/10.1109/embc.2015.7319010.

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Pavone, Francesco S. "3d Human Brain Digital Histopatology". In Optics and the Brain. Washington, D.C.: OSA, 2018. http://dx.doi.org/10.1364/brain.2018.bf4c.1.

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Murphy, Tim H. "Point-source Maps: Relations between Mesoscopic Imaging of Mouse Cortex and Neuronal Spiking". In Optics and the Brain. Washington, D.C.: OSA, 2015. http://dx.doi.org/10.1364/brain.2015.brt2b.1.

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Drew, Patrick J. "Optical Dissection of Mesoscale Cerebral Hemodynamics in the Behaving Brain". In Optics and the Brain. Washington, D.C.: OSA, 2016. http://dx.doi.org/10.1364/brain.2016.bm4d.4.

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Rapporti di organizzazioni sul tema "Brain"

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Nudo, Randolph. A Brain-Machine-Brain Interface for Rewiring of Cortical Circuitry after Traumatic Brain Injury. Fort Belvoir, VA: Defense Technical Information Center, settembre 2011. http://dx.doi.org/10.21236/ada561375.

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Nudo, Randolph J. A Brain-Machine-Brain Interface for Rewiring of Cortical Circuitry after Traumatic Brain Injury. Fort Belvoir, VA: Defense Technical Information Center, settembre 2012. http://dx.doi.org/10.21236/ada570590.

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Mohseni, Pedram. A Brain-Machine-Brain Interface for Rewiring of Cortical Circuitry after Traumatic Brain Injury. Fort Belvoir, VA: Defense Technical Information Center, settembre 2013. http://dx.doi.org/10.21236/ada598378.

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Nudo, Randolph J. A Brain-Machine-Brain Interface for Rewiring of Cortical Circuitry after Traumatic Brain Injury. Fort Belvoir, VA: Defense Technical Information Center, settembre 2013. http://dx.doi.org/10.21236/ada598379.

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Najm, Imad. Deep Brain Stimulation of Treatment of Traumatic Brain Injury. Fort Belvoir, VA: Defense Technical Information Center, ottobre 2009. http://dx.doi.org/10.21236/ada548984.

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Monteiro-Benson, Misha. Will Kazakhstan’s brain drain become a wartime brain gain? East Asia Forum, ottobre 2023. http://dx.doi.org/10.59425/eabc.1697018415.

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Williams, Timothy J., Ramesh Balakrishnan, Fabien Delalondre, Felix Schuermann, Eilif Muller e Marc Oliver Gewaltig. Large-Scale Simulation of Brain Tissue, Blue Brain Project, EPFL. Office of Scientific and Technical Information (OSTI), maggio 2018. http://dx.doi.org/10.2172/1483995.

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Aaron Seitz, Aaron Seitz. Can brain training help soldiers with brain injury regain hearing? Experiment, giugno 2014. http://dx.doi.org/10.18258/2793.

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Singh, Manbir, Peter Gruen, Chi-Shing Zee, Edward Grant e Jeongwon Jeong. MRI-DTI Tractography to Quantify Brain Connectivity in Traumatic Brain Injury. Fort Belvoir, VA: Defense Technical Information Center, aprile 2009. http://dx.doi.org/10.21236/ada501253.

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David, Patty, e Vicki Gelfeld. Brain Health Research Study. AARP Research, gennaio 2015. http://dx.doi.org/10.26419/res.00096.001.

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