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Literatura académica sobre el tema "Neural activity recording"

Autor: Grafiati

Publicado: 10 de marzo de 2023

Última modificación: 11 de marzo de 2023

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Artículos de revistas sobre el tema "Neural activity recording"

Xu, Wei, Jingxin Wang, Simin Cheng y Xiaomin Xu. "Flexible organic transistors for neural activity recording". Applied Physics Reviews 9, n.º 3 (septiembre de 2022): 031308. http://dx.doi.org/10.1063/5.0102401.

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Flexible electronics capable of interacting with biological tissues, and acquiring and processing biological information, are increasingly demanded to capture the dynamic physiological processes, understand the living organisms, and treat human diseases. Neural interfaces with a high spatiotemporal resolution, extreme mechanical compliance, and biocompatibility are essential for precisely recording brain activity and localizing neuronal patterns that generate pathological brain signals. Organic transistors possess unique advantages in detecting low-amplitude signals at the physiologically relevant time scales in biotic environments, given their inherent amplification capabilities for in situ signal processing, designable flexibility, and biocompatibility features. This review summarizes recent progress in neural activity recording and stimulation enabled by flexible and stretchable organic transistors. We introduce underlying mechanisms for multiple transistor building blocks, followed by an explicit discussion on effective design strategies toward flexible and stretchable organic transistor arrays with improved signal transduction capabilities at the transistor/neural interfaces.

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Loi, Daniela, Caterina Carboni, Gianmarco Angius, Gian Nicola Angotzi, Massimo Barbaro, Luigi Raffo, Stanisa Raspopovic y Xavier Navarro. "Peripheral Neural Activity Recording and Stimulation System". IEEE Transactions on Biomedical Circuits and Systems 5, n.º 4 (agosto de 2011): 368–79. http://dx.doi.org/10.1109/tbcas.2011.2123097.

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Aslam, J., P. Merken, R. Huys, M. Akif Erismis, R. Firat Yazicioglu, R. Puers y C. Van Hoof. "Activity based neural front-end recording system". Electronics Letters 47, n.º 21 (2011): 1170. http://dx.doi.org/10.1049/el.2011.1966.

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Liu, Xin, Chi Ren, Zhisheng Huang, Madison Wilson, Jeong-Hoon Kim, Yichen Lu, Mehrdad Ramezani, Takaki Komiyama y Duygu Kuzum. "Decoding of cortex-wide brain activity from local recordings of neural potentials". Journal of Neural Engineering 18, n.º 6 (15 de noviembre de 2021): 066009. http://dx.doi.org/10.1088/1741-2552/ac33e7.

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Abstract Objective. Electrical recordings of neural activity from brain surface have been widely employed in basic neuroscience research and clinical practice for investigations of neural circuit functions, brain–computer interfaces, and treatments for neurological disorders. Traditionally, these surface potentials have been believed to mainly reflect local neural activity. It is not known how informative the locally recorded surface potentials are for the neural activities across multiple cortical regions. Approach. To investigate that, we perform simultaneous local electrical recording and wide-field calcium imaging in awake head-fixed mice. Using a recurrent neural network model, we try to decode the calcium fluorescence activity of multiple cortical regions from local electrical recordings. Main results. The mean activity of different cortical regions could be decoded from locally recorded surface potentials. Also, each frequency band of surface potentials differentially encodes activities from multiple cortical regions so that including all the frequency bands in the decoding model gives the highest decoding performance. Despite the close spacing between recording channels, surface potentials from different channels provide complementary information about the large-scale cortical activity and the decoding performance continues to improve as more channels are included. Finally, we demonstrate the successful decoding of whole dorsal cortex activity at pixel-level using locally recorded surface potentials. Significance. These results show that the locally recorded surface potentials indeed contain rich information of the large-scale neural activities, which could be further demixed to recover the neural activity across individual cortical regions. In the future, our cross-modality inference approach could be adapted to virtually reconstruct cortex-wide brain activity, greatly expanding the spatial reach of surface electrical recordings without increasing invasiveness. Furthermore, it could be used to facilitate imaging neural activity across the whole cortex in freely moving animals, without requirement of head-fixed microscopy configurations.

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Tan, Kwan Ling, Ming Yuan Cheng, Wei Guo Chen, Rui Qi Lim, Maria Ramona B. Damalerio, Lei Yao, Peng Li, Yuan Dong Gu y Min Kyu Je. "Polyethylene Glycol-Coated Polyimide-Based Probe with Neural Recording IC for Chronic Neural Recording". Advanced Materials Research 849 (noviembre de 2013): 183–88. http://dx.doi.org/10.4028/www.scientific.net/amr.849.183.

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Neural probe array is utilized in neural recording, in the aim to understand the neural activity. Silicon is the common substrate used in neural probe array. However, due to the rigid nature, the silicon-based neural probe array causes cell damage during implantation into the brain tissue. This would reduce the signal-to-noise ratio. Therefore, flexible polymer probe is more suitable as it can help to minimize the tissue damage and thus increasing the signal-to-noise ratio. The lack of stiffness for the flexible probe is solved by coating it with polyethylene glycol (PEG). It stiffens the probe and can be dissolved in water, which allows the polymer probe to regain its flexibility. The proposed integrated probe with reduced distance between probe and ASIC will further help to improve the signal-to-noise ratio during neural recording. The coated flexible probe regained original impedance of 14.1 kΩ at a frequency of 1 kHz. A bench-top neural recording with the flexible probe array in saline solution will also be acquired.

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Hiramoto, Masaki y Hollis T. Cline. "Tetrode Recording in the Xenopus laevis Visual System Using Multichannel Glass Electrodes". Cold Spring Harbor Protocols 2021, n.º 11 (3 de febrero de 2021): pdb.prot107086. http://dx.doi.org/10.1101/pdb.prot107086.

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The Xenopus tadpole visual system shows an extraordinary extent of developmental and visual experience–dependent plasticity, establishing sophisticated neuronal response properties that guide essential survival behaviors. The external development and access to the developing visual circuit of Xenopus tadpoles make them an excellent experimental system in which to elucidate plastic changes in neuronal properties and their capacity to encode information about the visual scene. The temporal structure of neural activity encodes a significant amount of information, access to which requires recording methods with high temporal resolution. Conversely, elucidating changes in the temporal structure of neural activity requires recording over extended periods. It is challenging to maintain patch-clamp recordings over extended periods and Ca2+ imaging has limited temporal resolution. Extracellular recordings have been used in other systems for extended recording; however, spike amplitudes in the developing Xenopus visual circuit are not large enough to be captured by distant electrodes. Here we describe a juxtacellular tetrode recording method for continuous long-term recordings from neurons in intact tadpoles, which can also be exposed to diverse visual stimulation protocols. Electrode position in the tectum is stabilized by the large contact area in the tissue. Contamination of the signal from neighboring neurons is minimized by the tight contact between the glass capillaries and the dense arrangement of neurons in the tectum. This recording method enables analysis of developmental and visual experience–dependent plastic changes in neuronal response properties at higher temporal resolution and over longer periods than current methods.

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Nagayasu, Kazuki. "Viral vectors for manipulation and recording of neural activity". Proceedings for Annual Meeting of The Japanese Pharmacological Society 93 (2020): 2—MS2. http://dx.doi.org/10.1254/jpssuppl.93.0_2-ms2.

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Sher, A., E. J. Chichilnisky, W. Dabrowski, A. A. Grillo, M. Grivich, D. Gunning, P. Hottowy et al. "Large-scale multielectrode recording and stimulation of neural activity". Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 579, n.º 2 (septiembre de 2007): 895–900. http://dx.doi.org/10.1016/j.nima.2007.05.309.

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Pégard, Nicolas C., Hsiou-Yuan Liu, Nick Antipa, Maximillian Gerlock, Hillel Adesnik y Laura Waller. "Compressive light-field microscopy for 3D neural activity recording". Optica 3, n.º 5 (12 de mayo de 2016): 517. http://dx.doi.org/10.1364/optica.3.000517.

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Liang, Bo y Xuesong Ye. "Towards high-density recording of brain-wide neural activity". Science China Materials 61, n.º 3 (8 de enero de 2018): 432–34. http://dx.doi.org/10.1007/s40843-017-9175-3.

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Tesis sobre el tema "Neural activity recording"

Azin, Meysam. "A Battery-Powered Multichannel Microsystem for Activity-Dependent Intracortical Microstimulation". Case Western Reserve University School of Graduate Studies / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=case1298389278.

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Kostick, Nathan H. "Novel Carbon-Nanotube Based Neural Interface for Chronic Recording of Glossopharyngeal Nerve Activity". Case Western Reserve University School of Graduate Studies / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=case1517920588275806.

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Rioult-Pedotti, Marc Guy. "Optical multisite recording of neural activity patterns in organotypic spinal cord tissue cultures /". [S.l.] : [s.n.], 1991. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=9393.

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Yang, Calvin Tseng. "Recording locomotor neural ensemble activity using 3-D microprobe arrays and the development of a flexible planar array for recording spinal small-field cord-dorsum potentials". Diss., Restricted to subscribing institutions, 2008. http://proquest.umi.com/pqdweb?did=1666917911&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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Suciu, Diana J. "NEURAL ACTIVITY WITHIN SOLID BREAST TUMORS AND THE IMPLICATIONS ON METASTASIS". Case Western Reserve University School of Graduate Studies / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=case1528117273992639.

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Youngstrom, Isaac. "Assessing Neural Function in Behaving Rodents Using Virtual Reality and Intracellular Recording: Modulation of Olfactory Bulb Interneuron Subthreshold Activity by Respiration". Case Western Reserve University School of Graduate Studies / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=case1433520980.

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Lago, Nicolò. "Characterization and modelling of organic devices for simultaneous stimulation and recording of cellular electrical activity with Reference-Less Electrolyte-Gated Organic Field-Effect Transistors". Doctoral thesis, Università degli studi di Padova, 2018. http://hdl.handle.net/11577/3426781.

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The study of neuronal and neurodegenerative diseases requires the development of new tools and technologies to create functional neuroelectronics allowing both stimulation and recording of cellular electrical activity. In the last decade organic electronics is digging its way in the field of bioelectronics and researchers started to develop neural interfaces based on organic semiconductors. The interest in such technologies arise from the intrinsic properties of organic materials such as low cost, transparency, softness and flexibility, as well the biocompatibility and the suitability in realizing all organic printed systems. In particular, organic field-effect transistor (OFET) -based biosensors integrate the sensing and signal amplification in a single device, paving the way to new implantable neural interfaces for in vivo applications. To master the sensing and amplification properties of the OFET-based sensors, it is mandatory to gain an intimate knowledge of the single transistors (without any analytes or cells) that cannot be limited to basic characterizations or to general models. Moreover, organic transistors are characterized by different working principles and properties as respect to their inorganic counterpart. We performed pulsed and transient characterization on different OFETs (both p-type and n-type) showing that, even though the transistors can switch on and off very fast, the accumulation and/or the depletion of the conductive channel continues for times as long as ten seconds. Such phenomenon must be carefully considered in the realization of a biosensor and in its applications, since the DC operative point of the device can drift during the recording of the cellular signals, thus altering the collected data. We further investigate such phenomenon by performing characterizations at different temperatures and by applying the deep level transient spectroscopy technique. We showed that the slow channel accumulation (and depletion) is due to the semiconductor density-of-states that must be occupied in order to bring the Fermi energy level close to the conduction band. This is a phenomenon that can takes several seconds and we described it by introducing a time-depend mobility. We also proposed a technique to estimate the behavior, in time, of the position of the Fermi energy level as respect to the conduction band. To understand the electrochemical transduction processes between living cell and organic biosensor, we realized two-electrodes structure (STACKs) where a drop of saline solution is put directly in contact with the organic semiconductor. On these devices, we performed electrochemical impedance spectroscopy at different DC polarizations and we developed an equivalent circuit model for the metal-organic semiconductor-solution structures that are typically used as transducers in biosensor devices. Our approach was extending the standard range of the bias voltages applied for devices that operate in water. This particular characterization protocol allowed to distinguish and investigate the different mechanisms that occur at the different layers and interfaces: adsorption of ions in the semiconductor; accumulation and charge exchange of carriers at the semiconductor/electrolyte interface; percolation of the ionic species through the organic semiconductor; ion diffusion across the electrolyte; ion adsorption and charge exchange at the platinum interface. We highlighted the presence of ion percolation through the organic semiconductor layer, which is described in the equivalent circuit model by means of a de Levie impedance. The presence of percolation has been demonstrated by environmental scanning electron microscopy and profilometry analysis. Although percolation is much more evident at high negative bias values, it is still present even at low bias conditions. In addition, we analyze two case studies of devices featuring NaCl (concentration of 0.1M) and MilliQ water as solution, showing that both cases can be considered as a particular case of the general model presented in this manuscript. The very good agreement between the model and the experimental data makes the model a valid tool for studying the transducing mechanisms between organic films and the physiological environment. Hence this model could be a useful tool not only for the characterization and failure analysis of electronic devices, such as water-gated transistors, electrophysiological interfaces, fuel cells, and others electrochemical systems, but also this model might be used in other applications, in which a solution is in intimate contact with another material to determine and quantify, if undesired mechanisms such as percolation and/or redox corrosive processes occur. Lastly, the knowledge gain on OFETs and STACKs were put together to realize electrolyte-gated field effect transistors (EGOFETs). We then developed a model to describes EGOFETs as neural interfaces. We showed that our model can be successfully applied to understand the behaviour of a more general class of devices, including both organic and inorganic transistors. We introduced the reference-less (RL-) EGOFET and we showed that it might be successfully used as a low cost and flexible neural interface for extracellular recording in vivo without the need of a reference electrode, making the implant less invasive and easier to use. The working principle underlying RL-EGOFETs involves self-polarization and back-gate stimulation, which we show experimentally to be feasible by means of a custom low-voltage high-speed acquisition board that was designed to emulate a real-time neuron response. Our results open the door to using and optimizing EGOFETs and RL-EGOFETs for neural interfaces.
Lo studio delle malattie neuronali e neuro-degenerative richiede lo sviluppo di nuovi strumenti e tecnologie per creare dispositivi neuro-elettronici funzionali che consentano sia la stimolazione che la registrazione dell'attività elettrica cellulare. Nell'ultimo decennio l'elettronica organica sta emergendo nel campo della bioelettronica e diversi gruppi di ricerca hanno iniziato a sviluppare interfacce neurali basate su semiconduttori organici. L'interesse per tali tecnologie deriva dalle proprietà intrinseche dei materiali organici quali basso costo, trasparenza, morbidezza e flessibilità, nonché la biocompatibilità e l'idoneità nella realizzazione di sistemi stampati completamente organici. In particolare, i biosensori basati sulla tecnologia a transistor ad effetto campo organico (OFET) integrano il sensing e l'amplificazione del segnale in un singolo dispositivo, aprendo la strada a nuove interfacce neurali impiantabili per applicazioni in vivo. Per padroneggiare le proprietà di rilevamento e amplificazione dei sensori basati su OFET, è obbligatorio acquisire una conoscenza approfondita dei singoli transistor (senza la presenza di analiti e/o cellule) che vadano oltre le caratterizzazioni di base o modelli generali. Inoltre, i transistor organici sono caratterizzati da diversi principi di funzionamento e diverse proprietà rispetto alla loro controparte inorganica. In questo lavoro abbiamo svolto caratterizzazioni impulsate e transienti su diversi OFET (sia di tipo p che di tipo n) mostrando che, anche se i transistor possono accendersi e spegnersi molto velocemente, l'accumulo e/o lo svuotamento del canale conduttivo continua per tempi che possono superare le decine di secondi. Tale fenomeno deve essere attentamente considerato nella realizzazione di un biosensore e nelle sue applicazioni, poiché il punto operativo DC del dispositivo può andare alla deriva durante la registrazione dei segnali cellulari, alterando così i dati raccolti. Questo fenomeno viene ulteriormente approfondito caratterizzano i dispositivi a diverse temperature e per mezzo della tecnica DLTS. Abbiamo dimostrato che il lento accumulo (e svuotamento) del canale è dovuto alla densità di stati del semiconduttore organico che devono poter essere occupati per portare il livello energetico di Fermi vicino alla banda di conduzione. Questo è un fenomeno che può richiedere diversi secondi che possiamo descrivere introducendo una mobilità dipendente dal tempo. Per comprendere i processi di trasduzione elettrochimica tra cellule viventi ed il biosensore organico, abbiamo realizzato una struttura a due elettrodi (STACK) in cui una goccia di soluzione salina viene messa direttamente a contatto con il semiconduttore organico. Su questi dispositivi, abbiamo eseguito la spettroscopia di impedenza elettrochimica a diverse polarizzazioni DC e abbiamo sviluppato un modello circuitale equivalente per le strutture metallo/semiconduttore organico/soluzione che vengono tipicamente utilizzate per la realizzazione di bio-trasduttori. Il nostro approccio prevede di estendere il range standard delle tensioni operative per questo genere di dispositivi. Ciò ha permesso di investigare e distinguere i diversi fenomeni che si verificano nei diversi strati e interfacce: adsorbimento di ioni nel semiconduttore; accumulo e scambio di cariche di portanti all'interfaccia semiconduttore/elettrolita; percolazione delle specie ioniche attraverso il semiconduttore organico; diffusione di ioni attraverso l'elettrolita; adsorbimento di ioni e scambio di carica all'interfaccia col metallo. Abbiamo evidenziato la presenza di percolazione ionica attraverso lo strato di semiconduttore organico, che è descritto nel modello circuitale per mezzo di un'impedenza di de Levie. La presenza di percolazione è stata dimostrata mediante microscopia elettronica a scansione ambientale e analisi profilometrica. Sebbene la percolazione sia molto più evidente a valori di bias negativi elevati, risulta presente anche a basse condizioni di bias. L'ottimo accordo tra il modello e i dati sperimentali rende il modello un valido strumento per studiare i meccanismi di trasduzione tra film organici e l'ambiente fisiologico. Quindi questo modello può essere uno strumento utile non solo per la caratterizzazione e l'analisi dei guasti dei dispositivi elettronici, come water-gated transistor, interfacce elettrofisiologiche, celle a combustibile e altri sistemi elettrochimici, ma anche nel caso in cui una soluzione è in intimo contatto con un altro materiale per determinare e/o quantificare se si verificano meccanismi indesiderati come percolazione e/o processi corrosivi. Infine, il bagaglio di conoscenze ottenuto studiando i dispositivi OFET e STACK è stato messo utillizato per realizzare dispositivi EGOFET. Abbiamo quindi sviluppato un modello per descrivere gli EGOFET come interfacce neurali. Abbiamo dimostrato che il nostro modello può essere applicato con successo per comprendere il comportamento di una classe più generale di dispositivi, compresi i transistor sia organici che inorganici. Abbiamo introdotto l'RL-EGOFET (reference-less EGOFET) e abbiamo dimostrato che questa struttura può essere utilizzata con successo come interfaccia neurale flessibile per il recording extracellulare in vivo senza la necessità di un elettrodo di riferimento, rendendo l'impianto meno invasivo e più facile da usare. I nostri risultati aprono la strada all'utilizzo e all'ottimizzazione di EGOFET e RL-EGOFET come interfacce neurali.

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Shimizu, Tomoko. "Effect of electrical stimulation of the infralimbic and prelimbic cortices on anxiolytic-like behavior of rats during the elevated plus-maze test, with particular reference to multiunit recording of the behavior-associated neural activity". Kyoto University, 2018. http://hdl.handle.net/2433/235988.

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Mitelut, Catalin C. "Characterizing single neuron activity patterns and dynamics using multi-scale spontaneous neuronal activity recordings of cat and mouse cortex". Thesis, University of British Columbia, 2017. http://hdl.handle.net/2429/63570.

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Throughout most of the 20th century the brain has been studied as a reflexive system with ever improving recording methods being applied within a variety of sensory and behavioural paradigms. Yet the brains of most animals (and all mammals) are spontaneously active with incoming sensory stimuli modulating rather than driving neural activity. The aim of this thesis is to characterize spontaneous neural activity across multiple temporal and spatial scales relying on biophysical simulations, experiments and analysis of recordings from the visual cortex of cats and dorsal cortex and thalamus of mouse. Biophysically detailed simulations yielded novel datasets for testing spike sorting algorithms which are critical for isolating single neuron activity. Sorting algorithms tested provided low error rates with operator skill being as important as sorting suite. Simulated datasets have similar characteristics to in vivo acquired data and ongoing larger-scope efforts are proposed for developing the next generation of spike sorting algorithms and extracellular probes. Single neuron spontaneous activity was correlated to dorsal cortex neural activity in mice. Spike-triggered-maps revealed that spontaneously firing cortical neurons were co-activated with homotopic and mono-synaptically connected cortical areas, whereas thalamic neurons co-activated with more diversely connected areas. Both bursting and tonic firing modes yielded similar maps and the time courses of spike-triggered-maps revealed distinct patterns suggesting such dynamics may constitute intrinsic single neuron properties. The mapping technique extends previous work to further link spontaneous neural activity across temporal and spatial scales and suggests additional avenues of investigation. Synchronized state cat visual and mouse sensory cortex electrophysiological recordings revealed that spontaneously occurring activity UP-state transitions fall into stereotyped classes of events that can be grouped. Single visual cortex neurons active during UP-state transitions fire in a partially preserved order extending previous findings on high firing rate neurons in rat somatosensory and auditory cortex. The firing order for many neurons changes over periods longer than 30-minutes suggesting a complex non-stationary temporal neural code may underlie spontaneous and stimulus evoked neural activity. This thesis shows that ongoing spontaneous brain activity contains substantial structure that can be used to further our understanding of brain function.
Medicine, Faculty of
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Peterson, Kristopher David. "Development of a micro recording probe for measurements of neuronal activity in freely moving animals". Thesis, Imperial College London, 2010. http://hdl.handle.net/10044/1/6347.

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To discover general principles of biological sensorimotor control, insects have become remarkably successful model systems. In contrast to highly complex mammals, the functional organization of the insect nervous system in combination with a well-defined behavioural repertoire turned out to provide ideal conditions for quantitative studies into the neural control of behaviour. In addition, the search for biologically inspired control algorithms has further accelerated research into the neuronal mechanisms underlying flight and gaze stabilization, especially in blowflies. However, recording the neuronal activity in freely behaving insects, in particular in comparatively small insects such as blowflies, still imposes a major technical challenge. To date, electrophysiological recordings in unrestrained flies have never been achieved. This thesis describes the design and testing of a micro recording probe to be used for monitoring extracellular electrical activity in the nervous system of freely moving blowflies. In principle, this probe could also be used to study the neuronal control of behaviour in any other animal species the size of which is bigger than that of a blowfly. The nature of neuronal signals and the objective to record neuronal activity from behaving blowflies puts massive constraints on the specifications of the probe. I designed a differential amplifier with high gain, high linearity, low noise, and low power consumption. To fit the probe in the blowfly‟s head capsule and in direct contact with the animal‟s brain, the amplifier is on an unpackaged die. The neuronal signals are in the order of a few 100s of μV in amplitude. To be able to digitize such small signals >1000 times amplification is desirable. The small signal amplitudes also necessitate minimization of circuit noise. Linearity is necessary to prevent distortion of signal shape. Since connecting wires would impede movement of the animal, the probe would need to be powered by batteries. Therefore, low power is needed for two reasons: (i) to increase battery life, and therefore recording time, and (ii) because heat caused by power expenditure may damage the blowfly‟s brain or change its behaviour. To reduce power consumption I used CMOS transistors biased in the subthreshold region and a 2.2 V low power supply. The amplifier was characterized after fabrication by means of measuring its frequency response, linearity, and noise. I also recorded signals from a blowfly's brain and compared the performance of my recording probe with the performance of a high specification commercial amplifier in the time and frequency domains.

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Libros sobre el tema "Neural activity recording"

Summerson, Samantha R. y Caleb Kemere. Multi-electrode Recording of Neural Activity in Awake Behaving Animals. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199939800.003.0004.

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Systems neuroscience is being revolutionized by the ability to record the activity of large numbers of neurons simultaneously. Chronic recording with multi- electrode arrays in animal models is a critical tool for studies of learning and memory, sensory processing, motor control, emotion, and decision-making. The experimental process for gathering large amounts of neural ensemble data can be very time consuming, however, the resulting data can be incredibly rich. We present a detailed overview of the process of acquiring multichannel neural data, with a particular focus on chronic tetrode recording in rodents.

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Fox, Kieran C. R. Neural Origins of Self-Generated Thought. Editado por Kalina Christoff y Kieran C. R. Fox. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780190464745.013.1.

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Functional magnetic resonance imaging (fMRI) has begun to narrow down the neural correlates of self-generated forms of thought, with current evidence pointing toward central roles for the default, frontoparietal, and visual networks. Recent work has linked the arising of thoughts more specifically to default network activity, but the limited temporal resolution of fMRI has precluded more detailed conclusions about where in the brain self-created mental content is generated and how this is achieved. This chapter argues that the unparalleled spatiotemporal resolution of intracranial electrophysiology (iEEG) in human epilepsy patients can begin to provide answers to questions about the specific neural origins of self-generated thought. The chapter reviews the extensive body of literature from iEEG studies over the past few decades and shows that many studies involving passive recording or direct electrical stimulation throughout the brain point to the medial temporal lobe as a key site of thought-generation.

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Frost, William y Jian-young Wu. Voltage-Sensitive Dye Imaging. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199939800.003.0008.

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Voltage sensitive dye imaging (VSD) can be used to record neural activity in hundreds of locations in preparations ranging from mammalian cortex to invertebrate ganglia. Because fast VSDs respond to membrane potential changes with microsecond temporal resolution, these are better suited than calcium indicators for recording rapid neural signals. Here we describe methods for using a 464- element photodiode array and fast VSDs to record signals ranging from large scale network activity in brain slices and in vivo mammalian preparations, to action potentials in over 100 individual neurons in invertebrate ganglia.

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Coleman, William L. y R. Michael Burger. Extracellular Single-Unit Recording and Neuropharmacological Methods. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199939800.003.0003.

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Small biogenic changes in voltage such as action potentials in neurons can be monitored using extracellular single unit recording techniques. This technique allows for investigation of neuronal electrical activity in a manner that is not disruptive to the cell membrane, and individual neurons can be recorded from for extended periods of time. This chapter discusses the basic requirements for an extracellular recording setup, including different types of electrodes, apparatus for controlling electrode position and placement, recording equipment, signal output, data analysis, and the histological confirmation of recording sites usually required for in vivo recordings. A more advanced extracellular recording technique using piggy-back style multibarrel electrodes that allows for localized pharmacological manipulation of neuronal properties is described in detail. Strategies for successful signal isolation, troubleshooting advice such as noise reduction, and suggestions for general laboratory equipment are also discussed.

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Reed, Sean, Sonia Jego y Antoine Adamantidis. Electroencephalography and Local Field Potentials in Animals. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199939800.003.0007.

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This chapter discusses the history, practice, and application of electroencephalography (EEG) and local field potential (LFP) recordings, with a particular focus on animal models. EEG measures the fluctuations of electrical activity resulting from ionic currents in the brain. These measurements are often taken from electrodes placed on the surface of the scalp, or in animal models, directly on the skull. LFP recordings are more invasive, measuring electrical current from all nearby dendritic synaptic activity within a volume of tissue. These two techniques are useful in determining how neural activity can synchronize during different behavioral or motivational states.

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Vanhatalo, Sampsa y J. Matias Palva. Infraslow EEG Activity. Editado por Donald L. Schomer y Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0032.

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Infraslow electroencephalographic (EEG) activity refers to frequencies below the conventional clinical EEG range that starts at about 0.5 Hz. Evidence suggests that salient EEG signals in the infraslow range are essential parts of many physiological and pathological conditions. In addition, brain is known to exhibit multitude of infraslow processes, which may be observed directly as fluctuations in the EEG signal amplitude, as infraslow fluctuations or intermittency in other neurophysiological signals, or as fluctuations in behavioural performance. Both physiological and pathological EEG activity may range from 0.01 Hz to several hundred Hz. In the clinical context, infraslow activity is commonly observed in the neonatal EEG, during and prior to epileptic seizures, and during sleep and arousals. Laboratory studies have demonstrated the presence of spontaneous infraslow EEG fluctuations or very slow event-related potentials in awake and sleeping subjects. Infraslow activity may not only arise in cortical and subcortical networks but is also likely to involve non-neuronal generators such as glial networks. The full, physiologically relevant range of brain mechanisms can be readily recorded with wide dynamic range direct-current (DC)-coupled amplifiers or full-band EEG (FbEEG). Due to the different underlying mechanisms, a single FbEEG recording can even be perceived as a multimodal recording where distinct brain modalities can be studied simultaneously by performing data analysis for different frequency ranges. FbEEG is likely to become the standard approach for a wide range of applications in both basic science and in the clinic.

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Gage, Greg y Tim Marzullo. How Your Brain Works. The MIT Press, 2022. http://dx.doi.org/10.7551/mitpress/12429.001.0001.

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Discover the hidden electrical world inside your nervous system using DIY, hands-on experiments, for all ages. No MD or PhD required! The workings of the brain are mysterious: What are neural signals? What do they mean? How do our senses really sense? How does our brain control our movements? What happens when we meditate? Techniques to record signals from living brains were once thought to be the realm of advanced university labs... but not anymore! This book allows anyone to participate in the discovery of neuroscience through hands-on experiments that record the hidden electrical world beneath our skin and skulls. In How Your Brain Works, neuroscientists Greg Gage and Tim Marzullo offer a practical guide—accessible and useful to readers from middle schoolers to college undergraduates to curious adults—for learning about the brain through hands-on experiments. Armed with some DIY electrodes, readers will get to see what brain activity really looks like through simple neuroscience experiments. Written by two neuroscience researchers who invented open-source techniques to record signals from neurons, muscles, hearts, eyes, and brains, How Your Brain Works includes more than forty-five experiments to gain a deeper understanding of your brain. Using a homemade scientific instrument called a SpikerBox, readers can see how fast neural signals travel by recording electrical signals from an earthworm. Or, turning themselves into subjects, readers can strap on some electrode stickers to detect the nervous system in their own bodies. Each chapter begins by describing some phenomenology of a particular area of neuroscience, then guides readers step-by-step through an experiment, and concludes with a series of open-ended questions to inspire further investigation. Some experiments use invertebrates (such as insects), and the book provides a thoughtful framework for the ethical use of these animals in education. How Your Brain Works offers fascinating reading for students at any level, curious readers, and scientists interested in using electrophysiology in their research or teaching. Example Experiments How fast do signals travel down a neuron? The brain uses electricity. . . but do neurons communicate as fast as lightning inside our bodies? In this experiment you will make a speed trap for spikes! Can we really enhance our memories during sleep? Strap on a brainwave-reading sweatband and test the power of cueing up and strengthening memories while you dream away! Wait, that's my number! Ever feel that moment of excitement when you see your number displayed while waiting for an opening at the counter? In this experiment, you will peer into your brainwaves to see what happens when the unexpected occurs and how the brain gets your attention. Using hip hop to talk to the brain. Tired of simply “reading” the electricity from the brain? Would you like to “write” to the nervous system as well? In this experiment you will use a smartphone and hack a headphone cable to see how brain stimulators (used in treating Parkinson's disease) really work. How long does it take the brain to decide? Using simple classroom rulers and a clever technique, readers can determine how long it takes the brain to make decisions.

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Krauzlis, Richard J. Attentional Functions of the Superior Colliculus. Editado por Anna C. (Kia) Nobre y Sabine Kastner. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199675111.013.014.

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The superior colliculus (SC) plays an important role in both overt and covert attention. In primates, the SC is well known to be a central component of the motor pathways that orient the eyes and head to important objects in the environment. Accordingly, neurons in the SC show enhanced responses that will be the target of orienting movements, compared to stimuli that will be ignored. Single-neuron recordings in the SC have revealed a variety of attention-related effects, including changes in activity related to bottom-up and top-down attention, attention capture, and inhibition of return. These findings support the view of the SC as a priority map that represents the location of important objects in the visual environment. Manipulation of SC activity by electrical microstimulation and chemical inactivation shows that the SC is not simply a recipient of attention-related effects, but plays a causal role in these processes. In particular, activity in the SC plays a major role in the selection of targets for saccades, and also for pursuit eye movements and movements of the hand. Moreover, activity in the SC is important not only for the control of overt attention, but also plays a crucial role in covert attention—the processing of visual signals for perceptual judgements even in the absence of orienting movements. The mechanisms mediating the role of the SC in the control of covert attention are not yet known, but current models emphasize interactions between the SC and areas of the cerebral cortex.

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Capítulos de libros sobre el tema "Neural activity recording"

Chen, Yonghong, Mukesh Dhamala, Anil Bollimunta, Charles E. Schroeder y Mingzhou Ding. "Current Source Density Analysis of Ongoing Neural Activity: Theory and Application". En Electrophysiological Recording Techniques, 27–40. Totowa, NJ: Humana Press, 2010. http://dx.doi.org/10.1007/978-1-60327-202-5_2.

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Jayachandran, Maanasa y Timothy A. Allen. "Candidate Neural Activity for the Encoding of Temporal Content in Memory". En Electrophysiological Recording Techniques, 147–81. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2631-3_7.

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Ozbay, Baris N., Gregory L. Futia, Ming Ma, Connor McCullough, Michael D. Young, Diego Restrepo y Emily A. Gibson. "Miniature Multiphoton Microscopes for Recording Neural Activity in Freely Moving Animals". En Neuromethods, 187–230. New York, NY: Springer US, 2023. http://dx.doi.org/10.1007/978-1-0716-2764-8_7.

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AbstractMiniaturized head-mounted microscopes for in vivo recording of neural activity have gained much recognition within the past decade of neuroscience research. In combination with fluorescent reporters, these miniature microscopes allow researchers to record the neural activity that underlies behavior, cognition, and perception in freely moving animals. Single-photon miniature microscopes are convenient for widefield recording but lack the increased penetration depth and optical sectioning capabilities of multiphoton imaging. Here we discuss the current state of head-mounted multiphoton miniature microscopes and introduce a miniature head-mounted two-photon fiber-coupled microscope (2P-FCM) for neuronal imaging with active axial focusing enabled using a miniature electrowetting lens. The 2P-FCM enables three-dimensional two-photon optical recording of structure and activity at multiple focal planes in a freely moving mouse. Detailed methods are provided in this chapter on the 2P-FCM design, operation, and software for data analysis.

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Jimbo, Y. y A. Kawana. "Multi-Site Recording of Neural Activity using Planar Electrode Arrays". En Neural Circuits and Networks, 125–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/978-3-642-58955-3_9.

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Sims, Ruth R., Imane Bendifallah, Kris Blanchard, Dimitrii Tanese, Valentina Emiliani y Eirini Papagiakoumou. "Optical Manipulation and Recording of Neural Activity with Wavefront Engineering". En Neuromethods, 1–48. New York, NY: Springer US, 2023. http://dx.doi.org/10.1007/978-1-0716-2764-8_1.

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AbstractOne of the central goals of neuroscience is to decipher the specific contributions of neural mechanisms to different aspects of sensory perception. Since achieving this goal requires tools capable of precisely perturbing and monitoring neural activity across a multitude of spatiotemporal scales, this aim has inspired the innovation of many optical technologies capable of manipulating and recording neural activity in a minimally invasive manner. The interdisciplinary nature of neurophotonics requires a broad knowledge base in order to successfully develop and apply these technologies, and one of the principal aims of this chapter is to provide some basic but fundamental background information in terms of both physiology and optics in the context of all-optical two-photon neurophysiology experiments. Most of this information is expected to be familiar to readers experienced in either domain, but is presented here with the aim of bridging the divide between disciplines in order to enable physicists and engineers to develop useful optical technologies or for neuroscientists to select appropriate tools and apply them to their maximum potential.The first section of this chapter is dedicated to a brief overview of some basic principles of neural physiology relevant for controlling and recording neuronal activity using light. Then, the selection of appropriate actuators and sensors for manipulating and monitoring particular neural signals is discussed, with particular attention paid to kinetics and sensitivity. Some considerations for minimizing crosstalk in optical neurophysiology experiments are also introduced. Next, an overview of the state-of-the-art optical technologies is provided, including a description of suitable laser sources for two-photon excitation according to particular experimental requirements. Finally, some detailed, technical, information regarding the specific wavefront engineering approaches known as Generalized Phase Contrast (GPC) and temporal focusing is provided.

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Miyakawa, Naohisa, Katsushige Sato, Hiraku Mochida, Shinichi Sasaki y Yoko Momose-Sato. "Functional Mapping of Neural Activity in the Embryonic Avian Visual System: Optical Recording with a Voltage-Sensitive Dye". En The Neural Basis of Early Vision, 194–98. Tokyo: Springer Japan, 2003. http://dx.doi.org/10.1007/978-4-431-68447-3_68.

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Ohye, Chihiro, Tohru Shibazaki, Yasuhiro Kawashima, Masafumi Hirato, Masaru Matsumura y Takashi Shibasaki. "Neural Activity of the Basal Ganglia in Parkinson’s Disease Studied by Depth Recording and Pet Scan". En Advances in Behavioral Biology, 637–44. Boston, MA: Springer New York, 1991. http://dx.doi.org/10.1007/978-1-4684-5871-8_68.

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Schirner, Michael y Petra Ritter. "Integrating EEG–fMRI Through Brain Simulation". En EEG - fMRI, 745–77. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-07121-8_30.

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AbstractEEG and fMRI are thought to measure partly distinct, partly overlapping, and certainly incomplete aspects of neuronal activity. Brain network models (BNMs) are used to simulate neuronal activity, like the dynamics of postsynaptic potentials, or spike-firing activity, and may conjointly predict both, EEG and fMRI, and therefore allow for the integration and the analysis of the two signals. The usual motivation for EEG–fMRI integration is to use both techniques in a complementary fashion by combining their strengths, while ameliorating their weaknesses. For instance, EEG measures electric activity on the scalp with a high temporal sampling rate, but a low spatial resolution (e.g., due to volume conduction effects). On the other hand, fMRI BOLD contrast is an indirect (proxy) measure of neural activity that is sensitive for the fluctuation of blood oxygenation at a relatively low temporal resolution. Some of the appeal of brain simulation-based integration of EEG–fMRI data is related to the idea that after fitting a neural model to reproduce observed activity, the internal activity of the model can tell us something about unobservable activity, like neural firing, which can only be measured invasively and in a spatially restricted manner. Brain simulation-based approaches have the potential to not only integrate EEG and fMRI, but basically data from every modality that can either directly (like multi-electrode recordings) or indirectly (like fMRI) be linked with the neural model.

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Saggau, P. y G. ten Bruggencate. "Topology Related Real-Time Monitoring of Neural Activity in Hippocampal Brain Slices by Noninvasive Optical Recording — A Step Towards Functional Aspects of Long-Term Potentiation (LTP)". En Synaptic Plasticity in the Hippocampus, 159–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-73202-7_46.

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Mureşan, Raul C., Gordon Pipa y Diek W. Wheeler. "Single-Unit Recordings Revisited: Activity in Recurrent Microcircuits". En Artificial Neural Networks: Biological Inspirations – ICANN 2005, 153–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11550822_25.

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Actas de conferencias sobre el tema "Neural activity recording"

Nii, Manabu, Kazunobu Takahama, Takuya Iwamoto, Takafumi Matsuda, Yuki Matsumoto y Kazusuke Maenaka. "Fuzzy neural network based activity estimation for recording human daily activity". En 2014 IEEE Symposium on Robotic Intelligence in Informationally Structured Space (RiiSS). IEEE, 2014. http://dx.doi.org/10.1109/riiss.2014.7009174.

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"AN ELECTRONIC INTERFACE FOR NEURAL ACTIVITY RECORDING AND STIMULATION". En International Conference on Biomedical Electronics and Devices. SciTePress - Science and and Technology Publications, 2010. http://dx.doi.org/10.5220/0002749702110214.

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McGovern, Brian, Nir Grossman, Rolando Berlinguer-Palmini, Mark Neil, Emmanuel Drakakis y Patrick Degenaar. "An optogenetic neural stimulation platform for concurrent induction and recording of neural activity". En BiOS, editado por Nikiforos Kollias, Bernard Choi, Haishan Zeng, Reza S. Malek, Brian J. Wong, Justus F. R. Ilgner, Kenton W. Gregory et al. SPIE, 2010. http://dx.doi.org/10.1117/12.842665.

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Zoladz, M., P. Kmon, P. Grybos, R. Szczygiel, R. Kleczek y P. Otfinowski. "A bidirectional 64-channel neurochip for recording and stimulation neural network activity". En 5th International IEEE/EMBS Conference on Neural Engineering (NER 2011). IEEE, 2011. http://dx.doi.org/10.1109/ner.2011.5910566.

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Baluch, F. y L. Itti. "A portable system for recording neural activity in indoor and outdoor environments". En 2012 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2012. http://dx.doi.org/10.1109/embc.2012.6346444.

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Moncion, Carolina, Satheesh Bojja-Venkatakrishnan, Jorge Riera Diaz y John L. Volakis. "Fully-Passive and Wireless Recording of Neural Activity in Freely Moving Animals". En 2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting. IEEE, 2020. http://dx.doi.org/10.1109/ieeeconf35879.2020.9329887.

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Lee, Taeju, Jee-Ho Park, Ji-Hyoung Cha, Namsun Chou, Doojin Jang, Ji-Hoon Kim, Il-Joo Cho, Seong-Jin Kim y Minkyu Je. "A Multimodal Multichannel Neural Activity Readout IC with 0.7μW/Channel Ca2+-Probe-Based Fluorescence Recording and Electrical Recording". En 2019 Symposium on VLSI Circuits. IEEE, 2019. http://dx.doi.org/10.23919/vlsic.2019.8778042.

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Lee, Taeju, Wonsuk Choi, Jinseok Kim y Minkyu Je. "Implantable Neural-Recording Modules for Monitoring Electrical Neural Activity in the Central and Peripheral Nervous Systems". En 2020 IEEE 63rd International Midwest Symposium on Circuits and Systems (MWSCAS). IEEE, 2020. http://dx.doi.org/10.1109/mwscas48704.2020.9184529.

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Li, Yang-Guo, Qingyun Ma, Mohammad Rafiqul Haider y Yehia Massoud. "An ultra-low-power bioamplifier for implantable large-scale recording of neural activity". En 2013 IEEE 14th Annual Wireless and Microwave Technology Conference (WAMICON). IEEE, 2013. http://dx.doi.org/10.1109/wamicon.2013.6572767.

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Zoladz, Miroslaw, Piotr Kmon, Jacek Rauza, Pawel Grybos y Tomasz Kowalczyk. "256-channel reconfigurable system for recording the electrophysiological activity of a neural tissue in vitro". En 2013 6th International IEEE/EMBS Conference on Neural Engineering (NER). IEEE, 2013. http://dx.doi.org/10.1109/ner.2013.6695995.

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