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https://www.readbyqxmd.com/read/28231395/functional-connectivity-in-amygdalar-sensory-pre-motor-networks-at-rest-new-evidence-from-the-human-connectome-project
#1
Nicola Toschi, Andrea Duggento, Luca Passamonti
The word "e-motion" derives from the Latin word "ex-moveo" which literally means "moving away from something / somebody". Emotions are thus fundamental to prime action and goal-directed behavior with obvious implications for individual's survival. However, the brain mechanisms underlying the interactions between emotional and motor cortical systems remain poorly understood. A recent diffusion tensor imaging study in humans has reported the existence of direct anatomical connections between the amygdala and sensory/(pre)motor cortices, corroborating an initial observation in animal research...
February 23, 2017: European Journal of Neuroscience
https://www.readbyqxmd.com/read/28230841/magnetoencephalography-for-brain-electrophysiology-and-imaging
#2
REVIEW
Sylvain Baillet
We review the aspects that uniquely characterize magnetoencephalography (MEG) among the techniques available to explore and resolve brain function and dysfunction. While emphasizing its specific strengths in terms of millisecond source imaging, we also identify and discuss current practical challenges, in particular in signal extraction and interpretation. We also take issue with some perceived disadvantages of MEG, including the misconception that the technique is redundant with electroencephalography. Overall, MEG contributes uniquely to our deeper comprehension of both regional and large-scale brain dynamics: from the functions of neural oscillations and the nature of event-related brain activation, to the mechanisms of functional connectivity between regions and the emergence of modes of network communication in brain systems...
February 23, 2017: Nature Neuroscience
https://www.readbyqxmd.com/read/28230767/an-adaptive-multi-sensor-data-fusion-method-based-on-deep-convolutional-neural-networks-for-fault-diagnosis-of-planetary-gearbox
#3
Luyang Jing, Taiyong Wang, Ming Zhao, Peng Wang
A fault diagnosis approach based on multi-sensor data fusion is a promising tool to deal with complicated damage detection problems of mechanical systems. Nevertheless, this approach suffers from two challenges, which are (1) the feature extraction from various types of sensory data and (2) the selection of a suitable fusion level. It is usually difficult to choose an optimal feature or fusion level for a specific fault diagnosis task, and extensive domain expertise and human labor are also highly required during these selections...
February 21, 2017: Sensors
https://www.readbyqxmd.com/read/28230528/biologically-plausible-learning-in-recurrent-neural-networks-reproduces-neural-dynamics-observed-during-cognitive-tasks
#4
Thomas Miconi
Neural activity during cognitive tasks exhibits complex dynamics that flexibly encode task-relevant variables. Chaotic recurrent networks, which spontaneously generate rich dynamics, have been proposed as a model of cortical computation during cognitive tasks. However, existing methods for training these networks are either biologically implausible, and/or require a continuous, real-time error signal to guide learning. Here we show that a biologically plausible learning rule can train such recurrent networks, guided solely by delayed, phasic rewards at the end of each trial...
February 23, 2017: ELife
https://www.readbyqxmd.com/read/28229628/impaired-glucose-tolerance-after-streptozotocin-microinjection-into-the-mediodorsal-prefrontal-cortex-of-the-rat
#5
B Nagy, I Szabó, G Takács, B Csetényi, E Hormay, Z Karádi
The mediodorsal prefrontal cortex (mdPFC) is a key structure of the central glucose-monitoring (GM) neural network. Previous studies indicate that intracerebral streptozotocin (STZ) microinjection-induced destruction of local chemosensory neurons results in feeding and metabolic alterations. The present experiments aimed to examine whether STZ microinjection into the mdPFC causes metabolic deficits. To do so, glucose tolerance test (GTT) and measurements of plasma metabolites were performed in STZ-treated or control rats...
December 2016: Physiol Int
https://www.readbyqxmd.com/read/28229308/eeg-signatures-of-dynamic-functional-network-connectivity-states
#6
E A Allen, E Damaraju, T Eichele, L Wu, V D Calhoun
The human brain operates by dynamically modulating different neural populations to enable goal directed behavior. The synchrony or lack thereof between different brain regions is thought to correspond to observed functional connectivity dynamics in resting state brain imaging data. In a large sample of healthy human adult subjects and utilizing a sliding windowed correlation method on functional imaging data, earlier we demonstrated the presence of seven distinct functional connectivity states/patterns between different brain networks that reliably occur across time and subjects...
February 22, 2017: Brain Topography
https://www.readbyqxmd.com/read/28229086/rb-an-essential-player-in-adult-neurogenesis
#7
Bensun C Fong, Ruth S Slack
The fundamental mechanisms underlying adult neurogenesis remain to be fully clarified. Members of the cell cycle machinery have demonstrated key roles in regulating adult neural stem cell (NSC) quiescence and the size of the adult-born neuronal population. The retinoblastoma protein, Rb, is known to possess CNS-specific requirements that are independent from its classical role as a tumor suppressor. The recent study by Vandenbosch et al. has clarified distinct requirements for Rb during adult neurogenesis, in the restriction of proliferation, as well as long-term adult-born neuronal survival...
2017: Neurogenesis (Austin, Tex.)
https://www.readbyqxmd.com/read/28228579/network-wide-oscillations-in-the-parkinsonian-state-alterations-in-neuronal-activities-occur-in-the-premotor-cortex-in-parkinsonian-non-human-primates
#8
Jing Wang, Luke A Johnson, Alicia L Jensen, Kenneth B Baker, Jerrold L Vitek
A number of studies suggest that Parkinson's disease (PD) is associated with alterations of neuronal activity patterns in the basal-ganglia-thalamocortical circuit. There are limited electrophysiological data, however, describing how premotor cortex, which is involved in movement and decision making, is likely impacted in PD. In this study, spontaneous local field potential (LFP) and single unit neuronal activity were recorded in the dorsal premotor area of non-human primates in both the naïve and parkinsonian state using the MPTP model of parkinsonism...
February 22, 2017: Journal of Neurophysiology
https://www.readbyqxmd.com/read/28228285/mass-spectrometry-profiling-of-hla-associated-peptidomes-in-mono-allelic-cells-enables-more-accurate-epitope-prediction
#9
Jennifer G Abelin, Derin B Keskin, Siranush Sarkizova, Christina R Hartigan, Wandi Zhang, John Sidney, Jonathan Stevens, William Lane, Guang Lan Zhang, Thomas M Eisenhaure, Karl R Clauser, Nir Hacohen, Michael S Rooney, Steven A Carr, Catherine J Wu
Identification of human leukocyte antigen (HLA)-bound peptides by liquid chromatography-tandem mass spectrometry (LC-MS/MS) is poised to provide a deep understanding of rules underlying antigen presentation. However, a key obstacle is the ambiguity that arises from the co-expression of multiple HLA alleles. Here, we have implemented a scalable mono-allelic strategy for profiling the HLA peptidome. By using cell lines expressing a single HLA allele, optimizing immunopurifications, and developing an application-specific spectral search algorithm, we identified thousands of peptides bound to 16 different HLA class I alleles...
February 21, 2017: Immunity
https://www.readbyqxmd.com/read/28227977/surrogate-analysis-of-fractal-dimensions-from-semg-sensor-array-as-a-predictor-of-chronic-low-back-pain
#10
Manouane Caza-Szoka, Daniel Massicotte, Francois Nougarou, Martin Descarreaux, Manouane Caza-Szoka, Daniel Massicotte, Francois Nougarou, Martin Descarreaux, Manouane Caza-Szoka, Daniel Massicotte, Martin Descarreaux, Francois Nougarou
In this paper, a method based on nonlinear analysis of sEMG sensor array signals (2 arrays of 5×13 sensors) to detect chronic low back pain is presented. The use of an FFT based surrogate analysis method isolates the nonlinear structure of the signals from the effect of the power spectrum. The fractal dimension is used for the nonlinear characteristic. From the sensor arrays, a certain number of channels which exhibits the most nonlinearity for a subject are kept as input of a small neural network. A leave-one-out type cross-validation method shows a success rate of 80%...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227976/user-intent-prediction-with-a-scaled-conjugate-gradient-trained-artificial-neural-network-for-lower-limb-amputees-using-a-powered-prosthesis
#11
Richard B Woodward, John A Spanias, Levi J Hargrove, Richard B Woodward, John A Spanias, Levi J Hargrove, John A Spanias, Richard B Woodward, Levi J Hargrove
Powered lower limb prostheses have the ability to provide greater mobility for amputee patients. Such prostheses often have pre-programmed modes which can allow activities such as climbing stairs and descending ramps, something which many amputees struggle with when using non-powered limbs. Previous literature has shown how pattern classification can allow seamless transitions between modes with a high accuracy and without any user interaction. Although accurate, training and testing each subject with their own dependent data is time consuming...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227973/improving-odorant-chemical-class-prediction-with-multi-layer-perceptrons-using-temporal-odorant-spike-responses-from-drosophila-melanogaster-olfactory-receptor-neurons
#12
Luqman R Bachtiar, Richard D Newcomb, Andrew V Kralicek, Charles P Unsworth, Luqman R Bachtiar, Richard D Newcomb, Andrew V Kralicek, Charles P Unsworth, Charles P Unsworth, Andrew V Kralicek, Richard D Newcomb, Luqman R Bachtiar
In this work, we examine the possibility of improving the prediction performance of an olfactory biosensor through the use of temporal spiking data. We present an Artificial Neural Network (ANN), in the form of an optimal hybrid Multi-Layer Perceptron (MLP) system for the classification of chemical odorants from olfactory receptor neuron spike responses of the Drosophila melanogaster fruit fly (DmOrs). The data used in this study contains the responses to 34 odorants from 6 individual DmOrs, of which we exploit the temporal spiking responses of a 500ms odorant stimulus window...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227964/cross-entropy-optimization-for-neuromodulation
#13
Harleen K Brar, Yunpeng Pan, Babak Mahmoudi, Evangelos A Theodorou, Harleen K Brar, Yunpeng Pan, Babak Mahmoudi, Evangelos A Theodorou, Yunpeng Pan, Harleen K Brar, Babak Mahmoudi, Evangelos A Theodorou
This study presents a reinforcement learning approach for the optimization of the proportional-integral gains of the feedback controller represented in a computational model of epilepsy. The chaotic oscillator model provides a feedback control systems view of the dynamics of an epileptic brain with an internal feedback controller representative of the natural seizure suppression mechanism within the brain circuitry. Normal and pathological brain activity is simulated in this model by adjusting the feedback gain values of the internal controller...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227963/predicting-seizures-from-local-field-potentials-recorded-via-intracortical-microelectrode-arrays
#14
Mehdi Aghagolzadeh, Leigh R Hochberg, Sydney S Cash, Wilson Truccolo, Mehdi Aghagolzadeh, Leigh R Hochberg, Sydney S Cash, Wilson Truccolo, Sydney S Cash, Wilson Truccolo, Mehdi Aghagolzadeh, Leigh R Hochberg
The need for new therapeutic interventions to treat pharmacologically resistant focal epileptic seizures has led recently to the development of closed-loop systems for seizure control. Once a seizure is predicted/detected by the system, electrical stimulation is delivered to prevent seizure initiation or spread. So far, seizure prediction/detection has been limited to tracking non-invasive electroencephalogram (EEG) or intracranial EEG (iEEG) signals. Here, we examine seizure prediction based on local field potentials (LFPs) from a small neocortical patch recorded via a 10×10 microelectrode array implanted in a patient with focal seizures...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227925/principal-component-analysis-can-decrease-neural-networks-performance-for-incipient-falls-detection-a-preliminary-study-with-hands-and-feet-accelerations
#15
Fiorenzo Artoni, Dario Martelli, Vito Monaco, Silvestre Micera, Fiorenzo Artoni, Dario Martelli, Vito Monaco, Silvestre Micera
Fall-related accidents constitute a major problem for elderly people and a burden to the health-care national system. It is therefore important to design devices (e.g., accelerometers) and machine learning algorithms able to recognize incipient falls as quickly and reliably as possible. Blind source separation (BSS) methods are often used as a preprocessing step before classification, however the effects of BSS on classification performance are not well understood. The aim of this work is to preliminarily characterize the effect that two methods, namely Principal and Independent Component Analysis (PCA and ICA) and their combined use have on the performance of a neural network in detecting incipient falls...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227924/a-hybrid-hardware-and-software-approach-for-cancelling-stimulus-artifacts-during-same-electrode-neural-stimulation-and-recording
#16
Stanislav Culaclii, Brian Kim, Yi-Kai Lo, Wentai Liu, Stanislav Culaclii, Brian Kim, Yi-Kai Lo, Wentai Liu, Brian Kim, Yi-Kai Lo, Wentai Liu, Stanislav Culaclii
Recovering neural responses from electrode recordings is fundamental for understanding the dynamics of neural networks. This effort is often obscured by stimulus artifacts in the recordings, which result from stimuli injected into the electrode-tissue interface. Stimulus artifacts, which can be orders of magnitude larger than the neural responses of interest, can mask short-latency evoked responses. Furthermore, simultaneous neural stimulation and recording on the same electrode generates artifacts with larger amplitudes compared to a separate electrode setup, which inevitably overwhelm the amplifier operation and cause unrecoverable neural signal loss...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227909/neuromorphic-circuit-modeling-directional-selectivity-in-the-visual-cortex
#17
Saeid Barzegarjalali, Alice C Parker, Saeid Barzegarjalali, Alice C Parker, Alice C Parker, Saeid Barzegarjalali
We have designed a neuromorphic circuit that models directional selectivity in the visual cortex, where selected neurons fire depending on the direction of object motion, along with the size and orientation of the object. The neuromorphic circuit is biomimetic. It consists of neurons and synapses, and models biological mechanisms. Neurons (including the Axon Hillock and the Dendritic Arbor) are designed with CMOS technology and synapses (both excitatory and inhibitory) are designed with Carbon Nanotube Transistors...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227907/understanding-the-role-of-astrocytic-gaba-in-simulated-neural-networks
#18
Kerstin Lenk, Eero Raisanen, Jari A K Hyttinen, Kerstin Lenk, Eero Raisanen, Jari A K Hyttinen, Kerstin Lenk, Jari Ak Hyttinen, Eero Raisanen
Astrocytes actively influence the behavior of the surrounding neuronal network including changes of the synaptic plasticity and neuronal excitability. These dynamics are altered in diseases like Alzheimer's, where the release of the gliotransmitter GABA is increased by affected, so called reactive astrocytes. In this paper, we aim to simulate a neural network with altered astrocytic GABA release. Therefore, we use our developed neuron-astrocyte model, called INEXA, which includes astrocyte controlled tripartite synapses and the astrocyte-astrocyte interaction...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227901/identifying-montages-that-best-detect-the-electroencephalogram-power-spectrum-alteration-during-freezing-of-gait-in-parkinson-s-disease-patients
#19
Quynh Tran Ly, A M Ardi Handojoseno, Moran Gilat, Nghia Nguyen, Rifai Chai, Yvonne Tran, Simon J G Lewis, Hung T Nguyen, Quynh Tran Ly, A M Ardi Handojoseno, Moran Gilat, Nghia Nguyen, Rifai Chai, Yvonne Tran, Simon J G Lewis, Hung T Nguyen, Nghia Nguyen, A M Ardi Handojoseno, Moran Gilat, Hung T Nguyen, Yvonne Tran, Simon J G Lewis, Quynh Tran Ly, Rifai Chai
Our research team has previously used four Electroencephalography (EEG) leads to successfully detect and predict Freezing of Gait (FOG) in Parkinson's disease (PD). However, it remained to be determined whether these four sensor locations that were arbitrarily chosen based on their role in motor control are indeed the most optimal for FOG detection. The aim of this study was therefore to determine the most optimal location and combination of sensors to detect FOG amongst a 32-channel EEG montage using our EEG classification system...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227834/development-of-semi-chronic-microdrive-system-for-large-scale-circuit-mapping-in-macaque-mesolimbic-and-basal-ganglia-systems
#20
Shaoyu Qiao, Kevin A Brown, Amy L Orsborn, Breonna Ferrentino, Bijan Pesaran, Shaoyu Qiao, Kevin A Brown, Amy L Orsborn, Breonna Ferrentino, Bijan Pesaran, Shaoyu Qiao, Amy L Orsborn, Breonna Ferrentino, Kevin A Brown, Bijan Pesaran
The development of novel neurotechnologies for treating refractory neuropsychiatry disorders depends on understanding and manipulating the dynamics of neural circuits across large-scale brain networks. The mesolimbic pathway plays an essential role in reward processing and mood regulation and disorders of this pathway underlie many neuropsychiatric disorders. Here, we present the design of a customized semi-chronic microdrive array that precisely targets the anatomical structures of non-human primate (NHP) mesolimbic and basal ganglia systems...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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