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https://www.readbyqxmd.com/read/28324930/rtms-enhanced-gamma-oscillation-through-strengthened-network-connection
#1
Mengmeng Dou, Xin Tian
Gamma oscillations emerge generally in working memory to aspect of higher cognitive functions, and typically with the interaction of brain network. How is gamma oscillatory activity influenced by the functional connection in the brain'a network? How can gamma oscillations be increased by neural modulation to result in potential benefits for working memory? The present study aims to investigate the intensity of gamma oscillations modulated by low frequency repetitive transcranial magnetic stimulation (rTMS), and the possible brain network mechanism of increased gamma oscillations during working memory task in rats...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28323296/new-photoheterolysis-precursors-to-study-oxenium-ions-combining-experiment-and-theory
#2
Yunfan Qiu, Arthur H Winter
The combination of theoretical calculations and laser flash photolysis experiments has aided in understanding the reactivity and properties of oxenium ions. Direct observation of the reactivity, spin configurations, and lifetimes of short-lived oxenium ions via laser flash photolysis (LFP) techniques is now possible due to the discovery of new photoprecursors to these species. These new precursors allowed the direct observation of the parent phenyloxenium ion in solution by using protonated hydroxylamine tetrafluoroborate salt...
March 21, 2017: Organic & Biomolecular Chemistry
https://www.readbyqxmd.com/read/28322553/label-free-chemical-imaging-of-latent-fingerprints-with-stimulated-raman-scattering-microscopy
#3
Benjamin Figueroa, Yikai Chen, Kyla Berry, Andrew Francis, Dan Fu
Fingerprints have long been the gold standard for personal identification in forensic investigations. Methods for cultivating and enhancing the visualization of latent fingerprints (LFPs) are continuously evolving. One important challenge is to identify suspicious chemicals present in fingerprint residues, which requires chemical imaging capability. Recently, vibrational spectroscopy has shown that LFP analysis through tape-lift, Raman mapping, and multivariate data analysis presents a useful tool for forensic investigation...
March 21, 2017: Analytical Chemistry
https://www.readbyqxmd.com/read/28298263/a-proof-of-principle-simulation-for-closed-loop-control-based-on-preexisting-experimental-thalamic-dbs-enhanced-instrumental-learning
#4
Ching-Fu Wang, Shih-Hung Yang, Sheng-Huang Lin, Po-Chuan Chen, Yu-Chun Lo, Han-Chi Pan, Hsin-Yi Lai, Lun-De Liao, Hui-Ching Lin, Hsu-Yan Chen, Wei-Chen Huang, Wun-Jhu Huang, You-Yin Chen
Deep brain stimulation (DBS) has been applied as an effective therapy for treating Parkinson's disease or essential tremor. Several open-loop DBS control strategies have been developed for clinical experiments, but they are limited by short battery life and inefficient therapy. Therefore, many closed-loop DBS control systems have been designed to tackle these problems by automatically adjusting the stimulation parameters via feedback from neural signals, which has been reported to reduce the power consumption...
February 24, 2017: Brain Stimulation
https://www.readbyqxmd.com/read/28286184/altered-functional-efficacy-of-hippocampal-interneuron-during-epileptogenesis-following-febrile-seizures
#5
Yeon Hee Yu, Kahyun Lee, Dal Sik Sin, Kyung-Ho Park, Dae-Kyoon Park, Duk-Soo Kim
Febrile seizure (FS) is the most common seizure type in infants and young children. FS may induce functional changes in the hippocampal circuitries. Abnormality of excitatory and inhibitory neurotransmissions was previously related to wide-spread seizure attack in the hippocampus following recurrent seizure onset. To clarify the involvement of expressional changes and functional alterations of hippocampal interneurons with epileptogenesis following FS, we investigated long-term effects following recurrent seizure in a hyperthermia-induced seizure animal model...
March 7, 2017: Brain Research Bulletin
https://www.readbyqxmd.com/read/28269704/multiscale-brain-machine-interface-decoders
#6
Han-Lin Hsieh, Maryam M Shanechi
Brain-machine interfaces (BMI) have vastly used a single scale of neural activity, e.g., spikes or electrocorticography (ECoG), as their control signal. New technology allows for simultaneous recording of multiple scales of neural activity, from spikes to local field potentials (LFP) and ECoG. These advances introduce the new challenge of modeling and decoding multiple scales of neural activity jointly. Such multi-scale decoding is challenging for two reasons. First, spikes are discrete-valued and ECoG/LFP are continuous-valued, resulting in fundamental differences in statistical characteristics...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28269702/predicting-seizures-from-local-field-potentials-recorded-via-intracortical-microelectrode-arrays
#7
Mehdi Aghagolzadeh, Leigh R Hochberg, Sydney S Cash, Wilson Truccolo
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/28269554/adaptive-decoding-using-local-field-potentials-in-a-brain-machine-interface
#8
Rosa So, Camilo Libedinsky, Kai Keng Ang, Wee Chiek Clement Lim, Kyaw Kyar Toe, Cuntai Guan
Brain-machine interface (BMI) systems have the potential to restore function to people who suffer from paralysis due to a spinal cord injury. However, in order to achieve long-term use, BMI systems have to overcome two challenges - signal degeneration over time, and non-stationarity of signals. Effects of loss in spike signals over time can be mitigated by using local field potential (LFP) signals for decoding, and a solution to address the signal non-stationarity is to use adaptive methods for periodic recalibration of the decoding model...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28269553/decoding-force-from-deep-brain-electrodes-in-parkinsonian-patients
#9
Syed A Shah, Huiling Tan, Peter Brown
Limitations of many Brain Machine Interface (BMI) systems using invasive electrodes include reliance on single neurons and decoding limited to kinematics only. This study investigates whether force-related information is present in the local field potential (LFP) recorded with deep brain electrodes using data from 14 patients with Parkinson's disease. A classifier based on logistic regression (LR) is developed to classify various force stages, using 10-fold cross validation. Least Absolute and Shrinkage Operator (Lasso) is then employed in order to identify the features with the most predictivity...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268628/idle-state-classification-using-spiking-activity-and-local-field-potentials-in-a-brain-computer-interface
#10
Jordan J Williams, Rex N Tien, Yoh Inoue, Andrew B Schwartz
Previous studies of intracortical brain-computer interfaces (BCIs) have often focused on or compared the use of spiking activity and local field potentials (LFPs) for decoding kinematic movement parameters. Conversely, using these signals to detect the initial intention to use a neuroprosthetic device or not has remained a relatively understudied problem. In this study, we examined the relative performance of spiking activity and LFP signals in detecting discrete state changes in attention regarding a user's desire to actively control a BCI device...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268500/a-multiple-kernel-learning-approach-for-human-behavioral-task-classification-using-stn-lfp-signal
#11
Hosein M Golshan, Adam O Hebb, Sara J Hanrahan, Joshua Nedrud, Mohammad H Mahoor
Deep Brain Stimulation (DBS) has gained increasing attention as an effective method to mitigate Parkinson's disease (PD) disorders. Existing DBS systems are open-loop such that the system parameters are not adjusted automatically based on patient's behavior. Classification of human behavior is an important step in the design of the next generation of DBS systems that are closed-loop. This paper presents a classification approach to recognize such behavioral tasks using the subthalamic nucleus (STN) Local Field Potential (LFP) signals...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28254363/the-human-globus-pallidus-internus-is-sensitive-to-rewards-evidence-from-intracerebral-recordings
#12
Thomas F Münte, Josep Marco-Pallares, Seza Bolat, Marcus Heldmann, Götz Lütjens, Wido Nager, Kirsten Müller-Vahl, Joachim K Krauss
BACKGROUND: The globus pallidus internus (GPi) is the final output relay of the basal ganglia for the control of movements but has also been shown to belong to a second pathway projecting to the lateral habenula. This latter pathway is related to reward processing. METHOD: This prompted us to record, in eight patients receiving deep brain stimulation of the GPi for the alleviation of various movement disorders, local field potentials (LFP) while these patients performed a lottery task...
February 14, 2017: Brain Stimulation
https://www.readbyqxmd.com/read/28250407/mechanical-stimulus-induced-wthdrawal-behavior-increases-subsequent-pre-stimulus-local-field-potential-power-in-the-rostral-anterior-cingulate-cortex-in-unanesthetized-rats
#13
Zui Shen, Jing Sun, Boyi Liu, Yongliang Jiang, Yuanyuan Wu, Jialing Wang, Xiaomei Shao, Jianqiao Fang
BACKGROUND The rostral anterior cingulate cortex (rACC) is important in pain expectation. Previous studies demonstrated that mechanical stimulus-induced withdrawal behaviors are spinally-mediated nocifensive reflexes in rats, but it is not known whether pain expectation is influenced by withdrawal behaviors. MATERIAL AND METHODS We reanalyzed previous mechanosensitivity measurements of 244 rats measured 5 times in succession. To study neural oscillation in the rACC, 1 recording microwire array was surgically implanted...
March 2, 2017: Medical Science Monitor: International Medical Journal of Experimental and Clinical Research
https://www.readbyqxmd.com/read/28231381/hippocampal-prefrontal-theta-phase-synchrony-in-planning-of-multi-step-actions-based-on-memory-retrieval
#14
Seiya Ishino, Susumu Takahashi, Masaaki Ogawa, Yoshio Sakurai
Planning of multi-step actions based on the retrieval of acquired information is essential for efficient foraging. The hippocampus (HPC) and prefrontal cortex (PFC) may play critical roles in this process. However, in rodents, many studies investigating such roles utilized T-maze tasks that only require one-step actions (i.e., selection of one of two alternatives), in which memory retrieval and selection of an action based on the retrieval cannot be clearly differentiated. In monkeys, PFC has been suggested to be involved in planning of multi-step actions; however, the synchrony between HPC and PFC has not been evaluated...
February 23, 2017: European Journal of Neuroscience
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
#15
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/28227965/multiscale-brain-machine-interface-decoders
#16
Han-Lin Hsieh, Maryam M Shanechi, Han-Lin Hsieh, Maryam M Shanechi, Han-Lin Hsieh, Maryam M Shanechi
Brain-machine interfaces (BMI) have vastly used a single scale of neural activity, e.g., spikes or electrocorticography (ECoG), as their control signal. New technology allows for simultaneous recording of multiple scales of neural activity, from spikes to local field potentials (LFP) and ECoG. These advances introduce the new challenge of modeling and decoding multiple scales of neural activity jointly. Such multi-scale decoding is challenging for two reasons. First, spikes are discrete-valued and ECoG/LFP are continuous-valued, resulting in fundamental differences in statistical characteristics...
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
#17
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/28227808/adaptive-decoding-using-local-field-potentials-in-a-brain-machine-interface
#18
Rosa So, Camilo Libedinsky, Kai Keng Ang, Wee Chiek Clement Lim, Kyaw Kyar Toe, Cuntai Guan, Rosa So, Camilo Libedinsky, Kai Keng Ang, Wee Chiek Clement Lim, Kyaw Kyar Toe, Cuntai Guan, Rosa So, Wee Chiek Clement Lim, Kai Keng Ang, Kyaw Kyar Toe, Camilo Libedinsky, Cuntai Guan
Brain-machine interface (BMI) systems have the potential to restore function to people who suffer from paralysis due to a spinal cord injury. However, in order to achieve long-term use, BMI systems have to overcome two challenges - signal degeneration over time, and non-stationarity of signals. Effects of loss in spike signals over time can be mitigated by using local field potential (LFP) signals for decoding, and a solution to address the signal non-stationarity is to use adaptive methods for periodic recalibration of the decoding model...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226808/idle-state-classification-using-spiking-activity-and-local-field-potentials-in-a-brain-computer-interface
#19
Jordan J Williams, Rex N Tien, Yoh Inoue, Andrew B Schwartz, Jordan J Williams, Rex N Tien, Yoh Inoue, Andrew B Schwartz, Rex N Tien, Andrew B Schwartz, Jordan J Williams, Yoh Inoue
Previous studies of intracortical brain-computer interfaces (BCIs) have often focused on or compared the use of spiking activity and local field potentials (LFPs) for decoding kinematic movement parameters. Conversely, using these signals to detect the initial intention to use a neuroprosthetic device or not has remained a relatively understudied problem. In this study, we examined the relative performance of spiking activity and LFP signals in detecting discrete state changes in attention regarding a user's desire to actively control a BCI device...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226674/a-multiple-kernel-learning-approach-for-human-behavioral-task-classification-using-stn-lfp-signal
#20
Hosein M Golshan, Adam O Hebb, Sara J Hanrahan, Joshua Nedrud, Mohammad H Mahoor, Hosein M Golshan, Adam O Hebb, Sara J Hanrahan, Joshua Nedrud, Mohammad H Mahoor, Joshua Nedrud, Adam O Hebb, Sara J Hanrahan, Mohammad H Mahoor, Hosein M Golshan
Deep Brain Stimulation (DBS) has gained increasing attention as an effective method to mitigate Parkinson's disease (PD) disorders. Existing DBS systems are open-loop such that the system parameters are not adjusted automatically based on patient's behavior. Classification of human behavior is an important step in the design of the next generation of DBS systems that are closed-loop. This paper presents a classification approach to recognize such behavioral tasks using the subthalamic nucleus (STN) Local Field Potential (LFP) signals...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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