123 resources related to Neural pathways
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The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted papers will be peer reviewed. Accepted high quality papers will be presented in oral and postersessions, will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE
The International Conference on Robotics and Automation (ICRA) is the IEEE Robotics and Automation Society’s biggest conference and one of the leading international forums for robotics researchers to present their work.
11th International Conference on Computational Intelligence and Communication Networks (CICN 2017) is organized to address various issues to support intelligentsolutions for society. The aim is to bring together worldwide leading researchers, developers, practitioners and educators interested in advancing the state of the art in computational intelligence and communication networks with the goal of exchanging knowledge that encompasses a broad range of disciplines among various distinct communities. It is expected that researchers will enhance collaboration across disciplines in order to support novel breakthroughs in the field.
The IEEE Sensors Conference is a forum for presentation, discussion, and exchange of state-of-the art information including the latest research and development in sensors and their related fields. It brings together researchers, developers, and practitioners from diverse fields including international scientists and engineers from academia, research institutes, and companies to present and discuss the latest results in the general field of sensors.
The Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems ...
Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.
Part I will now contain regular papers focusing on all matters related to fundamental theory, applications, analog and digital signal processing. Part II will report on the latest significant results across all of these topic areas.
Telephone, telegraphy, facsimile, and point-to-point television, by electromagnetic propagation, including radio; wire; aerial, underground, coaxial, and submarine cables; waveguides, communication satellites, and lasers; in marine, aeronautical, space and fixed station services; repeaters, radio relaying, signal storage, and regeneration; telecommunication error detection and correction; multiplexing and carrier techniques; communication switching systems; data communications; and communication theory. In addition to the above, ...
Both general and technical articles on current technologies and methods used in biomedical and clinical engineering; societal implications of medical technologies; current news items; book reviews; patent descriptions; and correspondence. Special interest departments, students, law, clinical engineering, ethics, new products, society news, historical features and government.
Proceedings of the IEEE 25th Annual Northeast Bioengineering Conference (Cat. No. 99CH36355), 1999
The details in timing and dynamics of inward (convergence) and outward (divergence) turning eye movements (vergence eye movements) were compared. Experiments showed that there were significant differences in the timing characteristics of convergence versus divergence movements. A model-based analysis showed that the dynamics were also different in these two vergence eye movements. Based on the assumption that these movements are ...
Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02., 2002
The sound localization of barn owl with respect to horizontal and vertical direction is made based on analysis of the interaural differences in arrival time and intensity of sound, respectively. The neural information processing of detection of interaural intensity difference (IID) is made on the neural pathway parallel with the pathway of interaural time difference (ITD) detection before both the ...
2003 IEEE 29th Annual Proceedings of Bioengineering Conference, 2003
The development of an artificial directionally selective pathway based on neural network architecture provides a critical element to the development of a complete artificial vision system. By developing algorithms which emulate the neural processing pathways within the retina, retinal implants can be developed which not only encode light in a feedforward manner but also include feedback mechanisms and computational pathways. ...
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 1988
Reactive hyperemia, following one minute of total cerebral ischemia in the rat's brain, is studied using an original mathematical model of cerebrovascular regulation. The effect of intrinsic vascular smooth muscle myogenic reactivity, of cholinergic efferent neural pathways on proximal arteries, and of vasodilating chemical substances (adenosine and H/sup +/) on pial arteries and arterioles have all been taken into account ...
Computers in Cardiology 2000. Vol.27 (Cat. 00CH37163), 2000
The authors studied the effects of esophageal electrical stimulation on heart rate variability power spectra and cortical evoked potentials (EPs) in healthy subjects. In the first study they stimulated the esophagus of 15 healthy subjects at 20 mA using 200 /spl mu/s wide pulses at frequencies from 0.1 Hz to 1 Hz. For the second study they stimulated the esophagus ...
Applying Control Theory to the Design of Cancer Therapy
Auditory Neural Pathway Simulation - IEEE Rebooting Computing 2017
ICASSP 2010 - Advances in Neural Engineering
Towards On-Chip Optical FFTs for Convolutional Neural Networks - IEEE Rebooting Computing 2017
Achieving Swarm Intelligence with Spiking Neural Oscillators - IEEE Rebooting Computing 2017
20 Years of Neural Networks: A Promising Start, A brilliant Future- Video contents
Spike Timing, Rhythms, and the Effective Use of Neural Hardware
Improved Deep Neural Network Hardware Accelerators Based on Non-Volatile-Memory: the Local Gains Technique: IEEE Rebooting Computing 2017
Lizhong Zheng's Globecom 2019 Keynote
Large-scale Neural Systems for Vision and Cognition
On the Physical Underpinnings of the Unusual Effectiveness of Probabilistic and Neural Computation - IEEE Rebooting Computing 2017
Behind Artificial Neural Networks
Emergent Neural Network in reinforcement learning
Artificial Neural Networks, Intro
Uncovering the Neural Code of Learning Control - Jennie Si - WCCI 2012 invited lecture
Overcoming the Static Learning Bottleneck - the Need for Adaptive Neural Learning - Craig Vineyard: 2016 International Conference on Rebooting Computing
Neural Processor Design Enabled by Memristor Technology - Hai Li: 2016 International Conference on Rebooting Computing
A Comparator Design Targeted Towards Neural Net - David Mountain - ICRC San Mateo, 2019
High Throughput Neural Network based Embedded Streaming Multicore Processors - Tarek Taha: 2016 International Conference on Rebooting Computing
The details in timing and dynamics of inward (convergence) and outward (divergence) turning eye movements (vergence eye movements) were compared. Experiments showed that there were significant differences in the timing characteristics of convergence versus divergence movements. A model-based analysis showed that the dynamics were also different in these two vergence eye movements. Based on the assumption that these movements are driven by a neural signal composed of a pulse and a step, the gain ratio between pulse and step components was much larger than one for convergence responses, but was close to or less than one in divergence responses. These data indicate that the neural control signal for divergence is close to a simple step rather than the combined pulse-step signal in convergence.
The sound localization of barn owl with respect to horizontal and vertical direction is made based on analysis of the interaural differences in arrival time and intensity of sound, respectively. The neural information processing of detection of interaural intensity difference (IID) is made on the neural pathway parallel with the pathway of interaural time difference (ITD) detection before both the signals arrive at the shell of central nucleus of the inferior colliculus (ICc shell). We have presented a neural model of ITD detection pathway (Inoue et al, Neurocomputing 2001, vol. 38-40, pp. 675-682). We present a neuronal model of the nucleus ventralis lemnisci lateralis pars posterior (VLVp) in which the signals of sound intensities coming from both the ears are first combined to be compared with each other. We clarify the functional role of mutual inhibitory connections between both VLVps observed experimentally in detection of IID. Outputs of IID sensitive neurons in both VLVps are projected bilaterally to ICc shell and the connections are inhibitory, whereas outputs of ITD sensitive neurons in ICc core projected to ICc shell are excitatory. It is shown using our neuronal models of VLVps, ICc core, and ICc shell that the neural map, in which ITD and IID are represented along the axes perpendicular mutually, can be generated in ICc shell by the excitatory inputs from ICc core and the inhibitory inputs from bilateral VLVps, as observed experimentally. We also show that the firing rate of ICc shell neuron are well represented by a suppressive multiplication of ITD and IID inputs.
The development of an artificial directionally selective pathway based on neural network architecture provides a critical element to the development of a complete artificial vision system. By developing algorithms which emulate the neural processing pathways within the retina, retinal implants can be developed which not only encode light in a feedforward manner but also include feedback mechanisms and computational pathways. In addition, the application of neural networks to the replication of neural pathways provides a more natural solution than by replicating these pathways in the conventional serial manner. Parallelism is the key to neurological pathway replication because biological neural networks are naturally parallel. Ultimately neural data flow computers will likely provide the best solution to biological replication do to the vast similarities between the electrical hardware and the biological architecture.
Reactive hyperemia, following one minute of total cerebral ischemia in the rat's brain, is studied using an original mathematical model of cerebrovascular regulation. The effect of intrinsic vascular smooth muscle myogenic reactivity, of cholinergic efferent neural pathways on proximal arteries, and of vasodilating chemical substances (adenosine and H/sup +/) on pial arteries and arterioles have all been taken into account in the model. The time pattern of cerebral blood flow and of the radii of cerebral vessels from major brain arteries to precapillary arterioles are simulated by the model during the ischemic and postischemic periods. The role played by the different regulatory actions in the development and maintenance of reactive hyperemia is analyzed.<<ETX>>
The authors studied the effects of esophageal electrical stimulation on heart rate variability power spectra and cortical evoked potentials (EPs) in healthy subjects. In the first study they stimulated the esophagus of 15 healthy subjects at 20 mA using 200 /spl mu/s wide pulses at frequencies from 0.1 Hz to 1 Hz. For the second study they stimulated the esophagus of 13 volunteers at currents from 2-20 mA and at 6/minute. For both studies the LF:HF ratio decreased significantly during stimulation when compared to resting levels. In the second study, the amplitude of the principal wave (P2) of the EP increased with the stimulus intensity. The authors' studies suggest that esophageal stimulation can permit one to access neural pathways of the autonomic nervous system.
Vergence eye movements are commonly treated as members of a distinct subclass of eye movements along with four types of conjugate movements: saccade, smooth pursuit, optokinetic response (OKR), and vestibulo-ocular reflex (VOR). According to this classification, many researchers try to determine the particular neural pathways or signal sources related to vergence, and have not been aware that most vergence eye movements are controlled using the same ocular motor system as conjugate movements. I suggest that, in fact, fusional vergence is saccade, accommodative vergence (Baker, R. et al., Ann. B. Y Acad Sci. Part IV, p.171 1981; Robinson, D.A., 1977) is smooth pursuit, flow induced vergence (Baker et al.) is OKP, and the vergence occurring by head movement is a family of VOR. I show the grounds for this suggestion.
This study investigates how the saccadic components (quick phases) of vestibular nystagmus are generated. We propose a neural network model for the vestibule saccadic pathway, which shows dynamic adaptation of the quick phase parameters in order to faithfully reproduce the vestibular nystagmus. A structure similar to that proposed in this paper is likely to exist in the neural pathway linking the vestibular nuclei to the PPRF (paramedian pontine reticular formation) through the nucleus prepositus hypoglossi.
This article describes the application of a Multi-Layer Perceptron (MLP) to the problem of diagnosing Multiple Sclerosis (MS). The classification information is obtained by a Trigeminal Evoked Potential (TEP) test. The performance of the MLP is compared with that of the human experts and the Bayes classifier. The efficiency of the neural network and the classical classifiers in conjunction with 4 types of features - the Fourier transform (FT), the peak position, the ARX model coefficient and the temporal wave form - are examined. Although a large clinical data base would be necessary, before this approach can be fully validated, the initial results are very promising. The MLP was found to be less susceptible to the number of features used. The ability of the MLP classifier to generalize is far better than that of the Bayes classifier.
Existing commercial vestibular evoked myogenic potentials (VEMP) testing systems are cabled systems, which impede certain experiments, particularly those that involve motion and rotation of the patient. This paper presents an autonomous wireless system to record VEMPs. The system uses IMEC's 60 muW 60 nV/VHz biopotential readout front-end to extract the electromyogram (EMG). It uses IMEC's low power processing and wireless platform to perform all signal processing locally, significantly reducing the amount of wireless data transmission. The system also implements a low power audio synthesizer and an amplifier to create the necessary audio or vibration stimuli that are applied to the patient. The system can perform 1000 measurements on 2 AA batteries.
Patients with neurodegenerative diseases loose all motor movements including impairment of speech, leaving the patients totally locked-in. One possible option for rehabilitation of such patients is using a brain machine interfaces (BMI) which uses their active cognition capabilities to control external devices and their environment. BMIs are designed using the electrical activity of the brain detected by scalp EEG electrodes. Classification of EEG signals extracted during mental tasks is a technique for designing a BMI. In this paper five different mental tasks from five subjects were studied, for classification combinations of two tasks are studied for each subject. A fuzzy based classification method is proposed for classification of the EEG mental task signals. Power of the spectral band frequencies of the EEG are used as features for training and testing the fuzzy classifier. Classification accuracies ranged from 65% to 100% for different combinations of mental tasks. The results validate the performance of the proposed algorithm for mental task classification.
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