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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 CDC is the premier conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.
The ACC is the annual conference of the American Automatic Control Council (AACC, the U.S. national member organization of the International Federation for Automatic Control (IFAC)). The ACC is internationally recognized as a premier scientific and engineering conference dedicated to the advancement of control theory and practice. The ACC brings together an international community of researchers and practitioners to discuss the latest findings in automatic control. The 2020 ACC technical program will
2020 IEEE International Symposium on Circuits and Systems (ISCAS)
The International Symposium on Circuits and Systems (ISCAS) is the flagship conference of the IEEE Circuits and Systems (CAS) Society and the world’s premier networking and exchange forum for researchers in the highly active fields of theory, design and implementation of circuits and systems. ISCAS2020 focuses on the deployment of CASS knowledge towards Society Grand Challenges and highlights the strong foundation in methodology and the integration of multidisciplinary approaches which are the distinctive features of CAS contributions. The worldwide CAS community is exploiting such CASS knowledge to change the way in which devices and circuits are understood, optimized, and leveraged in a variety of systems and applications.
All areas of ionizing radiation detection - detectors, signal processing, analysis of results, PET development, PET results, medical imaging using ionizing radiation
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.
IEEE Transactions on Biomedical Engineering, 2014
A novel signal-processing strategy is proposed to enhance speech for listeners with hearing loss. The strategy focuses on improving vowel perception based on a recent hypothesis for vowel coding in the auditory system. Traditionally, studies of neural vowel encoding have focused on the representation of formants (peaks in vowel spectra) in the discharge patterns of the population of auditory-nerve (AN) ...
First International IEEE EMBS Conference on Neural Engineering, 2003. Conference Proceedings., 2003
This paper presents a new approach for hearing restoration in patients suffering from sensorineural hearing loss. We focus on the development of a midbrain auditory prosthesis, implanted into the central nucleus of the inferior colliculus (ICC). We performed experiments in a guinea pig model to initially explore the tonotopic map that exists between ICC and the primary auditory cortex (A1), ...
2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2018
The brain integrates information from different sensory modalities to form a representation of the environment and facilitate behavioral responses. The auditory midbrain or inferior colliculus (IC) is a pivotal station in the auditory system, integrating ascending and descending information from various auditory sources and cortical systems. The present study investigated the modulation of auditory responses in the IC by visual ...
2012 46th Annual Conference on Information Sciences and Systems (CISS), 2012
Neural information for encoding and processing temporal information in speech sounds occurs over different time-courses. We are interested in temporal mechanisms for neural coding of both pitch and formant frequencies of voiced sounds such as vowels. In particular, in this study we will describe a strategy for quantifying the ability to discriminate changes in spectral peaks, or formant frequencies, based ...
Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228), 2001
It is known that the intermediate part of the cerebellum plays a key role in adjusting the motion of distal part of limbs to make the movement smooth. In the paper, a computational model for the intermediate part of the cerebellum which ensures smooth contact motion with environment is developed. In this model, the cerebellum realizes a smooth contact motion ...
A novel signal-processing strategy is proposed to enhance speech for listeners with hearing loss. The strategy focuses on improving vowel perception based on a recent hypothesis for vowel coding in the auditory system. Traditionally, studies of neural vowel encoding have focused on the representation of formants (peaks in vowel spectra) in the discharge patterns of the population of auditory-nerve (AN) fibers. A recent hypothesis focuses instead on vowel encoding in the auditory midbrain, and suggests a robust representation of formants. AN fiber discharge rates are characterized by pitch-related fluctuations having frequency-dependent modulation depths. Fibers tuned to frequencies near formants exhibit weaker pitch-related fluctuations than those tuned to frequencies between formants. Many auditory midbrain neurons show tuning to amplitude modulation frequency in addition to audio frequency. According to the auditory midbrain vowel encoding hypothesis, the response map of a population of midbrain neurons tuned to modulations near voice pitch exhibits minima near formant frequencies, due to the lack of strong pitch- related fluctuations at their inputs. This representation is robust over the range of noise conditions in which speech intelligibility is also robust for normal-hearing listeners. Based on this hypothesis, a vowel-enhancement strategy has been proposed that aims to restore vowel encoding at the level of the auditory midbrain. The signal processing consists of pitch tracking, formant tracking, and formant enhancement. The novel formant-tracking method proposed here estimates the first two formant frequencies by modeling characteristics of the auditory periphery, such as saturated discharge rates of AN fibers and modulation tuning properties of auditory midbrain neurons. The formant enhancement stage aims to restore the representation of formants at the level of the midbrain by increasing the dominance of a single harmonic near each formant and saturating that frequency channel. A MATLAB implementation of the system with low computational complexity was developed. Objective tests of the formant-tracking subsystem on vowels suggest that the method generalizes well over a wide range of speakers and vowels.
This paper presents a new approach for hearing restoration in patients suffering from sensorineural hearing loss. We focus on the development of a midbrain auditory prosthesis, implanted into the central nucleus of the inferior colliculus (ICC). We performed experiments in a guinea pig model to initially explore the tonotopic map that exists between ICC and the primary auditory cortex (A1), the initial center for auditory perception. Using multichannel electrodes, we were able to stimulate along 16 different ICC sites and simultaneously record from 16 different Al sites. Both electrodes were placed along similar tonotopic gradients. ICC stimulation in low frequency regions induced activity in low frequency regions of A1, and similar trends were seen for higher frequencies. ICC stimulation appears to be very specific, causing minimal spreading of activity across A1 sites, and stimulation threshold levels were significantly lower than that currently obtained using cochlear prostheses. These results indicate that an ICC-based auditory implant may provide a more focused means of stimulation at lower threshold levels for hearing restoration compared to current cochlear prostheses. The tonotopic map between ICC and A1 suggests that a frequency place code may be utilized in a midbrain auditory prosthesis.
The brain integrates information from different sensory modalities to form a representation of the environment and facilitate behavioral responses. The auditory midbrain or inferior colliculus (IC) is a pivotal station in the auditory system, integrating ascending and descending information from various auditory sources and cortical systems. The present study investigated the modulation of auditory responses in the IC by visual stimuli of different frequencies and intensities in rats using functional MRI (fMRI). Low-frequency (1 Hz) high-intensity visual stimulus suppressed IC auditory responses. However, high-frequency (10 Hz) or low-intensity visual stimuli did not alter the IC auditory responses. This finding demonstrates that cross-modal processing occurs in the IC in a manner that depends on the stimulus. Furthermore, only low-frequency high-intensity visual stimulus elicited responses in non-visual cortical regions, suggesting that the above cross- modal modulation effect may arise from top-down cortical feedback. These fMRI results provide insight to guide future studies of cross-modal processing in sensory pathways.
Neural information for encoding and processing temporal information in speech sounds occurs over different time-courses. We are interested in temporal mechanisms for neural coding of both pitch and formant frequencies of voiced sounds such as vowels. In particular, in this study we will describe a strategy for quantifying the ability to discriminate changes in spectral peaks, or formant frequencies, based on the responses of neural models. Previous studies have explored this question based on responses of computational models for the auditory periphery, that is, responses of the population of auditory-nerve (AN) fibers (e.g. -). In this study we quantify formant-frequency discrimination based on the responses of models for auditory midbrain neurons at the level of the inferior colliculus (IC). These neurons are tuned to both audio frequency and to low-frequency amplitude modulations, such as those associated with pitch.
It is known that the intermediate part of the cerebellum plays a key role in adjusting the motion of distal part of limbs to make the movement smooth. In the paper, a computational model for the intermediate part of the cerebellum which ensures smooth contact motion with environment is developed. In this model, the cerebellum realizes a smooth contact motion by estimating the conditions of environment in the intermediate part of cerebellar hemisphere and tuning the desired motion via rubrospinal tract. The stability of contact motion is proven theoretically along the Lyapunov's direct method and its feasibility is demonstrated through some computer simulations. A redundant description of contact force using mirror symmetrically positioned two viscoelastic springs is introduced in the synthesis of a contact motion controller. It makes the synthesis of a consistent controller for both single arm contact motion and bimanual cooperative motion possible.
In this paper, an auditory attention driven computational model of the auditory midbrain is proposed based on a spiking neural network  in order to localize attended sound sources in reverberant environments. Both bottom-up attention driven by sensors and top-down attention driven by the cortex are modeled at the level of an auditory midbrain nucleus - the inferior colliculus (IC). Improvements of the model in  is made to increase biological plausibility. First, inter-neuron inhibitions are modeled among the IC neurons which have the same characteristic frequency but different spatial response. This is designed to mimic the precedence effect  to produce localization results in reverberate environments. Secondly, descending projections from the auditory cortex (AC) to the IC are model to simulate the top-down attention so that focused sound sources can be better sensed in noise or multiple sound source situations. Our model is implemented on a mobile robot with a manikin head equipped with binaural microphones and tested in a real environment. The results shows that our attention driven model can give more accurate localization results than prior models.
Control of locomotion in different kinds of animals, or so-called bio-robot, has been reported. Bio-robot is a technology based on the information communication between the nerve tissue and the computer. In this work, to study the locomotion control in carp's brain, a Parylene-based wire microelectrode is fabricated for stimulation in midbrain. Compared with traditional microelectrodes, wire electrodes provide better bio-compatibility and good mechanical stability. The whole electrode was covered by Parylene C film, except the stimulation sites which are exposed by lift-off process, thus the interface impedance is significantly reduced. After the fabrication, crucian carps was anesthetized in MS-222 water solution and the cranium was partially removed to expose the midbrain. After all these steps, electrodes are tested to see if they are properly insulated. Then one electrode is implanted into the crucian carp's midbrain by surgical procedure and the movement of the fish is observed by a video camera. The caudal fin movement of crucain carp is successfully induced by applying a single polar pulse train. This result proved the former theory that control region of carp is located in midbrain. On the other hand, the experiment shows great potential and promising future in the bio-robotic fish.
This paper proposes a spiking neural network (SNN) of the mammalian auditory midbrain to achieve binaural sound source localisation with a mobile robot. The network is inspired by neurophysiological studies on the organisation of binaural processing in the medial superior olive (MSO), lateral superior olive (LSO) and the inferior colliculus (IC) to achieve a sharp azimuthal localisation of sound source over a wide frequency range in situations where there is auditory clutter and reverberation. Three groups of artificial neurons are constructed to represent the neurons in the MSO, LSO and IC that are sensitive to interaural time difference (ITD), interaural level difference (ILD) and azimuth angle respectively. The ITD and ILD cues are combined in the IC using Bayes's theorem to estimate the azimuthal direction of a sound source. Two of known IC cells, onset and sustained-regular are modelled. The azimuth estimations at different robot positions are then used to calculate the sound source position by a triangulation method using an environment map constructed by a laser scanner. The experimental results show that the addition of ILD information significantly increases sound localisation performance at frequencies above 1 kHz. The mobile robot is able to localise a sound source in an acoustically cluttered and reverberant environment.
The inferior colliculus (IC) is the main converging station in the auditory midbrain and important for processing of complex sounds. However, the functional mapping of natural complex sounds to its neural representation is not yet very well understood, and good modeling approaches would be useful. To evaluate prediction models, we use recordings from groups of neurons in the IC of guinea pigs which were acoustically presented a set of 11 conspecific vocalizations. The different vocalizations display various envelope types and spectral contents. Using cross-correlation, we compare the predicted and recorded temporal neural responses for two approaches. The first model is a modification of the biophysically detailed Meddis model, and the second one is a filtering approach around the neuron's preferred frequency. Surprisingly, we find that for responses to natural sounds from groups of neurons, the filtering approach yields better predictions than the biophysically detailed model. Thus, the collective, integrated response can be well described by a frequency-band selective representation.
We propose a biologically realistic spiking neural network that accounts for the dynamic spatiotemporal transformations within the midbrain superior colliculus (SC) motor map for saccadic eye movements. The model is constrained by observed firing patterns of saccade-related SC cells, where burst durations and peak firing rates vary systematically with their location in the motor map, while keeping a constant number of spikes in their bursts. Our functional network model reproduces the spike trains of single cells in an SC population encoding visually-evoked saccades. In our one-dimensional network the SC neurons are described by adaptive integrate-and-fire models, and lateral excitatory-inhibitory connections. The network scheme is suitable for a full 2D extension. Furthermore, the model offers a basis for neuronal algorithms for spatiotemporal transformations and bioinspired optimal control signal generators.
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