16 resources related to Optic Tectum
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2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI 2020)
The IEEE International Symposium on Biomedical Imaging (ISBI) is the premier forum for the presentation of technological advances in theoretical and applied biomedical imaging. ISBI 2020 will be the 17th meeting in this series. The previous meetings have played a leading role in facilitating interaction between researchers in medical and biological imaging. The 2020 meeting will continue this tradition of fostering cross-fertilization among different imaging communities and contributing to an integrative approach to biomedical imaging across all scales of observation.
2011 International Conference on Human Health and Biomedical Engineering (HHBE)
Provide opportunities not only to exchange new ideas and application experiences, also to establish business relations and research partners for future collaboration in the areas of medicine, public health, and biomedical engineering.
No periodicals are currently tagged "Optic Tectum"
 Proceedings of the Eighteenth IEEE Annual Northeast Bioengineering Conference, 1992
A system has been developed for multineuronal studies through a single extracellular microelectrode. This system is used to detect and study the behavior of local neuronal nets, formed by the dendritic appendages of tectral cells in the superficial tectum of the frog. The system consists of a software package for visual stimulation, spike detection, and classification, calculation of cross-correlograms of ...
IEEE 1988 International Conference on Neural Networks, 1988
The authors demonstrate that the toad optic tectum has memory and can implement a recurrent on-center off-sound neural net with quenching threshold. The main addition to previous tectal models is the quenching threshold, which is defined as a threshold that determines which features are transferred into memory. This implies that the memory is efferently organized, that is, that it stores ...
Proceedings of the 15th Annual International Conference of the IEEE Engineering in Medicine and Biology Societ, 1993
Proceedings of 1993 International Conference on Neural Networks (IJCNN-93-Nagoya, Japan), 1993
Using intracellular recording techniques, we recorded the responses of tectal neurons of the frog to moving visual configurations. Most of the responses sampled in this experiment originated from class 3 retinal ganglion cells. We classified EPSPs according to their shapes into two quantitative criterions, rise time and peak amplitude. Rise time histograms for observed EPSPs had a single peak. This ...
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium, 2000
We present a model for the processing of different movement patterns in the early visual system. The model consists of two processing stages: retina and optic tectum. The temporal structure of movement patterns is translated into a temporal structure of neural responses. This is accomplished by applying gain control in the retina, depressive synaptic transmission and adaptation in tectum to ...
IEEE Magnetics Distinguished Lecture - Mitsuteru Inoue
IEEE Jun-Ichi Nishizawa Medal - Joe C. Campbell - 2018 IEEE Honors Ceremony
Key Enablers and Obstacles to a Successful 5G Deployment - Mark T. Watts - IEEE Sarnoff Symposium, 2019
Engineering Social Good: Technology and Moral Responsibility | IEEE TechEthics Virtual Panel
A system has been developed for multineuronal studies through a single extracellular microelectrode. This system is used to detect and study the behavior of local neuronal nets, formed by the dendritic appendages of tectral cells in the superficial tectum of the frog. The system consists of a software package for visual stimulation, spike detection, and classification, calculation of cross-correlograms of the spike trains, and visualization of the results. The sites of recording offer a large area for studying the interaction of units that participate in these local dendritic nets. Preliminary results suggest that there is a great number of direct functional interactions of excitatory nature mostly, modulated in part by the nature and location of the stimulus.<<ETX>>
The authors demonstrate that the toad optic tectum has memory and can implement a recurrent on-center off-sound neural net with quenching threshold. The main addition to previous tectal models is the quenching threshold, which is defined as a threshold that determines which features are transferred into memory. This implies that the memory is efferently organized, that is, that it stores prey and mate features. An alternative, afferently organized model would store all R2 and R3 input in separate memories and provide a selection mechanism to determine what information is transferred out of memory and is integrated to form efferent commands. The author's model augments the quenching threshold mechanism by demonstrating that TP inhibition can rely on the differential sensitivity of R2 and R3 cells to suppress selectively certain features from memory. In this way, it can modulate the quality as well as the quantity of features stored in memory.<<ETX>>
Using intracellular recording techniques, we recorded the responses of tectal neurons of the frog to moving visual configurations. Most of the responses sampled in this experiment originated from class 3 retinal ganglion cells. We classified EPSPs according to their shapes into two quantitative criterions, rise time and peak amplitude. Rise time histograms for observed EPSPs had a single peak. This implies the localization of activated synapses, which is consistent with the morphological findings in frog's optic tectum. Amplitude histograms had several peaks which are regularly spaced by 0.3 to 0.6 mV. Through such examination, we successfully identified unitary EPSPs evoked by class 3 retinal fibers. We also observed unitary IPSPs in the same manner. These results were mainly obtained from responses elicited by manual movement of black cardboard. In the experiment where a computer controlled stimulus (a moving light slit) was used, the relationship between the position of the stimulus and rise time of EPSPs was examined.
We present a model for the processing of different movement patterns in the early visual system. The model consists of two processing stages: retina and optic tectum. The temporal structure of movement patterns is translated into a temporal structure of neural responses. This is accomplished by applying gain control in the retina, depressive synaptic transmission and adaptation in tectum to obtain a model that recovers during low activity in motion pauses. The model is especially sensitive to beginning movement after such pauses, enabling fast prey capture reactions in tongue-projecting salamanders.
Advances in microscopy and biochemistry now allow investigators to image the calcium dynamics of hundreds to thousands of neurons in awake behaving animals. However, as speed and resolution of such techniques rapidly increase, so do the dimension and complexity of the data collected. ICA has been widely employed to reveal independent non-Gaussian sources underlying large data sets consisting of mixed sources. We apply a recently developed sparse regression method, the Elastic Net (ENET), to the columns of the mixing matrix of a independent component analysis (ICA) procedure. This regression method automatically selects only those columns of the mixing matrix relevant to a dependent variable of interest. Further, because ICA is a linear operator, we can easily project the ldquorelevance filteredrdquo data back into the native data space for interpretation. We demonstrate the utility of this method on 3D calcium imaging data collected from the optic tectum of an awake behaving larval zebrafish watching a prey-like stimulus.
The authors discuss the integration of sensory information in biological systems. In particular, they consider the structure in vertebrate animals that utilizes multiple sensory inputs to orient the sensor platform, i.e. the body or the head, toward objects of interest. This structure is known as the optic tectum in lower vertebrates and the superior colliculus in mammals. The representation of the various sensory modalities on the tectum follows the maplike image format of the retina. This requires in some cases a considerable transformation from the original representation of the sensory input available from the other sensors. As an example, the authors present a detailed discussion of the visual/acoustic object localization system of the barn owl along with a model for the adaptive coregistration of the coordinate systems of the visual and acoustic maps on the tectum.<<ETX>>
Autonomous robotic systems need to adjust their sensorimotor coordinations so as to maintain good performance in the presence of changes in their sensory and motor characteristics. Biological systems are able to adapt to large variations in their physical and functional properties. The adjustment of orienting behavior has been carefully investigated in the barn owl, a nocturnal predator with highly developed auditory capabilities. In the optic tectum of the barn owl, an area well-known to be involved in the production of orienting behavior, neural maps of space in the visual, auditory, and motor modalities are found in close alignment with each other. As a neurophysiological correlate of the adjustment of motor responses, neural maps in the tectum tend to realign if the sensory inputs are manipulated. We have recently proposed that the development and maintenance of such map alignment can be explained through a process of learning, in which plasticity is mediated by the activation of diffuse-projecting neuromodulatory systems which respond to innate or acquired salient cues. This proposal was tested using a detailed computer model of the principal neural structures involved in the process of spatial localisation in the barn owl. Here we consider the application of this model to the control of the orienting behavior of a robotic system in the presence of auditory and visual stimulation. The system we consider is composed of a robotic head equipped with two lateral microphones and a camera. We show that the model produces accurate orienting behavior toward both auditory and visual stimuli during normal visual experience, after alteration of the visual inputs, and after the reestablishment of normal visual conditions. The results illustrate that an architecture specifically designed to account for biological phenomena can produce flexible and robust control of a robotic system.
The corpus mamillare in tilapia is a prominent nucleus in the inferior lobe and has been shown to receive gustatory afferents from the inferior lobe and lateral torus, and to project to the telencephalon, nucleus ventromedialis thalami, optic tectum, and nucleus posterior periventricularis. The present study also revealed that the corpus mamillare receives afferents from the corpus glomerulosum pars anterior and nucleus lateralis valvulae, and projects to the nucleus dorsomedialis thalami in additional to fiber connections of the corpus mamillare in the above-mentioned. Because the corpus glomerulosum pars anterior is known to be a visual relay nucleus, the present study suggests that the percomorph corpus mamillare may also receive visual input besides gustatory information. Projection of the corpus mamillare to the nucleus dorsomedialis thalami was confirmed by reciprocal tracer injections. Tracer injections into the corpus mamillare densely labeled terminals in the ipsilateral nucleus dorsomedialis thalami. In contrast, injections into the nucleus dorsomedialis thalami labeled neurons in the ipsilateral corpus mamillare. Therefore, we suggest that the nucleus dorsomedialis thalami is a main projection target of the corpus mamillare in percomorph teleosts.
Visual attention is a mechanism that enables the visual system to detect potentially important objects in complex environment. Most computational visual attention models are designed with inspirations from mammalian visual systems. However, electrophysiological and behavioral evidences indicate that avian species are animals with high visual capability that can process complex information accurately in real time. Therefore, the visual system of the avian species, especially the nuclei related to the visual attention mechanism, are investigated in this paper. Afterwards, a hierarchical visual attention model is proposed for saliency detection. The optic tectum neuron responses are computed and the self-information is used to compute primary saliency maps in the first hierarchy. The “ winner-take-all ” network in the tecto-isthmal projection is simulated and final saliency maps are estimated with the regularized random walks ranking in the second hierarchy. Comparison results verify that the proposed model, which can define the focus of attention accurately, outperforms several state-of-the-art models. This study provides insights into the relationship between the visual attention mechanism and the avian visual pathways. The computational visual attention model may reveal the underlying neural mechanism of the nuclei for biological visual attention.
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