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  • Benchmarks  (1)
  • Cobalt staining  (1)
  • 1
    ISSN: 1432-1351
    Keywords: Cobalt staining ; Gas chromatography-mass spectrometry ; Immunohistochemistry ; Insect ; Neuromodulation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Medicine
    Notes: Abstract The two Protocerebral-Medulla 4 neurons (PM4a and b) in the locust brain have adjacent cell bodies in the medial deutocerebrum. They project through the posterior protocerebrum, forming limited arborisations en route, and enter the lobula and medulla of the ipsilateral optic lobe, where they form extensive, overlapping arborisations. The PM4a and b neurons are octopamine immunoreactive. Their octopamine content (approximately 25 pg per cell) is confirmed by gas chromatography-mass spectrometry; each cell contains approximately 25 pg p-octopamine. Simultaneous intracellular recording from exposed PM4a and b cell bodies reveals that the two cells are physiologically indistinguishable. They receive multimodal sensory inputs. Tactile/mechanosensory stimuli to much of the animal's body and head, acoustic stimuli, and simple visual stimuli all give rise to e.p.s.p.s and action potentials in the PM4 cell body. Simultaneous recording from the cell body in the deutocerebrum and the axon in the lobula demonstrates that action potentials are predominantly initiated in the deutocerebrum and propagate centrifugally, towards the optic lobe. Occasionally, bright light flashes will initiate an action potential in the axon in the optic stalk, which probably propagates bidirectionally: centripetally to the cell body, and centrifugally into the optic lobe. The extensive arborisations in the lobula and medulla are therefore likely to be sites of octopamine release. Because PM4 neurons are octopaminergic, project to the optic lobe, and receive modalities of sensory input known to dishabituate the Descending Contralateral Movement Detector (DCMD) visual interneuron, it is proposed that PM4 neurons are neuromodulatory — mediating dishabituation or arousal of the visual system.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Neural computing & applications 7 (1998), S. 334-342 
    ISSN: 1433-3058
    Keywords: Benchmarks ; Learning criteria ; Multilayer perceptron networks ; Pattern classification ; Radial basis function networks ; Training methods
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract This paper presents a study of two learning criteria and two approaches to using them for training neural network classifiers, specifically a Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) networks. The first approach, which is a traditional one, relies on the use of two popular learning criteria, i.e. learning via minimising a Mean Squared Error (MSE) function or a Cross Entropy (CE) function. It is shown that the two criteria have different charcteristics in learning speed and outlier effects, and that this approach does not necessarily result in a minimal classification error. To be suitable for classification tasks, in our second approach an empirical classification criterion is introduced for the testing process while using the MSE or CE function for the training. Experimental results on several benchmarks indicate that the second approach, compared with the first, leads to an improved generalisation performance, and that the use of the CE function, compared with the MSE function, gives a faster training speed and improved or equal generalisation performance.
    Type of Medium: Electronic Resource
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