scholarly journals Neurospecificity in the cricket cercal system

1984 ◽  
Vol 112 (1) ◽  
pp. 7-25
Author(s):  
R. K. Murphey ◽  
W. W. Walthall ◽  
G. A. Jacobs
Keyword(s):  
Nervous System ◽  
Receptive Fields ◽  
Sensory System ◽  
Dendritic Structure ◽  
Competitive Interactions ◽  
Joint Function ◽  
Detailed Understanding ◽  
First Order ◽  
Main Components ◽  
Cricket Cercal System

Studies of neurospecificity in the cricket cercal sensory system are reviewed and a decade of experimentation is examined in the light of recently obtained anatomical data. The nearly complete description of the anatomy indicates that the excitatory receptive fields of directionally-selective interneurones are a joint function of an orderly afferent projection and the dendritic structure of the first order interneurones. The detailed understanding of the anatomy is shown to be a powerful tool in the interpretation of previously published physiological experiments and the design of new ones. The mechanisms which shape the orderly afferent projection are then described and compared with the work on vertebrate sensory systems. It is concluded that both positional interactions of the type conceived by Sperry (1963) and competitive interactions of the type conceived by Hubel, Wiesel & LeVay (1977) are involved in producing the cercal afferent projection. Thus the two main components of the neurospecificity concept are shown to exist in the cricket nervous system. The limits of a purely anatomical approach to the study of neurospecificity are considered in light of the work on this cricket sensory system.

Glioblastoma and primary central nervous system lymphoma: differentiation using MRI derived first-order texture analysis – a machine learning study

2021 ◽  
pp. 197140092199897
Author(s):  
Sarv Priya ◽  
Caitlin Ward ◽  
Thomas Locke ◽  
Neetu Soni ◽  
Ravishankar Pillenahalli Maheshwarappa ◽  
...  
Keyword(s):  
Machine Learning ◽  
Central Nervous System ◽  
Nervous System ◽  
Diagnostic Performance ◽  
Model Performance ◽  
Area Under The Curve ◽  
Central Nervous System Lymphoma ◽  
First Order ◽  
Single Slice ◽  
Contrast Enhanced

Objectives To evaluate the diagnostic performance of multiple machine learning classifier models derived from first-order histogram texture parameters extracted from T1-weighted contrast-enhanced images in differentiating glioblastoma and primary central nervous system lymphoma. Methods Retrospective study with 97 glioblastoma and 46 primary central nervous system lymphoma patients. Thirty-six different combinations of classifier models and feature selection techniques were evaluated. Five-fold nested cross-validation was performed. Model performance was assessed for whole tumour and largest single slice using receiver operating characteristic curve. Results The cross-validated model performance was relatively similar for the top performing models for both whole tumour and largest single slice (area under the curve 0.909–0.924). However, there was a considerable difference between the worst performing model (logistic regression with full feature set, area under the curve 0.737) and the highest performing model for whole tumour (least absolute shrinkage and selection operator model with correlation filter, area under the curve 0.924). For single slice, the multilayer perceptron model with correlation filter had the highest performance (area under the curve 0.914). No significant difference was seen between the diagnostic performance of the top performing model for both whole tumour and largest single slice. Conclusions T1 contrast-enhanced derived first-order texture analysis can differentiate between glioblastoma and primary central nervous system lymphoma with good diagnostic performance. The machine learning performance can vary significantly depending on the model and feature selection methods. Largest single slice and whole tumour analysis show comparable diagnostic performance.

Preparing for the unpredictable: adaptive feedback enhances the response to unexpected communication signals

2012 ◽  
Vol 107 (4) ◽  
pp. 1241-1246 ◽  
Author(s):  
Gary Marsat ◽  
Leonard Maler
Keyword(s):  
Nervous System ◽  
Sensory Input ◽  
Low Frequency ◽  
Excitatory Input ◽  
Negative Image ◽  
Communication Signals ◽  
First Order ◽  
Communication Signal ◽  
Apical Dendrites ◽  
Spike Bursts

To interact with the environment efficiently, the nervous system must generate expectations about redundant sensory signals and detect unexpected ones. Neural circuits can, for example, compare a prediction of the sensory signal that was generated by the nervous system with the incoming sensory input, to generate a response selective to novel stimuli. In the first-order electrosensory neurons of a gymnotiform electric fish, a negative image of low-frequency redundant communication signals is subtracted from the neural response via feedback, allowing unpredictable signals to be extracted. Here we show that the cancelling feedback not only suppresses the predictable signal but also actively enhances the response to the unpredictable communication signal. A transient mismatch between the predictive feedback and incoming sensory input causes both to be positive: the soma is suddenly depolarized by the unpredictable input, whereas the neuron's apical dendrites remain depolarized by the lagging cancelling feedback. The apical dendrites allow the backpropagation of somatic spikes. We show that backpropagation is enhanced when the dendrites are depolarized, causing the unpredictable excitatory input to evoke spike bursts. As a consequence, the feedback driven by a predictable low-frequency signal not only suppresses the response to a redundant stimulus but also induces a bursting response triggered by unpredictable communication signals.

Models for New Corrugated and Porous Solar Air Collectors under Transient Operation

2017 ◽  
Vol 42 (1) ◽  
Author(s):  
Qahtan Adnan Abed ◽  
Viorel Badescu ◽  
Adrian Ciocanea ◽  
Iuliana Soriga ◽  
Dorin Bureţea
Keyword(s):  
Climatic Conditions ◽  
Meteorological Conditions ◽  
Bias Error ◽  
First Order ◽  
Solar Air Collector ◽  
Section Surface ◽  
South Eastern Europe ◽  
Main Components ◽  
Theoretical Results ◽  
Good Agreement

AbstractMathematical models have been developed to evaluate the dynamic behavior of two solar air collectors: the first one is equipped with a V-porous absorber and the second one with a U-corrugated absorber. The collectors have the same geometry, cross-section surface area and are built from the same materials, the only difference between them being the absorbers. V-corrugated absorbers have been treated in literature but the V-porous absorbers modeled here have not been very often considered. The models are based on first-order differential equations which describe the heat exchange between the main components of the two types of solar air heaters. Both collectors were exposed to the sun in the same meteorological conditions, at identical tilt angle and they operated at the same air mass flow rate. The tests were carried out in the climatic conditions of Bucharest (Romania, South Eastern Europe). There is good agreement between the theoretical results and experiments. The average bias error was about 7.75 % and 10.55 % for the solar air collector with “V”-porous absorber and with “U”-corrugated absorber, respectively. The collector based on V-porous absorber has higher efficiency than the collector with U-corrugated absorber around the noon of clear days. Around sunrise and sunset, the collector with U-corrugated absorber is more effective.

Signals and noise in the elasmobranch electrosensory system

1999 ◽  
Vol 202 (10) ◽  
pp. 1349-1355 ◽  
Author(s):  
J.C. Montgomery ◽  
D. Bodznick
Keyword(s):  
Direct Current ◽  
Noise Suppression ◽  
Receptive Fields ◽  
Sensory System ◽  
Mate Recognition ◽  
Common Mode ◽  
Central Processing ◽  
Temporal Properties ◽  
Efferent Neurons ◽  
Bioelectric Fields

Analyzing signal and noise for any sensory system requires an appreciation of the biological and physical milieu of the animal. Behavioral studies show that elasmobranchs use their electrosensory systems extensively for prey detection, but also for mate recognition and possibly for navigation. These biologically important signals are detected against a background of self-generated bioelectric fields. Noise-suppression mechanisms can be recognized at a number of different levels: behavior, receptor anatomy and physiology, and at the early stages of sensory processing. The peripheral filters and receptor characteristics provide a detector with permissive temporal properties but restrictive spatial characteristics. Biologically important signals probably cover the range from direct current to 10 Hz, whereas the bandwidth of the receptors is more like 0.1-10 Hz. This degree of alternating current coupling overcomes significant noise problems while still allowing the animal to detect external direct current signals by its own movement. Self-generated bioelectric fields modulated by breathing movement have similar temporal characteristics to important external signals and produce very strong modulation of electrosensory afferents. This sensory reafference is essentially similar, or common-mode, across all afferent fibers. The principal electrosensory neurons (ascending efferent neurons; AENs) of the dorsal octavolateralis nucleus show a greatly reduced response to common-mode signals. This suppression is mediated by the balanced excitatory and inhibitory components of their spatial receptive fields. The receptive field characteristics of AENs determine the information extracted from external stimuli for further central processing.

scholarly journals Neural network models of the tactile system develop first-order units with spatially complex receptive fields

2017 ◽  
Author(s):  
Charlie W. Zhao ◽  
Mark J. Daley ◽  
J. Andrew Pruszynski
Keyword(s):  
Neural Network ◽  
Network Performance ◽  
Receptive Fields ◽  
Network Models ◽  
Network Architectures ◽  
Learning Tools ◽  
Neural Network Models ◽  
First Order ◽  
Wide Range ◽  
Tactile System

AbstractFirst-order tactile neurons have spatially complex receptive fields. Here we use machine learning tools to show that such complexity arises for a wide range of training sets and network architectures, and benefits network performance, especially on more difficult tasks and in the presence of noise. Our work suggests that spatially complex receptive fields are normatively good given the biological constraints of the tactile periphery.

Projections from sensory neurons developing at ectopic sites in insects

Development ◽  
1981 ◽  
Vol 65 (Supplement) ◽  
pp. 209-224
Author(s):  
Hilary Anderson
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Sensory Neurons ◽  
Sensory Systems ◽  
Genetic Mutation ◽  
Detailed Understanding ◽  
Giant Interneuron ◽  
The Central Nervous System ◽  
Ectopic Neurons

This paper reviews recent experiments which attempt to gain more understanding about the recognition processes involved in the formation of neuronal connexions by studying the degree of specificity with which sensory neurons form their central connexions. This is done by generating ectopic neurons (either by transplantation or by genetic mutation) whose axons grow into novel regions of the central nervous system, and then examining their projections and synapses. The sensory systems reviewed are: the Antennapedia, spineless-aristapedia, proboscipedia, and bithorax homeotic mutants of Drosphila melanogaster; the cercus-to-giant interneuron system of crickets, and the wind-sensitive hair system of locusts. The results show that ectopic neurons form projections that are discrete and characteristic, not random and chaotic. In those cases where single classes of sensilla have been studied, they follow either their normal CNS pathways or those pathways normally used by their segmental homologues. Ectopic sensory neurons can also form appropriate functional connexions in some cases but not in others. Possible reasons are discussed, but detailed understanding of the underlying events requires further experimentation.

Coding Principles in Adaptation

2019 ◽  
Vol 5 (1) ◽  
pp. 427-449 ◽  
Author(s):  
Alison I. Weber ◽  
Kamesh Krishnamurthy ◽  
Adrienne L. Fairhall
Keyword(s):  
Nervous System ◽  
Visual System ◽  
Functional Role ◽  
Receptive Fields ◽  
Sensory Systems ◽  
Spike Frequency Adaptation ◽  
Theoretical Frameworks ◽  
Different Types ◽  
Common Principle

Adaptation is a common principle that recurs throughout the nervous system at all stages of processing. This principle manifests in a variety of phenomena, from spike frequency adaptation, to apparent changes in receptive fields with changes in stimulus statistics, to enhanced responses to unexpected stimuli. The ubiquity of adaptation leads naturally to the question: What purpose do these different types of adaptation serve? A diverse set of theories, often highly overlapping, has been proposed to explain the functional role of adaptive phenomena. In this review, we discuss several of these theoretical frameworks, highlighting relationships among them and clarifying distinctions. We summarize observations of the varied manifestations of adaptation, particularly as they relate to these theoretical frameworks, focusing throughout on the visual system and making connections to other sensory systems.

scholarly journals EVALUATION OF THE EFFECT OF YOGIC PRACTICES ON RAKTAGATA VATA (ESSENTIAL HYPERTENSION)

2018 ◽  
Vol 11 (9) ◽  
pp. 425
Author(s):  
Pradeep Kumar Pal ◽  
Neera Saini ◽  
Mishra Vn ◽  
Awasthi Hh
Keyword(s):  
Quality Of Life ◽  
Blood Pressure ◽  
Nervous System ◽  
Essential Hypertension ◽  
System Control ◽  
Energy Channel ◽  
Hypertensive Patients ◽  
First Order ◽  
Positive Effects

Objective: Essential hypertension is the most frequent kind of hypertension and also known as primary hypertension or idiopathic, affecting 95% of hypertensive patients. This study was conducted to see the effect of Yogic practices as Nadi Shodhana Pranayama (NSP = cleaning of subtle energy channel along with regulation of rhythm of breathing) and Dhyana (meditation) on the symptoms of Raktagata Vata (essential hypertension), blood pressure, and Hamilton’s anxiety rating scale.Methods: This clinical study was conducted on 50 cases of Raktagata Vata, and these were randomly divided into two subgroups: (1) Control and (2) intervention consisting of 25 cases in each subgroup. Yogic practices were done regularly for 3 months by the registered cases in both subgroups. Light medication of first order initially was also prescribed to intervention subgroup.Result: In both subgroups, significant results (p<0.001) were observed and most of the symptoms of Raktagata Vata improved better in the intervention than control subgroup. Significant results (p<0.001) were also observed in blood pressure along with Hamilton’s anxiety scale scoring.Conclusion: Yogic practices impact positive effects on Agya Chakra (hypothalamus-cerebral system), control autonomic nervous system and improve the quality of life of Raktagata Vata patients by improving symptoms and regulating the blood pressure.

Extrasynaptic receptors on cell bodies of neurons in central nervous system of the leech

1977 ◽  
Vol 40 (2) ◽  
pp. 446-452 ◽  
Author(s):  
P. B. Sargent ◽  
K. W. Yau ◽  
J. G. Nicholls
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Glutamic Acid ◽  
Systematic Study ◽  
Receptive Fields ◽  
Aminobutyric Acid ◽  
Gamma Aminobutyric Acid ◽  
Light Touch ◽  
Nociceptive Neurons ◽  
Extrasynaptic Receptors

1. A systematic study has been made of the sensitivity of identified sensory and motoneurons in the leech central nervous system to chemical transmitter substances. 2. The following substances elicited responses from the cell bodies of individual neurons: acetylcholine, 5-hydroxytryptamine, gamma-aminobutyric acid, glutamic acid, glycine, dopamine, and norepinephrine. Since the cell bodies of leech neurons are free of synapses, the receptors that give rise to these responses are extrasynaptic. 3. Sensory and motoneurons of different function had characteristic complements of extrasynaptic receptors. For example, mechanosensory cells responding to light touch, to pressure, and to noxious stimuli could be distinguished by their responses to iontophoretically applied compounds. For one of these modalities (nociceptive), neurons with different receptive fields but otherwise similar properties had markedly distinct extrasynaptic receptors. The possible significance of extrasynaptic receptors is discussed.

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