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Coding of pheromone signal by olfactory receptor neurons in Agrotis ipsilon
Kováčová, Kristýna ; Košťál, Lubomír (advisor) ; Pokora, Ondřej (referee)
i Abstract The main objective of the thesis is to describe differences in the activity of male A. ipsilon olfactory receptor neurons (ORNs) when stimulated by different temporal dynamics of the concentration of the conspecific female pheromone. First, under the artificial situation of constant pulse stimulation, and second, with a fluctuating signal resembling the natural situation. For this purpose, the experimental data were collected in the collaborating laboratory (Dr. P. Lucas, INRAe, Versailles, France) by employing a novel olfactometer system that enables precise temporal control of the pheromone delivery to individual sensilla. Using the R programming language, we analyzed various descriptors of the response reliability, randomness, and variability, as well as the information content of the evoked activity. The results are interpreted in the context of the classical efficient coding hypothesis, which states that sensory neurons are evolutionarily adapted to natural stimuli. The main finding is that although the response variability is widely spread across the ORN population, sometimes with no visible difference between the constant and fluctuating stimulation types, the fluctuating stimulus is usually encoded with systematically higher reliability, as revealed by the inspection of individual ORNs....
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Information processes in neurons
Šanda, Pavel ; Lánský, Petr (advisor) ; Popelář, Jiří (referee) ; Pospíšil, Zdeněk (referee)
Neurons communicate by action potentials. This process can be described by very detailed biochemical models of neuronal membrane and its channels, or by simpler phenomenological models of membrane potential (integrate-and- fire models) or even by very abstract models when only time of spikes are considered. We took one particular description - stochastic leaky integrate-and-fire model - and compared it with recorded in-vivo intracellular activity of the neuron. We estimated parameters of this model, compared how the model simulation corresponds with a real neuron. It can be concluded that the data are generally consistent with the model. At a more abstract level of description, the spike trains are analyzed without considering exact membrane voltage and one asks how the external stimulus is encoded in the spike train emitted by neurons. There are many neuronal codes described in literature and we focused on the open problem of neural code responsible for spatial hearing in mammals. Several theories explaining the experimental findings have been proposed and we suggest a specific variant of so called slope-encoding model. Neuronal circuit mimick- ing auditory pathway up to the first binaural neuron was constructed and experimental results were reproduced. Finally, we estimated the minimal number of such...
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Activity and Memory in Biologically Motivated Neural Network.
Štroffek, Július ; Maršálek, Petr (advisor) ; Zápotocký, Martin (referee) ; Hozman, Jiří (referee)
This work presents biologically motivated neural network model which works as an auto-associative memory. Architecture of the presented model is similar to the architecture of the Hopfield network which might be similar to some parts of the hippocampal network area CA3 (Cornu Amonis). Patterns learned and retrieved are not static but they are periodically repeating sequences of sparse synchronous activities. Patterns were stored to the network using the modified Hebb rule adjusted to store cyclic sequences. Capacity of the model is analyzed together with the numerical simulations. The model is further extended with short term potentiation (STP), which is forming the essential part of the successful pattern recall process. The memory capacity of the extended version of the model is highly increased. The joint version of the model combining both approaches is discussed. The model might be able to retrieve the pattern in short time interval without STP (fast patterns) or in a longer time period utilizing STP (slow patterns). We know from our everyday life that some patterns could be recalled promptly and some may need much longer time to reveal. Keywords auto-associative neural network, Hebbian learning, neural coding, memory, pattern recognition, short-term potentiation 1
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Information processes in neurons
Šanda, Pavel ; Lánský, Petr (advisor) ; Popelář, Jiří (referee) ; Pospíšil, Zdeněk (referee)
Neurons communicate by action potentials. This process can be described by very detailed biochemical models of neuronal membrane and its channels, or by simpler phenomenological models of membrane potential (integrate-and- fire models) or even by very abstract models when only time of spikes are considered. We took one particular description - stochastic leaky integrate-and-fire model - and compared it with recorded in-vivo intracellular activity of the neuron. We estimated parameters of this model, compared how the model simulation corresponds with a real neuron. It can be concluded that the data are generally consistent with the model. At a more abstract level of description, the spike trains are analyzed without considering exact membrane voltage and one asks how the external stimulus is encoded in the spike train emitted by neurons. There are many neuronal codes described in literature and we focused on the open problem of neural code responsible for spatial hearing in mammals. Several theories explaining the experimental findings have been proposed and we suggest a specific variant of so called slope-encoding model. Neuronal circuit mimick- ing auditory pathway up to the first binaural neuron was constructed and experimental results were reproduced. Finally, we estimated the minimal number of such...
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