Entender como o cérebro processa informação é um dos problemas mais fascinantes da ciência de nossos dias. Para resolvê-lo, é fundamental estudarmos os mecanismos de representação e transmissão de informação de um único neurônio, a unidade fundamental de processamento do cérebro. Grande parte dos neurônios representa a informação por seqüências de pulsos elétricos, ou potenciais de ação. Nós usamos a mosca como modelo para estudar como a arborização dendrítica do neurônio influencia a quantidade de informação transmitida pela estrutura temporal da seqüência de pulsos. O mapeamento retinotópico da informação no sistema visual da mosca permite que as arborizações dendríticas de certos neurônios sejam estimuladas localmente através da região que corresponde a essa localização no campo visual. Nós apresentamos imagens em movimento em várias regiões do campo visual da mosca e medimos a resposta do neurônio H1, sensível a movimentos horizontais. Usando a teoria da informação, calculamos a quantidade de informação transmitida para cada uma dessas regiões do campo visual e a relacionamos com outras propriedades do neurônio, como por exemplo a sensibilidade espacial e eficiência. Nossos resultados sugerem que a arborização dendrítica influencia a codificação temporal de maneira significativa, indicando que o neurônio pode usar a estrutura temporal da sequência de pulsos para codificar outros parâmetros do estímulo, ou para aumentar a confiabilidade da codificação dependendo da região excitada / Understanding how the brain processes information about the outside world is one of the most fascinating problems of modern science. This involves the analysis of information representation and transmission in the fundamental processing element of the brain - the neuron. In the cortex neurons represent information by sequences of electrical pulses, or spikes. We use the fly as a model to study how the amount of information transmitted by the temporal structure of the spike trains depends on the neuron\'s dendritic arborization. The retinotopic mapping of information in the fly\'s visual system allows the stimulation of specific regions of the neuron\'s dendritic tree through the visual stimulation of the respective region in the visual field of the fly. We show an image moving in the preferred direction of the motion-sensitive neuron H1 in specific regions of the fly\'s visual field and measure the electrical response of the neuron. Using information theory, we calculate the amount of information transmitted for each of these regions and compare it with other properties of the neuron, for example, the spatial sensitivity. Our results suggest that the dendritic arborization influentes the temporal coding in a significant way, indicating that the neuron could use the temporal structure of the spike train to codify other parameters of the stimulus, or to increase the reliability of the code depending on the excited region

Entender como o cérebro processa informação é um dos problemas mais fascinantes da ciência de nossos dias. Para resolvê-lo, é fundamental estudarmos os mecanismos de representação e transmissão de informação de um único neurônio, a unidade fundamental de processamento do cérebro. Grande parte dos neurônios representa a informação por seqüências de pulsos elétricos, ou potenciais de ação. Nós usamos a mosca como modelo para estudar como a arborização dendrítica do neurônio influencia a quantidade de informação transmitida pela estrutura temporal da seqüência de pulsos. O mapeamento retinotópico da informação no sistema visual da mosca permite que as arborizações dendríticas de certos neurônios sejam estimuladas localmente através da região que corresponde a essa localização no campo visual. Nós apresentamos imagens em movimento em várias regiões do campo visual da mosca e medimos a resposta do neurônio H1, sensível a movimentos horizontais. Usando a teoria da informação, calculamos a quantidade de informação transmitida para cada uma dessas regiões do campo visual e a relacionamos com outras propriedades do neurônio, como por exemplo a sensibilidade espacial e eficiência. Nossos resultados sugerem que a arborização dendrítica influencia a codificação temporal de maneira significativa, indicando que o neurônio pode usar a estrutura temporal da sequência de pulsos para codificar outros parâmetros do estímulo, ou para aumentar a confiabilidade da codificação dependendo da região excitada / Understanding how the brain processes information about the outside world is one of the most fascinating problems of modern science. This involves the analysis of information representation and transmission in the fundamental processing element of the brain - the neuron. In the cortex neurons represent information by sequences of electrical pulses, or spikes. We use the fly as a model to study how the amount of information transmitted by the temporal structure of the spike trains depends on the neuron\'s dendritic arborization. The retinotopic mapping of information in the fly\'s visual system allows the stimulation of specific regions of the neuron\'s dendritic tree through the visual stimulation of the respective region in the visual field of the fly. We show an image moving in the preferred direction of the motion-sensitive neuron H1 in specific regions of the fly\'s visual field and measure the electrical response of the neuron. Using information theory, we calculate the amount of information transmitted for each of these regions and compare it with other properties of the neuron, for example, the spatial sensitivity. Our results suggest that the dendritic arborization influentes the temporal coding in a significant way, indicating that the neuron could use the temporal structure of the spike train to codify other parameters of the stimulus, or to increase the reliability of the code depending on the excited region

<p>In order to understand how the brain functions, under normal as well as pathological conditions, it is important to study the mechanisms underlying information integration. Depending on the nature of an input arriving at a synapse, different strategies may be used by the neuron to integrate and respond to the input. Naturally, if a short train of high-frequency synaptic input arrives, it may be beneficial for the neuron to be equipped with a fast mechanism that is highly sensitive to inputs on a short time scale. If, on the contrary, inputs arriving with low frequency are to be processed, it may be necessary for the neuron to possess slow mechanisms of integration. For example, in certain working memory tasks (e. g. delay-match-to-sample), sensory inputs may arrive separated by silent intervals in the range of seconds, and the subject should respond if the current input is identical to the preceeding input. It has been suggested that single neurons, due to intrinsic mechanisms outlasting the duration of input, may be able to perform such calculations. In this work, I have studied a mechanism thought to be particularly important in supporting the integration of low-frequency synaptic inputs. It is mediated by a cascade of events that starts with activation of group I metabotropic glutamate receptors (mGlu1/5), and ends with a membrane depolarization caused by a current that is mediated by canonical transient receptor potential (TRPC) ion channels. This current, denoted I_TRPC, is the focus of this thesis.</p><p>A specific objective of this thesis is to study the role of I_TRPC in the integration of synaptic inputs arriving at a low frequency, < 10 Hz. Our hypothesis is that, in contrast to the well-studied, rapidly decaying AMPA and NMDA currents, I_TRPC is well-suited for supporting temporal summation of such synaptic input. The reason for choosing this range of frequencies is that neurons often communicate with signals (spikes) around 8 Hz, as shown by single-unit recordings in behaving animals. This is true for several regions of the brain, including the entorhinal cortex (EC) which is known to play a key role in producing working memory function and enabling long-term memory formation in the hippocampus.</p><p>Although there is strong evidence suggesting that I_TRPC is important for neuronal communication, I have not encountered a systematic study of how this current contributes to synaptic integration. Since it is difficult to directly measure the electrical activity in dendritic branches using experimental techniques, I use computational modeling for this purpose. I implemented the components necessary for studying I_TRPC, including a detailed model of extrasynaptic glutamate concentration, mGlu1/5 dynamics and the TRPC channel itself. I tuned the model to replicate electrophysiological in vitro data from pyramidal neurons of the rodent EC, provided by our experimental collaborator. Since we were interested in the role of I_TRPC in temporal summation, a specific aim was to study how its decay time constant (τ_decay) is affected by synaptic stimulus parameters.</p><p>The hypothesis described above is supported by our simulation results, as we show that synaptic inputs arriving at frequencies as low as 3 - 4 Hz can be effectively summed. We also show that τ_decay increases with increasing stimulus duration and frequency, and that it is linearly dependent on the maximal glutamate concentration. Under some circumstances it was problematic to directly measure τ_decay, and we then used a pair-pulse paradigm to get an indirect estimate of τ_decay.</p><p>I am not aware of any computational model work taking into account the synaptically evoked I_TRPC current, prior to the current study, and believe that it is the first of its kind. We suggest that I_TRPC is important for slow synaptic integration, not only in the EC, but in several cortical and subcortical regions that contain mGlu1/5 and TRPC subunits, such as the prefrontal cortex. I will argue that this is further supported by studies using pharmacological blockers as well as studies on genetically modified animals.</p> / QC 20101005

In order to understand how the brain functions, under normal as well as pathological conditions, it is important to study the mechanisms underlying information integration. Depending on the nature of an input arriving at a synapse, different strategies may be used by the neuron to integrate and respond to the input. Naturally, if a short train of high-frequency synaptic input arrives, it may be beneficial for the neuron to be equipped with a fast mechanism that is highly sensitive to inputs on a short time scale. If, on the contrary, inputs arriving with low frequency are to be processed, it may be necessary for the neuron to possess slow mechanisms of integration. For example, in certain working memory tasks (e. g. delay-match-to-sample), sensory inputs may arrive separated by silent intervals in the range of seconds, and the subject should respond if the current input is identical to the preceeding input. It has been suggested that single neurons, due to intrinsic mechanisms outlasting the duration of input, may be able to perform such calculations. In this work, I have studied a mechanism thought to be particularly important in supporting the integration of low-frequency synaptic inputs. It is mediated by a cascade of events that starts with activation of group I metabotropic glutamate receptors (mGlu1/5), and ends with a membrane depolarization caused by a current that is mediated by canonical transient receptor potential (TRPC) ion channels. This current, denoted ITRPC, is the focus of this thesis. A specific objective of this thesis is to study the role of ITRPC in the integration of synaptic inputs arriving at a low frequency, &lt; 10 Hz. Our hypothesis is that, in contrast to the well-studied, rapidly decaying AMPA and NMDA currents, ITRPC is well-suited for supporting temporal summation of such synaptic input. The reason for choosing this range of frequencies is that neurons often communicate with signals (spikes) around 8 Hz, as shown by single-unit recordings in behaving animals. This is true for several regions of the brain, including the entorhinal cortex (EC) which is known to play a key role in producing working memory function and enabling long-term memory formation in the hippocampus. Although there is strong evidence suggesting that ITRPC is important for neuronal communication, I have not encountered a systematic study of how this current contributes to synaptic integration. Since it is difficult to directly measure the electrical activity in dendritic branches using experimental techniques, I use computational modeling for this purpose. I implemented the components necessary for studying ITRPC, including a detailed model of extrasynaptic glutamate concentration, mGlu1/5 dynamics and the TRPC channel itself. I tuned the model to replicate electrophysiological in vitro data from pyramidal neurons of the rodent EC, provided by our experimental collaborator. Since we were interested in the role of ITRPC in temporal summation, a specific aim was to study how its decay time constant (τdecay) is affected by synaptic stimulus parameters. The hypothesis described above is supported by our simulation results, as we show that synaptic inputs arriving at frequencies as low as 3 - 4 Hz can be effectively summed. We also show that τdecay increases with increasing stimulus duration and frequency, and that it is linearly dependent on the maximal glutamate concentration. Under some circumstances it was problematic to directly measure τdecay, and we then used a pair-pulse paradigm to get an indirect estimate of τdecay. I am not aware of any computational model work taking into account the synaptically evoked ITRPC current, prior to the current study, and believe that it is the first of its kind. We suggest that ITRPC is important for slow synaptic integration, not only in the EC, but in several cortical and subcortical regions that contain mGlu1/5 and TRPC subunits, such as the prefrontal cortex. I will argue that this is further supported by studies using pharmacological blockers as well as studies on genetically modified animals. / QC 20101005