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g-pacheco committed Apr 17, 2024
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43 changes: 8 additions & 35 deletions Apoio/index.md
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title: Apoio
nav:
order: 6
tooltip: Apoiadores do I Congresso da SBBE.
tooltip: Sobre os apoiadores do I Congresso da SBBE.
---

# {% include icon.html icon="fa-solid fa-money-check-dollar" %}Apoio

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## What are the neural mechanisms underlying learning?
## First sponsor.
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We aim to explore the fundamental principles underlying learning in a reduced and experimenter-defined neuronal circuit. To achieve this goal, we will employ a neuroprosthetic paradigm to elicit specific behaviors in restrained or freely behaving rodents. We will then manipulate the neural substrate of these behaviors using electrical or optical stimulation, and characterize the functional response both at the neural and behavioral level.

Our objective is to gain a deeper understanding of how the brain reinforces neural patterns and acquires new cognitive skills, and how these processes can be modulated through neuro-stimulation. Through this investigation, we hope to shed light on the neural mechanisms underlying learning and pave the way for the development of novel neuro-technology-based interventions for cognitive disorders.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut a dui suscipit, dignissim quam in, egestas turpis. Praesent at sapien tellus. Fusce mollis porta cursus. Quisque libero tortor, commodo sed sollicitudin in, consequat eu sem. Ut elementum porta purus eu tincidunt.

{%
include button.html
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## How does dopamine release lead to learning?
## Second sponsor.
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Dopamine acts as a reinforcer of preferred behavior. However, the neural mechanisms by which this occurs remain unclear. To investigate this, we employ photo-pharmacology techniques to manipulate dopamine receptors and/or employ optical stimulation within dopaminergic regions. Specifically, we explore the impact of dopamine signaling on neuroprosthetic learning by selectively activating or inhibiting specific dopamine receptors within cell-type specific neurons in the cortex and striatum. Through these experiments, we will uncover the underlying mechanisms by which dopamine reinforces neural patterns and how this reinforcement ultimately leads to learning.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut a dui suscipit, dignissim quam in, egestas turpis. Praesent at sapien tellus. Fusce mollis porta cursus. Quisque libero tortor, commodo sed sollicitudin in, consequat eu sem. Ut elementum porta purus eu tincidunt.

{%
include button.html
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{%
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image="images/dopamine.png"
image="images/Sponsors/UFPR.png"
flip=true
text=text
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# Improving neuroprosthetics

## Optimizing neuro-stimulation paradigms
## Third sponsor.
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To achieve real-time control over neural function, it is essential for neuro-engineering solutions to evolve towards more effective bi-directional communication between biological and artificial systems when studying and perturbing neuronal circuits. However, the identification and selective stimulation of appropriate neurons or precise neurotransmitter signaling can be challenging in a constantly evolving network-wide activity.

The potential advantages of unsupervised learning algorithms for controlling the stimulation of single neurons or dopamine receptors have yet to be fully explored. To address this, we develop new experimental protocols utilizing closed-loop strategies, which can select and drive the most effective neuro-stimulation for studying, perturbing, and enhancing neural reinforcement.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut a dui suscipit, dignissim quam in, egestas turpis. Praesent at sapien tellus. Fusce mollis porta cursus. Quisque libero tortor, commodo sed sollicitudin in, consequat eu sem. Ut elementum porta purus eu tincidunt.

{%
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include feature.html
image="images/optimizing_stim.png"
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## Artificially assisting the neural mechanisms of learning
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We recently implanted a basic neuroprosthetic skill using single-neuron targeted stimulation in the motor cortex. Now, we want to determine the rules and limitations of artificially implanted skills by studying the underlying physiological changes in neural reinforcement that drive this artificial learning. Furthermore, we will investigate how to assist the brain in solving more complex learning tasks by guiding perturbations over specific neuronal ensembles causally linked to behavior.
Recently, cell-specific neuro-stimulation has emerged as a possible therapy for neurodegenerative diseases. We use closed-loop neuroprosthetic paradigms combined with neuro-stimulation with single-cell resolution, photo-pharmacology, and animal models of cognitive dysfunction to test and prototype neurotechnology-based solutions for these disorders.

{%
include button.html
flip=true
style="bare"
%}

{% endcapture %}

{%
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image="images/assisting_learning.png"
flip=false
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5 changes: 1 addition & 4 deletions Local do Evento/index.md
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# {% include icon.html icon="fa-solid fa-location-dot" %}Local do Evento

O I Congresso da Sociedade Brasileira de Biologia Evolutiva ocorrerá no campus Jardim Botânico da Universidade Federal do Paraná (UFPR), a mais antiga e uma das mais tradicionais universidades do Brasil, com uma rica história acadêmica e uma reputação de excelência em pesquisa.
O **I Congresso da Sociedade Brasileira de Biologia Evolutiva** ocorrerá no campus Jardim Botânico da Universidade Federal do Paraná (UFPR), a mais antiga e uma das mais tradicionais universidades do Brasil, com uma rica história acadêmica e uma reputação de excelência em pesquisa.

O campus Jardim Botânico proporciona aos visitantes um ambiente tranquilo e inspirador, ideal para a troca de conhecimento e ideias. A programação será concentrada nos Auditórios Gralha Azul e Maurício Bissoli, ambos localizados no Setor de Ciências da Saúde da UFPR. Além disso, o campus está próximo a importantes pontos turísticos de Curitiba, oferecendo aos participantes do evento a oportunidade de explorar a cultura e as belezas da cidade.

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link="https://maps.app.goo.gl/vfkBnX4yWVTmu1i79"
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{% include section.html %}

{% capture col1 %}

{%
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{% include section.html dark=true %}


{% include cols.html col1=col1 col2=col2 col3=col3 %}
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[data-dark="true"] {
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4 changes: 2 additions & 2 deletions _styles/image.scss
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img {
max-width: 200px;
max-height: 200px;
max-width: 300px;
max-height: 300px;
}
Binary file added images/Sponsors/UFPR.png
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