Neuroscience Data Analysis

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Related lectures (32)

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Scientific Computing in Neuroscience

Explores the history and tools of scientific computing in neuroscience, emphasizing the simulation of neurons and networks.

Building Neural Networks: Assembly Strategies

Focuses on assembling neural network building blocks and dealing with data sparseness using various strategies and assumptions.

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Data, big data, clouds and IoT

Explores data representation, databases, cloud computing, and challenges in the cloud environment.

In Silico Neuroscience: Modern Approaches and Applications

Introduces modern neuroscience approaches and applications, emphasizing computational modeling and its importance in understanding the brain.

In Silico Neuroscience: Network Simulation

Delves into simulating network dynamics in in silico neuroscience, covering spontaneous and evoked activity, in-vitro and in-vivo simulations, and sensitivity analysis.

Approaches and Rationale of Simulation Neuroscience

Explores the overview, rationale, and strategies of simulation neuroscience, emphasizing the challenges of reconstructing and simulating the brain.

Data Wrangling with Hive: Managing Big Data Efficiently

Covers data wrangling techniques using Apache Hive for efficient big data management.

Gitlab Agent for Kubernetes (`agentk`)

Covers the setup of a Gitlab agent for Kubernetes, focusing on installation, version control, and troubleshooting.

Structured Synaptic Connectivity in Hippocampal Regions

Explores synaptic connectivity in hippocampal regions, emphasizing the complexity of neuronal networks and the role of modeling approaches.