
Beginner-friendly introduction to SNP chip technology in genomics, covering basic concepts, data handling, allele coding, and chip types. Ideal for those new to genomics seeking to understand SNP data analysis.

Explore DNA basics, genomic revolution, and markers in this beginner-friendly introduction to genomics theory, covering fundamental concepts and their applications in modern science.

Learn to use Structure software for population admixture analysis using SNP data. Covers data preparation, project setup, analysis execution, and result visualization with a goat genotype example.

Comprehensive tutorial on using varLD software for analyzing selection signatures based on linkage disequilibrium, covering prerequisites, data preparation, execution, and result visualization.

Explore glutamatergic circuits in cortex and thalamus, focusing on functional classification, postsynaptic receptors, and metabotropic components. Gain insights into dynamic basal ganglia and modulation of driver inputs.

Explore stochastic rewiring in neural networks, covering plasticity, noise, and reward-based learning, with insights into parameter dynamics and experimental findings.

Explore how the neocortex might use grid cell-like mechanisms to learn object structure, drawing parallels between spatial navigation and object recognition in the brain.

Explore the prefrontal cortex's role in meta-reinforcement learning, connecting neuroscience and AI through recurrent neural networks and cognitive tasks like Harlow's experiment.

Explore automated reconstruction of neural wiring diagrams using advanced techniques like generative adversarial networks and crowdsourcing, with applications in connectomics and targeted brain data discovery.

Explore hippocampal memory, cognition, and sleep's role through phase processing, decoding, spatial navigation, and neural mechanisms in this comprehensive lecture.

Explore hippocampal structure, memory coding, and electrophysiology techniques. Delve into working hypotheses and data interpretation in neuroscience research.

Explore advanced neural models and mechanisms of human visual object recognition, including linear decoders, adversarial attacks, and individual variability in visual processing.

Explore primate face recognition, from neural substrates to computational principles, examining face cells, processing systems, and recognition architectures in this comprehensive overview.

Explore how fly neurons process visual motion direction, focusing on cellular mechanisms, biophysical models, and recent discoveries in Drosophila's neural circuits for motion detection.

Explore how songbirds develop neural sequences for vocalizations, examining the role of auditory memory in shaping motor circuits and facilitating song learning through reinforcement mechanisms.

Explores primate visual cortex responses during natural viewing, revealing how neurons in the interior temporal cortex react to faces and repeated fixations, providing insights into our stable visual perception.

Explore parallel systems for social and spatial reasoning in the brain's apex network, examining cognitive architecture, neural mechanisms, and evolutionary origins through fMRI experiments and theoretical frameworks.

Hands-on tutorial exploring RNNs in cognitive neuroscience through coding exercises. Learn to train and analyze RNNs for various tasks, with lecture and workshop components using Google Colab Notebooks.

Explore primate social intelligence, face perception, and neural mechanisms behind facial recognition and social interactions.

Explore primate and machine vision computations, comparing face recognition, image processing, and neural networks. Gain insights into computational neuroscience and visual perception illusions.

Explore brain imaging techniques, functional specialization, and neural networks in understanding human cognition. Insights on face recognition, predictive models, and the organization of mental processes.