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Explore the concept of compositionality across various domains, including language, tool use, and drawing, with insights into its mechanisms and applications in cognitive science.
Explore efficient representation and learning through abstraction, focusing on cognitive space clustering and its impact on memory, navigation, and planning in complex environments.
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 scale-dependent kernels in machine learning, covering overfitting, statistical theory, and practical applications in regression and interpolation.
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.
Explore hippocampal mechanisms underlying memory and cognition, including structure, storage, retrieval, brain oscillations, and spatial firing patterns.
Explore how number sense emerges from brain manipulation, examining experiments, perceptions, and the role of supervised learning in developing numerical understanding.
Explore selective attention, eye movements, and neural synchrony in this comprehensive examination of cognitive processes and perceptual mechanisms.
Explore cognitive modeling to reverse-engineer human common sense, examining AI progress, scientific context, and probabilistic programming techniques for capturing learning and constructing models.
Explore the neural foundations of consciousness, examining brain structures and theories with neuroscientist Christof Koch in this thought-provoking lecture.
Explore the mechanisms of human visual object recognition, focusing on systems-level models, reverse engineering, and the ventral visual stream's role in perception and AI applications.
Explore cutting-edge models of human visual object recognition, their implications for AI, and strategies for future research in neuroscience and machine learning.
Explore brain-inspired AI advancements, focusing on object recognition, contextual reasoning, and model performance. Gain insights into cutting-edge computational approaches and their applications.
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