Information processing
Recent articles
Explaining ‘the largest unexplained number in brain science’: Q&A with Markus Meister and Jieyu Zheng
The human brain takes in sensory information roughly 100 million times faster than it can respond. Neuroscientists need to explore this perceptual paradox to better understand the limits of the brain, Meister and Zheng say.
Explaining ‘the largest unexplained number in brain science’: Q&A with Markus Meister and Jieyu Zheng
The human brain takes in sensory information roughly 100 million times faster than it can respond. Neuroscientists need to explore this perceptual paradox to better understand the limits of the brain, Meister and Zheng say.
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Home makeover helps rats better express themselves: Q&A with Raven Hickson and Peter Kind
The “Habitat”—a complex environment with space for large social groups—expands the behavioral repertoire of rodent models, Hickson and Kind say.
Home makeover helps rats better express themselves: Q&A with Raven Hickson and Peter Kind
The “Habitat”—a complex environment with space for large social groups—expands the behavioral repertoire of rodent models, Hickson and Kind say.
Tatiana Engel explains how to connect high-dimensional neural circuitry with low-dimensional cognitive functions
Neuroscientists have long sought to understand the relationship between structure and function in the vast connectivity and activity patterns in the brain. Engel discusses her modeling approach to discovering the hidden patterns that connect the two.
Tatiana Engel explains how to connect high-dimensional neural circuitry with low-dimensional cognitive functions
Neuroscientists have long sought to understand the relationship between structure and function in the vast connectivity and activity patterns in the brain. Engel discusses her modeling approach to discovering the hidden patterns that connect the two.
Beyond the algorithmic oracle: Rethinking machine learning in behavioral neuroscience
Machine learning should not be a replacement for human judgment but rather help us embrace the various assumptions and interpretations that shape behavioral research.
Beyond the algorithmic oracle: Rethinking machine learning in behavioral neuroscience
Machine learning should not be a replacement for human judgment but rather help us embrace the various assumptions and interpretations that shape behavioral research.