Differential Encoding of Time by Prefrontal and Striatal Network Dynamics.
Konstantin I BakhurinVishwa GoudarJustin L ShobeLeslie D ClaarDean V BuonomanoSotiris C MasmanidisPublished in: The Journal of neuroscience : the official journal of the Society for Neuroscience (2017)
The neural representation of time is thought to be distributed across multiple functionally specialized brain structures, including the striatum and cortex. However, until now, the neural code for time has not been compared quantitatively between these areas. Here, we performed large-scale recordings in the striatum and orbitofrontal cortex of mice trained on a stimulus-reward association task involving a delay period and used a machine-learning algorithm to quantify how well populations of simultaneously recorded neurons encoded elapsed time from stimulus onset. We found that, although both areas encoded time, the striatum consistently outperformed the orbitofrontal cortex. These results suggest that the striatum may refine the code for time by integrating information from multiple inputs.
Keyphrases
- functional connectivity
- resting state
- machine learning
- prefrontal cortex
- neural network
- deep learning
- palliative care
- artificial intelligence
- healthcare
- high resolution
- working memory
- spinal cord
- resistance training
- health information
- high fat diet induced
- big data
- parkinson disease
- cerebral ischemia
- blood brain barrier
- mass spectrometry
- skeletal muscle
- deep brain stimulation
- brain injury
- body composition
- social media