Neural population coding: combining insights from microscopic and mass signals.

Area of Science:

• Neuroscience
• Computational Neuroscience
• Systems Neuroscience

Background:

• Behavior emerges from coordinated neural population activity.
• Neural population activity can be measured via multi-neuron recordings and neuroimaging.
• Understanding the interplay between local network dynamics and large-scale brain states is crucial for comprehending information processing.

Purpose of the Study:

• To review recent progress in integrating neural recordings and neuroimaging to understand neural information processing.
• To elucidate how interactions between local and large-scale neural dynamics shape neural representations and behavior.

Main Methods:

• Multi-neuron recordings to study local network properties (heterogeneity, sparseness, timing, correlation).
• Neuroimaging to investigate long-range coupling and brain state influences on local activity.
• Computational approaches to integrate data from different scales.

Main Results:

• Neural recordings reveal how local population activity characteristics influence information processing.
• Neuroimaging demonstrates the impact of long-range coupling and brain states on perception and local activity.
• Integration of multi-scale data begins to explain state-dependent information representation and control of distributed populations.

Conclusions:

• Combining local and large-scale neural activity investigations provides an integrated perspective on neural information processing.
• Interactions between local population activity and large-scale dynamics are fundamental to shaping neural representations and behavior.
• Future research should focus on integrating multi-level data to fully understand the neural basis of behavior.