Multi-scale neural decoding and analysis.

Area of Science:

• Neuroscience
• Computational Neuroscience
• Systems Neuroscience

Background:

• Neural activity, crucial for behavior and cognition, is complex and spatiotemporal.
• Single measurement modalities offer incomplete assessments of the neural code due to tradeoffs in spatial and temporal resolution.

Purpose of the Study:

• To advocate for integrating multi-modal neural recordings to overcome single-modality limitations.
• To provide a roadmap for multi-scale neural decoding techniques for a holistic understanding of brain function.

Main Methods:

• Review of conventional methodologies for characterizing neural activity at different scales.
• Discussion of contemporary examples combining different measurement modalities.
• Examination of analytical techniques for integrating information across scales.

Main Results:

• Multi-modal approaches enhance understanding of system-level neural mechanisms by combining complementary strengths.
• Integration of activity across multiple scales reveals deeper insights into neural processes.
• Technologies enabling multi-scale studies are discussed, along with their potential.

Conclusions:

• Multi-scale neural decoding offers significant benefits over single-modality analyses.
• Systematically interrogating complex spatiotemporal mechanisms requires multi-scale approaches.
• This review highlights the importance of multi-scale analyses for understanding cognition and behavior.