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Inferring thalamocortical monosynaptic connectivity in vivo
Yi Juin Liew1,2, Aurélie Pala1, Clarissa J Whitmire1
1Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia.
Journal of Neurophysiology
|May 12, 2021
Summary
Researchers developed a new statistical framework to infer synaptic connectivity in the brain using in vivo recordings. This method helps understand neural communication critical for perception and behavior, even with limited targeting capabilities.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Systems Neuroscience
Background:
- Simultaneous electrophysiological recordings from large neuronal populations are becoming more common.
- Understanding causal relationships between neurons and neural patterns underlying perception and behavior is a key goal.
- In vivo studies of synaptic connectivity are sparse due to limitations in targeting and reliance on indirect measures.
Purpose of the Study:
- To establish a general experimental and computational framework for inferring synaptic connectivity in vivo.
- To address the challenge of determining causal relationships between monosynaptically connected neurons.
- To enable large-scale assessment of synaptic connectivity within and across brain structures.
Main Methods:
- Utilized in vivo extracellular single-unit recordings in the rodent thalamocortical pathway (ventral-posterior medial (VPm) and somatosensory cortex (S1)).
- Applied a statistical signal detection framework to analyze recorded neural activity.
- Investigated the trade-off between network activity levels and neuronal synchronization for inferring connectivity.
Main Results:
- Identified a trade-off where high network activity aids inference but can be masked by neuronal synchronization.
- Developed a framework for establishing connectivity in multisite, multielectrode recordings using statistical inference.
- Demonstrated a method to assess potential monosynaptic connectivity from population spiking activity.
Conclusions:
- The proposed framework enables the assessment of synaptic connectivity from population spiking activity.
- This approach generalizes to large-scale recording technologies for studying neural circuits.
- Advances understanding of information transfer across brain regions, crucial for perception and behavior.
