Directed and acyclic synaptic connectivity in the human layer 2-3 cortical microcircuit.
Yangfan Peng1, Antje Bjelde1, Pau Vilimelis Aceituno2
1Institute of Neurophysiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, 10117 Berlin, Germany.
Science (New York, N.Y.)
|April 18, 2024
Summary
Human brain connectivity differs significantly from rodents. Our study reveals unique network properties in the temporal cortex, suggesting new principles for cortical computation.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Systems Neuroscience
Background:
- Neuronal network computation is limited by connectivity.
- Rodent cortical connectivity principles are not fully understood in humans.
- Human cortex evolution and expansion necessitate studying its unique network properties.
Purpose of the Study:
- Investigate network properties in the human temporal cortex.
- Compare human cortical connectivity to established rodent models.
- Understand how human cortical connectivity influences neural dynamics and computation.
Main Methods:
- Analyzed multineuron patch-clamp recordings from human temporal cortex layer 2-3 pyramidal neurons.
- Examined network properties including reciprocity, synaptic strength, and connection probability.
- Utilized neuronal models to assess the impact of observed connectivity principles on network dynamics.
Main Results:
- Human temporal cortex connectivity exhibits significant differences from rodents.
- Reciprocity was randomly distributed, and synaptic strength was independent of connection probability.
- Supragranular temporal cortex connectivity followed a directed, mostly acyclic graph topology.
- Modeling these principles enhanced the dimensionality of network dynamics.
Conclusions:
- Human cortical connectivity principles diverge from rodent models.
- The observed directed and acyclic topology plays a critical role in cortical computation.
- These findings offer new insights into the computational capabilities of the human brain.
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