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Strong and reliable synaptic communication between pyramidal neurons in adult human cerebral cortex

Sarah Hunt, Yoni Leibner, Eline J. Mertens, Natalí Barros-Zulaica, Lida Kanari, Tim S. Heistek, Mahesh Karnani, Romy Aardse, René Wilbers, Djai B. Heyer, Natalia A. Goriounova, Matthijs B Verhoog, Guilherme Testa-Silva, Joshua Obermayer, Tamara Versluis, Ruth Benavides‐Piccione, Philip de Witt-Hamer, Sander Idema, David P. Noske, Johannes C. Baayen, Ed S. Lein, Javier DeFelipe, Henry Markram, Huibert D. Mansvelder, Felix Schürmann, Idan Segev, Christiaan P. J. de Kock

2022Cerebral Cortex93 citationsDOIOpen Access PDF

Abstract

Synaptic transmission constitutes the primary mode of communication between neurons. It is extensively studied in rodent but not human neocortex. We characterized synaptic transmission between pyramidal neurons in layers 2 and 3 using neurosurgically resected human middle temporal gyrus (MTG, Brodmann area 21), which is part of the distributed language circuitry. We find that local connectivity is comparable with mouse layer 2/3 connections in the anatomical homologue (temporal association area), but synaptic connections in human are 3-fold stronger and more reliable (0% vs 25% failure rates, respectively). We developed a theoretical approach to quantify properties of spinous synapses showing that synaptic conductance and voltage change in human dendritic spines are 3-4-folds larger compared with mouse, leading to significant NMDA receptor activation in human unitary connections. This model prediction was validated experimentally by showing that NMDA receptor activation increases the amplitude and prolongs decay of unitary excitatory postsynaptic potentials in human but not in mouse connections. Since NMDA-dependent recurrent excitation facilitates persistent activity (supporting working memory), our data uncovers cortical microcircuit properties in human that may contribute to language processing in MTG.

Topics & Concepts

NeuroscienceCerebral cortexPsychologyNeural dynamics and brain functionNeuroscience and Neuropharmacology ResearchEEG and Brain-Computer Interfaces