Top-down modulation in canonical cortical circuits with short-term plasticity

被引:0
|
作者
Waitzmann, Felix [1 ,2 ]
Wu, Yue Kris [1 ,2 ]
Gjorgjieva, Julijana [1 ,2 ]
机构
[1] Tech Univ Munich, Sch Life Sci, D-85354 Freising Weihenstephan, Germany
[2] Max Planck Inst Brain Res, Computat Neural Circuits Grp, Frankfurt, Germany
基金
欧洲研究理事会;
关键词
interneuron; short-term plasticity; inhibition stabilization; paradoxical effect; VISUAL-CORTEX; INHIBITORY STABILIZATION; DYNAMICAL REGIME; NETWORKS; NEURONS; MECHANISM;
D O I
10.1073/pnas.2311040121
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Cortical dynamics and computations are strongly influenced by diverse GABAergic interneurons, including those expressing parvalbumin (PV), somatostatin (SST), and vasoactive intestinal peptide (VIP). Together with excitatory (E) neurons, they form a canonical microcircuit and exhibit counterintuitive nonlinear phenomena. One instance of such phenomena is response reversal, whereby SST neurons show opposite responses to top-down modulation via VIP depending on the presence of bottom-up sensory input, indicating that the network may function in different regimes under different stimulation conditions. Combining analytical and computational approaches, we demonstrate that model networks with multiple interneuron subtypes and experimentally identified short-term plasticity mechanisms can implement response reversal. Surprisingly, despite not directly affecting SST and VIP activity, PV -toE short-term depression has a decisive impact on SST response reversal. We show how response reversal relates to inhibition stabilization and the paradoxical effect in the presence of several short-term plasticity mechanisms demonstrating that response reversal coincides with a change in the indispensability of SST for network stabilization. In summary, our work suggests a role of short-term plasticity mechanisms in generating nonlinear phenomena in networks with multiple interneuron subtypes and makes several experimentally testable predictions.
引用
收藏
页数:12
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