Format

Send to

Choose Destination
J Neurosci. 2019 Jul 25. pii: 3169-18. doi: 10.1523/JNEUROSCI.3169-18.2019. [Epub ahead of print]

Correlation transfer by layer 5 cortical neurons under recreated synaptic inputs in vitro.

Author information

1
Molecular, Cellular, and Network Excitability Lab, Department of Biomedical Sciences and Institute Born-Bunge, Universiteit Antwerpen, Wilrijk B-2610, Belgium.
2
Université Libre de Bruxelles (ULB), IRIBHM, and ULB Neuroscience Institute, Brussels, B-1050 Belgium.
3
VIB-KU Leuven Center for Brain & Disease Research, Leuven B-3000, Belgium.
4
Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven B-3000, Belgium.
5
Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA 15260, United States of America.
6
Center for the Neural Basis of Cognition, University of Pittsburgh and Carnegie Mellon University, Pittsburgh, PA 15213, USA.
7
Department of Mathematics, University of Pittsburgh, Pittsburgh, PA 15260, USA.
8
Molecular, Cellular, and Network Excitability Lab, Department of Biomedical Sciences and Institute Born-Bunge, Universiteit Antwerpen, Wilrijk B-2610, Belgium michele.giugliano@uantwerpen.be.
9
Scuola Internazionale Superiore di Studi Avanzati, Neuroscience sector, Trieste, Italy.

Abstract

Correlated electrical activity in neurons is a prominent characteristic of cortical microcircuits. Despite a growing amount of evidence concerning both spike-count and subthreshold membrane potential pairwise correlations, little is known about how different types of cortical neurons convert correlated inputs into correlated outputs. We studied pyramidal neurons and two classes of GABAergic interneurons of layer 5 in neocortical brain slices obtained from rats of both sexes, and we stimulated them with biophysically realistic correlated inputs, generated using dynamic clamp. We found that the physiological differences between cell types manifested unique features in their capacity to transfer correlated inputs. We used linear response theory and computational modeling to gain clear insights into how cellular properties determine both the gain and timescale of correlation transfer, thus tying single-cell features with network interactions. Our results provide further ground for the functionally distinct roles played by various types of neuronal cells in the cortical microcircuit.SIGNIFICANCE STATEMENTNo matter how we probe the brain, we find correlated neuronal activity over a variety of spatial and temporal scales. For the cerebral cortex, significant evidence has accumulated on trial-to-trial co-variability in synaptic inputs activation, subthreshold membrane potential fluctuations, and output spike trains. While we do not yet fully understand their origin and whether they are detrimental or beneficial for information processing, we believe that clarifying how correlations emerge is pivotal for understanding large-scale neuronal network dynamics and computation. Here, we report quantitative differences between excitatory and inhibitory cells, as they relay input correlations into output correlations. We explain this heterogeneity by simple biophysical models and provide the most experimentally validated test of a theory for the emergence of correlations.

Supplemental Content

Full text links

Icon for HighWire
Loading ...
Support Center