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Sparse recurrent excitatory connectivity in the microcircuit of the adult mouse and human cortex

Stephanie C Seeman, Luke Campagnola, Pasha A Davoudian, Alex Hoggarth, Travis A Hage, Alice Bosma-Moody, Christopher A Baker, Jung H. Lee, Stefan Mihalas, Corinne Teeter, Andrew L Ko, Jeffrey G Ojemann, Ryder P Gwinn, Daniel L Silbergeld, Charles Cobbs, John Phillips, Ed Lein, Gabe Murphy, Christof Koch, Hongkui Zeng, Tim Jarsky

Preprint posted on May 08, 2018 https://www.biorxiv.org/content/early/2018/05/08/292706

New work from @AllenInstitute compares synaptic connectivity in human cortex to the commonly studied mouse visual cortex. Very insightful study from preproduction data -- looking forward to the full production data release!

Selected by Mahesh Karnani

Categories: neuroscience

Summary

This preprint from Tim Jarsky’s team at the Allen Institute for Brain Science shows synaptic connectivity profiles within cortical layers in neurosurgical samples of human brain and compares them thoroughly to samples from mouse brain. Compared to the commonly studied mouse visual cortex, the human frontal and temporal cortex has more synaptically connected neurons forming a denser recurrent microcircuit. The conclusions are compatible with previous work and help place findings from the mouse in a translational perspective.

 

Context

Understanding how the brain generates activity patterns that underlie thought and behaviour necessitates knowledge of communication protocols in local microcircuits that are composed of synaptically connected neurons. Synaptic communication in microcircuits of the rodent brain has been studied for decades, using multi-cell patch clamp recordings in acutely isolated brain slices. This work has resulted in detailed – although still incomplete – knowledge of connectivity patterns in rodent sensory cortex 1,2 and an ongoing transition toward studying how the microcircuit layout affects dynamics of brain activity and cortical computations. Similar work in the human cortex is yet to be done, although some laboratories do have access to neurosurgical samples of human brain, resected during removal of brain tumours, for example.

One such laboratory is at the Allen Institute for Brain Science, which has already contributed big datasets from many large-scale projects to the neuroscience community, creating comprehensive databases of meso-scale connectivity, marker expression, and morphologies of human and mouse neurons 3. The institute is currently working on several highly interesting projects and accelerates dissemination of results through its online database and preprinting regularly on Biorxiv. Their latest work compares connectivity in human frontal and temporal cortex to mouse visual cortex. The presented dataset is from a “pipeline’s system integration test” and is expected to lead to a comprehensive dataset, as the team starts routine operation of the workflow.

 

 

Key findings

This study is very exciting because it shows increased connectivity and synaptic weights in human cortex compared to the mouse visual cortex. The study confirms previous reports of high connectivity in human cortex 4 and gives a translational perspective compared to results obtained in mouse cortex. Whereas previous work identified complex multisynaptic events triggered by single action potentials in human cortex 4,5, this study aimed to minimize their occurrence since they can interfere with assessment of monosynaptic connectivity. Lowering the occurrence of complex events was achieved by modifying experimental variables such as decreased recording temperature and calcium and potassium concentrations of the extracellular medium compared to the previous studies.

Recurrent synaptic connectivity in human L2/3 is relatively dense. From Seeman et al., 2018, Figure 2 (under CC-BY-NC-ND 4.0).

 

While lower than in human cortex, connectivity in the mouse visual cortex was high compared to a previous study 2. The authors have two results that bear on this and similar discrepancies in the literature. Firstly, connectivity is highly distance dependent and should thus be reported as a function of distance in order to compare across labs. Secondly, led by co-first-author Luke Campagnola, the team have devised a machine learning based method for estimating synapse detection limits during paired recordings. This approach can be used to compare results from different labs if the raw data are made available.

 

Why I chose this preprint 

I work on connectivity in the mouse brain, and often think about how applicable these results are to our efforts to understand our own brains. Evolutionary and structural arguments suggest there is a “translational bridge”, but it is very important to have direct comparative data. The key physiological differences include the high connectivity in human cortex reported in this preprint and enlarged excitatory synapses on inhibitory interneurons 5–7. Together these endow human cortex the propensity for complex multisynaptic events triggered by single action potentials. This is exceedingly rare in rodent microcircuits 8 and could partly explain the ability of the human neocortex to perform highly complex tasks. However, it seems from this preprint that the complex events are quite sensitive to extracellular medium composition. It would be interesting to see more direct, controlled comparisons of complex events across recording conditions and species.

 

What next?

The authors have made a powerful pipeline for generating important results from human cortex. While it will be highly informative to use their protocols with single action potentials and firing trains in one cell at a time to characterize synaptic responses, even more could be learned through simultaneous firing protocols in multiple cells. This could reveal cooperatively scaling excitation and disynaptic inhibition 9,10 which may be drastically different in human cortex, given the differences noted so far. The presented human data are within layers and across pyramidal cells only, and it will be interesting to see in future publications how connectivity across layers and interneurons compares to mouse.

 

References:

  1. Lefort, S., Tomm, C., Floyd Sarria, J.-C. & Petersen, C. C. H. The Excitatory Neuronal Network of the C2 Barrel Column in Mouse Primary Somatosensory Cortex. Neuron 61, 301–316 (2009).
  2. Jiang, X. et al. Principles of connectivity among morphologically defined cell types in adult neocortex. Science. 350, aac9462-aac9462 (2015).
  3. http://www.brain-map.org/.
  4. Molnár, G. et al. Complex events initiated by individual spikes in the human cerebral cortex. PLoS Biol. 6, e222 (2008).
  5. Szegedi, V. et al. High-Precision Fast-Spiking Basket Cell Discharges during Complex Events in the Human Neocortex. eNeuro 4, ENEURO.0260-17.2017 (2017).
  6. Szegedi, V. et al. Plasticity in Single Axon Glutamatergic Connection to GABAergic Interneurons Regulates Complex Events in the Human Neocortex. PLoS Biol. 14, e2000237 (2016).
  7. Molnár, G. et al. Human pyramidal to interneuron synapses are mediated by multi-vesicular release and multiple docked vesicles. Elife 5, e18167 (2016).
  8. Brecht, M. Neuronal communication: firing spikes with spikes. Curr. Biol. 22, R633-5 (2012).
  9. Kapfer, C., Glickfeld, L. L., Atallah, B. V & Scanziani, M. Supralinear increase of recurrent inhibition during sparse activity in the somatosensory cortex. Nat. Neurosci. 10, 743–53 (2007).
  10. Berger, T. K., Silberberg, G., Perin, R. & Markram, H. Brief Bursts Self-Inhibit and Correlate the Pyramidal Network. PLoS Biol. 8, e1000473 (2010).

Tags: human brain, synaptic connectivity

Posted on: 31st May 2018

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  • Author's response

    Tim Jarsky shared

    We are thankful for the opportunity to discuss and receive feedback on our recent manuscript through preLights. We share Mahesh’s excitement regarding the increased rate of connectivity and strength of recurrent excitatory connections in human, compared to mouse. We anticipate building out our human datasets to include the short-term dynamics in near physiological (~1.3 mM) external calcium concentrations. We believe this type of data will be useful for building a network model that will inform our understanding of human cortical processing.

    The challenge of characterizing local cortical connectivity with the detail necessary to build useful computational models is enormous. We’ve taken a modest step to help bring the community closer to this goal by gathering a relatively large, standardized data set from a range of synapse types and layers in adult mouse and human, that we intend to share. We are also interested in accelerating progress by helping and working with the larger scientific community. We wish to open a dialog with laboratories performing similar experiments (publicly on preLights would be fantastic) so that we can work toward building datasets that can be compared and combined more easily. We believe that a comprehensive integrated data set gives us the best chance to answer many of the interesting questions raised in this preLight and ultimately a better understanding of human cognition.

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