Assessment of Connectivity in Neuronal Cultures by Recording from Axonal Arbors
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1
RIKEN , Quantitative Biology Center, Germany
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2
ETH Zurich, Department of Biosystems Science and Engineering, Switzerland
Motivation
A key problem in neuroscience is to understand the relationship between structure and function. Here, we present a novel method that estimates the morphological connectivity and compares it to a measure of functional connectivity.
Material and Methods
Dissociated neurons from E16-18 rat neocortex were cultured at low density on high-density microelectrode arrays (HDMEAs, Frey et al., 2010). After identification of axon initial segments, network activity was recorded, and action potentials were tracked along full axonal arbors of single neurons at subcellular resolution.
Morphological connectivity was estimated according to Peter's rule from the overlap of axonal and dendritic fields, using parameters for the dendritic field diameter and the minimum overlap area ratio. Functional connectivity was assumed, when the ISI histograms showed a clear peak (z-score>25) as compared to randomized surrogate data.
Results
We developed a python library (PyTau) with fast implementation of procedures to calculate and visualize morphological and functional connectivity in neuronal networks based on HDMEA recordings. Furthermore, we observed a high correlation of inferred delay values between neurons.
Discussion
Since in this study only 25 neurons and their respective axonal arbors were analyzed, there remain many neurons in the recorded network unknown. Newer generations of HDMEAs with a larger number of parallel readout channels will make it possible to essentially record from all neurons so that the whole neuronal network can be assessed.
Conclusion
Although preliminary results were obtained on a small network with many hidden units, our method can easily be scaled to handle large datasets, which enables a comprehensive analysis of neuronal cultures including morphology, connectivity and activity. We have applied this method to study the effects of temperature on sleep and memory in vitro (Bullmann et al., 2016).
References
Bullmann, T. et al. 2016. 10th international Meeting on Substrate-integrated Microelectrode Arrays, Reutlingen, Germany.
Frey, U. et al. 2010. IEEE Journal of Solid-State Circuits 45(2): 467–482.
Figure 1
Inferred morphological connectivity.
Axonal delay map (colorcoded green-yellow) and dendritic fields with r=100μm around the axon initial segment (grey circles, left panel) are used to infer connectivity. When their overlap exceeded 5%, a connection with axonal delay τAxon was assigned (right panel).
Keywords:
connectivity,
axonal arbors,
Peter's rule,
spike time lag
Conference:
MEA Meeting 2016 |
10th International Meeting on Substrate-Integrated Electrode Arrays, Reutlingen, Germany, 28 Jun - 1 Jul, 2016.
Presentation Type:
Poster Presentation
Topic:
MEA Meeting 2016
Citation:
Huber
S,
Bullmann
T,
Deligkaris
K,
Hierlemann
A and
Frey
U
(2016). Assessment of Connectivity in Neuronal Cultures by Recording from Axonal Arbors.
Front. Neurosci.
Conference Abstract:
MEA Meeting 2016 |
10th International Meeting on Substrate-Integrated Electrode Arrays.
doi: 10.3389/conf.fnins.2016.93.00077
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Received:
22 Jun 2016;
Published Online:
24 Jun 2016.
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Correspondence:
Dr. Stefan Huber, RIKEN, Quantitative Biology Center, Kobe, Germany, stefanhuber1993@googlemail.com