Abstract
How neurons are connected in the brain to perform computation is a key issue in neuroscience. Recently, the development of calcium imaging and multi-electrode array techniques have greatly enhanced our ability to measure the firing activities of neuronal populations at single cell level. Meanwhile, the intracellular recording technique is able to measure subthreshold voltage dynamics of a neuron. Our work addresses the issue of how to combine these measurements to reveal the underlying network structure. We propose the spike-triggered regression (STR) method, which employs both the voltage trace and firing activity of the neuronal population to reconstruct the underlying synaptic connectivity. Our numerical study of the conductance-based integrate-and-fire neuronal network shows that only short data of 20 ~ 100 s is required for an accurate recovery of network topology as well as the corresponding coupling strength. Our method can yield an accurate reconstruction of a large neuronal network even in the case of dense connectivity and nearly synchronous dynamics, which many other network reconstruction methods cannot successfully handle. In addition, we point out that, for sparse networks, the STR method can infer coupling strength between each pair of neurons with high accuracy in the absence of the global information of all other neurons.
Highlights
Activities of neurons are central to information encoding and processing in the brain
It remains an important issue of how αilj is related to the underlying neuronal dynamics, in particular, the synaptic coupling structure sij
By regressing the subthreshold voltage trace on the spike trains of presynaptic neurons, the subthreshold voltage responses to presynaptic spikes are captured by the response kernel αilj
Summary
Activities of neurons are central to information encoding and processing in the brain. Calcium imaging can capture the firing activity of each individual neuron in a population (Stosiek et al, 2003; Grewe et al, 2010). Multielectrode array (MEA) can be deployed to directly measure extracellular signals to obtain spikes of individual neurons in a population through spike sorting (Litke et al, 2004; Field et al, 2010; Shimono and Beggs, 2015). The intracellular recording can track the membrane potential to reveal the integration of synaptic inputs. Given spike information of a neuronal population obtained from calcium imaging or MEA and the membrane potential traces via intracellular recording of neurons, we ask the question of how to combine these two types of measurement to capture the underlying network structure.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
