2017
DOI: 10.1152/jn.00398.2017
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Coupling of synaptic inputs to local cortical activity differs among neurons and adapts after stimulus onset

Abstract: Cortical activity contributes significantly to the high variability of sensory responses of interconnected pyramidal neurons, which has crucial implications for sensory coding. Yet, largely because of technical limitations of in vivo intracellular recordings, the coupling of a pyramidal neuron's synaptic inputs to the local cortical activity has evaded full understanding. Here we obtained excitatory synaptic conductance ( g) measurements from putative pyramidal neurons and local field potential (LFP) recording… Show more

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Cited by 10 publications
(12 citation statements)
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“…We modeled a single cortical column as a network of 800 excitatory and 100 inhibitory LIF neurons, with relatively strong inhibitory-to-excitatory synapses (Gabernet et al, 2005). We imposed spatial clustering via "small-world" network connectivity (Bujan et al, 2015;Litwin-Kumar & Doiron, 2012;Wright, Hoseini, Yasar, et al, 2017), with 10% re-wiring probability. Inhibitory LIF neurons had shorter membrane time constants (Gentet et al, 2010) and refractory periods (1 ms for inhibitory, 2 ms for excitatory), which -together with the TC connection properties described above -supported higher firing rates in inhibitory neurons, as observed here during wakefulness ( Fig.…”
Section: Thalamocortical Network Modelmentioning
confidence: 99%
“…We modeled a single cortical column as a network of 800 excitatory and 100 inhibitory LIF neurons, with relatively strong inhibitory-to-excitatory synapses (Gabernet et al, 2005). We imposed spatial clustering via "small-world" network connectivity (Bujan et al, 2015;Litwin-Kumar & Doiron, 2012;Wright, Hoseini, Yasar, et al, 2017), with 10% re-wiring probability. Inhibitory LIF neurons had shorter membrane time constants (Gentet et al, 2010) and refractory periods (1 ms for inhibitory, 2 ms for excitatory), which -together with the TC connection properties described above -supported higher firing rates in inhibitory neurons, as observed here during wakefulness ( Fig.…”
Section: Thalamocortical Network Modelmentioning
confidence: 99%
“…Recorded Vm fluctuations taken in the dark (no visual stimulation) were interpreted as ongoing activity. Such ongoing cortical activity was interrupted by visual stimulation of the retina with whole-field flashes and naturalistic movies as described previously (Wright et al, 2017a;Wright et al, 2017b;Wright and Wessel, 2017). An uninterrupted recording of ongoing activity lasted for 2 to 5 minutes.…”
Section: Intracellular Recordingsmentioning
confidence: 99%
“…Researchers have tried many ways to map synaptic activity recorded at the soma to population events and dynamics 1 , 2 , 46 49 . Machine learning algorithms are sensible options but often don’t permit scientific inference beyond their predictions themselves 5 , 30 ,.…”
Section: Discussionmentioning
confidence: 99%
“…Unfortunately, the transformation of presynaptic population dynamics into synaptic input and then to neural output is very messy. Synaptic inputs can interfere with each other and are obscured by single-neuron biophysical effects, such as membrane properties [1][2][3] . Whole-cell recording methods observe these as fluctuations of current and potential at the neuronal cell body, i.e., the soma.…”
mentioning
confidence: 99%