Orientation preference in L23 V1 pyramidal neurons (Park et al 2019)

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Accession:231185
"Pyramidal neurons integrate synaptic inputs from basal and apical dendrites to generate stimulus-specific responses. It has been proposed that feed-forward inputs to basal dendrites drive a neuron’s stimulus preference, while feedback inputs to apical dendrites sharpen selectivity. However, how a neuron’s dendritic domains relate to its functional selectivity has not been demonstrated experimentally. We performed 2-photon dendritic micro-dissection on layer-2/3 pyramidal neurons in mouse primary visual cortex. We found that removing the apical dendritic tuft did not alter orientation-tuning. Furthermore, orientation-tuning curves were remarkably robust to the removal of basal dendrites: ablation of 2 basal dendrites was needed to cause a small shift in orientation preference, without significantly altering tuning width. Computational modeling corroborated our results and put limits on how orientation preferences among basal dendrites differ in order to reproduce the post-ablation data. In conclusion, neuronal orientation-tuning appears remarkably robust to loss of dendritic input."
Reference:
1 . Park J, Papoutsi A, Ash RT, Marin MA, Poirazi P, Smirnakis SM (2019) Contribution of apical and basal dendrites to orientation encoding in mouse V1 L2/3 pyramidal neurons Nature Communications 10:5372
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Model Information (Click on a link to find other models with that property)
Model Type:
Brain Region(s)/Organism: Neocortex;
Cell Type(s): Neocortex L2/3 pyramidal GLU cell;
Channel(s): I L high threshold; I T low threshold; I A; I K,Ca; I M; I K; I Na,t;
Gap Junctions:
Receptor(s): GabaA; NMDA; AMPA;
Gene(s):
Transmitter(s): Gaba; Glutamate;
Simulation Environment: NEURON;
Model Concept(s): Vision;
Implementer(s): Papoutsi, Athanasia [athpapoutsi at gmail.com];
Search NeuronDB for information about:  Neocortex L2/3 pyramidal GLU cell; GabaA; AMPA; NMDA; I Na,t; I L high threshold; I T low threshold; I A; I K; I M; I K,Ca; Gaba; Glutamate;
COMMENT

26 Ago 2002 Modification of original channel to allow variable time
step and to correct an initialization error.
    Done by Michael Hines(michael.hines@yale.e) and Ruggero
Scorcioni(rscorcio@gmu.edu) at EU Advance Course in Computational
Neuroscience. Obidos, Portugal
11 Jan 2007
    Glitch in trap where (v/th) was where (v-th)/q is. (thanks Ronald
van Elburg!)

na.mod

Sodium channel, Hodgkin-Huxley style kinetics.  

Kinetics were fit to data from Huguenard et al. (1988) and Hamill et
al. (1991)

qi is not well constrained by the data, since there are no points
between -80 and -55.  So this was fixed at 5 while the thi1,thi2,Rg,Rd
were optimized using a simplex least square proc

voltage dependencies are shifted approximately from the best
fit to give higher threshold

Author: Zach Mainen, Salk Institute, 1994, zach@salk.edu

ENDCOMMENT

INDEPENDENT {t FROM 0 TO 1 WITH 1 (ms)}

NEURON {
	SUFFIX na
	USEION na READ ena WRITE ina
	RANGE m, h, gna, gbar
	GLOBAL tha, thi1, thi2, qa, qi, qinf, thinf
	RANGE minf, hinf, mtau, htau
	GLOBAL Ra, Rb, Rd, Rg
	GLOBAL q10, temp, tadj, vmin, vmax, vshift
}

PARAMETER {
	gbar = 1000   	(pS/um2)	: 0.12 mho/cm2
	vshift = -10	(mV)		: voltage shift (affects all)
								
	tha  = -35:-30:-35	(mV)		: v 1/2 for act		(-42)
	qa   = 9.8:9	(mV)		: act slope		
	Ra   = 0.182	(/ms)		: open (v)		
	Rb   = 0.14:0.124	(/ms)		: close (v)		

	thi1  = -50	(mV)		: v 1/2 for inact 	
	thi2  = -75	(mV)		: v 1/2 for inact 	
	qi   = 5	(mV)	        : inact tau slope
	thinf  = -65	(mV)		: inact inf slope	
	qinf  = 6.2	(mV)		: inact inf slope
	Rg   = 0.0091	(/ms)		: inact (v)	
	Rd   =0.024	(/ms)		: inact recov (v) 

	temp = 23	(degC)		: original temp 
	q10  = 2.3			: temperature sensitivity

	v 		(mV)
	dt		(ms)
	celsius		(degC)
	vmin = -120	(mV)
	vmax = 100	(mV)
}


UNITS {
	(mA) = (milliamp)
	(mV) = (millivolt)
	(pS) = (picosiemens)
	(um) = (micron)
} 

ASSIGNED {
	ina 		(mA/cm2)
	gna		(pS/um2)
	ena		(mV)
	minf 		hinf
	mtau (ms)	htau (ms)
	tadj
}
 

STATE { m h }

INITIAL { 
	trates(v+vshift)
	m = minf
	h = hinf
}

BREAKPOINT {
        SOLVE states METHOD cnexp
        gna = tadj*gbar*m*m*m*h
	ina = (1e-4) * gna * (v - ena)
} 

LOCAL mexp, hexp 

DERIVATIVE states {   :Computes state variables m, h, and n 
        trates(v+vshift)      :             at the current v and dt.
        m' =  (minf-m)/mtau
        h' =  (hinf-h)/htau
}

PROCEDURE trates(v) {  
                      
        
        TABLE minf,  hinf, mtau, htau
	DEPEND  celsius, temp, Ra, Rb, Rd, Rg, tha, thi1, thi2, qa, qi, qinf
	
	FROM vmin TO vmax WITH 199

	rates(v): not consistently executed from here if usetable == 1

:        tinc = -dt * tadj

:        mexp = 1 - exp(tinc/mtau)
:        hexp = 1 - exp(tinc/htau)
}


PROCEDURE rates(vm) {  
        LOCAL  a, b

	a = trap0(vm,tha,Ra,qa)
	b = trap0(-vm,-tha,Rb,qa)

        tadj = q10^((celsius - temp)/10)

	mtau = 1/tadj/(a+b)
	minf = a/(a+b)

		:"h" inactivation 

	a = trap0(vm,thi1,Rd,qi)
	b = trap0(-vm,-thi2,Rg,qi)
	htau = 1/tadj/(a+b)
	hinf = 1/(1+exp((vm-thinf)/qinf))
}


FUNCTION trap0(v,th,a,q) {
	if (fabs((v-th)/q) > 1e-6) {
	        trap0 = a * (v - th) / (1 - exp(-(v - th)/q))
	} else {
	        trap0 = a * q
 	}
}