This repository includes the model used in "Input-modulation as an alternative to conventional learning strategies" by Esin Yavuz and Thomas Nowotny, accepted for the ICANN 2016 conference.

It consists of a model of plasticity in the honeybee olfactory system, modulated by appetitive conditioning. The model is simulated using the GeNN framework (Yavuz et al. 2016).

Neuron and non-plastic synapse models are based on Nowotny et al. 2013, where more information can be found. Mechanisms for input-modulation by reinforcement learning are explained in Yavuz and Nowotny 2016.

Prerequisites:

• CUDA Toolkit (tested on v 6.5 and 7. The version of GeNN used in this paper won't work with v 8.0 because of the redefinition of the atomicAdd function for the double precision).
• GeNN v2.1.1 (available here: https://github.com/genn-team/genn/tree/2.1.1)

#Neuron Parameters

##ORN Parameters

Parameter	Value
t_spike (spike width)	0.1 ms
t_refract (refractory period + spike with)	0.2 ms
V_rest (resting potential)	-60.0 mV
V_spike (potential at top of spike)	50.0 mV
b_rate (base firing rate)	3 Hz
l_max (maximum rate allowed)	50.0 Hz
\alpha (rate of adaptation)	4 Hz
\beta (rate of recovery from adaptation)	2 Hz

##PN Parameters

Parameter	Value
g_Na (Na conductance)	7.15 \mu S
E_Na (Na equipotential)	50.0 mV
g_K (K^+ conductance)	1.43 \mu S
E_K (K equipotential)	-95.0 mV
g_l (leak conductance)	26.72 nS
E_l (leak equipotential)	-63.563 mV
C (membrane capacitance density)	143 pF
I_0 (bias current)	0.0 A

##LN Parameters

Parameter	Value
g_Na (Na conductance)	7.15 \mu S
E_Na (Na equipotential)	50.0 mV
g_K (K^+ conductance)	1.43 \mu S
E_K (K equipotential)	-95.0 mV
g_l (leak conductance)	26.72 nS
E_l (leak equipotential)	-63.563 mV
C (membrane capacitance density)	143 pF
g_M (M conductance)	40 nS
kM_\alpha (rise rate for M activation)	25 Hz
kM_\beta (fall rate for M activation)	1.0 Hz
I_0 (bias current)	0.0 A

##LHI Parameters

Parameter	Value
g_Na (Na conductance)	7.15 \mu S
E_Na (Na equipotential)	50.0 mV
g_K (K^+ conductance)	1.43 \mu S
E_K (K equipotential)	-95.0 mV
g_l (leak conductance)	26.72 nS
E_l (leak equipotential)	-63.563
C (membrane capacitance density)	143 pF
g_M (M conductance)	60 nS
kM_\alpha (rise rate for M activation)	80 Hz
kM_\beta (fall rate for M activation)	1.0 Hz
I_0 (bias current)	-80.0 pA

#Synapse Paremeters

##ORN-PN synapses (non-plastic)

Parameter	Value
g (conductance)	0.021 nS
\sigma_g (jitter for initialising g)	0.05
E_rev (reversal potential)	0.0 mV
\beta (postsynaptic decay rate)	20 Hz

##ORN-PN synapses (plastic)

Parameter	Value
g_ini (initial value for conductance)	0.021 nS
E_rev (reversal potential)	0.0 mV
\beta (postsynaptic decay rate)	20 Hz
g_max (maximal conductance)	0.045 nS
\tau_{decay} (decay time for recovery)	300 s
\g_mid (medium value for conductance)	0.021 pS
\g_slope (slope of the STDP curve)	0.021 nS
p_0 (baseline for eligibility curve)	-5e-12
\tau_p (time constant of eligibility decay)	1.5 s
A (cste to be added to p for STDP)	6e-14
\tau_{STDP} (time constant of STDP decay)	12 ms

##ORN-LN synapses (non-plastic)

Parameter	Value
g (conductance)	0.012 nS
\sigma_g (jitter for initialising g)	0.1
E_rev (reversal potential)	0.0 mV
\beta (postsynaptic decay rate)	20 Hz

##PN-LN synapses (non-plastic)

Parameter	Value
g (conductance)	0.3 nS
\sigma_g (jitter for initialising g)	0.1
E_rev (reversal potential)	0.0 mV
\beta (postsynaptic decay rate)	20 Hz

##LN-PN synapses (non-plastic)

Parameter	Value
g (conductance)	1 nS
E_rev (reversal potential)	-80.0 mV
\beta (postsynaptic decay rate)	10 Hz

##LN-LN synapses (non-plastic)

Parameter	Value
g (conductance)	1.2 nS
E_rev (reversal potential)	-80.0 mV
\beta (postsynaptic decay rate)	10 Hz

##PN-LHI synapses (non-plastic)

Parameter	Value
g (conductance)	0.017 nS
\sigma_g (jitter for initialising g)	0.05
E_rev (reversal potential)	0.0 mV
\beta (postsynaptic decay rate)	10 Hz

#Reward parameters

Parameter	Value
R_{0} (baseline reward -- or -1 x expectance )	-8.0
R_max (value of given reward)	40.0
\tau_{R} (Time constant of reward rise/decay)	50 ms

REFERENCES