Using Single Neuron Dynamics to Predict Synchronous Global Network - PowerPoint PPT Presentation

Using Single Neuron Dynamics to Predict Synchronous Global Network Activities Robert Kim Neurosciences Graduate Program University of California, San Diego December 8, 2017 Neurodynamics Final Project December 8, 2017 1 / 16

Outline Background 1 Methods 2 Results 3 Summary 4 Neurodynamics Final Project December 8, 2017 2 / 16

Outline Background 1 Methods 2 Results 3 Summary 4 Neurodynamics Final Project December 8, 2017 3 / 16

Background Based on the previous findings from Neurodynamics Final Project December 8, 2017 4 / 16

Background Based on the previous findings from Rat cortical neurons artificially grown on a multi-electrode arrays (Figure from Tajima, S. et al. Locally embedded presages of global network bursts. PNAS , 114: 9517-9522, 2017) Neurodynamics Final Project December 8, 2017 4 / 16

Background 1 0.9 0.8 Mean Firing Activity 0.7 0.6 0.5 0.4 0.3 0.2 0.1 5 10 15 20 25 30 Time (sec) Neurodynamics Final Project December 8, 2017 5 / 16

Background 1 0.9 0.8 Mean Firing Activity 0.7 0.6 0.5 0.4 0.3 0.2 0.1 5 10 15 20 25 30 Time (sec) 1 0.8 0.6 x 2 (t) 0.4 0.2 1 0.8 0.6 0.9 0.8 (Figure from Tajima, S. et al. Locally embedded presages of 0.4 0.7 x 1 (t) 0.6 0.5 0.4 0.2 global network bursts. PNAS , 114: 9517-9522, 2017) 0.3 0.2 x(t) 0.1 Neurodynamics Final Project December 8, 2017 5 / 16

Outline Background 1 Methods 2 Results 3 Summary 4 Neurodynamics Final Project December 8, 2017 6 / 16

Methods Izhikevich neurons will be used to replicate some of the findings of Tajima et al. 0 . 04 v 2 + 5 v + 140 − u + I v ˙ = ˙ = a · ( bv − u ) u if v 35 mV, v = c and u = u + d ≥ Neurodynamics Final Project December 8, 2017 7 / 16

Methods Izhikevich neurons will be used to replicate some of the findings of Tajima et al. 0 . 04 v 2 + 5 v + 140 − u + I v ˙ = ˙ = a · ( bv − u ) u if v 35 mV, v = c and u = u + d ≥ 20 v (mV) 0 -20 -40 -60 -80 -100 -50 0 50 100 150 200 250 300 350 400 Time (ms) 20 0 v (mV) -20 -40 -60 -80 -100 -50 0 50 100 150 200 250 300 350 400 Time (ms) 20 v (mV) 0 -20 -40 -60 -80 -100 -50 0 50 100 150 200 250 300 350 400 Time (ms) 0 v (mV) -50 -100 -100 -50 0 50 100 150 200 250 300 350 400 Time (ms) Neurodynamics Final Project December 8, 2017 7 / 16

Methods RS Excitatory Neuron a = 0 . 02, b = 0 . 13 c = − 65 mV, d = 8 20 Voltage (mV) 0 -20 -40 -60 -80 200 400 600 800 1000 Time (ms) Neurodynamics Final Project December 8, 2017 8 / 16

Methods RS Excitatory Neuron FS Inhibitory Neuron a = 0 . 02, b = 0 . 13 a = 0 . 1, b = 0 . 13 c = − 65 mV, d = 8 c = − 65 mV, d = 2 20 20 Voltage (mV) Voltage (mV) 0 0 -20 -20 -40 -40 -60 -60 -80 200 400 600 800 1000 200 400 600 800 1000 Time (ms) Time (ms) Neurodynamics Final Project December 8, 2017 8 / 16

Methods Network Configuration 450 Izhikevich neurons 360 RS excitatory neurons 90 FS inhibitory neurons Neurodynamics Final Project December 8, 2017 9 / 16

Methods Network Configuration 450 Izhikevich neurons 360 RS excitatory neurons 90 FS inhibitory neurons Sparsely and randomly connected to one another (40% connections) Neurodynamics Final Project December 8, 2017 9 / 16

Methods Network Configuration 450 Izhikevich neurons 360 RS excitatory neurons 90 FS inhibitory neurons Sparsely and randomly connected to one another (40% connections) No external/inject current Neurodynamics Final Project December 8, 2017 9 / 16

Outline Background 1 Methods 2 Results 3 Summary 4 Neurodynamics Final Project December 8, 2017 10 / 16

Results Neurons 130 131 132 133 134 135 136 Time (sec) 1 Mean Firing Activity 0 130 131 132 133 134 135 136 Time (sec) Neurodynamics Final Project December 8, 2017 11 / 16

Results Dynamics of individual neurons were able to forecast/predict the spontaneous global burst. 1 1 0.9 0.9 0.8 0.8 0.7 0.7 0.6 0.6 b 1 (t) x 1 (t) 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 0 0.2 0.4 0.6 0.8 1 b(t) x(t) Neurodynamics Final Project December 8, 2017 12 / 16

Results Dynamics of individual neurons were able to forecast/predict the spontaneous global burst. 1 1 0.9 0.9 0.8 0.8 0.7 0.7 0.6 0.6 b 1 (t) x 1 (t) 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 0 0.2 0.4 0.6 0.8 1 b(t) x(t) Neurodynamics Final Project December 8, 2017 12 / 16

Results Dynamics of individual neurons were able to forecast/predict the spontaneous global burst. 1 1 0.9 0.9 0.8 0.8 0.7 0.7 0.6 0.6 b 1 (t) x 1 (t) 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 0 0.2 0.4 0.6 0.8 1 b(t) x(t) Neurodynamics Final Project December 8, 2017 12 / 16

Results Dynamics of individual neurons were able to forecast/predict the spontaneous global burst. 1 1 0.9 0.9 0.8 0.8 0.7 0.7 0.6 0.6 b 1 (t) x 1 (t) 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 0 0.2 0.4 0.6 0.8 1 b(t) x(t) Neurodynamics Final Project December 8, 2017 12 / 16

Results Dynamics of individual neurons were able to forecast/predict the spontaneous global burst. 1 1 0.9 0.9 0.8 0.8 0.7 0.7 0.6 0.6 b 1 (t) x 1 (t) 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 0 0.2 0.4 0.6 0.8 1 b(t) x(t) Neurodynamics Final Project December 8, 2017 12 / 16

Results Dynamics of individual neurons were able to forecast/predict the spontaneous global burst. 1 1 0.9 0.9 0.8 0.8 0.7 0.7 0.6 0.6 b 1 (t) x 1 (t) 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 0 0.2 0.4 0.6 0.8 1 b(t) x(t) Neurodynamics Final Project December 8, 2017 12 / 16

Results Dynamics of individual neurons were able to forecast/predict the spontaneous global burst. 1 1 0.9 0.9 0.8 0.8 0.7 0.7 0.6 0.6 b 1 (t) x 1 (t) 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 0 0.2 0.4 0.6 0.8 1 b(t) x(t) Neurodynamics Final Project December 8, 2017 12 / 16

Results Single Neuron Dynamics Forecast Mean Population Dynamics Forecast 1 1 0.9 0.9 0.8 0.8 0.7 0.7 0.6 0.6 b 1 (t) b 1 (t) 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.2 0.1 0.1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 b(t) b(t) Neurodynamics Final Project December 8, 2017 13 / 16

Outline Background 1 Methods 2 Results 3 Summary 4 Neurodynamics Final Project December 8, 2017 14 / 16

Summary Main findings of Tajima et al. were also observed in a network of Izhikevich neurons Future work: Investigate the synaptic connectivity and strength of “good predictor” neurons Investigate the effects of sparsity and E/I balance on predictability Investigate the effects of synaptic strength on predictability Neurodynamics Final Project December 8, 2017 15 / 16

Acknowledgement Gerald Pao, MD, PhD Neurodynamics Final Project December 8, 2017 16 / 16

Acknowledgement Gerald Pao, MD, PhD Any questions? Neurodynamics Final Project December 8, 2017 16 / 16