220 likes | 1.94k Views
Effects of Excitatory and Inhibitory Potentials on Action Potentials. Amelia Lindgren. Overview of A Neuron. Found in brain, spinal cord and nervous system Electrically excitable Communicate via electrical and chemical synapses Made up of a soma (cell body), dendritic tree and an axon.
E N D
Effects of Excitatory and Inhibitory Potentials on Action Potentials Amelia Lindgren
Overview of A Neuron • Found in brain, spinal cord and nervous system • Electrically excitable • Communicate via electrical and chemical synapses • Made up of a soma (cell body), dendritic tree and an axon
Axon Properties • Where action potential is propagated • Contains voltage gated sodium and potassium channels • Contains leak channels (Cl- channels and passive K+ channels) • Resting membrane potential: ~ -67 mV
Action Potential • Occurs when membrane potential exceeds the threshold potential • Occurs when Na+ channels are activated (influx of Na+) • Causes positive slope of action potential • K+ channels open slightly later (efflux of K+) • Causes downward slope of action potential
Action Potential Cont. • To achieve an action potential • Pre-synaptic cell action potential releases Ca2+ in the axon terminal • Axon terminal releases vesicles filled with neurotransmitters • Inhibit or help create an action potential • Excitatory Neurotransmitters: • Acetylcholine • glutamate • Inhibitory Neurotransmitters: • GABA • glycine
Excitatory Post Synaptic Potentials (EPSP) Creates positive synaptic potential Positive charged ions flow in Allows Na+ into cell Easier for Action Potential to fire Inhibitory Post Synaptic Potentials (IPSP) Decreases the potential of the membrane Increases permeability of K+ K+ flows out of cell Decreases the chances of an action potential Post Synaptic Potentials
Temporal Summation One neuron acting on another Potential starts before the previous one ends Amplitudes of potentials summate to create larger potential Spatial Summation Multiple cells provide input Input is received in different areas Input is summated to create a larger potential Ways to Achieve Action Potential
αm=0.1(25-v)/ (e(25-v)/10 -1) αh= 0.07e-v/20 αn= 0.01(10-v)/(e(10-v)/10 -1) βm= 4e-v/18 βh=1/(e(30-v)/10 +1) βn=0.125e-v/80 gNa=120 gK=36 gL=0.3 vNa=115 vK=-12 vL=10.6 Parameters of Neuron
Stimulation of 9 μA Key: ▀ = membrane potential (mV) ▀= stimulus current (μA) ▀=m(v) ▀= n(v) ▀ =h(v)
Stimulation of 5 μA Key: ▀ = membrane potential (mV) ▀= stimulus current (μA) ▀=m(v) ▀= n(v) ▀ =h(v)
Stimulation of 3.7 μA Key: ▀ = membrane potential (mV) ▀= stimulus current (μA) ▀=m(v) ▀= n(v) ▀ =h(v)
Stimulation of 3.6 μA Key: ▀ = membrane potential (mV) ▀= stimulus current (μA) ▀=m(v) ▀= n(v) ▀ =h(v)
Threshold potential • At 3.7 μA an action potential occurs • at 3.6 μA one does not • threshold value is in between • Threshold potential is typically around -55mV
Successive Stimulations of 6 μA at t=0 ms and t=10 Key: ▀ = membrane potential (mV) ▀= stimulus current (μA) ▀=m(v) ▀= n(v) ▀ =h(v)
Sequential Stimulation of 6 μA at t=5 ms and 7 μA at t=10 ms Key: ▀ = membrane potential (mV) ▀= stimulus current (μA) ▀=m(v) ▀= n(v) ▀ =h(v)
Temporal Summation Stimulation of 2.5 μA at t=0 ms and 2.5 μA at t= .6ms Key: ▀ = membrane potential (mV) ▀= stimulus current (μA) ▀=m(v) ▀= n(v) ▀ =h(v)
Temporal Stimulation of 2 μA and 1 μA Key: ▀ = membrane potential (mV) ▀= stimulus current (μA) ▀=m(v) ▀= n(v) ▀ =h(v)
Spatial Summation Stimulation of 8 μA and -3 μA Key: ▀ = membrane potential (mV) ▀= stimulus current (μA) ▀=m(v) ▀= n(v) ▀ =h(v)
Spatial Summation of Stimulation of 5 μA and -4 μA Key: ▀ = membrane potential (mV) ▀= stimulus current (μA) ▀=m(v) ▀= n(v) ▀ =h(v)
Observations • Increasing the intensity does not increase the size of the action potential • Action potential is “all or none” response • Potentials can summate to elicit or inhibit and action potential • Must reach a specific threshold potential to create and action potential that will be propagated
Conclusion • Many different ways to elicit an action potential or to inhibit one • Temporal and Spatial Summation allow for greater complexity in neural networks • This allows for greater complexity in organisms • neuron can communicate with multiple neurons > greater efficiency.