Talk: Using Phase Models to Understand Synaptic Integration in the Basal Ganglia
will give a talk with the title
"Using Phase Models to Understand Synaptic Integration in the Basal Ganglia"
Time: Tuesday, 26.06.12; 9:15 AM
Location: Freie Universität,
Takustr. 6,
seminar room 003
Abstract:
The basal ganglia are conventionally viewed as a pair of opponent feedforward pathways—the “direct” and “indirect” pathways. However, the basal ganglia contain several recurrent projections, most notably the reciprocal connections between the subthalamic nucleus and the external segment of the globus pallidus. Furthermore, many basal ganglia neurons are autonomously active, requiring no extrinsic input to fire, and exhibit complex physiological properties that shape their response to input. To understand the basal ganglia, we need models that are simple enough to shed light on the collective behavior of interconnected, autonomously oscillating neurons yet accurate enough to correctly represent their response to synaptic input. Phase models, where the state of the neuron is reduced to a single number (phase), offer one such approach. A neuron’s phase denotes the fraction of its oscillation cycle it has traversed, and synaptic inputs act by advancing or delaying the neuron's phase, thereby shortening or lengthening the time to the next spike. The response to a synaptic input depends on the phase at which the input arrives, and the function describing that relationship is called the phase response curve (PRC). Concentrating on the subthalamic nucleus, I measured PRCs with EPSPs and current injection, analyzed a biophysical model to understand how intrinsic conductances control the shape of the PRC, and assessed how well phase models represent the response of neurons to synaptic input. Subthalamic neurons are well described by phase models, and analysis of the biophysical basis of their PRCs illuminated the ways in which their intrinsic physiological properties shape their response to synaptic input.
The basal ganglia are conventionally viewed as a pair of opponent feedforward pathways—the “direct” and “indirect” pathways. However, the basal ganglia contain several recurrent projections, most notably the reciprocal connections between the subthalamic nucleus and the external segment of the globus pallidus. Furthermore, many basal ganglia neurons are autonomously active, requiring no extrinsic input to fire, and exhibit complex physiological properties that shape their response to input. To understand the basal ganglia, we need models that are simple enough to shed light on the collective behavior of interconnected, autonomously oscillating neurons yet accurate enough to correctly represent their response to synaptic input. Phase models, where the state of the neuron is reduced to a single number (phase), offer one such approach. A neuron’s phase denotes the fraction of its oscillation cycle it has traversed, and synaptic inputs act by advancing or delaying the neuron's phase, thereby shortening or lengthening the time to the next spike. The response to a synaptic input depends on the phase at which the input arrives, and the function describing that relationship is called the phase response curve (PRC). Concentrating on the subthalamic nucleus, I measured PRCs with EPSPs and current injection, analyzed a biophysical model to understand how intrinsic conductances control the shape of the PRC, and assessed how well phase models represent the response of neurons to synaptic input. Subthalamic neurons are well described by phase models, and analysis of the biophysical basis of their PRCs illuminated the ways in which their intrinsic physiological properties shape their response to synaptic input.