Ramping activity in the striatum

Abstract

Control of the timing of behavior is thought to require the basal ganglia (BG) and BG pathologies impair performance in timing tasks. Temporal interval discrimination depends on the ramping activity of medium spiny neurons (MSN) in the main BG input structure, the striatum, but the underlying mechanisms driving this activity are unclear. Here, we combine an MSN dynamical network model with an action selection system applied to an interval discrimination task. We find that when network parameters are appropriate for the striatum so that slowly fluctuating marginally stable dynamics are intrinsically generated, up and down ramping populations naturally emerge which enable significantly above chance task performance. We show that emergent population activity is in very good agreement with empirical studies and discuss how MSN network dysfunction in disease may alter temporal perception.

Pathological cell assembly dynamics in a striatal MSN network model

“…Here we take steps, using computational modeling, to try to understand how aberrant striatal cell assembly population dynamics relates to the complex array of underlying cellular and synaptic pathophysiologies found in PD and LID. In previous work (Ponzi and Wickens, 2008 , 2010 , 2012 , 2013 , 2022 ; Ponzi et al, 2020 ) we showed that an inhibitory MSN network could generate switching cell assembly activation patterns in good agreement with experimental studies (Carrillo-Reid et al, 2008 ), providing network parameters, in particular the strength and distribution of excitatory driving and the strength of recurrent inhibition between MSNs, was appropriate for the striatum. However when network parameters are altered away from their true striatal values, various types of pathological cell assembly dynamics can be found (Ponzi and Wickens, 2012 , 2022 ; Ponzi et al, 2020 ) including patterns resembling those found in 6OHDA and LID slices.…”

“…In previous work (Ponzi and Wickens, 2008 , 2010 , 2012 , 2013 , 2022 ; Ponzi et al, 2020 ) we showed that an inhibitory MSN network could generate switching cell assembly activation patterns in good agreement with experimental studies (Carrillo-Reid et al, 2008 ), providing network parameters, in particular the strength and distribution of excitatory driving and the strength of recurrent inhibition between MSNs, was appropriate for the striatum. However when network parameters are altered away from their true striatal values, various types of pathological cell assembly dynamics can be found (Ponzi and Wickens, 2012 , 2022 ; Ponzi et al, 2020 ) including patterns resembling those found in 6OHDA and LID slices. Here we quantitatively estimate computational network model parameters from empirical slice data using the deep learning framework, Simulation Based Inference (SBI).…”

“…To reproduce these dynamics we extended a previously published model of the striatal MSN network (Ponzi and Wickens, 2010 , 2013 , 2022 ; Ponzi et al, 2020 ) to include short-term plasticity between the MSNs. We used a well validated MSN cell model (Ponzi et al, 2020 ) with a full complement of ion-channels which has been shown to accurately reproduce characteristics of MSN spiking activity, such as the long delay to first spike ( Figure 2A ).…”

“…We investigated a 400 cell network and took the synaptic short-term plasticity and connectivity parameters from a recent detailed striatal connectome study (Hjorth et al, 2020 ; see Methods). We varied the two most important factors which are known to control network model cell assembly dynamics (Ponzi and Wickens, 2010 , 2012 , 2013 , 2022 ; Ponzi et al, 2020 ). These are the strength of recurrent inhibition between MSNs, here denoted G I , which controls the postsynaptic IPSP size when a presynaptic MSN spikes, and the MSN excitation level, here denoted G E .…”

Effects of caffeine on temporal perception in Rattus norvegicus

“…Medium spiny neurons (MSNs) are the principal neurons in the striatum. These neurons express both adenosine and dopamine receptors, and they are a key component of the basal ganglia and play a crucial role in regulating timing processes [39,40]. MSNs receive inputs from various cortical regions, including the prefrontal cortex (PFC), motor cortex, and sensory cortices.…”