Abstract
Everyday, we encounter situations where available choices are nearly equally rewarding (high conflict) calling for some tough decision making. Experimental recordings showed that the activity of Sub Thalamic Nucleus (STN) increases during such situations providing the extra time needed to make the right decision, teasing apart the most rewarding choice from the runner up closely trailing behind. This prolonged deliberation necessary for decision making under high conflict was absent in Parkinson's disease (PD) patients who underwent Deep Brain Stimulation (DBS) surgery of STN. In an attempt to understand the underlying cause of such adverse response, we built a 2D spiking network model (50 × 50 lattice) of Basal ganglia incorporating the key nuclei. Using the model we studied the Probabilistic learning task (PLT) in untreated, treated (L-Dopa and Dopamine Agonist) and STN-DBS PD conditions. Based on the experimental observation that dopaminergic activity is analogous to temporal difference (TD) and induces cortico-striatal plasticity, we introduced learning in the cortico-striatal weights. The results show that healthy and untreated conditions of PD model were able to more or less equally select (avoid) the rewarding (punitive) choice, a behavior that was absent in treated PD condition. The time taken to select a choice in high conflict trials was high in normal condition, which is in agreement with experimental results. The treated PD (Dopamine Agonist) patients made impulsive decisions (small reaction time) which in turn led to poor performance. The underlying cause of the observed impulsivity in DBS patients was studied in the model by (1) varying the electrode position within STN, (2) causing antidromic activation of GPe neurons. The effect of electrode position on reaction time was analyzed by studying the activity of STN neurons where, a decrease in STN neural activity was observed for certain electrode positions. We also observed that a higher antidromic activation of GPe neurons does not impact the learning ability but decreases reaction time as reported in DBS patients. These results suggest a probable role of electrode and antidromic activation in modulating the STN activity and eventually affecting the patient's performance on PLT.
Highlights
Parkinson’s disease (PD) is a neurodegenerative disorder known to be caused due to the death of dopaminergic neurons in the mid-brain structure called Substantia Nigra pars compacta (SNc) (Obeso et al, 2008) of Basal Ganglia (BG)
Though stimulation to the Sub Thalamic Nucleus (STN) of BG is widely followed as the gold standard for PD (Garcia et al, 2005) due to its effectiveness in alleviating the motor symptoms, various experimental studies show a controversial effect of Deep Brain Stimulation (DBS) on cognition (Jahanshahi et al, 2000) on impulsivity (Frank et al, 2007; Smeding et al, 2009; Brittain et al, 2012)
Using the same computational BG model (Mandali et al, 2015), we study the effect of DBS parameters on performance in Probabilistic learning task (PLT) in terms of accuracy and reaction time (RT)
Summary
Parkinson’s disease (PD) is a neurodegenerative disorder known to be caused due to the death of dopaminergic neurons in the mid-brain structure called Substantia Nigra pars compacta (SNc) (Obeso et al, 2008) of Basal Ganglia (BG). It has been observed that the “ON” time (where the medication is effective in relieving the symptoms) decreases as the disease progresses and 80% of the patients develop L-DOPA induced dyskinesias as a side effect (Schrag and Quinn, 2000). Under these circumstances, surgical intervention through Deep Brain Stimulation (DBS) is advised as an alternative treatment wherein an electrode is implanted and external stimulation is given to one or more nuclei of the brain. Though stimulation to the Sub Thalamic Nucleus (STN) of BG is widely followed as the gold standard for PD (Garcia et al, 2005) due to its effectiveness in alleviating the motor symptoms, various experimental studies show a controversial effect of DBS on cognition (Jahanshahi et al, 2000) on impulsivity (Frank et al, 2007; Smeding et al, 2009; Brittain et al, 2012)
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