Involvement of Basal Ganglia Network in Motor Disabilities Induced by Typical Antipsychotics

BACKGROUND:Clinical treatments with typical antipsychotic drugs (APDs) are accompanied by extrapyramidal motor side-effects (EPS) such as hypokinesia and catalepsy. As little is known about electrophysiological substrates of such motor disturbances, we investigated the effects of a typical APD, alpha-flupentixol, on the motor behavior and the neuronal activity of the whole basal ganglia nuclei in the rat. METHODS AND FINDINGS:The motor behavior was examined by the open field actimeter and the neuronal activity of basal ganglia nuclei was investigated using extracellular single unit recordings on urethane anesthetized rats. We show that alpha-flupentixol induced EPS paralleled by a decrease in the firing rate and a disorganization of the firing pattern in both substantia nigra pars reticulata (SNr) and subthalamic nucleus (STN). Furthermore, alpha-flupentixol induced an increase in the firing rate of globus pallidus (GP) neurons. In the striatum, we recorded two populations of medium spiny neurons (MSNs) after their antidromic identification. At basal level, both striato-pallidal and striato-nigral MSNs were found to be unaffected by alpha-flupentixol. However, during electrical cortico-striatal activation only striato-pallidal, but not striato-nigral, MSNs were found to be inhibited by alpha-flupentixol. Together, our results suggest that the changes in STN and SNr neuronal activity are a consequence of increased neuronal activity of globus pallidus (GP). Indeed, after selective GP lesion, alpha-flupentixol failed to induce EPS and to alter STN neuronal activity. CONCLUSION:Our study reports strong evidence to show that hypokinesia and catalepsy induced by alpha-flupentixol are triggered by dramatic changes occurring in basal ganglia network. We provide new insight into the key role of GP in the pathophysiology of APD-induced EPS suggesting that the GP can be considered as a potential target for the treatment of EPS

The neural bases of decision learning in the basal ganglia : an electrophysiological and behavioral approach in the non-human primate

Une question fondamentale en neuroscience, ainsi que dans de nombreuses disciplines s’intéressant à la compréhension du comportement, telles que la psychologie, l’Economie, et la sociologie, concerne les processus décisionnels par lesquels les animaux et les humains sélectionnent des actions renforcées positivement ou négativement. Les processus décisionnels ainsi que leur base neuronale demeurent mal compris. D’autre part de nombreuses études ont révélé que les humains ainsi que les animaux prennent souvent des décisions sous-optimales. Notre principal objectif a été de comprendre la raison de ces comportements sous-optimaux. Par ailleurs, l’altération des processus sous-tendant la prise de décision, entraîne des pathologies. La compréhension des mécanismes décisionnels est essentielle au développement de stratégies de traitements plus efficaces. Dans cette étude nous avons proposé une nouvelle approche de l’étude des comportements décisionnels, basée sur l’hétérogénéité des préférences créées au cours de l’apprentissage du choix. Puis nous avons corrélé l’activité du putamen et du globus pallidus interne aux comportements préalablement décrits. Nos résultats montrent que bien que les primates apprennent à identifier la meilleure option et convergent vers une stratégie optimale dans un nombre important de sessions, ils n’arrivent pas en moyenne à optimiser leur comportement. Nous avons montré que ce comportement suboptimal des primates est caractérisé par la création de préférences irrationnelles par ces derniers pour des paramètres non pertinents de l’environnement. Nous avons finalement montré que bien qu’un faible nombre de neurones du putamen encode la valeur de l’action, leur contribution à l’activité de population est faible. L’activité du putamen reflète les futures performances des primates et prédit donc la formation des comportements irrationnels et rationnels.A fundamental question in neuroscience, as well as in various fields such as economics, psychology and sociology, concerns the decision making processes by which animals and humans select actions based on reward and punishment. Both decision making processes and their neural basis are still poorly understood. Also, both human and animals often make suboptimal decisions in many tasks studied. Our first aim is to improve the understanding of why such sub-optimal decisions are made. Also, the alteration of decision making processes causes diseases, the understanding of whose mechanisms is essential in developing better treatment strategies. In this report, we propose a new approach which consists in extracting the neural substrates of choice behavior heterogeneity in between sessions. Our results show that although primates learn on average to identify the best option and converge to an optimal policy in a consequent number of sessions, they fail on average to optimize their behavior. We revealed that this suboptimal behavior was characterized by an unexpected high behavioral heterogeneity during the task that was due to the creation of irrelevant preferences by the monkeys. We finally show that although a few neurons of the putamen encode the action value, their contribution to the overall population activity is weak. Putamen activity rather reflects the futures performances and predicts the creation of rational and irrational behaviors

The neural bases of decision learning in the basal ganglia : an electrophysiological and behavioral approach in the non-human primate

Une question fondamentale en neuroscience, ainsi que dans de nombreuses disciplines s’intéressant à la compréhension du comportement, telles que la psychologie, l’Economie, et la sociologie, concerne les processus décisionnels par lesquels les animaux et les humains sélectionnent des actions renforcées positivement ou négativement. Les processus décisionnels ainsi que leur base neuronale demeurent mal compris. D’autre part de nombreuses études ont révélé que les humains ainsi que les animaux prennent souvent des décisions sous-optimales. Notre principal objectif a été de comprendre la raison de ces comportements sous-optimaux. Par ailleurs, l’altération des processus sous-tendant la prise de décision, entraîne des pathologies. La compréhension des mécanismes décisionnels est essentielle au développement de stratégies de traitements plus efficaces. Dans cette étude nous avons proposé une nouvelle approche de l’étude des comportements décisionnels, basée sur l’hétérogénéité des préférences créées au cours de l’apprentissage du choix. Puis nous avons corrélé l’activité du putamen et du globus pallidus interne aux comportements préalablement décrits. Nos résultats montrent que bien que les primates apprennent à identifier la meilleure option et convergent vers une stratégie optimale dans un nombre important de sessions, ils n’arrivent pas en moyenne à optimiser leur comportement. Nous avons montré que ce comportement suboptimal des primates est caractérisé par la création de préférences irrationnelles par ces derniers pour des paramètres non pertinents de l’environnement. Nous avons finalement montré que bien qu’un faible nombre de neurones du putamen encode la valeur de l’action, leur contribution à l’activité de population est faible. L’activité du putamen reflète les futures performances des primates et prédit donc la formation des comportements irrationnels et rationnels.A fundamental question in neuroscience, as well as in various fields such as economics, psychology and sociology, concerns the decision making processes by which animals and humans select actions based on reward and punishment. Both decision making processes and their neural basis are still poorly understood. Also, both human and animals often make suboptimal decisions in many tasks studied. Our first aim is to improve the understanding of why such sub-optimal decisions are made. Also, the alteration of decision making processes causes diseases, the understanding of whose mechanisms is essential in developing better treatment strategies. In this report, we propose a new approach which consists in extracting the neural substrates of choice behavior heterogeneity in between sessions. Our results show that although primates learn on average to identify the best option and converge to an optimal policy in a consequent number of sessions, they fail on average to optimize their behavior. We revealed that this suboptimal behavior was characterized by an unexpected high behavioral heterogeneity during the task that was due to the creation of irrelevant preferences by the monkeys. We finally show that although a few neurons of the putamen encode the action value, their contribution to the overall population activity is weak. Putamen activity rather reflects the futures performances and predicts the creation of rational and irrational behaviors

Neural activity at Single cell level.

<p>Perievent rasters and perievent histograms for an example (<b>A</b>) L-Neuron, B) F-Neuron, C) IP-Neuron and D) R-Neuron. The perievent rasters and perievent histograms are aligned either at the start of the trials or at cue onset, separately for trials in which most rewarding (dark blue) and less rewarding (light blue) cue was chosen. (<b>B</b>) Stacked bar charts of the distribution of the recorded neurons.</p

Complex Population Response of Dorsal Putamen Neurons Predicts the Ability to Learn

<div><p>Day-to-day variability in performance is a common experience. We investigated its neural correlate by studying learning behavior of monkeys in a two-alternative forced choice task, the two-armed bandit task. We found substantial session-to-session variability in the monkeys’ learning behavior. Recording the activity of single dorsal putamen neurons we uncovered a dual function of this structure. It has been previously shown that a population of neurons in the DLP exhibits firing activity sensitive to the reward value of chosen actions. Here, we identify putative medium spiny neurons in the dorsal putamen that are cue-selective and whose activity builds up with learning. Remarkably we show that session-to-session changes in the <i>size</i> of this population and in the intensity with which this population encodes cue-selectivity is correlated with session-to-session changes in the <i>ability</i> to learn the task. Moreover, at the population level, dorsal putamen activity in the very <i>beginning</i> of the session is correlated with the performance at the <i>end</i> of the session, thus predicting whether the monkey will have a "good" or "bad" learning day. These results provide important insights on the neural basis of inter-temporal performance variability.</p> </div

Reconstruction of the recording sites.

<p>The dots show the estimate locations of the electrodes tip during recording sessions (scale in mm). The recording sites of monkey 1 and 2 have been pooled. The colored areas correspond to the sensorimotor territories of the putamen identified in Takada et al[28]. <i>CMAd: dorsal </i><i>cingulated </i><i>motor </i><i>area, CMAr: rostral </i><i>cingulated </i><i>motor </i><i>area, pre-SMA: pre-supplementary </i><i>motor </i><i>area, M1: primary </i><i>motor </i><i>cortex, SMA: supplementary </i><i>motor </i><i>area</i>.</p

The task.

<p>In each trial, two cues were displayed simultaneously in two out of four randomly chosen possible positions on the screen. The monkey signaled its choice by moving the cursor to one of the cues and was rewarded by 300 μl of fruit juice with a predefined fixed probability that depended on the choice. We used 3 different pairs of reward probabilities for the two cues: (0.9 vs. 0.6), (0.75 vs. 0.25) and (0.67 vs. 0.33). Top right shows example combinations of displayed cues during different sessions.</p

Characterization of cell subtypes.

<p>(<b>A</b>) Filtered signal obtained from extracellular recording of a dorsal putamen neuron amplified with a gain of 10³ (bandpass filter 300 Hz-6 KHz). (<b>B</b>) The parameters of mean waveforms for each neuron were plotted against each other, revealing three clusters. After spike sorting, the width of each phase of each spike was calculated. Spikes were then clustered using three parameters related to the length of the waveform: the length of the total negative deflections (Peak length), the length of the valley, and the sum of these two parameters (Total length). (<b>C</b>) Distribution of the waveform’s total length for the each type of neurons; color codes are as above. (<b>D</b>) Distribution of the firing rate of the neurons; color codes are as above. E, Population firing rate for the three cell subtypes. The firing rate of the interneurons was significantly higher than that of the MSNs. F, Distribution of the coefficient of variation (CV) of the interspike intervals of the three types of neuron. The interspike intervals of the presumed MSNs tend to be more variable than that of the presumed interneuron types.</p

α-flupentixol alters the firing patterns of substantia nigra <i>pars reticulata</i> neurons.

<p>(A and B) Sections of extracellular recordings of action potentials, before and after injection respectively, showing that α-flupentixol reduced the firing rate and made the pattern irregular. (C and D) Interspike interval histograms, (E and F) density histograms, respectively before and after α-flupentixol injection confirming the disorganization of the firing pattern induced by α-flupentixol in the same neuron.</p