Observational learning has been investigated in monkeys mainly using conspecifics or humans as models to observe. Some studies attempted to clarify the social agent's role and to test whether ...non-human primates could learn from observation of a non-social agent, usually mentioned as a 'ghost display' condition, but they reported conflicting results. To address this question, we trained three rhesus monkeys in an object-in-place task consisting of the presentation of five subsequent problems composed of two objects, one rewarded and one unrewarded, for six times, or runs. Three types of learning conditions were tested. In the individual learning condition, the monkeys performed the first run, learned from it and improved their performance in the following runs. In the social and non-social learning conditions, they observed respectively a human model and a computer performing the first run and learned by the observation of their successes or errors. In all three conditions, the monkeys themselves received the reward after correct choices only. One-trial learning occurred in all three conditions. The monkeys performed over chance in the second run in all conditions, providing evidence of non-social observational learning with differential reward in macaque monkeys using a "ghost display" condition in a cognitive task.
Recent studies have shown that temporal stability of the neuronal activity over time can be estimated by the structure of the spike-count autocorrelation of neuronal populations. This estimation, ...called the intrinsic timescale, has been computed for several cortical areas and can be used to propose a cortical hierarchy reflecting a scale of temporal receptive windows between areas. In this study, we performed an autocorrelation analysis on neuronal populations of three basal ganglia (BG) nuclei, including the striatum and the subthalamic nucleus (STN), the input structures of the BG, and the external globus pallidus (GPe). The analysis was performed during the baseline period of a motivational visuomotor task in which monkeys had to apply different amounts of force to receive different amounts of reward. We found that the striatum and the STN have longer intrinsic timescales than the GPe. Moreover, our results allow for the placement of these subcortical structures within the already-defined scale of cortical temporal receptive windows. Estimates of intrinsic timescales are important in adding further constraints in the development of computational models of the complex dynamics among these nuclei and throughout cortico-BG-thalamo-cortical loops.
A standard view in the literature is that decisions are the result of a process that accumulates evidence in favor of each alternative until such accumulation reaches a threshold and a decision is ...made. However, this view has been recently questioned by an alternative proposal that suggests that, instead of accumulated, evidence is combined with an urgency signal. Both theories have been mathematically formalized and supported by a variety of decision-making tasks with constant information. However, recently, tasks with changing information have shown to be more effective to study the dynamics of decision making. Recent research using one of such tasks, the tokens task, has shown that decisions are better described by an urgency mechanism than by an accumulation one. However, the results of that study could depend on a task where all fundamental information was noiseless and always present, favoring a mechanism of non-integration, such as the urgency one. Here, we wanted to address whether the same conclusions were also supported by an experimental paradigm in which sensory evidence was removed shortly after it was provided, making working memory necessary to properly perform the task. Here, we show that, under such condition, participants' behavior could be explained by an urgency-gating mechanism that low-pass filters the mnemonic information and combines it with an urgency signal that grows with time but not by an accumulation process that integrates the same mnemonic information. Thus, our study supports the idea that, under certain situations with dynamic sensory information, decisions are better explained by an urgency-gating mechanism than by an accumulation one.
The influence of recent decisions on future goal selection Genovesio, Aldo; Ferraina, Stefano
Philosophical transactions of the Royal Society of London. Series B. Biological sciences,
11/2014, Letnik:
369, Številka:
1655
Journal Article
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Recent decisions about actions and goals can have effects on future choices. Several studies have shown an effect of the previous trial history on neural activity in a subsequent trial. Often, but ...not always, these effects originate from task requirements that make it necessary to maintain access to previous trial information to make future decisions. Maintaining the information about recent decisions and their outcomes can play an important role in both adapting to new contingencies and learning. Previous goal decisions must be distinguished from goals that are currently being planned to avoid perseveration or more general errors. Output monitoring is probably based on this separation of accomplished past goals from pending future goals that are being pursued. Behaviourally, it has been shown that the history context can influence the location, error rate and latency of successive responses. We will review the neurophysiological studies in the literature, including data from our laboratory, which support a role for the frontal lobe in tracking previous goal selections and outputs when new goals need to be accomplished.
In previous reports, we described neuronal activity in the polar (PFp), dorsolateral (PFdl), and orbital (PFo) PFC as monkeys performed a cued strategy task with two spatial goals. On each trial, a ...cue instructed one of two strategies: Stay with the previous goal or shift to the alternative. A delay period followed each cue, and feedback followed each choice, also at a delay. Our initial analysis showed that the mean firing rate of a population of PFp cells encoded the goal chosen on a trial, but only near the time of feedback, not earlier in the trial. In contrast, PFdl cells encoded goals and strategies during the cue and delay periods, and PFo cells encoded strategies in those task periods. Both areas also signaled goals near feedback time. Here we analyzed trial-to-trial variability of neuronal firing, as measured by the Fano factor (FF): the ratio of variance to the mean. Goal-selective PFp neurons had two properties: (1) a lower FF from the beginning of the trial compared with PFp cells that did not encode goals and (2) a weak but significant inverse correlation between FF throughout a trial and the degree of goal selectivity at feedback time. Cells in PFdl and PFo showed neither of these properties. Our findings indicate that goal-selective PFp neurons were engaged in the task throughout a trial, although they only encoded goals near feedback time. Their lower FF could improve the ability of other cortical areas to decode its selected-goal signal.
The prefrontal cortex maintains information in memory through static or dynamic population codes depending on task demands, but whether the population coding schemes used are learning-dependent and ...differ between cell types is currently unknown. We investigate the population coding properties and temporal stability of neurons recorded from male macaques in two mapping tasks during and after stimulus-response associative learning, and then we use a Strategy task with the same stimuli and responses as control. We identify a heterogeneous population coding for stimuli, responses, and novel associations: static for putative pyramidal cells and dynamic for putative interneurons that show the strongest selectivity for all the variables. The population coding of learned associations shows overall the highest stability driven by cell types, with interneurons changing from dynamic to static coding after successful learning. The results support that prefrontal microcircuitry expresses mixed population coding governed by cell types and changes its stability during associative learning.
In neurophysiology, nonhuman primates represent an important model for studying the brain. Typically, monkeys are moved from their home cage to an experimental room daily, where they sit in a primate ...chair and interact with electronic devices. Refining this procedure would make the researchers' work easier and improve the animals' welfare. To address this issue, we used home-cage training to train two macaque monkeys in a non-match-to-goal task, where each trial required a switch from the choice made in the previous trial to obtain a reward. The monkeys were tested in two versions of the task, one in which they acted as the agent in every trial and one in which some trials were completed by a "ghost agent". We evaluated their involvement in terms of their performance and their interaction with the apparatus. Both monkeys were able to maintain a constant involvement in the task with good, stable performance within sessions in both versions of the task. Our study confirms the feasibility of home-cage training and demonstrates that even with challenging tasks, monkeys can complete a large number of trials at a high performance level, which is a prerequisite for electrophysiological studies of monkey behavior.
Predicting the behavior of others is a fundamental skill in primate social life. We tested the role of medial frontal cortex in the prediction of other agents' behavior in two male macaques, using a ...monkey-human interactive task in which their actor-observer roles were intermixed. In every trial, the observer monitored the actor's choice to reject it for a different one when he became the actor on the subsequent trial. In the delay period preceding the action, we identified neurons modulated by the agent's identity, as well as a group of neurons encoding the agent's future choice, some of which were neurons that showed differential patterns of activity between agents. The ability of these neurons to flexibly move from 'self-oriented' to 'other-oriented' representations could correspond to the "other side of the coin" of the simulative mirroring activity. Neurons that changed coding scheme, together with neurons exclusively involved in the prediction of the other agent's choice, show a neural substrate for predicting or anticipating others' choices beyond simulation.
Cortical activity related to erroneous behavior in discrimination or decision-making tasks is rarely analyzed, yet it can help clarify which computations are essential during a specific task. Here, ...we use a hidden Markov model (HMM) to perform a trial-by-trial analysis of the ensemble activity of dorsolateral prefrontal cortex (PFdl) neurons of rhesus monkeys performing a distance discrimination task. By segmenting the neural activity into sequences of metastable states, HMM allows us to uncover modulations of the neural dynamics related to internal computations. We find that metastable dynamics slow down during error trials, while state transitions at a pivotal point during the trial take longer in difficult correct trials. Both these phenomena occur during the decision interval, with errors occurring in both easy and difficult trials. Our results provide further support for the emerging role of metastable cortical dynamics in mediating complex cognitive functions and behavior.
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•Prefrontal activity in monkeys performing a distance discrimination task is metastable•Duration of metastable states is longer before errors•Latency of state transition is longer in correct difficult trials•States may code for relative distance based on stimulus features or presentation order
Benozzo et al. analyze the neural activity in the prefrontal cortex of rhesus monkeys performing a distance discrimination task. The neural activity is a sequence of metastable states. State durations are longer before errors and at the beginning of the deliberation period in trials characterized by correct difficult discriminations.
We have previously shown how the Frontal Pole cortex (FPC) neurons play a unique role in both the monitoring and evaluating of self-generated decisions during feedback in a visually cued strategy ...task. For each trial of this task, a cue instructed one of two strategies: to either stay with the previous goal or shift to the alternative goal. Each cue was followed by a delay period, then each choice was followed by a feedback. FPC neurons show goal-selective activity exclusively during the feedback period. Here, we studied how neural correlation dynamically changes, along with a trial in FPC. We classified the cells as goal-selective and not goal-selective (NS) and analyzed the time-course of the cross-correlations in 76 pairs of neurons from each group. We compared a control epoch with the feedback epoch and we found higher correlations in the latter one between goal-selective neurons than between NS neurons, in which the correlated activity dropped during feedback. This supports the involvement of goal-selective cells in the evaluation of self-generated decisions at the feedback time. We also observed a dynamic change of the correlations in time, indicating that the connections among cell-assemblies were transient, changing between internal states at the feedback time. These results indicate that the changing of the pattern of neural correlations can underlie the flexibility of the prefrontal computations.
•Goal selective cells correlate at feedback time but not during the delay more than non-selective cells.•Neural correlations of the goal selective cells change dynamically across time.•Reduction in correlation between non-selective cells may enhance the transmission of goal selective signals at feedback time.
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