Derrik E. Asher

Simulation of how neuromodulation influences cooperative behavior

Neuromodulators can have a strong effect on how organisms cooperate and compete for resources. To better understand the effect of neuromodulation on cooperative behavior, a computational model of the dopaminergic and serotonergic systems was constructed and tested in games of conflict and cooperation. This neural model was based on the assumptions that dopaminergic activity increases as expected reward increases, and serotonergic activity increases as the expected cost of an action increases. The neural model guided the behavior of an agent that played a series of Hawk-Dove games against an opponent. The agent adapted its behavior appropriately to changes in environmental conditions and to changes in its opponents strategy. The neural agent tended to engage in Hawk-like behavior in low-risk situations and Dove-like behavior in high-risk situations. When the simulated dopaminergic activity was greater than the serotonergic activity, the agent tended to escalate a fight. These results suggest how the neuromodulatory systems shape decision-making and adaptive behavior in competitive and cooperative situations.

Effect of neuromodulation on performance in game playing: A modeling study

Neuromodulators can have a strong effect on how organisms learn and compete for resources. Neuromodulators, such as dopamine (DA) and serotonin (5-HT), are known to be important in predicting rewards, costs, and punishments. To better understand the effect of neuromodulation on decision-making, a computational model of the dopaminergic and serotonergic systems was constructed and tested in games of conflict. This neural model was based on the assumptions that dopaminergic activity increases as expected reward increases, and serotonergic activity increases as the expected cost of an action increases. Specifically, the neural model guided the learning of an agent that played a series of Hawk-Dove games against an opponent. The model responded appropriately to changes in environmental conditions or to changes in its opponents strategy. The neural agent became Dove-like in its behavior when its dopaminergic system was compromised, and became Hawk-like in its behavior when its serotonergic system was compromised. Our model suggests how neuromodulatory systems can shape decision-making and adaptive learning in competitive situations.

A dynamic, embodied paradigm to investigate the role of serotonin in decision-making

Serotonin (5-HT) is a neuromodulator that has been attributed to cost assessment and harm aversion. In this review, we look at the role 5-HT plays in making decisions when subjects are faced with potential harmful or costly outcomes. We review approaches for examining the serotonergic system in decision-making. We introduce our group’s paradigm used to investigate how 5-HT affects decision-making. In particular, our paradigm combines techniques from computational neuroscience, socioeconomic game theory, human–robot interaction, and Bayesian statistics. We will highlight key findings from our previous studies utilizing this paradigm, which helped expand our understanding of 5-HT’s effect on decision-making in relation to cost assessment. Lastly, we propose a cyclic multidisciplinary approach that may aid in addressing the complexity of exploring 5-HT and decision-making by iteratively updating our assumptions and models of the serotonergic system through exhaustive experimentation.

Social contracts and human-computer interaction with simulated adapting agents

Game theory is commonly used to study social behavior in cooperative or competitive situations. One socioeconomic game, Stag Hunt, involves the trade-off between social and individual benefit by offering the option to hunt a low-payoff hare alone or a high-payoff stag cooperatively. Stag Hunt encourages the creation of social contracts as a result of the payoff matrix, which favors cooperation. By playing Stag Hunt with set-strategy computer agents, the social component is degraded because of the inability of subjects to dynamically affect the outcomes of iterated games, as would be the case when playing against another subject. However, playing with an adapting agent has the potential to evoke unique and complex reactions in subjects because of its ability to change its own strategy based on its experience over time, both within and between games. In the present study, 40 subjects played the iterated Stag Hunt with five agents differing in strategy: exclusive hare hunting, exclusive stag hunting, random, Win-Stay-Lose-Shift, and adapting. The results indicated that the adapting agent caused subjects to spend more time and effort in each game, exhibiting a more complicated path to their destination. This suggests that adapting agents exhibit behavior similar to human opponents, evoking more natural social responses in subjects.

Evolution of biologically plausible neural networks performing a visually guided reaching task

An evolutionary strategy (ES) algorithm was utilized to evolve a simulated neural network based on the known anatomy of the posterior parietal cortex (PPC), to perform a visually guided reaching task. In this task, a target remained visible for the duration of a trial, and an agents goal was to move its hand to the target as rapidly as possible and remain for the duration of that trial. The ES was used to tune the strength of 15609 connections between neural areas and 4 parameters governing the neural dynamics. The model had sensory latencies replicating those found in recording studies with monkeys. The ES ran 100 times and generated very diverse networks that could all perform the task well. The evolved networks 1) showed velocity profiles consistent with biological movements, and 2) found solutions that reflect short-range excitation and long-range, contralateral inhibition similar to neurobiological networks. These results provide theoretical evidence for the important parameters and projections governing sensorimotor transformations in neural systems.

The importance of lateral connections in the parietal cortex for generating motor plans

Substantial evidence has highlighted the significant role of associative brain areas, such as the posterior parietal cortex (PPC) in transforming multimodal sensory information into motor plans. However, little is known about how different sensory information, which can have different delays or be absent, combines to produce a motor plan, such as executing a reaching movement. To address these issues, we constructed four biologically plausible network architectures to simulate PPC: 1) feedforward from sensory input to the PPC to a motor output area, 2) feedforward with the addition of an efference copy from the motor area, 3) feedforward with the addition of lateral or recurrent connectivity across PPC neurons, and 4) feedforward plus efference copy, and lateral connections. Using an evolutionary strategy, the connectivity of these network architectures was evolved to execute visually guided movements, where the target stimulus provided visual input for the entirety of each trial. The models were then tested on a memory guided motor task, where the visual target disappeared after a short duration. Sensory input to the neural networks had sensory delays consistent with results from monkey studies. We found that lateral connections within the PPC resulted in smoother movements and were necessary for accurate movements in the absence of visual input. The addition of lateral connections resulted in velocity profiles consistent with those observed in human and non-human primate visually guided studies of reaching, and allowed for smooth, rapid, and accurate movements under all conditions. In contrast, Feedforward or Feedback architectures were insufficient to overcome these challenges. Our results suggest that intrinsic lateral connections are critical for executing accurate, smooth motor plans.

Visual field mapping of visuomotor adaptation to prisms

Stratton (Psych. Rev., 1897) first described visuomotor adaptation to altered visual input by wearing inverting prism spectacles. A number of studies (e.g., Miyauchi et al., J. Physio., 2004) have tried to confirm his findings and further examine the question of how responses in visual cortex change during this adaptation process. There is evidence from these studies that changes occur in parieto-occipital cortex. Recently, several human visual field maps have been described in parietal cortex that are thought to be involved in visuomotor integration (Swisher et al., J. Neurosci., 2007). Here, we further investigate the adaptation of these cortical maps to an extreme alteration of visuomotor processing.

Hemispheric differences of color responses in human ventral visual cortex

INTRODUCTION. Human ventral occipito-temporal cortex (VOT) has been shown to contain several visual field maps involved in the color and shape processing pathways (Brewer et al., 2005; Arcaro and Kastner, 2007). Patient lesion studies indicate that there may be hemispheric differences in the pathways subserving color vision and word form recognition. Here we compare the organization of the color responses between hemispheres in human ventral visual cortex.