Jan Morén

EMOTIONAL LEARNING: A COMPUTATIONAL MODEL OF THE AMYGDALA

We describe work in progress with the aim of constructing a computational model of emotional learning and processing inspired by neurophysiological findings. The main brain areas modeled are the amygdala and the orbitofrontal cortex and the interaction between them. We want to show that (1) there exists enough physiological data to suggest the overall architecture of a computational model, (2) emotion plays a clear role in learning the behavior. We review neurophysiological data and present a computational model that is subsequently tested in simulation.

Ikaros: Building cognitive models for robots

The Ikaros project started in 2001 with the aim of developing an open infrastructure for system-level brain modeling. The system has developed into a general tool for cognitive modeling as well as robot control. Here we describe the main parts of the Ikaros system and how it has been used to implement various cognitive systems and to control a number of different robots ranging from robot arms and hands to active vision systems and mobile robots.

Behavioural Strategies in Web Interaction: A View from Eye-movement Research

Publisher Summary The use of eye tracking has revealed some interesting facts about how users interact with web pages. The interaction between the user and the web page is highly user-driven. Because they are aware of where the Internet ads (banners) are located, they know the way to avoid them, using active-avoidance strategies, which seem to be a result of conditioning. The condition of not looking at the Internet ads while surfing may also be transferred to a new context. The learned inhibition against looking at web advertising is thus both more general and less domain specific than previously assumed. Both the communicative value and the immediate behavioral responses of the Internet users can be measured using eye-tracking methods. Eye tracking has proved to be a powerful tool in evaluating the interaction between a user and a web site because it allows simultaneous recording of attention and behavior.

The Mechanism of Saccade Motor Pattern Generation Investigated by a Large-Scale Spiking Neuron Model of the Superior Colliculus

The subcortical saccade-generating system consists of the retina, superior colliculus, cerebellum and brainstem motoneuron areas. The superior colliculus is the site of sensory-motor convergence within this basic visuomotor loop preserved throughout the vertebrates. While the system has been extensively studied, there are still several outstanding questions regarding how and where the saccade eye movement profile is generated and the contribution of respective parts within this system. Here we construct a spiking neuron model of the whole intermediate layer of the superior colliculus based on the latest anatomy and physiology data. The model consists of conductance-based spiking neurons with quasi-visual, burst, buildup, local inhibitory, and deep layer inhibitory neurons. The visual input is given from the superficial superior colliculus and the burst neurons send the output to the brainstem oculomotor nuclei. Gating input from the basal ganglia and an integral feedback from the reticular formation are also included. We implement the model in the NEST simulator and show that the activity profile of bursting neurons can be reproduced by a combination of NMDA-type and cholinergic excitatory synaptic inputs and integrative inhibitory feedback. The model shows that the spreading neural activity observed in vivo can keep track of the collicular output over time and reset the system at the end of a saccade through activation of deep layer inhibitory neurons. We identify the model parameters according to neural recording data and show that the resulting model recreates the saccade size-velocity curves known as the saccadic main sequence in behavioral studies. The present model is consistent with theories that the superior colliculus takes a principal role in generating the temporal profiles of saccadic eye movements, rather than just specifying the end points of eye movements.

Toward a spiking-neuron model of the oculomotor system

We present a physiologically plausible spiking neuron-level model of the superior colliculus as part of the saccade-generating visual system. Two major features of the area are the bursting behavior of its output neurons that drive eye movements, and the spreading neuron activation in the intermediate layer during a saccade. We show that the bursting activity profile that drives the main sequence behavior of saccadic eye movements can be generated by a combination of NMDA and cholinergic receptors driven by a local circuit. We also show how the long-range spreading activation can occur, and propose that the functional role for this mechanism is to track the general activity level and trigger a system-wide reset at the end of a saccade.

Behavioural Strategies in Web Interaction

Publisher Summary The use of eye tracking has revealed some interesting facts about how users interact with web pages. The interaction between the user and the web page is highly user-driven. Because they are aware of where the Internet ads (banners) are located, they know the way to avoid them, using active-avoidance strategies, which seem to be a result of conditioning. The condition of not looking at the Internet ads while surfing may also be transferred to a new context. The learned inhibition against looking at web advertising is thus both more general and less domain specific than previously assumed. Both the communicative value and the immediate behavioral responses of the Internet users can be measured using eye-tracking methods. Eye tracking has proved to be a powerful tool in evaluating the interaction between a user and a web site because it allows simultaneous recording of attention and behavior.

Chapter 28 – Behavioural Strategies in Web Interaction: A View from Eye-movement Research

Publisher Summary The use of eye tracking has revealed some interesting facts about how users interact with web pages. The interaction between the user and the web page is highly user-driven. Because they are aware of where the Internet ads (banners) are located, they know the way to avoid them, using active-avoidance strategies, which seem to be a result of conditioning. The condition of not looking at the Internet ads while surfing may also be transferred to a new context. The learned inhibition against looking at web advertising is thus both more general and less domain specific than previously assumed. Both the communicative value and the immediate behavioral responses of the Internet users can be measured using eye-tracking methods. Eye tracking has proved to be a powerful tool in evaluating the interaction between a user and a web site because it allows simultaneous recording of attention and behavior.