The book of GENESIS (2nd ed.): exploring realistic neural models with the GEneral NEural SImulation System
Children and robots learning to play hide and seek
Proceedings of the 1st ACM SIGCHI/SIGART conference on Human-robot interaction
The NEURON Book
First steps toward natural human-like HRI
Autonomous Robots
Teachable robots: Understanding human teaching behavior to build more effective robot learners
Artificial Intelligence
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In the past three decades, the interest in trust has grown significantly due to its important role in our modern society. Everyday social experience involves ''confidence'' among people, which can be interpreted at the neurological level of a human brain. Recent studies suggest that oxytocin is a centrally-acting neurotransmitter important in the development and alteration of trust. Its administration in humans seems to increase trust and reduce fear, in part by directly inhibiting the amygdala. However, the cerebral microcircuitry underlying this mechanism is still unknown. We propose the first biologically realistic model for trust, simulating spiking neurons in the cortex in a real-time human-robot interaction simulation. At the physiological level, oxytocin cells were modeled with triple apical dendrites characteristic of their structure in the paraventricular nucleus of the hypothalamus. As trust was established in the simulation, this architecture had a direct inhibitory effect on the amygdala tonic firing, which resulted in a willingness to exchange an object from the trustor (virtual neurorobot) to the trustee (human actor). Our software and hardware enhancements allowed the simulation of almost 100,000 neurons in real time and the incorporation of a sophisticated Gabor mechanism as a visual filter. Our brain was functional and our robotic system was robust in that it trusted or distrusted a human actor based on movement imitation.