PDCON:Conference/Santiago - Making music with biological neural networks in Pd-Gem: Difference between revisions

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Author: Hernán Kerlleñevich
Author: Hernán Kerlleñevich


In this paper we present SANTIAGO, a biological neural network environment built in PD-GEM. The interface focuses in the vast potential for interactive sound art creation emerging from biological neural networks, as a paradigmatic complex system for musical exploration. Our motivation relies upon the idea of relating metaphorically neural behaviors to electronic and acoustic instruments notes, by means of flexible mapping strategies. In this spirit, we introduce a simple, yet dynamically rich, neural system to develop new interfaces for generative music composition and performance.
In this paper we present SANTIAGO, a biological neural network environment built in Pd-Gem. The interface focuses in the vast potential for interactive sound art creation emerging from biological neural networks, as a paradigmatic complex system for musical exploration. Our motivation relies upon the idea of relating metaphorically neural behaviors to electronic and acoustic instruments notes, by means of flexible mapping strategies. In this spirit, we introduce a simple, yet dynamically rich, neural system to develop new interfaces for generative music composition and performance.


The interface is named SANTIAGO, after the renowned Spanish physiologist Santiago Ramon y Cajal. It consists of a modular patch, including a core for biological neural network simulations and diverse input/output modules that can be mapped to the desired musical parameters, as pitch, duration, intensity, timbre, beat, etc. The network consists of units (neurons) connected by unidirectional links (synapses) and are characterized by a continuous level (voltage). The neural model used is a two dimentional simple one, but it still mimics the activity of real biological neurons.
The interface is named SANTIAGO, after the renowned Spanish physiologist Santiago Ramon y Cajal. It consists of a modular patch, including a core for biological neural network simulations and diverse input/output modules that can be mapped to the desired musical parameters, as pitch, duration, intensity, timbre, beat, etc. The network consists of units (neurons) connected by unidirectional links (synapses) and are characterized by a continuous level (voltage). The neural model used is a two dimentional simple one, but it still mimics the activity of real biological neurons.
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