((LAPSo)) ~ Acoustics and Sound Perception Lab

Publicaciones

Kerlleñevich, H.; Riera, P. E.; Eguía, M.C. "Santiago. A real-time biological neural network environment for generative music creation" C. Di Chio et al. (Eds.): EvoApplications 2011, Part II, LNCS 6625, pp. 344--353. Springer, Heidelberg (2011)

Kerlleñevich, H.; Eguía, M.C. and Riera, P.E. "An Open Source Interface based on Biological Neural Networks for Interactive Music Performance". Proceedings of New Interfaces For Musical Expression (2011)

PUBLICATION SOUND EXAMPLES

The following examples contain audio samples of single and several interconnected neurons, of six typical neuron types:

- RS: Regular Spiking
- CH: Chattering
- FS: Fast Spiking
- IB: Intrinsecally Bursting
- LT: Low Threshold
- RZ: Resonator

The Firing Rate (time average of events) controls exponentially the pitch of the sound events. For a Firing Rate (FR) of 0, the pitch is 369.9 HZ. For the Maximum Stable Firing Rate (MSFR) of each neuron, pitch is 739.9 HZ.

ONE NEURON

In these one neuron cases, the event series are the result of a DC current ramp, going from 0 to 50 (arbitrary units)

RS: REGULAR SPIKING MSFR = 4.82 (5)

CH: CHATTERING MSFR = 19.65 (20)

FS: FAST SPIKING MSFR = 34.97 (35)

IB: INTRENSICALLY BURSTING MSFR = 9.63 (10)

1N IB 01 DC CURRENT RAMP 0 TO 50

RS: LOW THRESHOLD MSFR = 16.42 (17)

RZ: RESONATOR MSFR = 19.10 (19)

SEVERAL NEURONS

An all-inhibitory ring network. Five Chattering neurons inhibit each other. In this example, they all begin synchronized, and by the action of the user, who injects excitatory pulses to each neuron alternatively, the pattern evolves into different a regular state with variations.

EVOMUSART EXAMPLES

The following examples correspond to the paper sent to EvoMUSART 2011: "Santiago: A Real-time Biological Neural Network Environment for Generative Music Creation"

A fully connected inhibition network working as a CPG. Notice the rhythm and periodicity of the pattern

Neurons 1 and 2 are Regular Spiking (RS) neurons, and both excite neuron 3, also RS. When their spikes are close enough in time, they make neuron 3 spike, acting as a coincidence detector. Neuron 4 is a Low Threshold neuron excited by neuron 2 and spikes every time neuron 2 does. At the same time, it inhibits 5 which has a chattering behavior.

NIME EXAMPLES

The following examples correspond to the paper sent to NIME 2011: "An Open Source Interface based on Biological Neural Networks for Interactive Music Performance"

A simple two-neuron example. The excitatory-inhibitory pair produces a non-recurrent pattern of dishcarges. In this example, the pitch is fixed.

A simple two-neuron example. The excitatory-inhibitory pair produces a non-recurrent pattern of dishcarges. In this example, the pitch varies as a function of the firing rate of each neuron.

A simple CPG built with four neurons. A group of three neurons that inhibit one neighbor and one excitatory neuron that synchronizes them. An alternating cycle begins in the inhibitory ring, after each synchronization, that evolves into a regular inter-event time.

The input current for N1 is set to 7. The result for N1, N2 and N3, is a 5/8 pattern, in which N1 falls in down-beat eight notes, N2 repeats a pattern of 4 eight notes + 1 eight note silence, and N3 stresses 2+3 groups. In the long run, N4 alternates stadistically 3 eight notes + 1 eight note silence and 2 eight notes + 1 eight note silence.

The input current for N1 is set to 11; this generates a 4/4 pattern in which N1 also falls in eight notes, N2 falls in quarter notes, N3 repeats a pattern of 3 eight notes + 1 eight note silence, and N4 falls in off-beat eight notes.

The input DC current is set to 14; this generates a polyrhythm of 7/8 + 5/8. N1 falls in eight notes, N2 and N3 stress 3+2+2 and 3+4 groups respectively and N4 stresses 2+3 groups in 5/8.

With an input DC current of 19, a 9/8 recurrent pattern arises. N1 falls in eight notes, N2 puts a stress every 3 eight notes, N3 stresses 3+6 groups and N4 falls always in eight notes number 3, 6 y 9.

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© (2011) / mailto:hernankerllenevich (A\T) gmail.com

Phone: 054-11-4275-7714 (LAPSo)