Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
| Original language | English |
|---|---|
| Title of host publication | Artificial Neural Networks and Machine Learning – ICANN 2018 - 27th International Conference on Artificial Neural Networks, 2018, Proceedings |
| Publisher | Springer Verlag |
| Pages | 314-321 |
| Number of pages | 8 |
| ISBN (Print) | 9783030014179 |
| DOIs | |
| Publication status | E-pub ahead of print - 27 Sep 2018 |
| Event | 27th International Conference on Artificial Neural Networks, ICANN 2018 - Rhodes, Greece Duration: 4 Oct 2018 → 7 Oct 2018 |
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 11139 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
| Conference | 27th International Conference on Artificial Neural Networks, ICANN 2018 |
|---|---|
| Country | Greece |
| City | Rhodes |
| Period | 4/10/18 → 7/10/18 |
Multiplicative or divisive changes in tuning curves of individual neurons to one stimulus (“input”) as another stimulus (“modulation”) is applied, called gain modulation, play an important role in perception and decision making. Since the presence of modulatory synaptic stimulation results in a multiplicative operation by proportionally changing the neuronal input-output relationship, such a change affects the sensitivity of the neuron but not its selectivity. Multiplicative gain modulation has commonly been studied at the level of single neurons. Much less is known about arithmetic operations at the network level. In this work we have evolved small networks of spiking neurons in which the output neurons respond to input with non-linear tuning curves that exhibit gain modulation—the best network showed an over 3-fold multiplicative response to modulation. Interestingly, we have also obtained a network with only 2 interneurons showing an over 2-fold response.
ID: 15580085