Doctoral dissertation

Stefanus Arinno Wirdatmadja: Turning the brain into the neuronal dance floor

Stefanus Arinno Wirdatmadja
Turning the brain into the neuronal dance floor
Using sound and light waves, Wireless Optogenetics Nanonetworking Device (WiOptND) controls the neurons in the brain, just like the crowd on the dance floor. This implantable device targets the wireless stimulation on the cellular level by its miniaturised design. Complemented with particular charging algorithm, the neuron orchestra can be conducted to produce elegant symphony creating particular action potential firing pattern.

Recently, brain implant has gained back its global spotlight due to live demonstration by Elon Musk, Neuralink. It showed how multiple neurons can be monitored simultaneously and represented by graph and sound signals. Unlike Neuralink’s demonstration, Stefanus Arinno Wirdatmadja’s doctoral thesis focuses on multiple neuron stimulation.

The proposed design highlights the miniaturised brain implant which stimulates the light-sensitive genetically engineered neurons a.k.a optogenetic constructs. Optogenetics – in principle – offers better precision in neuron stimulation compared to conventional implanted electrodes. Additionally, the acoustic wave is utilised to wirelessly activate the implant and at the same time, harvest the energy to power the circuit, resulting in batteryless device.

“The design of the device opens more possibility for experimental researchers who are dealing with freely moving animals, such as mice. This avoids wire tangle during the observation, in addition to more natural behaviour of the observed objects. On human, clinical trials both in optogenetics and brain implants have been done, showing their promising future. This device is one potential candidate for human brain implant implementation,” Wirdatmadja says.

The doctoral dissertation of MSc. Stefanus Arinno Wirdatmadja in the field of communications engineering titled Wireless Optogenetics Nanonetworking Device (WiOptND): Opto-acoustic Brain Machine Interface will be publicly examined in the Faculty of Information Technology and Communication Sciences at Tampere University at 12.00 on Thursday 5th November 2020. The Opponent will be Professor Wolfgang H. Gerstacker from Friedrich-Alexander-Universität, Erlangen-Nürnberg, Germany. The Custos will be Professor Evgeny Kucheryavy from the Faculty of Information Technology and Communication Sciences at Tampere University.

The event can be followed via remote connection.

The dissertation is available online at the http://urn.fi/URN:ISBN:978-952-03-1728-7 The Faculty Office will provide a pdf version of the entire doctoral dissertation upon request. Please send an email to cee.doc.tau [at] tuni.fi