This it the list of theses defended in our group. The topics vary from single neuron model to psychological experiments in virtual reality!
we set to compare how well different machine learning algorithms are able to predict a rat’s position just based on its hippocampal neural activity <...> we analysed data recorded from an experiment where rats were trained to choose left or right direction in a 8-shaped maze while they were run- ning in a wheel. In this case we perform a dimensionality reduction of the neuronal data to visualize its dynamics during the decision time.
In this thesis RSA is implemented on a well known fMRI dataset in neuroscience, that was produced by a studying the categorical representations of objects in the ventral temporal cortex of human subjects. We carry out RSA on this dataset using different notions of distance and give an overview of how the end results of the analysis are affected by each distance notion. In total 9 different distance measures were evaluated for calculating the similarity between activation patterns in fMRI data.
Calcium-based single neuron models have been shown to elicit different modes of synaptic plasticity. In the present study one such model was implemented and its learning behaviour studied. Behaviour of the implemented neuron agreed qualitatively with prior work in all regards except selectivity to correlation in input. The neuron was found to im- plement a linear filter responding linearly to partial presentations of learned pat- terns.
This thesis describes an SSVEP-based BCI implemented as a practical part of this work. <...> The BCI implemented as a part of this thesis uses widely known PSDA and CCA feature extraction methods and introduces a new way to combine these methods. Combining different methods improves the performance of a BCI. The application was tested only superficially and the following results were obtained: 2.61 ± 0.28 s target detection time, 85.81 ± 6.39 % accuracy and 27.73 ± 5.11 bits/min ITR.
The main purpose of this thesis is to create a toolbox that enables to create memory experiments in virtual reality. The toolbox will have a random game room generator, level editor and an experiment creator. It will support four different types of memory experiment methods.
The aim of the present thesis is to develop a toolbox that allows one to easily prepare, reproduce and carry out change blindness experiments in virtual reality. For this, toolbox enables to design levels by modifying objects’ position, appearance and adding new ones. Also personalised experiments can be created and executed.
Projekti eesmärgiks on uurida tehisnärvivõrkude olemust ja töömehaanikat ning luua mobiilrakendus, mille abil saaks neid ära kasutada. Selleks uuriti lähemalt 2012. aastal korraldatud ImageNet 2012 konkursi võitjate loodud tehisnärvivõrku. Uurimise käigus tehti selgeks, mida tehisnärvivõrk endast kujutab, kuidas konkreetne CaffeNet mudel loodud on ja kuidas seda on treenitud. Sama mudelit kasutati ka käesoleva töö käigus loodud lahenduse loomises, mis võimaldab teha mobiilirakendusega foto ning rakendus näitab, mis selle foto peal on.