Joint PhD’s with KU Leuven

 

In the beginning of 2021 the agreement for Joint PhD study between UL and KU Leuven was refined and confirmed. The list of potential research topics was introduced to students in COGDEC Summer School 2021 advertisement and was shared with some other faculties of UL (Faculty of arts, Faculty of electrical engineering, Faculty of mathematics and physics). 

 

The first researcher from UL was admitted to Joint PhD study in April 2021, the second one was admitted in June 2021. As the result of excellent previous collaboration with KU Leuven, one researcher was offered a full scholarship for a PhD at KU Leuven, starting in November 2021.

Joint PhD proposals

 

UL, Faculty of Medicine and KU Leuven offer 6 Joint PhD proposals.  Students, who are interested in Joint PhD between UL and KU Leuven are given the opportunity to visit KU Leuven’s Laboratory for Neuro- and Psychophysiology.  This offer includes transportation and accommodation costs for a 10-day visit, where students will be able to get familiar with the Lab’s environment and will discuss further research collaboration and possible Joint PhD admission.

Please note:

COGDEC project does not cover PhD scholarship or costs of any other collaboration that might emerge from this visit. For additional information please send us an e-mail to: cogdec@mf.uni-lj.si

Topics:

Effects of confounds on EEG-based biomarkers of mild cognitive decline

Keywords: EEG, mild cognitive impairment, confounds

 

Abstract:

According to the 2017 report of Global Voice of Dementia around 50 million patients worldwide are diagnosed with dementia of which Alzheimer's disease (AD) is the largest group. As pharmacological treatments of AD is still beyond reach, considerable effort is currently put into early detection with goal to postpone institutionalization. Currently there are few promising EEG signatures that could differentiate between healthy individuals and the ones with mild cognitive impairment (MCI), however it is still not clear how much of this differentiation can be attributed to the individual characteristics of the study participants. The proposed PhD will address this issue by charting the relationships between these candidate EEG signatures and a number of confounding factors that can influence the clinical manifestation of AD. This way, we can advance our stride towards the objective electrophysiological biomarker for early detection of cognitive decline.

 

Studying cognitive reserve with EEG in patients with mild cognitive impairment

Keywords: mild cognitive impairment, cognitive reserve, EEG

Abstract:

It has been shown that cognitive reserve (CR) can postpone the clinical manifestation of cognitive decline and maintain individual’s normal functioning even in presence of certain degree of brain impairment. However, once individual exhausts his/her cognitive reserve and enters the stage of decompensation, the, patients present with a cognitive decline that in short time leads to dementia. The role of CR in mild cognitive impairment (MCI) and the value of its compensation mechanisms is less clear. The current PhD will investigate the role of CR in evolution of clinical and electrophysiological changes in patients with MCI and assess if the exhaustion of CR happens already in the stage of MCI or it lasts until patients enter the dementia stage.

 

Using neural networks to uncover hidden relations in cognitive decline-related EEG data

Keywords: DNN, explainable AI

Abstract:

Deep neural networks (DNNs) have witnessed modest successes in cognitive neuroscience as they offer only limited capabilities to account for prior knowledge. In recent years, the interest in explainable and interpretable AI has grown tremendously with a plethora of algorithms capable of explaining what the DNN has extracted from the data (“features”). This proposal aims at using first shallow neural networks, and in a later stage deep neural networks, to identify and gain insight into the relevance of extracted EEG features of patients suffering from cognitive decline.

Using functional connectivity brain networks as a biomarker of cognitive impairment

Keywords; Source localization, biomarker, functional connectivity

Abstract:

It has been shown that cognitive impairment coincides with changes in functional brain networks. However, due to restrictions in accuracy and fine-tuning of functional brain networks, the connection to cognitive impairment has only been done with static brain networks. With recent advances in source localization accuracy and sparsity, it has become possible to construct more accurate and finer functional connectivity brain networks. This PhD aims to build on these recent advances to gain insight into dynamic time-varying functional connectivity. In a second stage, these time-varying functional connectivity maps will be used to investigate the link to cognitive impairment.

 

Using Block Term Tensor Regression with source reconstructed EEG to investigate finger dexterity

Keywords; Source localization, BCI, Block term decomposition

Abstract:

Tensor-based techniques, like Block Term Tensor Regression (BTTR) for Brain Computer Interfaces (BCIs) are believed to better account for the complex structure of brain signals compared to conventional techniques. Source localization from EEG is a notoriously difficult inverse problem but essential to identify the brain regions implicated in information processing at high temporal resolution. The aim of the PhD is to investigate the effect of source reconstruction on the performance of decoding finger movement using BTTR.

EEG-based biomarkers of early mild cognitive impairment

Keywords: MCI, biomarkers, machine learning, signal processing

Abstract:

Faced with an ageing population, many western countries are witnessing an increased risk of their elder population to develop mild cognitive impairment (MCI), which eventually could develop into dementia. At this point, the used techniques to detect MCI are invasive, laborious, expensive or require skilled staffing, all of which renders them unsuitable for preemptive screening. This PhD will focus on machine learning and signal processing techniques, applied to public datasets of MCI and dementia patients and healthy controls, to arrive at an EEG-based biomarker with which the risk of MCI can be assessed.

Joint papers

 

UL trainers and other COGDEC related researchers are collaborating actively with advanced project partners. One of trainers participated during the research work and preparation of the article Electrophysiological Proxy of Cognitive Reserve Index, which was published in Frontiers in Human Neuroscience in July 2021 (link). Article had 900+ views in first three months.

Next trainer and several other COGDEC related researchers participated during the research work and preparation of article Lay Public View of Neuroscience and Science-Based Brain Health Recommendations in Slovenia, which  was published in Frontiers in Public Health in July 2021 (link). Article had 950+ views in first three months.

One of Early stage researchers, in collaboration with Elvira Khachatryan (KU Leuven), continued working on a review paper on preclinical Alzheimer's disease, neuroimaging and the influence of protective and risk factors. Authors screened 1197 papers and after 4 waves of screening, the final pool included 193 papers, with 33 of them being subsequently excluded due to discrepancies between the authors. The remaining 150 papers were categorized into 9 different categories and summarized in article. Authors are currently reviewing and editing the text, improving on the clarity, and making sure that the paper is concise. The review paper is in its final phase and is planned to be submitted in Autumn 2021.

Joint projects and applications

 

KU Leuven and UL are joined by partners from Sweden, The Netherlands and Germany in the HORIZON-EIC-2021-PATHFINDER proposal called “DeepCognition: Revolutionizing Assessment of Cognitive Reserve and Cognitive Decline using Model-Based Deep Learning Methods” (Challenge driven call, Section III, Tools to measure & stimulate activity in brain tissue). Proposal is planned to be submitted before the 27 October 2021 deadline.

 

MUG and UL worked on another joint project application to national research agencies - Slovenian Research Agency (ARRS) and Austrian Science Fund (FWF), titled “Late consequences of COVID19 on brain function and structure”. The application was submitted in March 2021 and is still under review.

 

During Summer 2021 MUG and UL started working on a new joint project that focuses on the analysis of magnetization transfer in the brain of patients suffering from multiple sclerosis. Preliminary results indicate that this project will provide the foundation for another joint project application.

Collaboration with other international projects

 

In Year 2021 cooperation with researchers within the project “Precision Medicine Interventions in Alzheimer’s Disease” (PMI-AD) was initiated. PMI-AD is a running project at University Medical Centre Ljubljana and is supported by the EU Joint Programme – Neurodegenerative Disease Research (JPND), the largest global research initiative aimed at tackling the challenge of neurodegenerative diseases. PMI-AD project is about Alzheimer’s disease, inflammation and synapse loss that are linked to premorbid genetic predispositions, and proteomic changes in cerebrospinal fluid and blood, and imaging changes, as seen with brain MRI techniques. Trainers who gained new MRI knowledge and techniques within COGDEC project in Graz are supposed to cooperate in PMI-AD project.

 

In May 2021 UL MF started with another H2020 project Alliance4Life-Actions (link). COGDEC members discussed the possibilities to jointly organize trainings, workshops, meetings with industry and national round tables.