Dear All,

We cordially invite you to the Ph.D. Seminar, which will be held on September 28 and 29, 2023 at 10.30 in the Konorski room (2nd floor). There will be 3 presentations each day:

28-09-2023

MSc Marcin Wołosiewicz

MSc Tomasz Nikołajew

MSc Ida Raciborska

29-09-2023

MSc Magdalena Stańczyk

MSc Ziemowit Sławiński

MSc Sylwia Bednarek

Information regarding speakers together with abstracts can be found below.

The seminar will be held in a hybrid mode.

Link to the meeting:

28-09-2023 https://zoom.us/j/99651178548?pwd=VzM3bXU4VFNXdFRwMUk2c3VURmU0UT09

29-09-2023 https://zoom.us/j/96292522633?pwd=VlRPOWUxaDlVMlhiOFpvcnlQdzhOZz09

With best regards,

Anna Filipek & Anna Nowicka

ABSTRACTS

28-09-2023

MSc Marcin Wołosiewicz
Laboratory of Molecular Medical Biochemistry
Supervisor: Prof. Paweł Dobrzyń, PhD, DSc

Title: Stearoyl-CoA desaturase 4 - a new player in the regulation of cardiac metabolism.

 Abstract:

Obesity is a major risk factor for cardiovascular disease, type 2 diabetes and other comorbidities. It develops under conditions of energy excess, which is stored as lipids in adipose and non-adipose tissues, leading to dysfunction of the latter. Lipogenesis is a process involved in lipid storage, the rate limiting step of which is fatty acids desaturation catalyzed by stearoyl-CoA desaturase (SCD). Many studies have shown beneficial effects of SCD1 deficiency, e.g. improved insulin sensitivity, reduced obesity, but the role of cardiac specific isoform SCD4 remains unknown. To address this issue, we used SCD4 knock-out (SCD4-/-) mice fed a high-fat diet (HFD) to induce obesity. Our results showed that under HFD condition, SCD4-/- mice had lower adiposity, improved insulin resistance index and preserved heart structure compared to control mice. Moreover, in the heart of SCD4-/- mice fed HFD, decreased lipid accumulation was accompanied by higher rate of lipolysis, increased mitochondria quality control, lower activity of NADH dehydrogenase and level of reactive oxygen species. In conclusion, SCD4 is an important factor in heart metabolism involved in the regulation myocardial structure and function, lipid metabolism, and is therefore a potent target for the treatment of obesity-related comorbidities.

MSc Tomasz Nikołajew

Laboratory of Neurobiology of Emotions

Proposed supervisor: Dr. Ewelina Knapska, PhD., DSc and auxiliary supervisor: Dr. Ksenia Meyza

Title: Emotional contagion in mouse model of Autism Spectrum Disorder.

 Abstract:

Lately, we can observe a steady increase in the number of autism spectrum disorder (ASD) diagnoses. The ASD population is characterised with deficits in social interactions and communication, as well as the presence of stereotyped behaviour. Lack of social skills often results with empathy impairment. Until recently, empathy were thought to occur only in humans, but a growing body of research indicates that emotional contagion – the simplest form of empathy, is widely found in nature, including in primates, marine mammals, birds and rodents. Despite the importance of the phenomenon, there is still little data on the neuronal basis of sharing emotions.

Aim of my PhD project was to assess the empathic abilities and the activity pattern within the amygdala and prefrontal cortex of Fmr1KO(FVB) mice (both males and females) - commonly used mouse model of ASD. To study this phenomena I employed Remote Transfer of Fear paradigm, in which mice are housed in pairs for three weeks, one labelled an Observer, and the other a Demonstrator. In the test session, the Demonstrator is subjected to aversive stimuli outside of the home cage, while the Observer remains there undisturbed. Then, the Demonstrator returns to the home cage, where it can freely interact with the Observer and first ten minutes of interactions are recorded. The activity of the amygdala and prefrontal cortex was assessed using immunohistochemistry against c-Fos protein, a standard neuronal novelty marker. Behaviour was measured by using software utilizing machine learning, for automatic pose estimation (DeepLabCut) and automatic classification and recognition of animal behaviour patterns (simBA).

Behavioural and c-Fos activation pattern results indicate the existence of deficits in emotional contagion in Fmr1KO(FVB) mice. Project was supported by the “Role of synaptic plasticity impairments in the development of asocial phenotype in mouse models of autism (NCN 2015/18/E/NZ4/00600)” grant.

MSc Ida Raciborska

Laboratory of Neuroinformatics

Proposed supervisor: Prof. Małgorzata Kossut, PhD, DSc

Title: Investigating learning-evoked plastic changes of orientation sensitivity in mouse primary visual cortex: integrating intrinsic signal optical imaging with the DREADD technique.

Abstract:

First, the intrinsic signal optical imaging (ISOI) technique was used to investigate orientation sensitivity bias in the visual cortex of young mice in vivo. Optical signals were recorded in response to moving light gratings that stimulated ipsi-, contra- and binocular eye inputs. ISOI facilitated the visualization of cortical areas activated by gratings of specific orientation and the observation of temporal changes in light scattering and changes of image of active areas during visual stimulations.

Second, the study focused on investigating the effects of classical conditioning, in which visual stimuli of specific orientation were paired with tail shock, on primary visual cortex activity recorded with the ISOI technique. Thirdly, the study investigated the importance of somatostatin interneurons (SOM-Ins) in the process of plastic changes evoked by classical conditioning, and their input in activation of primary visual cortex by introducing the DREADD selective inhibition technique.

Using ISOI, recordings of changes in the light-scattering signal showed that classical conditioning training led to increased activity in the visual cortex compared to the naive group. Furthermore, assessment of active areas revealed a concentration of activity, as evidenced by a reduction in the size of active regions. SOM-expressing interneurons appeared to play a key role in the occurrence of plastic changes, as the experimental group in which SOM –Ins  activity was blocked using the DREADD method did not show the conditioning-induced changes.

These results confirm the reliability of ISOI as a technique for imaging the activity of large populations of neurons in the mouse visual cortex. With this technique  orientation sensitivity in the primary visual cortex of the young mouse can be characterized, both by changes in response amplitudes of the light-scattering during time of record and changes of extent of active areas. The study finds that activity of SOM-Ins in the cortex is necessary in formation of association between conditioned and unconditioned stimulus.

29-09-2023

MSc Magdalena Stańczyk

Laboratory of Neurophysiology of Mind

Suggested supervisor: Dr. Aneta Szymaszek, PhD, DSc

Title: Temporal dynamics of  human behaviours: behavioural and neural correlates.

 Abstract:

            Temporal processing constitutes a neural underpinning of many cognitive functions such as memory, attention, language, planning ability, which are characterised by a specific temporal dynamics. According to the hierarchical model of temporal processing (Pöppel, 2009), several temporal domains (1. tens of milliseconds; 2. hundreds of milliseconds; 3. a few seconds), referring to various cognitive functions, may be distinguished. Further, theoretical framework indicate that our temporal behavior on basic domain – tens of milliseconds – determine our temporal functioning on other domains. However, between- domains relations has not been explored so far.

            The aim of this study was to investigate the relationship between particular temporal domains, i.e., to verify whether the performance on the basic domain – tens of milliseconds – is related to participants behaviour on the other domains. Moreover, we aimed to specify the brain areas responsible for human temporal processing on a different time domains.

            The 118 healthy young participants, took part in the study. Firstly, the participants followed the task assessing their performance on basic – tens of milliseconds time domain, which allows to identified High Level Performers (HLP) and Low Level Performers (LLP) in temporal ability. Then, subjects underwent tasks measuring their efficiency on the hundreds of milliseconds and a few seconds domains. Finally, they participated in the fMRI study to specify brain areas responsible for temporal processing at particular domains.

            Results indicated that HLP display better performance on the other temporal domains. Furthermore, the HLP exhibit brain activation mostly in core ‘temporal’ areas (e.g., right hemispheric insula and inferior parietal lobule), whereas, LLP engage additionally the areas dedicated for attention and working memory (anterior cingulate cortex and left superior frontal gyrus).

            Our findings suggest that participants’ performance on the basic domain could be a good predictor of their temporal behaviour on different time domains, which was observed in specific brain representation.

Supported by National Science Centre, Poland, grant no. 2018/29/B/HS6/02038.

MSc Ziemowit Sławiński

Laboratory of Neuroinformatics

Proposed supervisor: Prof. Daniel Wójcik, PhD, DSc

Title: Exploring Dendritic Plasticity: How Synaptic and Ion Channel Adaptations Enable Single Neurons to Rival Artificial Neural Network Complexity.

 Abstract:

In the traditional view, we often see a single neuron as less computationally efficient than a multilayer artificial neural network. But is this truly the case? Our investigation delves deep into the computational efficiency of morphologically complex neurons, especially their ability to distinguish between different synaptic patterns. We posed a question: What's the simplest dendritic structure that can master tasks usually reserved for multilayered artificial networks? This exploration not only challenges long-held beliefs about single neuron capabilities but also bridges the gap between biological and artificial neural computation.

Furthermore, building upon the foundational homeostatic models pioneered by Eve Marder, we introduced an enhanced model tailored for morphologically complex neurons. Central to our method is the fine-tuning of diverse ion channel composition throughout the whole dendritic tree, ensuring a good balance of homeostatic activity.

Our findings reveal that training to recognize synaptic patterns and the homeostatic tuning of ion channels can be unified under one computational strategy. This perspective encourages a more holistic understanding of dendritic tree adaptation, encompassing both synaptic and ion channel modifications. In essence, our study offers a fresh lens through which to understand neuronal learning, merging the worlds of artificial and biological neural networks.

MSc Sylwia Bednarek

Laboratory of Neuroinformatics

Suggested supervisor: Dr. Piotr Majka, PhD, DSc

Title: Deep learning based registration and mapping of the mouse brain

Abstract:

Integrating neuroimaging information across multiple techniques and spatial scales is a fundamental part of whole-brain mapping studies. This process requires a species-specific brain atlas, such as the Allen Mouse Brain Atlas. However, mapping some imaging modalities, like optically cleared brains, poses major challenges and is inherently limited in accuracy due to insufficient feature correspondence between the images. To address the limitations of multi-modal image registration, I used a deep-learning-based modality conversion technique to create additional layers of information in the Allen Brain Atlas. These synthetic templates, corresponding to iDISCO autofluorescence and cell density information, reduce the prohibitively complex problem of multi-modal registration to a much simpler one of unimodal alignment. The presented approach, together with automatic landmark generation, significantly improves mapping accuracy and quality, and can be generalized to a wider spectrum of applications. In addition, to facilitate the handling of voluminous imaging datasets, I have developed the LSFMPy toolbox. This software package efficiently stores terabyte-scale datasets while providing access to subsets of images of interest at different resolutions and in desired reference spaces. The computational pipeline was validated on experimental data focused on learning in response to appetitive or aversive stimuli.