Navigation auf uzh.ch

Suche

Psychologisches Institut Methoden der Plastizitätsforschung

Themen für Bachelorarbeiten

Übersicht der Bachelorarbeitsthemen dieser Professur

Durch Klick auf die einzelnen Themen werden die Detail-Informationen angezeigt.

  • Themenvergabe durch Präsenztermin
    Bei Interesse melden Sie sich zu Beginn des Semesters bei der angegebenen Kontaktperson via E-Mail.
    Betreuungsperson der Bachelorarbeit: Prof. Dr. N. Langer

 


offen:

  • Cortical Neurodynamics of declining Inhibitory Control in healthy ageing

    Beschreibung: Neuropsychological studies indicate that healthy ageing is associated with a decline of inhibitory control of attentional and behavioural systems, to inhibit prepotent responses is critical for successful goal-directed behaviours.
    A widely accepted measure of inhibitory control is the antisaccade task that requires both the inhibition of a reflexive saccadic response toward a visual target and the initiation of a voluntary eye movement in the opposite direction.
    This thesis aims to bring together and discuss evidence of decreasing inhibitory control in older adults using electroencephalography and eye-tracking recordings from the antisaccade task.

    Literature:
    [1] Hwang, Kai, et al. "Cortical neurodynamics of inhibitory control." Journal of Neuroscience 34.29 (2014): 9551-9561.
    [2] Plomecka, Martyna Beata, et al. "Aging effects and test/retest reliability of inhibitory control for saccadic eye movements." Eneuro 7.5 (2020).
    [3] Constantinidis, Christos, and Beatriz Luna. "Neural substrates of inhibitory control maturation in adolescence." Trends in neurosciences 42.9 (2019): 604-616.
    Kontakt: Martyna Plomecka, E-Mail

    [ Einzelthema ]
    Status: offen (erfasst / geändert: 26.07.2021)
  • What is fixation- static or dynamic event? The role of fixational eye movements in vision.

    Beschreibung: 3 Papers:

    Martinez-Conde, S., Macknik, S. & Hubel, D. The role of fixational eye movements in visual perception. Nat Rev Neurosci 5, 229?240 (2004). https://doi.org/10.1038/nrn1348

    Rucci, M., & Poletti, M. (2015). Control and Functions of Fixational Eye Movements. Annual review of vision science, 1, 499?518. https://doi.org/10.1146/annurev-vision-082114-035742

    Krauzlis Richard J. , Goffart Laurent and Hafed Ziad M. 2017 Neuronal control of fixation and fixational eye movementsPhil. Trans. R. Soc. B3722016020520160205

    Kontakt: Dr. Tzvetan Popov, E-Mail

    [ Einzelthema ]
    Status: offen (erfasst / geändert: 20.07.2021)
  • How fast do we see the world: origin and mechanisms of express and regular saccades in humans?

    Beschreibung: 3 Papers:

    Kingstone A, Klein RM. What are human express saccades? Percept Psychophys. 1993 Aug;54(2):260-73. doi: 10.3758/bf03211762. PMID: 8361841.

    Fischer B, Boch R (1983) Saccadic eye movements after extremely short reaction times in the monkey. Brain Res 260: 21?26

    Fischer, B., & Weber, H. (1993). Express saccades and visual attention. Behavioral and Brain Sciences, 16(3), 553-567. doi:10.1017/S0140525X00031575

    Kontakt: Dr. Tzvetan Popov, E-Mail

    [ Einzelthema ]
    Status: offen (erfasst / geändert: 20.07.2021)
  • P300 / neural correlate of learning across the lifespan

    Beschreibung: The learning process is one of the main topics of research in multiple disciplines such as psychology, neuroscience, behavioral ecology, evolutionary theory and computer science. The neural mechanism of memory formation and how it changes with age remains unclear. The use of neurophysiological measures can offer valuable insights into the learning process due to the ability of linking neural signals to complex behaviors. Electroencephalographic studies show that some components of event-related potentials (ERP) may provide information about the learning process itself and objectively measure learning success. These components include P300, a positive deflection with a latency of around 300 after stimulus onset.

    Polich, J. (2007). Updating P300: An integrative Theory of P3a and P3b. Clin. Neurophysiol., 118(10): 2128-2148.
    Tinga, A. M., de Back, T. T., Louwerse, M. M. (2019). Non-invasive neurophysiological measures of learning: A meta-analysis. Neuroscience and Biobehavioral Reviews, 99: 59-99.
    Kontakt: Dawid Strzelczyk, E-Mail

    [ Einzelthema ]
    Status: offen (erfasst / geändert: 21.01.2021)
  • Artificial Intelligence in Psychiatry (Betreuer Nicolas Langer)

    Beschreibung: Literatur:

    Woo CW, Chang LJ, Lindquist MA, Wager TD. (2017). Building better biomarkers: brain models in translational neuroimaging. Nature Neuroscience

    Zarley, D. (2019, January 28). Meet the scientists who are training AI to diagnose mental illness [Web log post]. Retrieved from https://www.theverge.com/2019/1/28/18197253/ai-mental-illness-artificial-intelligence-science-neuroimaging-mri

    Wardenaar, K. J., & De Jonge, P. (2013). Diagnostic heterogeneity in psychiatry: towards an empirical solution. BMC Medicine, 11(1). doi:10.1186/1741-7015-11-201

    Walsh, C. G., Ribeiro, J. D., & Franklin, J. C. (2017). Predicting Risk of Suicide Attempts Over Time Through Machine Learning. Clinical Psychological Science, 5(3), 457-469. doi:10.1177/2167702617691560

    Vieira, S., Pinaya, W. H., & Mechelli, A. (2017). Using deep learning to investigate the neuroimaging correlates of psychiatric and neurological disorders: Methods and applications. Neuroscience & Biobehavioral Reviews, 74, 58-75. doi:10.1016/j.neubiorev.2017.01.002

    Torous, J., Onnela, J., & Keshavan, M. (2017). New dimensions and new tools to realize the potential of RDoC: digital phenotyping via smartphones and connected devices. Translational Psychiatry, 7(3), e1053-e1053. doi:10.1038/tp.2017.25

    Stark, H. (2017, September/October 30). Artificial intelligence is here and it wants to revolutionize psychiatry. Forbes

    Torous, J. (2014). Mobile technology and global mental health. Asian Journal of Psychiatry, 10, 69-70. doi:10.1016/j.ajp.2013.07.004

    Rutledge, R. B., Chekroud, A. M., & Huys, Q. J. (2019). Machine learning and big data in psychiatry: toward clinical applications. Current Opinion in Neurobiology, 55, 152-159. doi:10.1016/j.conb.2019.02.006

    Reece, A. G., & Danforth, C. M. (2017). Erratum to: Instagram photos reveal predictive markers of depression. EPJ Data Science, 6(1). doi:10.1140/epjds/s13688-017-0118-4

    Place, S., Blanch-Hartigan, D., Rubin, C., Gorrostieta, C., Mead, C., Kane, J., ? Azarbayejani, A. (2017). Behavioral Indicators on a Mobile Sensing Platform Predict Clinically Validated Psychiatric Symptoms of Mood and Anxiety Disorders. Journal of Medical Internet Research, 19(3), e75. doi:10.2196/jmir.6678

    Neighborhood Psychiatry. (2018, February 13). Can artificial intelligence improve psychiatric diagnosis? Retrieved from https://www.psychologytoday.com/intl/blog/psychiatry-the-people/201802/can-artificial-intelligence-improve-psychiatric-diagnosis

    Meyer-Lindenberg, A. (2018). Künstliche Intelligenz in der Psychiatrie ? ein Überblick. Der Nervenarzt, 89(8), 861-868. doi:10.1007/s00115-018-0557-6

    Just, M. A., Pan, L., Cherkassky, V. L., McMakin, D. L., Cha, C., Nock, M. K., & Brent, D. (2017). Machine learning of neural representations of suicide and emotion concepts identifies suicidal youth. Nature Human Behaviour, 1(12), 911-919. doi:10.1038/s41562-017-0234-y

    Corcoran, C. M., Carrillo, F., Fernández-Slezak, D., Bedi, G., Klim, C., Javitt, D. C., ? Cecchi, G. A. (2018). Prediction of psychosis across protocols and risk cohorts using automated language analysis. World Psychiatry, 17(1), 67-75. doi:10.1002/wps.20491

    Deshpande, G., Wang, P., Rangaprakash, D., & Wilamowski, B. (2015). Fully Connected Cascade Artificial Neural Network Architecture for Attention Deficit Hyperactivity Disorder Classification From Functional Magnetic Resonance Imaging Data. IEEE Transactions on Cybernetics, 45(12), 2668-2679. doi:10.1109/tcyb.2014.2379621

    Bedi, G., Carrillo, F., Cecchi, G. A., Slezak, D. F., Sigman, M., Mota, N. B., Ribeiro, S., Javitt, D. C., Copelli,
    M., & Corcoran, C. M. (2015). Automated analysis of free speech predicts psychosis onset in high-risk
    youths. Npj Schizophrenia, 1(1), 15030. https://doi.org/10.1038/npjschz.2015.30

    Bedi, G., Cecchi, G. A., Slezak, D. F., Carrillo, F., Sigman, M., & de Wit, H. (2014). A Window into the Intoxicated
    Mind? Speech as an Index of Psychoactive Drug Effects. Neuropsychopharmacology, 39(10),
    2340?2348. https://doi.org/10.1038/npp.2014.80
    Kontakt: Prof. Dr. Nicolas Langer, E-Mail

    [ Einzelthema ]
    Status: offen (erfasst / geändert: 19.01.2020)
  • Rey-Osterrieth complex figure (ROCF)

    Beschreibung: Der Rey–Osterrieth Complex Figure Test (ROCF) ist ein neuropsychologischer Test zur Erfassung der Fähigkeit der räumlich visuellen Konstruktion und der visuellen Gedächtnisleistung. Auch wird der Test zur Erfassung exekutiver Funktionen eingesetzt. Der Test wurde ursprünglich 1941 von André Rey entwickelt und 1944 von Paul Alexandre Osterrieth standardisiert. Das Ziel des Tests war es, zwischen Wahrnehmungs- und Gedächtnisstörungen unterscheiden zu können, und ob die Störungen auf Lernschwierigkeiten oder hirnorganische Ursachen zurückzuführen sind.
    Kontakt: Prof. Dr. Nicolas Langer, E-Mail

    [ Einzelthema ]
    Status: offen (erfasst / geändert: 17.01.2020)
  • Neural Correlates of Working Memory Training

    Beschreibung: folgt
    Kontakt: Prof. Dr. Nicolas Langer, E-Mail

    [ Einzelthema ]
    Status: offen (erfasst / geändert: 17.01.2020)

 


vergeben:

  • Age Effects of Neuro- and Psychophysiological underpinning of Inhibitory Control.

    Beschreibung: Neuropsychological studies indicate a reduction in the inhibitory control of attentional and behavioral systems in older people. A widely accepted measure of inhibitory control is the antisaccade task, in which participants inhibit a reactive saccade to a visual target to perform a voluntary saccade in the opposite direction. In addition, the EEG beta-band activity is known to be associated with the processing components during anti- and prosaccades. The aim of this thesis is to bring together and discuss evidence of decreasing inhibitory control in older adults using electroencephalography and eye-tracking recordings
    Anzahl Arbeiten für dieses Thema:
    Zeitrahmen:
    Eingabedatum:
    Kontakt: Martyna Plomecka, E-Mail

    Status: vergeben (erfasst / geändert: 26.07.2021)
  • Morphologic characteristics of the cortex during brain development in ADHD

    Beschreibung: ADHD is a frequent disorder in children and adolescents characterised by increased levels of hyperactivity and inattention. Yet, the underlying mechanisms of ADHD are not well understood. The aim of this thesis it so bring together current findings on morphologic characteristics of the cortex during brain development in ADHD. The findings shall be discussed critically with respect to their responsibility in the heterogeneity of symptoms in this disorder.
    Anzahl Arbeiten für dieses Thema:
    Zeitrahmen:
    Eingabedatum:
    Kontakt: Sabine Dziemian, E-Mail

    Status: vergeben (erfasst / geändert: 16.06.2020)
  • Deep learning for detecting memory impairment from electroencephalography recordings.

    Beschreibung: Deep learning is a powerful machine learning method for big data analysis. The student will summarize and evaluate recent studies using deep learning on electroencephalography (EEG) data for detecting memory impairments, such as the early onset of mild cognitive impairment or dementia. Literatur: - Bi X, Wang H (2019) Early Alzheimer's disease diagnosis based on EEG spectral images using deep learning. Neural Netw. 114:119-135. - Durstewitz D, Koppe G, Meyer-Lindenberg A (2019) Deep neural networks in psychiatry. Mol Psychiatry. 24(11):1583-1598. - Ieracitano C, Mammone N, Hussain A, Morabito FC (2019) A novel multi-modal machine learning based approach for automatic classification of EEG recordings in dementia. Neural Netw. 123:176-190. - Kim D, Kim K (2018) Detection of Early Stage Alzheimer's Disease using EEG Relative Power with Deep Neural Network. Conf Proc IEEE Eng Med Biol Soc. 2018:352-355. - Liu X, Chen K, Wu T, Weidman D, Lure F, Li J (2018) Use of multimodality imaging and artificial intelligence for diagnosis and prognosis of early stages of Alzheimer's disease. Transl Res. 194:56-67. - Morabito F C, Campolo M, Ieracitano C, Ebadi J M, Bonanno L, Bramanti A, Desalvo S, Mammone N and Bramanti P (2016) Deep convolutional neural networks for classification of mild cognitive impaired and Alzheimer?s disease patients from scalp EEG recordings. IEEE 2nd Int. Forum on Research and Technologies for Society and Industry Leveraging a Better Tomorrow. - Morabito FC, Campolo M, Mammone N, Versaci M, Franceschetti S, Tagliavini F, Sofia V, Fatuzzo D, Gambardella A, Labate A, Mumoli L, Tripodi GG, Gasparini S, Cianci V, Sueri C, Ferlazzo E, Aguglia U (2017) Deep Learning Representation from Electroencephalography of Early-Stage Creutzfeldt-Jakob Disease and Features for Differentiation from Rapidly Progressive Dementia. Int J Neural Syst. 27(2):1650039. - Roy Y, Banville H, Albuquerque I, Gramfort A, Falk TH, Faubert J (2019) Deep learning-based electroencephalography analysis: a systematic review. J Neural Eng. 16(5):051001.
    Anzahl Arbeiten für dieses Thema:
    Zeitrahmen:
    Eingabedatum: 07.01.2020
    Kontakt: Dr. Christian Pfeiffer, E-Mail

    Status: vergeben (erfasst / geändert: 17.01.2020)
  • The role of eye movements in cognitive aging

    Beschreibung:
    Anzahl Arbeiten für dieses Thema:
    Zeitrahmen:
    Eingabedatum:
    Kontakt: , E-Mail

    Status: (erfasst / geändert: 11.12.2018)
  • The use of drift-diffusion models in decision-making research

    Beschreibung:
    Anzahl Arbeiten für dieses Thema:
    Zeitrahmen:
    Eingabedatum:
    Kontakt: , E-Mail

    Status: (erfasst / geändert: 11.12.2018)
  • The resting state EEG frequency spectrum as a biomarker for dementia?

    Beschreibung:
    Anzahl Arbeiten für dieses Thema:
    Zeitrahmen:
    Eingabedatum:
    Kontakt: , E-Mail

    Status: (erfasst / geändert: 12.07.2018)
  • What are resting state EEG microstates?

    Beschreibung:
    Anzahl Arbeiten für dieses Thema:
    Zeitrahmen:
    Eingabedatum:
    Kontakt: , E-Mail

    Status: (erfasst / geändert: 12.07.2018)
  • The role of phase-amplitude-coupling in working memory

    Beschreibung: Neural oscillations and their interaction play a key role in various cognitive processes. Phase-amplitude-coupling, a form of cross-frequency-coupling, has been reported to be directly linked to memorisation. The aim of this thesis is to bring together and critically discuss evidence of phase-amplitude-coupling in electroencephalography recordings that indicate memory processes, with the main focus on working memory.
    Anzahl Arbeiten für dieses Thema:
    Zeitrahmen:
    Eingabedatum:
    Kontakt: , E-Mail

    Status: (erfasst / geändert: 12.07.2018)
  • Contralateral delay activity as a neural correlate of working memory processes.

    Beschreibung: Contralateral delay activity (CDA) is a widely studied phenomenon in memory research. Its sensitivity to working memory load is a replicated finding and advances our understanding of underlying processes. Furthermore it may be useful in the investigation of age related decline in working memory capacity.
    Anzahl Arbeiten für dieses Thema:
    Zeitrahmen:
    Eingabedatum:
    Kontakt: , E-Mail

    Status: (erfasst / geändert: 12.07.2018)
  • Steady State Visually Evoked Potentials (SSVEP)

    Beschreibung:
    Anzahl Arbeiten für dieses Thema:
    Zeitrahmen:
    Eingabedatum:
    Kontakt: , E-Mail

    Status: (erfasst / geändert: 12.07.2018)
  • Antisaccade task as a early marker for different psychiatric disorders

    Beschreibung: keine
    Anzahl Arbeiten für dieses Thema:
    Zeitrahmen:
    Eingabedatum:
    Kontakt: , E-Mail

    Status: (erfasst / geändert: 18.12.2017)
  • New ways of studying mental disorders

    Beschreibung: keine
    Anzahl Arbeiten für dieses Thema:
    Zeitrahmen:
    Eingabedatum:
    Kontakt: , E-Mail

    Status: (erfasst / geändert: 07.11.2017)
  • Reliability of neuroscientific measures

    Beschreibung: keine
    Anzahl Arbeiten für dieses Thema:
    Zeitrahmen:
    Eingabedatum:
    Kontakt: , E-Mail

    Status: (erfasst / geändert: 07.11.2017)
  • Social Network/Engagement as a protective factor on healthy aging

    Beschreibung: keine
    Anzahl Arbeiten für dieses Thema:
    Zeitrahmen:
    Eingabedatum:
    Kontakt: , E-Mail

    Status: (erfasst / geändert: 07.11.2017)
  • Genetic protective and risk factors on healthy aging

    Beschreibung: keine
    Anzahl Arbeiten für dieses Thema:
    Zeitrahmen:
    Eingabedatum:
    Kontakt: , E-Mail

    Status: (erfasst / geändert: 07.11.2017)
  • Semantic Memory Impairment in Alzheimer’s Disease

    Beschreibung: keine
    Anzahl Arbeiten für dieses Thema:
    Zeitrahmen:
    Eingabedatum:
    Kontakt: , E-Mail

    Status: (erfasst / geändert: 13.06.2017)
  • Genetic protective and risk factors on healthy aging

    Beschreibung: keine
    Anzahl Arbeiten für dieses Thema:
    Zeitrahmen:
    Eingabedatum:
    Kontakt: , E-Mail

    Status: (erfasst / geändert: 13.06.2017)
  • Physical activity as a protective factor on healthy aging

    Beschreibung: keine
    Anzahl Arbeiten für dieses Thema:
    Zeitrahmen:
    Eingabedatum:
    Kontakt: , E-Mail

    Status: (erfasst / geändert: 13.06.2017)
  • Social Network/Engagement as a protective factor on healthy aging

    Beschreibung: keine
    Anzahl Arbeiten für dieses Thema:
    Zeitrahmen:
    Eingabedatum:
    Kontakt: , E-Mail

    Status: (erfasst / geändert: 13.06.2017)
  • New Ways of Studying Mental Disorders

    Beschreibung: keine
    Anzahl Arbeiten für dieses Thema:
    Zeitrahmen:
    Eingabedatum:
    Kontakt: , E-Mail

    Status: (erfasst / geändert: 11.07.2016)
  • Processing Speed from a Developmental and Clinical Perspective

    Beschreibung: keine
    Anzahl Arbeiten für dieses Thema:
    Zeitrahmen:
    Eingabedatum:
    Kontakt: , E-Mail

    Status: (erfasst / geändert: 11.07.2016)
  • Reliability of Neuroscientific Measures

    Beschreibung: keine
    Anzahl Arbeiten für dieses Thema:
    Zeitrahmen:
    Eingabedatum:
    Kontakt: , E-Mail

    Status: (erfasst / geändert: 11.07.2016)