The Clinical Neuroscience Laboratory at Üsküdar University is an interdisciplinary research and application center established to investigate the neurobiological foundations of central nervous system disorders, behavioral abnormalities, and cognitive (cognitive) processes using advanced brain imaging, electrophysiological measurement, and neuromodulation techniques.
- Primary Objective: To identify the cellular and network-level brain mechanisms underlying neurological, psychiatric, and psychological pathologies; and to develop objective neurobiomarkers for diagnosis, monitoring, and treatment.
- Key Features: The laboratory has the capacity to simultaneously process and perform in-depth analysis of electrophysiological signals obtained from clinical populations, structural/functional neuroimaging data, and computerized cognitive performance metrics.
- Academic Contribution: By bringing together the disciplines of medicine, psychology, engineering, and artificial intelligence under the umbrella of translational neuroscience, the laboratory supports scientific research at the academic level by equipping students with the skills to process raw brain data, develop biosignal algorithms, and master clinical neuroscience methodologies.
Equipment and Technical Infrastructure in the Laboratory
The laboratory’s infrastructure includes state-of-the-art hardware and software capable of analyzing and modulating the human brain’s electrical activity, blood flow parameters, and responses to external stimuli at the micro level:
- High-Density Electroencephalography (EEG) Systems: Multi-channel measurement devices that record the microvolt-level electrical activity of neural networks in the cerebral cortex from the scalp with high temporal resolution, enabling source localization analyses.
- Event-Related Potential (ERP) Measurement Modules: Integrated analysis systems that detect the brain’s electrical response profiles within microseconds to functional, visual, or auditory stimuli presented to participants.
- Transcranial Direct Current Stimulation (tDCS) and tACS Devices: Neuromodulation systems that non-invasively (without requiring surgical intervention) modulate neural excitability by applying low-intensity currents at the microampere level to specific cortical regions.
- Eye-Tracking Integrations: Optical systems that simultaneously record fixation points, saccadic movements, and changes in pupil diameter (pupillometry) with EEG during stimulus tracking.
- Functional Neuroimaging and Modeling Software: Computational workstations that analyze raw data from systems such as functional magnetic resonance imaging (fMRI) and fNIRS, and perform voxel-based morphometry and functional connectivity mapping.
- Computerized Neurocognitive Test Batteries: Digital testing and stimulation software that measures attention, working memory, reaction time, and executive functions according to international standards.
Research Areas and Application Areas
Applied curricula conducted in the laboratory, graduate thesis studies, and R&D projects cover the most strategic areas of modern clinical neuroscience:
- Clinical Neuroimaging and Biomarker Discovery: Quantitative analysis to identify functional brain network abnormalities specific to disorders such as schizophrenia, bipolar disorder, major depressive disorder, Alzheimer’s, and Parkinson’s.
- Neuromodulation and Neuroplasticity Research: Investigating the effects of non-invasive brain stimulation methods (such as tDCS) on neural networks, learning rates, and the restoration of cognitive functions at the cellular and network levels.
- Computational Neuroscience and Biosignal Processing: Studies on the classification of raw EEG waves through mathematical filtering techniques, spectral power analyses, and machine learning algorithms.
- Cognitive Neuroscience and Behavioral Experiments: Testing the neural correlates of human decision-making, emotional processes, and motor planning mechanisms using experimental paradigms.
Contributions to Students and the Industry
The Clinical Neuroscience Laboratory prepares students for the future world of digital health and neurotechnology by integrating their theoretical knowledge of medicine and psychology with advanced technological data processing skills.
- Multidisciplinary Work Culture: Students learn firsthand how to process biological data using engineering tools and how to transform it into diagnostic value in the fields of clinical psychology and psychiatry.
- Industry Employment Opportunities: Researchers who graduate with expertise in the advanced neuroimaging, biosignal processing, and neuromodulation systems used in this laboratory find employment in hospitals’ neurology and psychiatry research centers, R&D laboratories developing neurotechnology and wearable health devices, biomedical software companies, and artificial intelligence-focused brain-computer interface (BCI) projects as “Neuroscience Specialists,” "Biological Signal Data Analyst," or "Clinical Researcher" with priority and high technical proficiency.
