Lesson 1Psychophysiology measures: heart rate variability (HRV) metrics, skin conductance response (SCR), respiratory measures, muscle EMGThis part introduces key body-mind measures, explaining how HRV, skin response, breathing, and muscle activity are recorded, handled, and read as signs of body balance, alertness, and feeling or thinking states.
HRV metrics and autonomic balanceSCR amplitude, latency, and habituationRespiratory rate and depth measuresFacial and skeletal muscle EMG basicsSignal preprocessing for psychophysiologyLesson 2Signal quality, preprocessing, artifact detection and removal for physiological and neuroimaging dataThis part details signal quality check and pre-handling for body and brain imaging data, including filtering, error finding, reject or fix, quality measures, and records for repeatable processes in research.
Signal-to-noise ratio and quality checksFiltering and baseline correctionEEG and EMG artifact detectionPhysiological noise in MRI and fMRIArtifact rejection versus correctionLesson 3Peripheral autonomic sensors and wearable devices: ECG, PPG, actigraphy, ambulatory monitoring considerationsThis part focuses on outer body sensors and wearables, including ECG, PPG, movement tracking, and daily monitoring, covering placement, sampling, movement errors, battery limits, and real-life data value.
ECG acquisition and R-peak detectionPPG signals and pulse wave analysisActigraphy and sleep–wake estimationAmbulatory monitoring design issuesMotion artifacts and adherence challengesLesson 4Electroencephalography (EEG): signal origins, frequency bands, event-related potentials (ERPs), and spatial/temporal resolutionThis part introduces EEG, covering signal sources, electrode setups, frequency groups, event potentials, and space-time detail, with basic pre-handling and common experiment ways for practical use.
Cortical generators of EEG signalsElectrode placement and montagesCanonical EEG frequency bandsERP components and cognitive tasksEEG spatial and temporal resolutionLesson 5Endocrine measures: cortisol sampling (saliva, blood), diurnal rhythms, immunoassay basics and interpretationThis part covers hormone checking in biopsychology, focusing on cortisol from saliva or blood, daily and stress rhythms, test principles, quality control, and reading in experiment and health settings.
Cortisol physiology and stress responseSaliva versus blood sampling protocolsDiurnal and ultradian cortisol rhythmsImmunoassay principles and standardsInterpreting cortisol in contextLesson 6Multimodal integration: combining EEG + psychophysiology or fMRI + cortisol—synchronization and alignment issuesThis part covers ways to combine EEG, fMRI, and body or hormone measures, focusing on time matching, space linking, sync tools, and analysis for full combined understanding in studies.
Rationale for multimodal measurementEEG plus autonomic signals integrationfMRI with cortisol or hormonesTemporal synchronization and triggersCoregistration and data fusion methodsLesson 7Limitations and confounds of measurement methods (e.g., indirect measures, spatial/temporal tradeoffs, invasiveness)This part looks at idea and real limits of biopsychology measures, including indirect signals, space-time balances, body invasion, movement and body confuses, and issues of trust and real-life fit.
Indirect neural and physiological indicesSpatial versus temporal resolution tradeoffsInvasiveness, burden, and safety issuesMotion, respiration, and cardiac confoundsReliability, validity, and generalizabilityLesson 8Basic statistics for biosignals: time-series analysis, spectral analysis, event detection, and summary metricsThis part reviews key stats for body signals, including basic measures, time-line modeling, frequency analysis, event finding, and handling non-steady changes, readying students for strong, repeatable signal work.
Descriptive and summary signal metricsTime-domain models for biosignalsSpectral and time–frequency analysisEvent detection and peak pickingHandling nonstationarity and trendsLesson 9Functional magnetic resonance imaging (fMRI): BOLD physiology, experimental designs (block vs event-related), preprocessing stepsThis part explains fMRI blood signal measuring, covering brain-blood linking, block vs event designs, key settings, and standard pre-handling to ready data for stats modeling and clear reading.
Neurovascular coupling and BOLD contrastBlock versus event-related paradigmsRepetition time, resolution, and coveragePreprocessing: motion and slice timingSpatial smoothing and normalizationLesson 10Structural MRI and diffusion MRI (DTI): gray matter morphometry, voxel-based morphometry, white matter tractography basicsThis part introduces structure and spread MRI, describing gray matter shape measures, voxel shape work, spread tensor modeling, and path tracing, linking to brain growth, aging, and disease changes.
T1-weighted anatomy and tissue contrastGray matter morphometry measuresVoxel-based morphometry workflowsDiffusion tensor metrics: FA and MDBasics of white matter tractography
