Lesson 1Psychophysiology measures: heart rate variability (HRV) metrics, skin conductance response (SCR), respiratory measures, muscle EMGThis part brings in key body-mind measures, explaining how HRV, skin response, breathing, and muscle activity are recorded, handled, and read as signs of body balance, wakefulness, 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 good check and pre-handling for body and brain image data, including filter, error find, reject vs fix, quality numbers, and notes for repeatable steps.
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 looks at outer body sensors and wearables, including ECG, PPG, actigraphy, and walking monitoring, addressing place, sample, move errors, battery limits, and real-life truth in data gathering.
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 brings in EEG, covering body signal starts, electrode setups, frequency groups, event-linked potentials, and space and time clearness, with basic pre-handling and common test ways.
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 check in biopsychology, stressing cortisol sample from spit or blood, daily and stress rhythms, test principles, quality control, and reading in test and clinic 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 mix EEG, fMRI, and outer or hormone measures, focusing on time match, space link, sync tools, and study ways for true mixed multi-data guesses.
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 and time trades, entering body, move and body mixes, and truth and real-life issues.
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 numbers for body signals, including describe numbers, time-line models, spectrum study, event find, and handling non-steady, readying students for strong, repeatable signal studies.
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 measure of BOLD signals, covering blood-vessel link, block vs event designs, key get params, and standard pre-steps that ready data for number models and 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 brings in structure and spread MRI, describing gray matter shape measure, voxel shape work, spread tensor model, and path tracing, and how these link to brain growth, aging, and illness.
T1-weighted anatomy and tissue contrastGray matter morphometry measuresVoxel-based morphometry workflowsDiffusion tensor metrics: FA and MDBasics of white matter tractography
