Steps
Step 1
Cognitive Function Topic Selection and Experimental Design
The core task of this step is to select a cognitive neuroscience research topic and design a scientific cognitive experiment plan. Choose from perception, attention, memory, language, thinking, decision-making, emotion.
• Select cognitive topic: choose from perception (visual/auditory processing), attention (selective, divided), memory (working, long-term, episodic, semantic), language (production, comprehension, bilingual), executive function (inhibitory control, cognitive flexibility, problem solving), decision-making and social cognition
• Experimental design: determine design type—block design, event-related design, mixed design; determine factorial design (within-subjects/between-subjects/mixed); set independent variables (experimental conditions) and dependent variables (behavioral + neural measures); control confounding variables
• Select techniques: choose research techniques—behavioral experiments (reaction time, accuracy), eye tracking (fixation, saccades), EEG/ERP, fMRI, TMS; develop experimental flow and stimulus presentation protocol (using E-prime, PsychoPy, Presentation)
Deliverable: Cognitive neuroscience experiment design proposal (research question, experimental design, technique selection, stimulus materials, flow timeline) | Quality standard: Scientific and rigorous experimental design, comprehensive variable control, appropriate technique selection, detailed and feasible plan
Step 2
Stimulus Material Preparation and Experimental Programming
The core task of this step is to prepare experimental stimulus materials and write the experimental program. Cognitive experiments require high standardization of stimulus materials with strict control of physical and psychological properties.
• Stimulus material preparation: create/select experimental stimuli—visual stimuli (words, pictures, faces, geometric figures) standardized for size, brightness, contrast using Photoshop, GIMP; auditory stimuli (speech, pure tones, environmental sounds) standardized for intensity, duration using Audacity, Praat; build stimulus library with normative ratings (familiarity, valence, arousal)
• Experimental programming: write experiment program using PsychoPy, E-prime, or Presentation—design experiment flow (instructions, practice, formal experiment, breaks), set stimulus presentation parameters (duration, SOA, response window), implement response collection (keyboard, button box, voice response), set pseudorandomization and counterbalancing
• Pilot testing and debugging: conduct small pilot study (3-5 subjects); test flow smoothness, stimulus effectiveness, program stability; adjust parameters (difficulty, duration, stimulus number); ensure experimental operability and data quality
Deliverable: Experimental stimulus library and program (standardized stimulus materials, experiment program code, stimulus rating data, pilot report) | Quality standard: Standard and normalized stimulus materials, stable and reliable program, validated by pilot experiment
Step 3
Participant Recruitment and Behavioral/Neuroimaging Data Acquisition
The core task of this step is to recruit participants and perform behavioral experiments and neuroimaging data acquisition. Participant recruitment requires consideration of sample representativeness and sample size.
• Participant recruitment: determine sample size (estimated based on effect size and statistical power); develop inclusion/exclusion criteria (age, handedness, vision/hearing, neuropsychiatric history); recruit participants (advertisements, recruitment platforms, course credit); obtain informed consent; collect demographic information and screening questionnaires
• Behavioral data collection: conduct behavioral experiments in standardized lab environment—keep quiet environment, appropriate lighting, consistent equipment; use professional response devices (button box, foot pedal); record reaction time, accuracy, eye movement data; experimenter remains neutral; record abnormalities during experiment
• Neuroimaging data acquisition (if applicable): EEG/ERP recording—use conductive gel to reduce electrode impedance (<5kΩ); set sampling rate (500-1000Hz); record reference and ground electrodes; fMRI acquisition—use standard head coil; acquire structural (T1-weighted) and functional (EPI) images; monitor head motion; record physiological signals (respiration, heartbeat)
Deliverable: Experimental dataset (behavioral data files, raw EEG/fMRI data, participant information table, experiment records, quality check report) | Quality standard: Sufficient sample size, standardized data collection, strict quality control, complete and reliable data
Step 4
Behavioral Data Analysis and Neuroimaging Data Processing
The core task of this step is to systematically process and statistically analyze behavioral and neuroimaging data, revealing behavioral and neural mechanisms of cognitive processes.
• Behavioral data analysis: use R, SPSS, or Python for statistical analysis of behavioral data—reaction time analysis (outlier removal, mean RT calculation), accuracy analysis, signal detection theory analysis (d', β); perform repeated measures ANOVA, t-tests, correlation analysis; draw behavioral result graphs
• ERP data analysis (if applicable): use EEGLAB, BrainVision Analyzer for ERP analysis—data preprocessing (filtering, re-referencing, EOG/EMG artifact removal, epoching, baseline correction, averaging); select ERP components (N1, P2, N2, P3, N400, LPC); measure amplitude and latency; perform statistical analysis
• fMRI data analysis (if applicable): use SPM, FSL, or AFNI for fMRI analysis—data preprocessing (slice timing, motion correction, spatial normalization, smoothing); build general linear model (GLM); perform task-state analysis (condition activation contrasts), functional connectivity analysis, MVPA; perform multiple comparison correction
Deliverable: Data analysis results (behavioral statistical results, ERP component analysis/fMRI brain activation maps, statistical parametric maps, result tables) | Quality standard: Correct and standard analysis methods, reliable and reproducible results, clear and professional visualization
Step 5
Cognitive Neural Mechanism Analysis and Research Report Writing
The core task of this step is to comprehensively analyze neural mechanisms of cognitive processes based on behavioral and neural data, and write a complete research report. Integrate behavioral and neuroimaging results.
• Cognitive neural mechanism integration: synthesize behavioral data and neuroimaging results; analyze neural mechanisms of cognitive processing—temporal course (processing stages reflected by ERP component sequences), spatial localization (functional significance of fMRI-activated brain regions), brain networks (brain region collaboration reflected by functional connectivity); build neural model of cognitive processing
• Write research report: follow cognitive neuroscience paper standards—abstract, introduction (cognitive theory + neural basis), materials and methods (participants, stimuli, equipment, procedure, data analysis methods), results (behavioral + neural results, presented in subsections), discussion (relationship to theory, comparison with previous studies, neural mechanism interpretation, limitations), conclusion, references; minimum 4000 words
• Create result figures: produce high-quality cognitive neuroscience figures—behavioral result statistics, ERP waveforms (topographic maps), fMRI activation maps (glass brain, slice views, 3D rendering), cognitive neural model diagrams; standard figure annotations meeting academic publication standards
Deliverable: Cognitive neuroscience research report (PDF format with complete research content, high-quality brain maps, in-depth mechanism discussion), data and code attachments | Quality standard: Complete report structure, reliable data, in-depth mechanism analysis, insightful discussion, professional and standard format