Metacognition key concepts

Lecture 1: Introduction to Metacognition

• Metacognition: Thinking about thinking, knowing about knowing. Awareness of cognitive processes (strengths, weaknesses, strategies).
• Metacognitive Knowledge: Knowledge about cognition, encompassing learner variables (self-knowledge), task variables (task demands), and strategy variables (learning strategies).
• Metacognitive Regulation: Ability to control and adjust cognitive processes, strategies, and behaviors to improve learning and performance.
• Metacognitive Experiences: Feelings and judgments related to cognitive processes. (Knowing, confidence, confusion).
• Miscalibrated Metacognition: Inaccuracies in self-assessment of performance. Can lead to overconfidence or underconfidence.
• Better-Than-Average Effect: Most individuals rate themselves as above average compared to peers.
• Dunning-Kruger Effect: Individuals with low competence unaware of their shortcomings; inflate self-assessments.
• Regression to the Mean: Extreme scores tend to move closer to average on subsequent measurements.
• Bayesian Shrinkage: Statistical approach; adjusts estimates based on prior knowledge or beliefs.
• First-Order Performance: Actual performance/ability on a task.

Lecture 2: Measuring Metacognition

• Metacognitive Accuracy: Group-level characteristic ("better-than-average effect"). Doesn't reflect individual differences.
• Confidence Ratings: Quantifies individual metacognitive ability. How closely confidence ratings match actual performance.
• Metacognitive Performance: Composed of sensitivity (discriminate between correct/incorrect) and bias (overestimate/underestimate performance).
• Signal Detection Theory (SDT): Framework for understanding decision-making under uncertainty. Separates sensitivity from criterion (threshold).
• Type-1 SDT: Focuses on stimulus representation and behavior in decisions.
• Type-2 SDT: Applies SDT principles to metacognitive judgments.
• Meta-d' Model: Extends SDT to metacognitive judgments. Separates bias from sensitivity. Allows comparison of type 1 and type 2 performance.
• Metacognitive Efficiency: Ratio of meta-d' to d'. A value of 1 represents perfect efficiency.
• 2-Alternative Forced Choice (2-AFC): Paradigm. Participants choose between two options.
• Reverse Engineering of Metacognition (ReMeta): New approach; overcomes limitations of meta-d' model. Aim to measure metacognitive sensitivity and bias independent of type 1 performance.
• Metacognitive Information Theory (Meta-I): A new approach to quantify information about decision accuracy contained in confidence ratings. Non-parametric; doesn't rely on specific modeling assumptions.

Lecture 3: Metacognition & Psychopathology

• Anosognosia: Lack of awareness/insight in neuropsychiatry. Failure to recognize illness or deficits.
• Depressive Realism: Depressed individuals have more realistic inferences about themselves and the world than non-depressed individuals.
• Insight: Insight can be preserved in some domains but impaired in others. Correlation with low mood, and improves treatment adherence.
• Lack of Insight in Schizophrenia: Common in Schizophrenia; inability to recognize illness, compliance with treatment; incorrect attribution of symptoms to non-illness factors (delusions).
• Metacognitive Deficits: Key role in various psychiatric disorders. Include lack of awareness of disorder, specific symptoms, and impaired self-evaluation.

Lecture 4: Metacognition & Belief Structures

• Metacognitive Sensitivity: Accurately assessing the quality of one's knowledge & judgments.
• Metacognitive Bias: Systematic errors in metacognitive judgments (overconfidence or underconfidence).

Lecture 5: Neural Correlates of Metacognition

• Neural Correlates: Specific brain regions/activity patterns associated with specific cognitive functions, including metacognition.
• Lesion Studies: Examining cognitive abilities of individuals with brain damage (lesions) to infer the role of brain regions.
• Neuroimaging: Techniques (fMRI, EEG, MEG) to visualize/measure brain activity.
• fMRI: Measures brain activity by detecting changes in blood flow. Good spatial resolution; poor temporal resolution.
• EEG: Measures brain activity by recording electrical signals from the scalp. Excellent temporal resolution, limited spatial resolution.
• MEG: Measures brain activity by detecting magnetic fields produced by electrical currents in the brain. Good balance of spatial/temporal resolution.
• TMS: Non-invasive technique; uses magnetic pulses to stimulate/inhibit specific brain regions.
• Prefrontal Cortex (PFC): Higher-level cognitive functions (planning, decision-making, working memory). Implicated in metacognition.

Lecture 6

• Intrapersonal: Within the individual.
• Suprapersonal: Beyond the self or interactions with others.
• Cultural Origins Hypothesis: Development through cultural learning and interactions, not solely genetic inheritance.

Lecture 7 - 8

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• Focus on specifics rather than summarizing the text overall.

Lecture 9: Improving Metacognition

• Metacognition: Monitoring and controlling cognitive processes.
• Metacognitive Sensitivity: Accuracy in judging performance.
• Metacognitive Bias: Tendency to overestimate or underestimate.
• Metacognitive Efficiency: Combines sensitivity and performance, guiding behavior.
• Cognitive-Attentional Syndrome (CAS): Maladaptive cognitive processes contributing to distress.
• Metacognitive Therapy (MCT): Therapy focusing on modifying maladaptive beliefs and attention.
• Cognitive Behavioural Therapy (CBT): Focuses on identifying/changing maladaptive thought patterns.
• Focused Attention Meditation: Maintaining attention on a single object/sensation.
• Noradrenaline: Neurotransmitter involved with attention, arousal, and memory.
• Propranolol: Medication blocking noradrenaline effects.