Topic C: Biological psychology AS
- Syllabus
- 2026
- Topic
- —
- Level
- AS
The central nervous system (CNS) consists of the brain and spinal cord. It receives information from sensory systems, integrates it and sends signals that coordinate responses. Neurons carry information within this system; neurotransmitters carry a chemical signal across the tiny gap between neurons.
| Part | Role in signalling |
|---|---|
| Dendrites | receive signals from other neurons |
| Cell body | integrates incoming signals and maintains the cell |
| Axon | carries an electrical impulse away from the cell body |
| Terminal buttons | release neurotransmitter from vesicles |
| Receptors on the next neuron | bind particular neurotransmitters and alter the likelihood that it will fire |
When an impulse reaches a terminal, vesicles release neurotransmitter into the synaptic cleft. Molecules diffuse across, bind to matching receptors and can excite or inhibit the postsynaptic neuron. The transmitter is then removed, for example by reuptake or enzymatic breakdown, so the signal is controlled rather than remaining permanently active.
A neurotransmitter does not create one fixed behaviour by itself. Its effect depends on receptor type, brain circuit, dose and context, so evidence linking serotonin or dopamine with behaviour is an association within a larger system, not a one-chemical explanation.
Aggression is linked to coordinated brain systems for threat, emotion and control. The prefrontal cortex helps evaluate consequences and inhibit impulsive responses; limbic structures help detect emotionally significant events and organise defensive responses.
| Area | Relevant function | Possible link with aggression |
|---|---|---|
| Prefrontal cortex | planning, judgement and impulse control | reduced or disrupted function may weaken inhibition of an aggressive response |
| Amygdala | evaluates threat and emotional salience | atypical activation or damage may distort threat processing or emotional regulation |
| Hypothalamus | coordinates autonomic and hormonal responses | altered regulation may change readiness for fight-or-flight responses |
| Wider limbic network | connects emotion, memory and bodily response | disruption can affect how a situation is interpreted and acted upon |
Brain scans and lesion cases can show that activity or damage is associated with aggression. Raine et al. found group differences across several regions in murderers who pleaded not guilty by reason of insanity, including reduced prefrontal activity. The pattern supports a network account rather than a single 'aggression centre'.
A brain difference does not prove that it caused violent behaviour: experience, injury, substance use and social environment may also affect both brain function and aggression. Biological differences are best treated as possible predispositions interacting with context.
Hormones and genes can influence systems involved in arousal, threat and impulse control, but they do not make aggression inevitable. Their effects vary with development, situation and learning.
| Factor | Proposed link | Evidence boundary |
|---|---|---|
| Testosterone | can alter development and activity in circuits involved in competition and threat | correlations cannot show whether testosterone raises aggression, aggression raises testosterone, or context affects both |
| Cortisol | helps regulate stress and arousal; unusually low or high patterns have been associated with aggression | findings differ across samples and types of aggression |
| MAOA | the gene codes for an enzyme that breaks down monoamine neurotransmitters | low-activity variants are associated with greater aggression especially under strong provocation or adversity, not in every carrier |
| Genetic relatedness | higher similarity in MZ than DZ twins can indicate genetic influence | shared treatment and environments can also increase similarity |
A useful model is gene-environment interaction: a biological variant may change sensitivity to provocation, while the environment supplies the trigger and the learned response options. McDermott et al. found the clearest MAOA group difference under high monetary provocation, illustrating this conditional effect.
Do not describe MAOA-L as an 'aggression gene' or infer a simple serotonin direction from genotype alone. The gene affects an enzyme within a developmental neurotransmitter system; observed behaviour remains probabilistic and multi-causal.
The sleep-wake cycle is circadian: it repeats roughly every 24 hours. An internal pacemaker produces the rhythm, while external zeitgebers provide time cues that synchronise it to the environmental day.
| Component | Timing role |
|---|---|
| Suprachiasmatic nucleus (SCN) | the main pacemaker in the hypothalamus; receives information about light from the eyes and coordinates daily rhythms |
| Pineal gland and melatonin | the SCN influences melatonin release; darkness usually increases melatonin and promotes biological night |
| Light-dark cycle | the strongest external zeitgeber; shifts the clock so it remains aligned with local day and night |
| Social routines, meals and clocks | additional cues that can help organise waking and sleeping times |
After night work or rapid travel, the internal clock can remain aligned with the previous light schedule. Morning light may suppress melatonin and raise alertness just when a night worker is trying to sleep. Timed light and regular routines can gradually shift the rhythm.
Light does not simply switch sleep on or off. Sleep pressure, behaviour and other cues also matter, and an internal rhythm can continue without daylight but usually drifts away from exactly 24 hours.
An infradian rhythm has a period longer than 24 hours. The menstrual cycle and the seasonal pattern of seasonal affective disorder (SAD) are examples, but each involves different biological processes.
| Rhythm | Main pattern | Important mechanism or boundary |
|---|---|---|
| Menstrual cycle | ovarian and uterine changes recur over about a month, with normal variation between people and cycles | changing oestrogen and progesterone coordinate ovulation and preparation or shedding of the uterine lining; behaviour cannot be predicted from cycle phase alone |
| Seasonal affective disorder | depressive episodes recur in a seasonal pattern, commonly during winter | shorter daylight may alter circadian timing, melatonin and serotonin-related systems; diagnosis requires a recurring clinical pattern, not ordinary dislike of winter |
Bright-light therapy aims to replace a missing seasonal light cue. A person typically uses a suitable light box in the morning on a regular schedule; light shifts circadian timing and can reduce excessive daytime melatonin-related sleepiness. Treatment strength, timing, eye or medication risks and professional advice matter.
Light therapy can reduce symptoms but is not a guaranteed cure, and social conditions or other biological factors can also contribute to SAD. Claims that menstrual cycles synchronise through pheromones remain contested and should not be treated as an established rule.
Research on bodily rhythms must separate an internally generated cycle from the environmental cues that reset it. Different methods provide complementary evidence, but each leaves a different alternative explanation.
| Research example | What it contributes | Main limitation |
|---|---|---|
| Siffre cave isolation | a sleep-wake rhythm continued without normal time cues and drifted from 24 hours, supporting an endogenous clock plus zeitgeber adjustment | an unusual setting and very small sample limit generalisation |
| SCN manipulation in animals | changing or damaging the SCN changes circadian timing, supporting a causal pacemaker role | invasive animal findings may not transfer completely to human sleep |
| Timed bright-light studies | experimentally timed light can shift human circadian rhythms, supporting light as a zeitgeber | artificial schedules may not represent everyday exposure |
| Menstrual/SAD field and treatment studies | repeated measures, seasonal comparisons and light-treatment outcomes connect infradian patterns with behaviour | self-report, confounds and correlations often prevent a single causal conclusion |
Judge a claim by design: an experiment can strengthen causal inference through manipulation and control; a case study provides depth; a correlation or longitudinal study shows association and change over time. Replication across methods is stronger than one dramatic finding.
A rhythm continuing in isolation does not mean external cues are unimportant, and a seasonal association does not prove light is the only cause. Internal and external controls normally operate together.
A correlation measures whether two co-variables vary together. Neither co-variable is manipulated, so the method describes a relationship rather than an experimental effect.
| Design decision | Example: sleep and exercise |
|---|---|
| Co-variable 1 | average hours of sleep per night recorded for seven days |
| Co-variable 2 | minutes of moderate-to-vigorous exercise recorded per week |
| Paired cases | both measurements must come from the same participant |
| Hypothesis | there will be a relationship between weekly exercise minutes and average nightly sleep hours in the sampled students |
Correlations are useful when variables occur naturally or cannot ethically be manipulated, such as age, hormone level or sleep habits. Operational definitions, a suitable sample and a consistent procedure make the measurements replicable. A scatter diagram and correlation coefficient then show direction and strength.
Calling one co-variable an IV and the other a DV wrongly implies causation. A directional hypothesis predicts a positive or negative relationship; a non-directional hypothesis predicts a relationship without choosing its direction.
A scatter diagram plots one paired score as one point. The overall pattern shows the direction and approximate strength of a relationship; the axes do not decide which variable causes the other.
| Pattern | Interpretation |
|---|---|
| Points rise from left to right | positive correlation: higher values of one co-variable tend to accompany higher values of the other |
| Points fall from left to right | negative correlation: higher values of one tend to accompany lower values of the other |
| No clear upward or downward pattern | zero or very weak correlation |
| Points lie close to a monotonic trend | stronger relationship |
| Points are widely dispersed | weaker relationship |
Give the graph an informative title, label both axes with the operationalised co-variable and unit, choose a scale that uses the plotting area, and plot every paired score accurately. Inspect possible outliers because one unusual case can change the apparent pattern and the coefficient.
Positive does not mean beneficial and negative does not mean absent. A curved relationship can be strong even if a rank or linear summary is small, so always inspect the scatter before relying on one coefficient.
A correlation cannot establish cause and effect because its design does not manipulate one variable while controlling alternatives. Two main uncertainties remain even when the coefficient is strong.
| Issue | Example: screen time and sleep |
|---|---|
| Directionality | more screen time might reduce sleep, or people who cannot sleep might use screens for longer |
| Third variable | workload, stress or household routine might increase screen use and reduce sleep |
| Measurement validity | estimated screen time or sleep may be inaccurate, creating or hiding a relationship |
| Sample restriction | a narrow range of ages or habits can weaken or distort the observed association |
Strengthen interpretation by measuring plausible third variables, using validated or objective measures, sampling a wider relevant population and following participants over time. A controlled experiment can test a causal hypothesis when manipulation is ethical, but it answers a narrower question than the original natural correlation.
Statistical significance means the sample relationship would be unlikely under the null model at the chosen threshold. It does not remove directionality, confounding, bias or poor operationalisation.
Spearman's rank correlation coefficient, rs, tests the strength and direction of a monotonic relationship between paired scores measured at least at the ordinal level. It is appropriate when the research question is correlational and the scores can be ranked.
r_s=1-\frac{6\sum d^2}{n(n^2-1)}
d is the difference between a case's two ranks and n is the number of paired cases. Rank both co-variables in the same direction, give tied scores their mean rank, calculate each d and d2, sum d2, then substitute and sense-check that −1≤rs≤1. The sign gives direction; closeness to 1 or −1 gives strength.
| Decision | Rule |
|---|---|
| Tail | use one-tailed only when a direction was justified before viewing results; otherwise use two-tailed |
| Significance level | choose the probability threshold in advance, commonly p≤.05 |
| Critical comparison | a result is significant when ∣rs∣ is equal to or greater than the table's critical value for n and the chosen tail |
| Conclusion | state direction, strength, significance and the operationalised co-variables; reject or fail to reject the null |
A significant rs does not prove causation or practical importance. A stricter threshold such as p≤.01 reduces Type I risk but increases Type II risk when sample size and effect stay the same.
Brain-scanning techniques differ in what they measure. CAT is mainly structural; PET and fMRI can index function. The technique must match the research question, safety constraints and required detail.
| Technique | Signal and output | Strength | Limitation |
|---|---|---|---|
| CAT/CT | multiple X-rays reconstructed into cross-sectional or 3D structural images | identifies gross structural damage or abnormality | ionising radiation; does not directly show moment-to-moment neural activity |
| PET | detects a radioactive tracer associated with metabolism or blood flow | maps functional activity and was used by Raine et al. | invasive tracer, relatively poor temporal resolution and limited repeat use |
| fMRI | uses magnetic fields to measure the BOLD blood-oxygen response | non-ionising functional images with good spatial resolution | indirect and delayed measure of neural activity; movement and metal safety matter |
To study aggression, researchers can compare activity in specified regions during a standard task or compare groups with carefully matched controls. Operationalising the task, pre-registering regions and using blind, consistent analysis reduces selective interpretation.
A coloured activation map is not a photograph of an aggressive thought. Scans require processing and interpretation, and group differences do not show that a brain region alone caused behaviour.
Twin studies compare similarity in monozygotic (MZ) twins, who share virtually all their segregating genes, with dizygotic (DZ) twins, who share on average about half. If MZ aggression is more concordant than DZ aggression, genetic influence is plausible.
| Step | Design decision |
|---|---|
| Define aggression | use the same observable rating, record or questionnaire for every twin |
| Establish zygosity | prefer genetic testing; appearance-based classification can mislabel pairs |
| Measure concordance | record whether both members show the defined outcome or correlate continuous aggression scores |
| Compare groups | use comparable MZ and same-sex DZ pairs and examine genetic, shared and non-shared environmental contributions |
A higher MZ similarity supports heritability within the studied population and environment. Shared environmental influence makes twins alike; non-shared experiences and measurement error make them differ. Brendgen et al. used peer and teacher ratings to compare physical and social aggression in six-year-old twins.
MZ twins may be treated more similarly than DZ twins, so the equal-environments assumption needs scrutiny. Heritability is not the percentage of one person's behaviour caused by genes, and it does not mean a trait cannot change.
List A provides the descriptive tools used across psychology. Choose a summary from the data type and distribution rather than calculating every statistic available.
| Analytical job | Appropriate choice |
|---|---|
| Typical score | mean for balanced interval/ratio data; median for ordered or skewed data; mode for the most frequent score or category |
| Spread | range for total span; standard deviation for dispersion around the mean |
| Organise | frequency table for counts; summary table for condition or variable statistics |
| Display | bar chart for separate categories; histogram for continuous intervals with touching bars |
| Part of a whole | percentage, ratio or fraction with the denominator made clear |
| Shape | normal distribution is symmetrical; positive skew has a long right tail, negative skew a long left tail |
| Qualitative meaning | code relevant material, develop and review themes, then support each theme with anonymised evidence |
Label tables and axes, retain units, check totals and denominators, and inspect unusual scores before choosing the mean or standard deviation. Descriptive statistics summarise the sample; they do not show whether a relationship or difference is statistically significant.
A reliable calculation can still misrepresent unsuitable data. The mean is distorted by extreme scores, a histogram is not a bar chart with decorative gaps, and a theme is a patterned meaning rather than a frequently repeated word.
Raine et al. tested whether people charged with murder or manslaughter who pleaded not guilty by reason of insanity (NGRI) showed different brain functioning from matched controls.
The study compared 41 NGRI participants (39 men and 2 women) with 41 controls matched on sex and similar characteristics. Participants completed a 32-minute continuous performance task after receiving a glucose tracer, then underwent PET scanning. Regional glucose metabolism was compared with cortical-peel and region-of-interest methods.
| Finding | Bounded interpretation |
|---|---|
| lower activity in prefrontal and parietal regions | may relate to weaker behavioural control or information processing |
| greater occipital activity | a group difference, not a direct aggression mechanism |
| left-right imbalances in amygdala, hippocampus and thalamus | supports involvement of a wider emotional network |
| lower corpus-callosum activity; no temporal or CPT performance difference | violence cannot be reduced to one region or general task failure |
PET provided objective physiological data and matching reduced several participant differences. However, the selected NGRI sample is not representative of all murderers, the CPT was not an aggressive task, medication history and diagnosis complicate interpretation, and the design cannot show that brain differences caused the offences.
The safest conclusion is that multiple brain differences may predispose some people to violent behaviour in combination with social, psychological and environmental factors—not that a scan identifies a murderer.
Brendgen et al. asked whether genetic, shared-environment and non-shared-environment influences differ for physical aggression and social aggression in six-year-old twins.
The longitudinal Montreal sample included 234 twin pairs. Same-sex twins were classified for zygosity mainly from physical resemblance at 18 months, with a proportion checked using DNA. At age six, peers selected photographs matching behavioural descriptions, while teachers completed established social and physical aggression scales. Parents provided written consent.
| Outcome | Teacher ratings | Peer ratings |
|---|---|---|
| Physical aggression variance | 63% genetic, 37% non-shared environment | 54% genetic, 46% non-shared environment |
| Social aggression variance | 20% genetic, 20% shared environment, 60% non-shared environment | 23% genetic, 23% shared environment, 54% non-shared environment |
Agreement across peer and teacher methods strengthens reliability, and the large twin sample permits genetic modelling. Yet appearance-based zygosity can be wrong, peers may nominate after recent conflict, ratings do not directly observe every act, and six-year-old mostly European-descent Montreal twins limit age and cultural generalisation.
Physical aggression showed a larger genetic contribution, whereas social aggression was more strongly influenced by environmental factors, especially experiences not shared by the twins. The study supports different influence patterns, not genetic determination.
McDermott et al. tested whether MAOA activity predicts costly aggressive punishment and whether its effect changes with environmental provocation.
Genetic samples from 78 male participants classified them as high-activity (MAOA-H) or low-activity (MAOA-L). In four rounds of a power-to-take game, a fictional opponent removed either 20% or 80% of money earned on a vocabulary task. Participants could pay to give that opponent unwanted hot sauce; whether and how much they allocated operationalised aggression.
| Outcome | 20% taken | 80% taken |
|---|---|---|
| gave some sauce: MAOA-H | 34% | 62% |
| gave some sauce: MAOA-L | 40% | 75% |
| gave maximum sauce: MAOA-H | 6% | 19% |
| gave maximum sauce: MAOA-L | 12% | 44% |
High provocation increased aggression overall, and the low-activity group responded most strongly when 80% was taken. This supports a gene-environment interaction: genotype altered sensitivity to provocation rather than producing the same behaviour in every situation.
The all-male sample and artificial punishment task limit generalisation, and deception raises informed-consent issues. Hot-sauce allocation is a behavioural proxy, not real violence; the findings do not justify labelling a person aggressive from genotype alone.
Hoefelmann et al. compared cross-sectional and prospective links between lifestyle behaviours and self-reported sleep quality and duration in Brazilian high-school students.
The secondary analysis used data from students aged 14-24 in 20 public schools. Of 2,000 initially selected, 989 completed baseline and nine-month assessments; 949 supplied longitudinal sleep-quality data and 950 sleep-duration data. Closed questionnaire items measured activity, screen use, food, soft drinks, alcohol, perceived sleep quality and daily sleep duration.
| Measure | Baseline/cross-sectional | Nine-month/prospective |
|---|---|---|
| negative sleep quality | 45.7% | 45.8% |
| under 8 hours sleep | 76.7% | 77.5% |
| lifestyle finding | several behaviours were associated with sleep in cross-sectional analysis | after adjustment, no behaviour predicted sleep quality or duration |
Poor perceived sleep and insufficient duration were common and stable, but an association measured at one time did not become a prospective prediction. This contrast demonstrates why cross-sectional correlation is weak evidence of causal direction.
Self-report can be inaccurate and attrition may make completers differ from the original sample. The broad 14-24 age range and Brazilian public-school context limit generalisation. The study does not show that physical activity worsens sleep; adjusted and prospective results require the narrower conclusion.
A biological-psychology practical must test a relationship between two operationalised co-variables, gather paired quantitative data ethically and report association without claiming causation.
| Stage | Required decision and record |
|---|---|
| Aim and hypothesis | choose aggression or body rhythms; state the population, both measurements and a justified directional or non-directional relationship |
| Design | define both co-variables precisely, choose and justify sampling, standardise instructions and identify plausible other variables |
| Ethics | obtain informed consent, allow withdrawal, protect confidentiality, minimise sensitive or harmful content and debrief |
| Collection | obtain both scores from each participant; use the same questionnaire, scale, device, timing and scoring rules |
| Description | present a data table, suitable central tendency and dispersion, and a scatter diagram with title, labelled axes and all paired points |
| Inference | rank both variables, calculate rs, state n, tail and p, compare ∣rs∣ with the critical value, then interpret direction, strength and significance |
| Report | write a replicable procedure, factual results and a discussion with conclusion, strengths, weaknesses and targeted improvements |
Suitable questions include the relationship between daily social-media time and average nightly sleep, or height in centimetres and a score from an established self-rated aggression scale. A diary or device can improve sleep-time validity; anonymous responses can reduce social-desirability pressure for aggression.
A significant correlation supports a relationship in the sample, not that one co-variable caused the other. Improvements must repair an identified weakness—for example measurement validity, sampling or a third variable—rather than merely changing the study.