You are viewing a free preview of this lesson.
Subscribe to unlock all 10 lessons in this course and every other course on LearningBro.
Almost everything biological psychology claims about aggression, localisation and the working brain rests on our ability to look inside a living skull. For most of history that was impossible: knowledge of brain function came from post-mortem dissection and from the tragic natural experiments of brain injury, such as Phineas Gage. The development of neuroimaging — techniques that visualise the structure and, crucially, the activity of the living brain — transformed the discipline into a genuine science of the mind. This lesson examines the four families of technique the Edexcel specification expects you to understand: CAT (CT) scans, PET scans, fMRI, and the electrical methods EEG and ERPs. For each we ask three questions that are the key to every exam answer: how does it work?, what is its spatial and temporal resolution?, and what are its strengths and limitations? Mastering the trade-offs between these methods — and understanding why Raine's classic study needed PET specifically — is what lets you evaluate biological evidence rather than merely describe it.
Key Definition: Neuroimaging refers to techniques that produce images of the structure or function of the living brain. Structural techniques (CAT, structural MRI) show anatomy; functional techniques (PET, fMRI, EEG, ERP) show activity over time.
This lesson addresses Edexcel 9PS0 — Paper 1, Topic 3: Biological Psychology, specifically the requirement to understand ways of studying the brain, including scanning techniques and their use in investigating the biological basis of behaviour. It develops AO1 (knowledge of how CAT, PET, fMRI, EEG and ERP work and what each measures), AO2 (selecting the appropriate technique for a given research question and applying it to studies such as Raine et al.) and AO3 (evaluating the techniques through the twin lenses of spatial and temporal resolution, and weighing invasiveness, cost and validity).
Connects to…
Before the individual methods, fix the two measurement dimensions on which they all trade off, because almost every evaluation point reduces to one of them.
The deep truth of neuroimaging is that no single technique is best on both dimensions. The electrical methods win on time but lose on space; the blood-flow methods win on space but lose on time. Knowing this trade-off is the evaluation.
Why does the trade-off exist at all? It is not an arbitrary limitation but a consequence of what each method actually measures. The electrical methods (EEG, ERP, MEG) tap the near-instantaneous electrical signalling of neurons, which is why their timing is superb; but that signal is recorded at a distance (the scalp), summed and blurred across millions of neurons and, for EEG, distorted by the skull, which is why their localisation is poor. The blood-flow methods (PET, fMRI) instead track the metabolic consequences of neural activity — glucose use, changes in blood oxygenation — which can be pinpointed in space to a millimetre or two, but which unfold seconds after the firing they reflect (the sluggish haemodynamic response), which is why their timing is poor. In short, fast electrical signals localise badly; well-localised metabolic signals are slow. Recognising that the trade-off is rooted in the physiology being measured — not just a table to memorise — is what lets you explain, rather than merely assert, why a given study is blind on one dimension.
A CAT scan (also CT, computerised tomography) passes multiple X-ray beams through the head from different angles; a computer combines the absorption data into cross-sectional images ("slices") of the brain. Denser tissue (bone, and abnormal masses such as tumours) absorbs more radiation and shows up lighter, so CAT reveals the brain's structure in detail.
CAT is fundamentally a structural technique: it shows anatomy, not activity. Its strengths are that it produces clearer images than a plain X-ray, is relatively quick and less expensive than MRI, and is invaluable clinically for detecting structural abnormalities — tumours, bleeds, and the damage left by a stroke or head injury. Its limitations are significant for psychology: it exposes the patient to ionising radiation (more than a standard X-ray), it provides only a static structural snapshot with no functional information, and its spatial resolution, while good, is inferior to MRI. For a psychologist interested in which regions are active during a task, CAT is of little use; its role is to map lesions and gross abnormalities.
A PET scan is a functional technique that measures metabolic activity. The participant is injected with a radioactive tracer — most commonly a form of glucose labelled with a positron-emitting isotope (fluorodeoxyglucose, FDG). Because active neurons consume glucose, the tracer accumulates in the busiest regions. As the isotope decays it emits positrons that collide with electrons, producing gamma rays the scanner detects; a computer maps their origin, producing a colour-coded image in which "hotter" colours indicate greater metabolic activity. PET therefore shows which regions are working hardest during a task.
PET's great strength is that it images function, revealing patterns of activity underlying cognition and behaviour, and it was historically important — it was the first widely used functional method and remains valuable in research on neurotransmitter systems and in oncology. This is exactly why Raine et al. (1997) used PET: they needed to compare glucose metabolism in the prefrontal cortex and limbic structures of murderers and controls while they performed a task, and PET measures precisely that.
PET's limitations, however, are serious. It is invasive, requiring injection of a radioactive tracer, which limits how often a person can be scanned and rules out many participants (e.g. pregnant women). Its temporal resolution is poor (activity is averaged over tens of seconds to a minute or more, as the tracer accumulates), so it cannot track fast cognitive events. Its spatial resolution is moderate — better than EEG but inferior to fMRI. And PET is expensive and requires an on-site cyclotron to make the short-lived isotopes. For most modern functional research, fMRI has largely superseded it — but Raine's study, conducted in the mid-1990s, reflects the technology of its time.
fMRI is the workhorse of modern cognitive neuroscience. It exploits the fact that active neurons demand more oxygen, delivered by increased blood flow. Oxygenated and deoxygenated haemoglobin have different magnetic properties, so a powerful magnetic field can detect the changing ratio — the BOLD signal (Blood-Oxygen-Level-Dependent). By tracking where blood oxygenation rises during a task, fMRI produces a dynamic, three-dimensional map of brain activity.
fMRI's strengths are considerable. It has excellent spatial resolution (around 1–2 mm), the best of the functional techniques, so it can localise activity to small structures. Critically, it is non-invasive — no radiation, no injection — so participants can be scanned repeatedly, including children and healthy volunteers, which vastly widens the research it enables. It produces clear images of both structure and function.
Its limitations centre on time and interpretation. Its temporal resolution is poor (around 1–4 seconds), because the haemodynamic (blood-flow) response lags several seconds behind the neural activity it reflects, so fMRI cannot capture the millisecond dynamics of neural firing. It is expensive, and requires the participant to lie very still in a noisy, enclosed scanner, which can be difficult and unrepresentative of real-world cognition. Most subtly, fMRI measures blood flow as a proxy for neural activity, not neural activity directly, and interpreting an active region as responsible for a behaviour risks the error of reverse inference — inferring a mental process from a pattern of activation. These are precisely the AO3 points that distinguish a strong evaluation.
Where PET and fMRI infer activity from blood flow, EEG (electroencephalography) measures the brain's electrical activity directly. Electrodes placed on the scalp record the summed electrical potentials of large populations of neurons, producing a trace of brainwaves. EEG is invaluable for studying overall states of arousal — it defines the stages of sleep, detects the abnormal activity of epilepsy, and tracks the rhythms (alpha, beta, delta, theta) that index wakefulness and drowsiness.
An ERP (event-related potential) is derived from EEG. A single EEG trace is too noisy to reveal the brain's response to a specific stimulus, so the stimulus is presented many times and the EEG segments are averaged together. Averaging cancels the random background noise and leaves the small, consistent electrical response evoked by the stimulus — the ERP. Specific ERP components (such as the P300, a positive deflection ~300 ms after a stimulus) are linked to particular cognitive processes such as attention and decision-making.
The electrical methods' outstanding strength is temporal resolution: they resolve activity to the millisecond, tracking the brain's response as it unfolds in real time — something neither PET nor fMRI can do. They are non-invasive and comparatively cheap. Their crippling limitation is spatial resolution: because the signal is recorded at the scalp, summed across many neurons and blurred by the skull, EEG/ERP cannot say precisely where in the brain the activity originates. They are also poor at detecting activity in deep structures. In short, EEG/ERP tells you when with superb precision but where only crudely — the mirror image of fMRI.
The table crystallises the trade-offs that drive every evaluation.
| Technique | Type | Measures | Spatial resolution | Temporal resolution | Invasive? | Key use |
|---|---|---|---|---|---|---|
| CAT / CT | Structural | X-ray density (anatomy) | Good | None (static) | Radiation | Detecting tumours, bleeds, lesions |
| PET | Functional | Glucose metabolism | Moderate | Poor (tens of s) | Radioactive tracer | Metabolic activity (e.g. Raine 1997) |
| fMRI | Functional | Blood oxygenation (BOLD) | Excellent (~1 mm) | Poor (~1–4 s) | Non-invasive | Localising task activity |
| EEG | Functional | Electrical activity | Poor | Excellent (~1 ms) | Non-invasive | Sleep stages, epilepsy, arousal |
| ERP | Functional | Averaged evoked potentials | Poor | Excellent (~1 ms) | Non-invasive | Timing of cognitive processes |
The recurring lesson is the space–time trade-off: fMRI buys spatial precision at the cost of temporal precision; EEG/ERP does the reverse. A researcher chooses the technique that matches the question — where is served by fMRI, when by ERP, metabolic activity over a whole task by PET, and structural abnormality by CAT or structural MRI.
Beyond EEG and ERP, a fourth electrical technique deserves mention because it partly overcomes their central weakness. Magnetoencephalography (MEG) measures the tiny magnetic fields produced by the electrical currents of firing neurons, using extremely sensitive detectors (SQUIDs) cooled to near absolute zero. Like EEG, MEG measures neural activity essentially directly and therefore keeps EEG's outstanding temporal resolution — resolving activity to the millisecond. Its advantage is spatial resolution: because magnetic fields, unlike electrical potentials, pass through the skull and scalp with little distortion, MEG localises the source of activity far more accurately than scalp EEG can. This makes MEG a valuable tool where a researcher needs both good timing and reasonable localisation — for example, tracing the millisecond-by-millisecond flow of activity between identified regions during a rapid cognitive task.
MEG's limitations are practical. It is very expensive and technically demanding, requires a magnetically shielded room to screen out the Earth's field and electrical interference, and is best at detecting activity in the superficial cortex rather than deep structures. It nonetheless illustrates an important point for evaluation: the space–time trade-off is not an iron law but a tendency that new technology can soften — MEG buys back much of the spatial information that ordinary EEG loses, without sacrificing temporal precision.
Because no single technique is strong on both spatial and temporal resolution, the most powerful modern designs deliberately combine methods so that each covers the other's blind spot. This is multimodal imaging, and reasoning about it explicitly is a reliable way to demonstrate top-band understanding of the space–time trade-off rather than merely stating it.
Subscribe to continue reading
Get full access to this lesson and all 10 lessons in this course.