Sensation & Perception: The Brain's Best Guess

Where is the hole in your vision? There is one in each eye, where the optic nerve leaves the retina and no receptors can detect light. At arm's length it is roughly the size of a tangerine. You never notice. The brain fills it in with the surroundings and gives you a seamless picture.

That filling-in is the whole subject in miniature. The eye reports a flickering, blurred, upside-down image at the back of the eyeball; the brain delivers a steady, sharp, three-dimensional world with colours and objects. Between the two is inference. Someone who has taken a sensation and perception course never again thinks of seeing as a camera.

Transduction: every sense starts by making spikes

The senses differ in what they detect but share a first step, transduction: a receptor cell turns a physical event into an electrical change, and from there the message travels as spikes (see Biological Psychology, 35/20). Light bends a molecule in a photoreceptor; sound waves bend hair cells in the inner ear; pressure opens channels in a touch receptor; odour molecules bind to receptors in the nose. The brain only ever receives spikes, and learns what they mean.

Sense	Receptor	What it detects
Vision	Rods and cones in the retina	Light intensity and wavelength
Hearing	Hair cells in the cochlea	Air-pressure waves
Touch	Mechanoreceptors in skin	Pressure, vibration, stretch
Smell and taste	Chemoreceptors	Molecules
Balance	Hair cells in the inner ear	Head acceleration

The first stage is astonishingly sensitive. In 1942 Selig Hecht, Shlaer and Pirenne had people sit in the dark and report flashes. Their results suggested that a rod cell can respond to a single photon, and that seeing a faint flash takes only about 5 to 14 photons being absorbed in the retina. The human eye has roughly 120 million rods, for dim light, and about 6 million cones, for detail and colour.

Thresholds and Weber's law: noticing ratios

How faint a light can you see? That is the absolute threshold. How much must something change before you notice? That is the just noticeable difference, the JND. Ernst Weber found in the 1830s that the JND is not a fixed amount. It is a fixed fraction of what you started with. Lift 100 grams and you notice an extra 2 g; hold a 1 kg bag and you need about 20 g more. Gustav Fechner built the field of psychophysics on that in 1860.

A 10 kg load needs about 200 g more before you feel it. Fechner turned the idea into a rule that sensation grows with the logarithm of the stimulus. Later S. S. Stevens argued that a power law fits many senses better, with the exponent differing by sense (about 0.6 for loudness and 3.5 for electric shock). Weber's law fails at the extremes of intensity, but it is a good first guess and explains why a candle is bright at night and invisible at noon.

Signal detection: every "did I see it?" is a decision

Weber and Fechner assumed a fixed threshold: below it you see nothing, above it you do. Real detection is noisier. A radiologist looks for a faint shadow, a lifeguard for a swimmer in trouble, a screener for a knife on a scan. The brain's internal signal fluctuates even when nothing is there, so on some nothing-trials it looks like something. Two things then decide what you say: how well the real signal stands out from the noise, and how willing you are to say "yes".

Signal detection theory, developed in the 1950s and used in psychology by David Green and John Swets (1966), separates them. Sensitivity, d′, is the distance between the "noise" and "signal" distributions in standard-deviation units. The criterion is the internal cut-off for saying yes. Move the cut-off and you trade hits for false alarms without changing sensitivity at all.

With d′ = 1.7 and a balanced cut-off you get about 80% hits and 20% false alarms. Push the cut-off up and false alarms fall to 3%, but hits fall to 44%. The same observer with the same eyes is either a nervous or a lax judge, and a manager who punishes only misses will get more false alarms. The same model describes medical tests, eyewitness line-ups and spam filters.

Colour vision: three detectors, millions of colours

Colour is not in the light. Light has wavelengths; colour is what the brain makes of how three kinds of cone cells respond. Thomas Young proposed three receptors in 1802. We now know them as the S, M and L cones, tuned roughly to 420, 530 and 560 nm. Their sensitivities overlap heavily, so every light produces a triple of responses, and the brain compares them.

A key consequence: different mixtures of light can give identical triples. Those are metamers, and you look at them on every screen: a display has only red, green and blue lights, yet it shows yellow, because red plus green light excites the L and M cones in the same proportion as pure yellow light. The cones cannot tell the difference.

In the model a mix of 540 nm and 640 nm light matches yellow at 580 nm exactly, but for blue-green at 500 nm no match exists, because you would need a negative amount of red. Real colour-matching experiments found the same, and in them an observer could match by adding red to the target instead. About one man in twelve and one woman in two hundred (of northern European ancestry; rates are lower elsewhere) have red-green deficiency, because the L and M cone pigments are alike or one is missing, so more lights become metamers to them.

The brain's guesses: illusions and predictive perception

The retinal image is ambiguous: the same image could come from a small near thing or a large far thing. The brain resolves it with assumptions built from experience. Hermann von Helmholtz called this unconscious inference in the 1860s. Modern versions, predictive processing, say perception is the brain's running prediction, corrected by incoming signals that report the error. Rao and Ballard proposed a model like this for visual cortex in 1999; Karl Friston, Andy Clark and Anil Seth have developed the wider case. Not everyone accepts that one principle explains the whole brain, and critics say the framework is too flexible to test, but its picture of perception as inference is widely used.

Illusions are the clearest evidence, since they are what a sensible assumption does in an unusual case. Look at the two lines below: one has fins turned out, one turned in. Your task is to make them look equal.

When the lines are really equal (100%), they should look different. The leading explanation is that fins-out and fins-in look like the near and far corners of rooms and buildings, and size is judged accordingly. The illusion is weaker in some small-scale societies, which fits the idea that it depends on experience with carpentered corners, though explanations are debated. Henrich and colleagues used this example in their 2010 WEIRD paper (see Research Methods in Psychology, 35/19). Another demo is the blind spot itself.

Another famous case is the 2015 photograph of "the dress", which people saw as blue-and-black or white-and-gold. Research suggests the difference comes from assumptions about the lighting, which the brain subtracts, so it is a guess made from different priors. Same signal, two sensible inferences.

Attention: you see what you look for

You cannot process everything, so attention selects. In 1999 Daniel Simons and Christopher Chabris had viewers count basketball passes in a video; about half of them failed to notice a person in a gorilla suit walking through the middle. This is inattentional blindness. A related effect, change blindness, was shown by Ronald Rensink and colleagues in 1997. Flick between two pictures with a brief blank in between and big changes go unseen for many seconds, because the blank hides the motion that would have attracted attention.

With the blank, most people take several seconds to find a single colour change. Without it, the change jumps out at once, because the swap makes a visible flicker. Magicians know this: the brain skips what is not attended, and what it skips it fills in with a guess.

What a graduate just sees

• The brain gets spikes, not pictures. Seeing is inference from receptor signals.
• We notice ratios, not amounts: a change is judged relative to what was there.
• Detecting is deciding: sensitivity and criterion are different things, and a cautious judge is not a worse sensor.
• Colour is a three-number summary of light, so very different spectra can look identical.
• Illusions are good assumptions applied in unusual cases, and some depend on culture.
• There is a blind spot you never notice, filled in by the brain.
• What you do not attend to can be missed even in plain view.
• Be wary of "I saw it with my own eyes": the eyes are the first step of the inference.

Where it shows up next

• Cognitive Psychology (35/22): attention and memory are the next stages; eyewitness error is perception plus memory.
• Biological Psychology (35/20): the cortex's visual and auditory areas are the lesion cases that taught us where perception is built.
• Consumer Behavior (34/58): packaging, shelf position and colour choices work through attention and the assumptions above.
• Machine learning (34/32): vision models learn their own features, and "adversarial examples" are machine illusions.
• In the world: airport screening, radiology, road safety (looked but failed to see), display and audio design, hearing aids, colour-blind-friendly charts.

If you want to go deeper

• 📘 Textbook. Jeremy Wolfe and colleagues, Sensation & Perception (Oxford University Press / Sinauer, 7th edition, 2024). Widely assigned, clearly illustrated, with the dress discussion revised.
• 📘 Textbook. E. Bruce Goldstein and James Brockmole, Sensation and Perception (Cengage). The other standard syllabus text.
• 📘 Gentler. Anil Seth, Being You (2021): perception as "controlled hallucination", written for general readers. Contested in parts.
• 🌐 Free course. MIT OpenCourseWare 9.35 Sensation and Perception (Spring 2009).