Your Brain Responds to a Click Before You Know What It Is

An electrode on the crown of the head and a click repeated hundreds of times, every few seconds, for several minutes. The person doesn’t have to respond to anything or press any button. For a few years in the 1980s, several research teams believed that the wave the brain draws in response to that sound could say a great deal about the listener’s intelligence.

The story of that idea shows how research moves forward: a spectacular finding, replications that scale it back, and an underlying question that is still open.

The trick that lets you “see” a clean brain reaction

Psychologist Arthur Jensen devotes a section of The g Factor (1998) to the evoked potential, the brain’s electrical response to a specific stimulus, recorded without the person having to perform any task.

The starting problem is that brain electrical activity is full of “noise”: random activity that hides any clear signal in a single recording. The solution resembles the one used in radar and sonar:

• An electrode is placed on the top of the head, with reference electrodes on the earlobes.
• A brief stimulus, such as a click, is repeated at intervals of a few seconds for several minutes.
• A computer averages hundreds of fragments of brain activity, each one aligned to the exact instant of the stimulus.

What is random cancels out in the average, and what repeats on every trial becomes visible. The result is a clean wave, with characteristic peaks and troughs, reflecting how that brain processes a very simple stimulus.

The Hendricksons’ “string” measure

The most striking version of this line of work came from Donna and Alan Hendrickson in 1980, in the first volume of Personality and Individual Differences. Their idea was easy to state: measure the length of the contour of the averaged wave, as if laying a string over all its peaks and troughs. A more jagged, complex wave would correspond to a nervous system that transmits information with fewer errors.

With auditory stimuli, the correlations they reported between this “string length” and IQ were around 0.7, an extraordinarily high figure for any biological measure. Blinkhorn and Hendrickson (1982) later published another study in Nature pointing in the same direction.

Jensen discusses this work alongside that of Richard Haier and his team, who used flashes of light instead of sounds. Haier, Robinson, Braden and Williams (1983) also found a relationship between features of the visual wave and psychometric intelligence, and Robinson, Haier and colleagues published a replication the following year. The two cases should be kept apart: the click belongs to the Hendricksons’ auditory paradigm, while Haier’s studies are visual.

What happened next: the replications

This is the part that usually gets left out of summaries. When other laboratories repeated the procedure, the correlations dropped sharply:

• Vetterli and Furedy (1985) pointed out fundamental problems with both the string measure and the “transmission error” theory behind it. Later analyses also showed that string length depends largely on the amplitude of the wave, so it is unclear what it actually reflects.
• Barrett and Eysenck (1992), working at the same London Institute of Psychiatry where the paradigm had been developed, carried out an extensive study and could not reproduce the strength of the original relationship.
• Bates and colleagues (1995) found that the relationship changed, and even reversed, depending on whether the person was paying attention to the stimuli or not. The difference between the two conditions predicted IQ better than either one alone.

That last finding qualifies the idea of an “effortless” recording. The brain doesn’t react in the same way to a sound it is listening to and a sound it is ignoring, and that difference in attention seems to be part of what was being measured.

Why this isn’t the same as an ordinary EEG

The spontaneous electroencephalogram (EEG) is the “background” activity recorded with no stimulus at all. It has also been studied in relation to IQ, for instance through the frequency of the alpha wave, with weak and unstable correlations.

The evoked potential, anchored to a precise stimulus repeated hundreds of times, offers a much cleaner signal. That is why Jensen considered it a more promising route. It’s the difference between listening to a room full of conversations and asking a single person to repeat the same sentence hundreds of times, keeping only what repeats identically.

What remains of the idea today

Research on the brain basis of intelligence did not abandon evoked potentials, but it changed focus. Instead of a single “complexity” figure, current studies measure specific components of the wave, such as the P300, during tasks that demand attention or working memory, and they find modest associations with general cognitive ability.

Three conclusions hold up with the available data:

• These are group correlations, obtained with many participants, not an individual measure. No recording of this kind can estimate a particular person’s IQ.
• The spectacular figures of the early studies did not survive replication, a common pattern when samples are small and measures are new.
• The underlying question is still legitimate: whether general mental ability leaves a trace in the way the brain processes very simple stimuli. It follows the same logic as reaction times and the brain’s energy efficiency.

Another biological correlate of intelligence that Jensen discussed, and that later research has reinterpreted, is the link between nearsightedness and intelligence.

Sources

• Jensen, A. R. (1998). The g Factor: The Science of Mental Ability. Praeger.
• Hendrickson, D. E., & Hendrickson, A. E. (1980). The biological basis of individual differences in intelligence. Personality and Individual Differences, 1(1), 3-33. https://doi.org/10.1016/0191-8869(80)90003-3
• Blinkhorn, S. F., & Hendrickson, D. E. (1982). Averaged evoked responses and psychometric intelligence. Nature, 295(5850), 596-597. https://doi.org/10.1038/295596a0
• Haier, R. J., Robinson, D. L., Braden, W., & Williams, D. (1983). Electrical potentials of the cerebral cortex and psychometric intelligence. Personality and Individual Differences, 4(6), 591-599. https://doi.org/10.1016/0191-8869(83)90113-7
• Robinson, D. L., Haier, R. J., Braden, W., & Krengel, M. (1984). Psychometric intelligence and visual evoked potentials: A replication. Personality and Individual Differences, 5(4), 487-489. https://doi.org/10.1016/0191-8869(84)90019-9
• Vetterli, C. F., & Furedy, J. J. (1985). Evoked potential correlates of intelligence: Some problems with Hendrickson’s string measure of evoked potential complexity and error theory of intelligence. International Journal of Psychophysiology, 3(1), 1-3. https://doi.org/10.1016/0167-8760(85)90012-1
• Barrett, P. T., & Eysenck, H. J. (1992). Brain evoked potentials and intelligence: The Hendrickson paradigm. Intelligence, 16(3-4), 361-381. https://doi.org/10.1016/0160-2896(92)90015-J
• Bates, T., Stough, C., Mangan, G., & Pellett, O. (1995). Intelligence and complexity of the averaged evoked potential: An attentional theory. Intelligence, 20(1), 27-39. https://doi.org/10.1016/0160-2896(95)90004-7