What the tests measure: seven areas of thinking

The tests on Neuropsych are grouped into seven areas of thinking. This guide explains what each area covers, where it shows up in daily life, what research says about it, and what a single score can and cannot tell you.

By Neuropsych · Published October 12, 2026

Each test is a short task adapted from a published research paradigm. These are not the versions a psychologist gives in a clinic, and a score from one sitting is a snapshot, not a verdict. The last section explains how to read your results together.

Processing speed

Processing speed is how quickly and accurately you take in simple information and act on it: spotting a symbol, matching a pair, pressing a key when something appears. It is not the same as how well you reason. Someone can solve hard problems well and still need more time for routine ones.

You notice it when reading and answering messages, keeping up in a fast conversation, filling in forms or working to a deadline. Timed exams lean on it heavily.

Speed on simple tasks changes with age more clearly than many other abilities, and Salthouse (1996) argued that slower processing accounts for much of the age-related change seen in other areas. Symbol-coding tasks are also unusually sensitive: scores shift with tiredness, illness, medicines and mood, which makes them good at noticing a change and poor at saying what caused it (Jaeger, 2018). A night without sleep slows responses and makes attention lapse more often, while reasoning accuracy is affected least (Lim and Dinges, 2010).

Tests in this area: Symbol Coding and Reaction Time.

Working memory

Working memory holds information in mind for a few seconds while you use or update it. Remembering a phone number is short-term memory. Saying its digits backwards while you still hold them is working memory.

It is small. Most adults can hold only about three to five chunks of information at once (Cowan, 2001), which is why long spoken instructions are easy to lose halfway through.

You notice it when following several steps at once, doing sums in your head, taking notes while you listen, or keeping track of a conversation that keeps changing.

Anxiety is linked with lower working memory scores on average (Moran, 2016), so a worried day can show up here. Practice on memory games improves the games you practice, but the gains do not spread to reasoning or other untrained skills (Melby-Lervåg and colleagues, 2016).

Tests in this area: Digit Span, Corsi Blocks, N-Back and Operation Span.

Executive function

Executive function is the set of control processes that keep behavior on track: holding back an automatic response, switching between rules, updating what you hold in mind and planning a few steps ahead. Miyake and colleagues (2000) showed that these parts are related but separable, so a person can be strong in one and weaker in another.

You notice it when planning a project, changing approach after something fails, resisting a habit such as taking the usual route, or juggling tasks that compete for your time.

These abilities keep developing through childhood and adolescence (Diamond, 2013). One finding matters when you read your own results: scores on lab tasks and answers to everyday questionnaires about executive function agree only weakly, because they capture different things (Toplak and colleagues, 2013). Doing well on a sorting task does not mean daily organization is easy, and the reverse is also true.

Tests in this area: Stroop, Trail Making, Card Sorting and Tower of London.

Fluid reasoning

Fluid reasoning is working out rules and relationships in material you have not seen before, without leaning on what you already know. Knowledge built up over years, such as vocabulary, is called crystallized ability. Fluid reasoning is what you can figure out on the spot.

You notice it when solving an unfamiliar problem, working out how a new system or app behaves, or learning a procedure from a few examples.

Matrix puzzles depend on finding the rules in a pattern and keeping several of them in mind at once, which ties them closely to working memory (Carpenter and colleagues, 1990). In adulthood, fluid reasoning tends to decline earlier than knowledge-based abilities, which hold steady or keep growing (Horn and Cattell, 1967).

Tests in this area: Matrix Reasoning and Pattern Completion.

Verbal comprehension

Verbal comprehension covers knowing words, seeing how ideas relate in language and finding words quickly when you need them. Much of it is built from reading, schooling and conversation over many years.

You notice it when finding the right word, explaining an idea clearly, understanding dense text or writing under time pressure.

Word knowledge is one of the most stable abilities in adult life. In one study, a word-reading test taken at 77 was strongly related to intelligence measured 66 years earlier (Crawford and colleagues, 2001). Language background matters too: bilingual children often know fewer words in each single language than children who speak only that language (Bialystok and colleagues, 2010), so take the verbal tests in the language you use most. Word fluency, naming as many words from a category as you can in a short time, draws on vocabulary and on how efficiently you search your memory (Shao and colleagues, 2014).

Tests in this area: Vocabulary, Similarities, Verbal Analogies and Word Fluency.

Number sense

Number sense covers judging quantities, understanding number symbols and place value, and recalling or checking simple arithmetic. Dyscalculia is a persistent difficulty in this area that schooling or general ability does not explain. A clinical guideline puts it at about 3 to 7 percent of children, adolescents and adults, and people with dyscalculia are much more likely than others to have dyslexia as well (Haberstroh and Schulte-Körne, 2019).

You notice it when handling money, reading times and measurements, estimating a total or copying numbers accurately.

Deciding which of two amounts is larger sounds trivial, but both comparing dots and comparing digits are linked with broader math skill, digits a little more strongly than dots (Schneider and colleagues, 2017). Dyscalculia does not look the same in everyone, and researchers still debate exactly how to define it (Kaufmann and colleagues, 2013). Anxiety about numbers is a different thing, though the two can occur together; dyscalculia vs math anxiety explains the difference.

Tests in this area: Subitizing, Magnitude Comparison, Number Line, Dot Comparison, Arithmetic Verification, Fact Retrieval, Counting, Place Value and Number Dictation. Four of them, with six questions about everyday numbers, make up the dyscalculia check.

Attention

Attention here means staying focused over time and holding back responses you do not want: ignoring distractions, not reacting too early, keeping steady through a long, dull task.

You notice it when reading long documents, listening in meetings, avoiding careless errors and waiting before you act.

ADHD is the condition most often linked with this area. An international consensus statement puts it at about 5.9 percent of young people and 2.5 percent of adults (Faraone and colleagues, 2021). On average, groups of people with ADHD miss more targets on long attention tasks (Huang-Pollock and colleagues, 2012) and have more variable reaction times (Kofler and colleagues, 2013). Those are group averages, and the groups overlap a lot: many people with ADHD score in the typical range on these tasks (Nigg and colleagues, 2005). A task score cannot diagnose ADHD or rule it out.

Poor sleep, stress, low mood and anxiety affect attention tasks too; ADHD or something else? covers the overlaps.

Tests in this area: Flanker, Go / No-Go, Stop-Signal and CPT. The ADHD check pairs six questions from the ASRS with four short tasks.

Reading your results as a whole

Your results are a set of separate scores, not a grade. What helps most is the shape: which areas stand out, in which direction, and whether that matches what you notice in daily life.

For most tests, your score is compared with published norms: results from groups of adults who did the same kind of task, matched to your age where the norms allow. A few tests, including most of the number tasks, have no matching published norms yet, so they show your own result without that comparison. The scoring engine page shows the calculation step by step.

Uneven profiles are normal. When healthy adults take a long battery of tests, most of them score low on at least one (Binder and colleagues, 2009). One low score among many is expected, not a sign that something is wrong.

Single scores also wobble. Several classic tasks, including Flanker, Stroop and Stop-Signal, show clear effects across groups but measure differences between individuals less reliably (Hedge and colleagues, 2018). Testing in a browser adds its own noise, because the device, the screen, the room and interruptions all affect timing (Germine and colleagues, 2019). Take the tests rested, somewhere quiet, on a device you know.

A profile cannot diagnose a condition, and it cannot say why a score is low. A clinician looks at your history, how long a difficulty has lasted, how much it affects your life and what else could explain it. Your results can be one useful piece of that conversation.

General information, not a diagnosis

This guide explains what the tests measure. It does not replace an assessment by a qualified clinician, and the sources it cites do not endorse Neuropsych.

References

  1. Salthouse TA. The processing-speed theory of adult age differences in cognition. Psychological Review. 1996;103(3):403-428. https://doi.org/10.1037/0033-295X.103.3.403
  2. Jaeger J. Digit Symbol Substitution Test: the case for sensitivity over specificity in neuropsychological testing. Journal of Clinical Psychopharmacology. 2018;38(5):513-519. https://doi.org/10.1097/JCP.0000000000000941
  3. Lim J, Dinges DF. A meta-analysis of the impact of short-term sleep deprivation on cognitive variables. Psychological Bulletin. 2010;136(3):375-389. https://doi.org/10.1037/a0018883
  4. Cowan N. The magical number 4 in short-term memory: a reconsideration of mental storage capacity. Behavioral and Brain Sciences. 2001;24(1):87-114. https://doi.org/10.1017/S0140525X01003922
  5. Moran TP. Anxiety and working memory capacity: a meta-analysis and narrative review. Psychological Bulletin. 2016;142(8):831-864. https://doi.org/10.1037/bul0000051
  6. Melby-Lervåg M, Redick TS, Hulme C. Working memory training does not improve performance on measures of intelligence or other measures of “far transfer”: evidence from a meta-analytic review. Perspectives on Psychological Science. 2016;11(4):512-534. https://doi.org/10.1177/1745691616635612
  7. Miyake A, Friedman NP, Emerson MJ, Witzki AH, Howerter A, Wager TD. The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: a latent variable analysis. Cognitive Psychology. 2000;41(1):49-100. https://doi.org/10.1006/cogp.1999.0734
  8. Diamond A. Executive functions. Annual Review of Psychology. 2013;64:135-168. https://doi.org/10.1146/annurev-psych-113011-143750
  9. Toplak ME, West RF, Stanovich KE. Practitioner review: do performance-based measures and ratings of executive function assess the same construct? Journal of Child Psychology and Psychiatry. 2013;54(2):131-143. https://doi.org/10.1111/jcpp.12001
  10. Carpenter PA, Just MA, Shell P. What one intelligence test measures: a theoretical account of the processing in the Raven Progressive Matrices Test. Psychological Review. 1990;97(3):404-431. https://doi.org/10.1037/0033-295X.97.3.404
  11. Horn JL, Cattell RB. Age differences in fluid and crystallized intelligence. Acta Psychologica. 1967;26:107-129. https://doi.org/10.1016/0001-6918(67)90011-X
  12. Crawford JR, Deary IJ, Starr J, Whalley LJ. The NART as an index of prior intellectual functioning: a retrospective validity study covering a 66-year interval. Psychological Medicine. 2001;31(3):451-458. https://doi.org/10.1017/S0033291701003634
  13. Bialystok E, Luk G, Peets KF, Yang S. Receptive vocabulary differences in monolingual and bilingual children. Bilingualism: Language and Cognition. 2010;13(4):525-531. https://doi.org/10.1017/S1366728909990423
  14. Shao Z, Janse E, Visser K, Meyer AS. What do verbal fluency tasks measure? Predictors of verbal fluency performance in older adults. Frontiers in Psychology. 2014;5:772. https://doi.org/10.3389/fpsyg.2014.00772
  15. Haberstroh S, Schulte-Körne G. The diagnosis and treatment of dyscalculia. Deutsches Ärzteblatt International. 2019;116(7):107-114. https://doi.org/10.3238/arztebl.2019.0107
  16. Schneider M, Beeres K, Coban L, et al. Associations of non-symbolic and symbolic numerical magnitude processing with mathematical competence: a meta-analysis. Developmental Science. 2017;20(3):e12372. https://doi.org/10.1111/desc.12372
  17. Kaufmann L, Mazzocco MM, Dowker A, et al. Dyscalculia from a developmental and differential perspective. Frontiers in Psychology. 2013;4:516. https://doi.org/10.3389/fpsyg.2013.00516
  18. Faraone SV, Banaschewski T, Coghill D, et al. The World Federation of ADHD International Consensus Statement: 208 evidence-based conclusions about the disorder. Neuroscience & Biobehavioral Reviews. 2021;128:789-818. https://doi.org/10.1016/j.neubiorev.2021.01.022
  19. Huang-Pollock CL, Karalunas SL, Tam H, Moore AN. Evaluating vigilance deficits in ADHD: a meta-analysis of CPT performance. Journal of Abnormal Psychology. 2012;121(2):360-371. https://doi.org/10.1037/a0027205
  20. Kofler MJ, Rapport MD, Sarver DE, et al. Reaction time variability in ADHD: a meta-analytic review of 319 studies. Clinical Psychology Review. 2013;33(6):795-811. https://doi.org/10.1016/j.cpr.2013.06.001
  21. Nigg JT, Willcutt EG, Doyle AE, Sonuga-Barke EJS. Causal heterogeneity in attention-deficit/hyperactivity disorder: do we need neuropsychologically impaired subtypes? Biological Psychiatry. 2005;57(11):1224-1230. https://doi.org/10.1016/j.biopsych.2004.08.025
  22. Binder LM, Iverson GL, Brooks BL. To err is human: “abnormal” neuropsychological scores and variability are common in healthy adults. Archives of Clinical Neuropsychology. 2009;24(1):31-46. https://doi.org/10.1093/arclin/acn001
  23. Hedge C, Powell G, Sumner P. The reliability paradox: why robust cognitive tasks do not produce reliable individual differences. Behavior Research Methods. 2018;50(3):1166-1186. https://doi.org/10.3758/s13428-017-0935-1
  24. Germine L, Reinecke K, Chaytor NS. Digital neuropsychology: challenges and opportunities at the intersection of science and software. The Clinical Neuropsychologist. 2019;33(2):271-286. https://doi.org/10.1080/13854046.2018.1535662

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