Showing posts with label metrics. Show all posts
Showing posts with label metrics. Show all posts

Tuesday, April 22, 2025

This is a Test


An at-home smell test could pave the way for early detection of Alzheimer's disease
Mar 2025, phys.org

What's wrong with UPSIT or Sniffin' Sticks?

"Forced-choice measures", that's what; they don't allow enough measurement of the higher order executive functioning that's so hideously complex in its relation to the deep limbic system.

Recall Bloom's Taxonomy as a scale of cognitive effort, where memorization is the easiest, using the least amount of cognitive power, and then goes up through comprehension, application, analysis, synthesis, evaluation.

Their new test is called the AROMHA Brain Health Test (ABHT), and it's actually a bunch of tests combined:
  • Odor percept identification (OPID) test - participants smell an odor, answer a question, and then choose from four provided odor names (this sounds like the basic UPSIT, which is an odor identification test, and uses multiple choice instead of open-ended)
  • Percept of odor episodic memory (POEM) test - participants distinguish between new odors and those presented earlier (so this is a memory test)
  • Odor discrimination (OD) test - participants identify pairs of smells as either the same or different (also called a pairwise similarity test)
  • ***This is new*** a meta-cognition measure embedded in the odor percept identification tasks, where participants sample the odor and then choose an odor name from a forced choice list of 4 options, but are then asked to evaluate their confidence: “I Guessed,” “I Narrowed Down to Three,” “I Narrowed Down to Two,” or “I Am Certain.”

via Laboratory of Olfactory Neurotranslation at McCance Center for Brain Health, and Department of Neurology at Massachusetts General Hospital: Benoît Jobin et al, The AROMHA brain health test is a remote olfactory assessment to screen for cognitive impairment, Scientific Reports (2025). DOI: 10.1038/s41598-025-92826-8

Partially unrelated image credit: AdobStockWassertest - Fraunhofer IGB - 2025

Tuesday, May 5, 2020

Semantic Bingo



In olfactory research, there's a test called a pairwise similarity test that's used to measure smells, allowing researchers to construction of a map of odor perception.

It's hard to make sense out of smells; it doesn't work like the rest of our sensory system. For a bunch of reasons it's proven quite difficult to produce a model which predicts how a molecule will be perceived.

It's not broken beyond repair, but it is frustrating because we can never seem to get an airtight model that works for all smells and for all people. With hundreds of different receptors, varying over thousands of alleles, scientists often look somewhere else for the organizing principles -- they look for patterns in the words themselves.

In a study from 2015, distributional semantics is used to create an odor map. They say it's the first attempt to do so. This technique rests on the theory that words occuring in similar contexts are in fact similar. Some of you might remember this as "context clues;" if you come across a new word while you're reading, use the surrounding context to help you guess what the word means.

So instead of trying to make a map of molecular features and receptor actuation potentials, they make a map of the words themselves. They use large text datasets, i.e., really big books, one of which was the Sigma-Aldrich Flavors and Fragrances catalog, then score words based on their co-occurances in the text.

I started this post just so I could paste these lists of words, so let's get on with it. On a scale of 0-1, how likely is it that these words can be interchanged?

Similarity Test:
bakery-bread  0.96
grass-lawn       0.96
dog-terrier      0.90
bacon-meat    0.88
oak-wood        0.84
daisy-violet     0.76
daffodil-rose   0.74

Nearest Neighbor Test:
apple - pear, banana, melon, apricot, pineapple
bacon - smoky, roasted, coffee, mesquite, mossy
brandy - rum, whiskey, wine-like, grape, fleshy
cashew - hazlenut, peanut, almond, hawthorne, jam
chocolate - cocoa, sweet, coffee, licorice, roasted
lemon - geranium, grapefruit, tart, floral
cheese - grassy, butter, oily, creamy, coconut
caramel - nutty, roasted, maple, butterscotch, coffee

Notes:
Kiela, D., Bulat, L. & Clark, S. Grounding semantics in olfactory perception. Assoc. Comput. Linguist. 231–326 (2015).

Distributional Semantics – represents the meanings of words as vectors in a “semantic space”, relying on the distributional hypothesis: the idea that words that occur in similar contexts tend to have similar meanings.