Eleven questions, all variations of the same one, keep showing up in my inbox: how do you actually build a spreadsheet for brain tracking that means something? I get asked this by people newly retired who've discovered nootropic data the way I did — by accident, with a cognitive health scare as the entry point instead of a hobby. Retired life left me with the hours to obsess over it, so here's the honest answer, organized the way I organize everything else: by question, not by chapter.
Somewhere in the middle of all this tracking, I caught myself rattling off an old client's seven-digit phone extension (cold, unprompted, hand not even on the receiver yet) and it struck me as such an odd little proof-of-life moment that I logged it as an event, not a score. Melatonin was the first thing I tried, on the theory that bad sleep was the real problem and everything else was just noise. It wasn't. My sleep numbers ticked up, my fog numbers barely moved, and that told me more than stacking good nights on top of each other ever would: whatever was going on wasn't purely a sleep problem, so I needed sharper questions, not just more rest.
None of that turned into a tidy narrative, though. It turned into questions — the same handful, asked by different people, in different words.
How Many Columns Does a Brain Health Spreadsheet Actually Need?
Fewer than you'd think, and not the ones people assume matter most. You don't need twenty categories to make this work — six to eight columns that isolate one variable at a time will do: sleep hours, a focus rating, a memory rating, an energy rating, dose and timing, and a plain yes-or-no for whatever hard task you tackled that day. Half of that column list got sketched out walking the White Rock Lake trail, not hunched over a keyboard, which tells you something about where the actual thinking happens. Cost belongs in there too, not because the number itself matters much, but because it forces you to ask whether a result justifies what you're putting into it. Every column should answer a question you could actually be wrong about — if a column can't disprove anything, it's decoration, not data, an accountant's version of a vanity metric.
Feeling Better Isn't the Same as Testing Better
Most people track a mood average and call it evidence. A seven out of ten on Tuesday feels like proof of something, but averages flatten exactly the days that matter — the ones with real pressure attached. So I stopped trusting the 1-to-10 columns on their own and added one blunt pass-fail test: pick one demanding task a day, something with actual stakes, and mark whether I got through it clean. Did I finish a complicated reconciliation without hitting a wall, yes or no. That single column is harder to fake than any mood score, because it either happened or it didn't. Part of what made this useful was tracking verbal recall specifically during those high-pressure windows — not whether I felt sharp, but whether the actual word showed up when I needed it.
Isn't a 1-to-10 Scale Just Guessing?
A former pharmacist I know from a supplement-tracking forum, Mireille Chatham, asks me this constantly, and she's not wrong to push. Her argument is that a subjective number without any sense of how fast a compound actually clears your system is close to meaningless, and I've come around to thinking she's right that the scale alone isn't the whole audit. My eyes ache in a very specific way after a couple hours of matching ingredient panels against research abstracts line by line, which is usually when I notice how often a label oversells what the underlying study actually found. Where Mireille and I differ is what to do about the gap — she wants more precision, I want more comparison points, which is really the same argument accountants have about materiality thresholds. Elsewhere I've written about separating a real placebo baseline from wishful thinking, and separately about what happens when a supplement's own label doesn't match what your numbers actually show — both worth a look if the 1-to-10 scale bothers you as much as it bothers her.
The B-Vitamin Line Item Nobody Tracks
One column that surprised me is the one for B vitamins, specifically B12, B6, and folate. These aren't exotic ingredients — they're part of the pathway your body uses to process homocysteine, and elevated homocysteine in the blood has been linked to a higher risk of cognitive decline as people get older. B12 deficiency in particular is one of the few reversible causes of cognitive symptoms, which is exactly the kind of finding that makes a numbers person sit up straight. Before any of this goes anywhere near publication, I run it past a friend of mine, Clifford Achebe — a former client of mine who now runs a medical supply distribution company — because he has zero patience for supplement hype and even less for me overstating what a correlation actually proves. If your own numbers show a B12 gap, that's a conversation for an actual doctor, not a spreadsheet column, though it's worth tracking well enough to know you have a conversation to have.
Deciding Whether Any of This Is Worth the Money
Deciding whether any of this is worth the money is a different audit than deciding whether it works at all. I think about it the same way I used to think about a client's marginal spend on any line item: the question was never "is this good," it was "is this good enough to justify itself against the next best option." I've broken that ROI question down in more detail elsewhere, treating a supplement budget the same way I'd treat any other recurring expense with a return I actually have to prove. Mornings and afternoons behave differently enough in my numbers that lumping them into one daily average hides real information, which is exactly why I went deeper specifically on afternoon fog in a separate piece instead of folding it into this one.
Reading Your Own Numbers Without Fooling Yourself
It's how I eventually saw a real correlation between my focus scores and how much sleep I'd gotten the night before — not a supplement effect at all, just sleep hiding in plain sight until I isolated it properly. Building a pivot table that cross-references your pass-fail results against whatever variable changed is the single most useful mechanical trick in any of this. That's the whole trap in one sentence: crediting the wrong variable because you never isolated the right one. I made a version of this same argument in an earlier piece comparing the spreadsheet against the fog directly, and the conclusion holds up here too. So if you take one thing from all this: don't grade a supplement on your mood average, grade it on whether it moves your hardest hour of the day, and don't trust any of it until you've isolated sleep as its own variable first. Everything else is just a nicer-looking spreadsheet than the one my wife still teases me about.