Imaging from more than 1,000 people suggests normal ageing and Alzheimer’s pathology reorganise brain communication in two distinct patterns — and the disease signature appears before cognitive symptoms do.

One of the persistent difficulties in Alzheimer’s research is telling the disease apart from time. Brains change with age in ways that overlap with the changes that disease produces, and when the two are measured in the same region with the same instrument, disentangling them is hard. A study from Lund University published in Nature Neuroscience argues that the two can in fact be separated — not by looking at individual regions, but by looking at the shape of the change across the whole brain.

The team analysed functional connectivity, a measure of how brain regions communicate with one another, in imaging data from more than 1,000 people. Rather than asking which regions showed more or less connectivity, the researchers asked how connectivity was reorganised along the brain’s large-scale axes of organisation. The two processes, ageing and Alzheimer’s pathology, turned out to run along different axes.

Two patterns, not one gradient

In the Alzheimer’s-associated pattern, communication patterns in higher-order regions — those involved in memory and integrative thought — became more similar to one another, while sensory and motor regions became more distinct. In normal ageing the pattern ran differently: regions involved in executive functions became more similar, and other regions became more distinct. Both processes moved connectivity across several brain areas simultaneously rather than striking one region at a time.

“Our analyses showed that brain communication reorganizes in one specific pattern during normal aging, and in a very distinct and different pattern as Alzheimer’s pathology accumulates,” said Jonathan Rittmo, a PhD student at Lund University and first author of the study.

The methodological argument matters as much as the finding. Studies of connectivity in Alzheimer’s have often reported increases in some regions and decreases in others, a pattern that has been difficult to interpret and inconsistent across cohorts. The Lund result suggests why: those local increases and decreases may be components of a single coordinated reorganisation that only becomes legible when measured as a whole.

“Rather than treating connectivity increases and decreases as isolated effects in individual brain regions, our results suggest that they need to be interpreted as parts of larger patterns shaped by the brain’s underlying organization,” said Jacob Vogel, an associate senior lecturer at Lund University whose team carried out the analysis.

Visible before the symptoms

The result the researchers found most striking concerns timing. The Alzheimer’s-associated connectivity pattern was already apparent in people who were cognitively unimpaired and carried only low levels of Alzheimer’s pathology.

“We already know that blood markers such as p-tau217 can reveal signs of Alzheimer’s disease before cognitive symptoms appear,” Rittmo said. “What surprised us was that the distinctive pattern of changes in brain communication was already apparent in people with low levels of Alzheimer’s pathology who were still cognitively unimpaired.”

That places the connectivity signature early in the disease course, in the same territory as the blood-based markers that have reshaped Alzheimer’s diagnosis over the past few years. It does not, however, make it a competitor to them. A blood draw is cheap and widely available; functional MRI is neither, and the connectivity pattern reported here is a group-level average rather than a per-person test.

Connectivity tracked cognition better than pathology did

A second result cuts in an unexpected direction. Among people who already had cognitive impairment, the connectivity pattern was more strongly related to cognitive function than the accumulation of amyloid-beta and tau — the two proteins that define Alzheimer’s pathologically — was.

This speaks to a long-running tension in the field. Amyloid and tau burden correlate only loosely with how impaired a person actually is; people with substantial pathology can remain sharp, and people with modest pathology can decline badly. If network-level reorganisation tracks symptoms more closely than protein load does, it may be closer to whatever is actually causing the impairment — or at least a better readout of it.

The researchers are explicit that this is not yet established. The patterns described are group-level findings and still need confirmation at the level of individuals, including the critical question of whether they predict later cognitive decline in a given person. That work is ongoing. The release reports no accuracy figures, no effect sizes and no information on how much of the variation in cognition the connectivity measure accounts for.

A long way from a therapy

Vogel sketched where the work might eventually lead, with appropriate hedging. “If we can determine the downstream consequences of these connectivity patterns, for example if they reflect harmful system-level stress, this could eventually point toward ways of modulating them therapeutically, for example through non-invasive brain stimulation,” he said.

Every clause in that sentence is conditional, and reasonably so. The study establishes that two patterns exist and differ; it does not establish that either is harmful, that either causes cognitive decline, or that shifting either would help anyone. Non-invasive brain stimulation for cognitive disorders has a long record of promising early results that have not consistently survived larger trials.

What the study does offer is a cleaner way to ask the question. If ageing and Alzheimer’s disease reorganise brain communication along genuinely distinct axes, then connectivity measurements that previously looked noisy and contradictory may become interpretable — and a signature that appears before symptoms do is worth understanding, whatever it eventually turns out to mean.

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Notes

1. “Different functional connectivity gradients reflect aging and Alzheimer’s disease.” Nature Neuroscience, 1 October 2026. DOI: 10.1038/s41593-026-02402-0.
2. Lund University. “Alzheimer’s disease and aging reshape brain communication in different ways.” EurekAlert!, 1 October 2026. https://www.eurekalert.org/news-releases/1146230.