Evidence map›Paper›PMID 42779828›Full record

ArticlebioRxiv : the preprint server for biology2026

A single cortical circuit implements fast and slow visual search.

Mattia F Pagnotta, Haojun Zhuang, S J Katarina Slama, David King-Stephens, Kenneth D Laxer, Tor Endestad, Anne-Kristin Solbakk, Jack J Lin, Robert T Knight

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Mattia F PagnottaHelen Wills Neuroscience Institute, University of California Berkeley, USA.ORCID 0000-0003-0304-7253
Haojun ZhuangHelen Wills Neuroscience Institute, University of California Berkeley, USA.
S J Katarina SlamaHelen Wills Neuroscience Institute, University of California Berkeley, USA.
David King-StephensDepartment of Neurology, University of California Irvine, USA.
Kenneth D LaxerCalifornia Pacific Medical Center, San Francisco, USA.
Tor EndestadUniversity of Oslo, Norway.
Anne-Kristin SolbakkUniversity of Oslo, Norway.
Jack J LinDepartment of Neurology, University of California Davis, USA.
Robert T KnightHelen Wills Neuroscience Institute, University of California Berkeley, USA.

Funding

Project 5: ComputationalP50MH109429 · NIMH · NATHAN S. KLINE INSTITUTE FOR PSYCH RES · PI Michael Peter Milham · 2017 to 2026
$25.3M
Neural circuit theory and trained recurrent network modeling of rapid learningU19NS107609 · NINDS · UNIVERSITY OF WASHINGTON · PI BUFFALO, ELIZABETH A · 2018 to 2022
$12.6M
Attention, Orientation and the Human Prefrontal CortexR01NS021135 · NINDS · UNIVERSITY OF CALIFORNIA DAVIS · PI Robert Thomas Knight · 1985 to 2026
$6.5M
NIMH NIH HHS P50 MH109429NINDS NIH HHS R01 NS021135NINDS NIH HHS U19 NS107609
6 · The paper itself

Abstract

How the brain produces different behaviors from a fixed anatomical substrate is a foundational question in neuroscience. The dominant account holds that behavioral flexibility requires distinct neural circuits: dedicated systems selectively recruited for different processing modes. An alternative proposes that flexibility arises not from switching between circuits, but from dynamically controlling the speed at which a shared circuit operates. Here, we test this account directly using intracranial EEG recordings from nineteen human patients performing two visual search tasks of markedly different difficulty: an easy color-singleton search and a difficult orientation search, a fast vs. slow dissociation attributed for four decades to distinct anatomical and oscillatory neural systems. We show that both search tasks recruit the same cortical regions, oscillatory frequencies, and processing hierarchy. Dynamic time warping reveals that the two neural trajectories are time-stretched versions of one another; the same temporal scaling appears within each condition between faster and slower trials, indexing response speed rather than the distinction between tasks. Alpha-band oscillations (~8-10 Hz) support this temporal scaling through two coordinated mechanisms: synchronizing activity across a posterior cortical network and phase-gating local high-frequency activity (70-150 Hz) within those regions at the same preferred phase in both conditions. These findings establish that, for the two tasks studied here, fast and slow visual search are not implemented by selecting between distinct dedicated circuits, but by adjusting the speed of a single alpha-coordinated architecture. The same principle may apply to other search tasks, and to other domains in which dual-process architectures have been invoked, a testable prediction for future studies.

Identifiers

PMID42779828
PMCPMC13596560

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.