Higher performers upregulate brain signal variability in response to more feature-rich visual input
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Abstract
The extent to which brain responses differ across varying cognitive demands is referred to as "neural differentiation," and greater neural differentiation has been associated with better cognitive performance in older adults. An emerging approach has examined within-person neural differentiation using moment-to-moment brain signal variability. A number of studies have found that brain signal variability differs by cognitive state; however, the factors that cause signal variability to rise or fall on a given task remain understudied. We hypothesized that top performers would modulate signal variability according to the complexity of sensory input, upregulating variability when processing more feature-rich stimuli. In the current study, 46 older adults passively viewed face and house stimuli during fMRI. Low-level analyses showed that house images were more feature-rich than faces, and subsequent computational modelling of ventral visual stream responses (HMAX) revealed that houses were more feature-rich especially in V1/V2-like model layers. Notably, we then found that participants exhibiting greater face-to-house upregulation of brain signal variability in V1/V2 (higher for house relative to face stimuli) also exhibited more accurate, faster, and more consistent behavioral performance on a battery of offline visuo-cognitive tasks. Further, control models revealed that face-house modulation of mean brain signal was relatively insensitive to offline cognition, providing further evidence for the importance of brain signal variability for understanding human behavior. We conclude that the ability to align brain signal variability to the richness of perceptual input may mark heightened trait-level behavioral performance in older adults.
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Older adults aged 59 to 73 with increased brain signal variability perform better on tasks.
“Older adults aged 59–73 years who exhibit upregulated brain signal variability show higher levels of task performance62.”
From Cognitive and behavioural flexibility: Neural mechanisms and clinical considerations (2021) · cites this paper as [62]
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- Authors
- Garrett, D. D., Epp, S. M., Kleemeyer, M., Lindenberger, U., & Polk, T. A.
- Affiliations
- Max Planck Institute for Human Development (DE)
- University of Michigan (US)
- Corresponding author
- Garrett, Douglas D.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2020-08
- Volume
- 217
- Pages
- 116836
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W3015562985
- Cited by
- 48
- References
- 60
- Citations by year
- 2026: 4 · 2025: 15 · 2024: 10 · 2023: 5 · 2022: 6 · 2021: 7 · 2020: 1
- FWCI
- 2.55
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- NeuroImage (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Max-Planck-Gesellschaft
- Deutsche Forschungsgemeinschaft
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- neuronal differentiation, brain signal variability, older adults, cognitive performance, ventral stream, HMAX model, within-person variability
- MeSH terms
- Facial Recognition, Aged, Brain, Brain Mapping, Cognition, Computer Simulation, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Oxygen, Photic Stimulation, Psychomotor Performance, Reaction Time, Visual Cortex, Visual Pathways
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