🧬 biology

Time of day shapes explicit and implicit contributions to visuomotor adaptation

This study demonstrates that time of day influences the speed of visuomotor adaptation primarily by enhancing the stability and directionality of explicit strategies in the afternoon, while implicit adaptation remains unaffected by daily fluctuations.

Original authors: Johanna MATHIOT, Charlène TRUONG, Jéremie GAVEAU, Ambra BISIO, Adrien GUZZO, Célia Ruffino, Charalambos PAPAXANTHIS

Published 2026-07-23

📖 6 min read🧠 Deep dive

CC BY 4.0

Original authors: Johanna MATHIOT, Charlène TRUONG, Jéremie GAVEAU, Ambra BISIO, Adrien GUZZO, Célia Ruffino, Charalambos PAPAXANTHIS

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ⚕️ This is an AI-generated explanation of a preprint that has not been peer-reviewed. It is not medical advice. Do not make health decisions based on this content. Read full disclaimer

Imagine your brain as a super-smart, high-tech navigation system inside a spaceship. Every time you reach for a cup of coffee or step onto a moving walkway, this system has to make split-second calculations. It relies on two distinct pilots working together. The first pilot is the "Strategist." This is the conscious, thinking part of your brain that says, "Hey, the cup is actually over there, not here! I need to aim my hand to the left." It's fast, deliberate, and uses your working memory. The second pilot is the "Auto-Pilot." This is the unconscious, automatic part that quietly rewires your muscle memory. It doesn't think; it just feels the error and slowly adjusts your internal map so your hand moves correctly without you having to think about it.

Scientists have long known that these two pilots work together to help us learn new movements. But a big question has remained: Does the time of day change how well these two pilots get along? We know that our bodies have a daily rhythm, like a clock ticking inside us, affecting when we feel most energetic or sleepy. While we know sleep helps us remember what we learned, we don't really know if the time you practice a skill changes how your brain learns it in the moment. This is the mystery a team of researchers set out to solve: does your brain's "learning mode" shift between morning and afternoon, and does it treat the conscious Strategist and the unconscious Auto-Pilot differently?

The Morning Fog vs. The Afternoon Spark

The researchers, led by Johanna Mathiot and her team, decided to test this by putting healthy adults through a "visual motor" challenge. They asked participants to point at targets on a screen, but with a twist: the computer secretly rotated the view of their hand by 45 degrees. If they reached straight for the target, the cursor would miss. To succeed, they had to learn to aim in the opposite direction.

The team split the participants into two groups: the "Morning Crew," who did the task at 10 a.m., and the "Afternoon Crew," who tackled it at 3 p.m. They ran three different versions of the experiment to see exactly what was happening under the hood.

The Big Discovery: The Afternoon Crew Adapted Faster
In the first experiment, where both the Strategist and the Auto-Pilot were working together, the results were clear. The Afternoon Crew adapted much faster during the early stages of the task. They figured out how to compensate for the rotation quickly. The Morning Crew, however, was slower to catch on.

But here is the plot twist: it wasn't because the morning group was "dumber" or had a broken Auto-Pilot. When the researchers looked closely at the data, they found that the Morning Crew's Strategist was having a bit of a crisis. They knew roughly how much they needed to correct their aim (the magnitude was right), but they were getting the direction mixed up. It was as if the Strategist was shouting, "We need to turn!" but sometimes shouting "Left!" when it should be "Right!" and then immediately changing its mind to "Left!" again. This confusion made their early learning sluggish.

In contrast, the Afternoon Crew's Strategist was calm, clear, and consistent. They knew exactly which way to turn and stuck with it. Meanwhile, the Auto-Pilot (the unconscious part) was doing the exact same job for both groups, regardless of the time of day. It was steady, reliable, and completely unaffected by the clock.

The "Isolation" Tests: What Happens When They Work Alone?
To be absolutely sure, the researchers ran two more experiments to see what happened if they forced the two pilots to work alone.

Experiment 2 (Strategist Only): They slowed down the feedback so the participants had to rely entirely on their conscious thinking, blocking the unconscious learning. In this scenario, the time of day didn't matter at all. Both the Morning and Afternoon crews learned at the same speed. This proved that the morning group's brain wasn't incapable of strategic thinking; it just struggled to coordinate that thinking with the unconscious system when both were active at the same time.
Experiment 3 (Auto-Pilot Only): They used a trick where the feedback was "clamped" (fixed) so the participants couldn't use a strategy and had to rely purely on unconscious learning. Again, the time of day made zero difference. Both groups' Auto-Pilots worked perfectly.

The Verdict: It's About the Handshake, Not the Hands
So, what does this all mean? The paper suggests that the time of day doesn't change the raw power of your brain's learning tools. Your Strategist and your Auto-Pilot are both fully functional in the morning and the afternoon.

The real difference lies in how well they shake hands. In the afternoon, the brain seems to be in a state where the conscious and unconscious systems coordinate beautifully. The Strategist gives clear instructions, and the Auto-Pilot smoothly integrates them. In the morning, however, the connection between these two systems seems a bit "noisy." The Strategist gets confused about direction, and this confusion slows down the whole learning process.

The researchers found that by the end of the learning session, both groups reached the same level of skill. The morning group just took a bit longer to get there because of that initial coordination glitch. This study highlights that our internal brain state—shaped by the time of day—acts like a conductor for an orchestra. In the afternoon, the musicians (the brain's different learning systems) play in perfect sync. In the morning, they might be a little out of tune with each other, even if they are all playing the right notes individually.

This discovery is a bit like realizing that you might drive a car better in the afternoon not because your eyes are sharper or your reflexes are faster, but because your brain is better at coordinating the steering wheel with the engine at that specific time. It suggests that if you are trying to learn a new physical skill, like a sport or a musical instrument, the time you choose to practice might change how quickly you get the hang of it, simply because of how your brain's different parts are talking to each other.

Problem Statement
Motor adaptation relies on the interaction between explicit (voluntary, strategic) and implicit (automatic, internal model updating) processes. While these mechanisms have been extensively characterized, it remains unknown how they vary across the day and whether they exhibit similar sensitivity to the time of day. Previous research indicates that internal brain states fluctuate due to circadian rhythms, wakefulness accumulation, and hormonal changes, influencing neuroplasticity and motor performance. However, it is unclear whether these daily fluctuations affect overall adaptation capacity or specifically alter the coordination between explicit and implicit learning systems.

Methodology
The study employed three complementary experiments involving 96 healthy adults to dissociate the contributions of explicit and implicit processes under different times of day (10:00 a.m. vs. 3:00 p.m.). All participants performed a visuomotor adaptation task involving a 45° counterclockwise (CCW) rotation of visual feedback.

Experiment 1 (Co-expression): Participants performed a standard adaptation task with online cursor feedback and were asked to verbally report their aiming direction every three trials. This allowed for the simultaneous engagement of explicit and implicit processes. Explicit adaptation was measured by the reported aiming angle, while implicit adaptation was calculated as the difference between the hand angle and the reported aiming angle.
Experiment 2 (Isolated Explicit): To isolate explicit learning, a delayed visual feedback paradigm was used (feedback presented 800 ms after movement completion). This delay prevents the integration of sensory prediction errors required for implicit adaptation, thereby isolating strategic adjustments.
Experiment 3 (Isolated Implicit): To isolate implicit learning, a clamped visual feedback paradigm was used. The cursor was fixed at a 45° CCW angle relative to the target regardless of the participant's movement, eliminating the need for explicit strategic corrections.

In all experiments, performance was analyzed across baseline, adaptation (early and late phases), and aftereffect phases. State-space models were fitted to the data to estimate retention ( $a$ ) and learning/error sensitivity ( $b$ ) parameters.

Key Results

Overall Adaptation (Experiment 1): Participants tested in the afternoon adapted significantly faster during the early phase of learning compared to those tested in the morning. This advantage was driven by a higher learning rate parameter ( $b$ ), indicating greater error sensitivity in the afternoon group. However, both groups reached similar asymptotic performance levels by the late adaptation phase, and aftereffects (a proxy for implicit retention) were comparable across groups.
Explicit Process (Experiment 1 & 2): In Experiment 1, the morning group's slower adaptation was associated with disrupted explicit strategies. While morning participants generated aiming corrections of appropriate magnitude (absolute values), they frequently expressed these strategies in the wrong direction (sign errors) and showed higher trial-to-trial inconsistency compared to the afternoon group. When explicit processes were isolated in Experiment 2 (delayed feedback), no time-of-day differences were observed; both groups adapted rapidly and efficiently with stable strategies.
Implicit Process (Experiment 1 & 3): Implicit adaptation remained stable throughout the day. In Experiment 1, implicit angles showed no significant difference between morning and afternoon groups. Experiment 3, which directly isolated implicit learning via clamped feedback, confirmed that implicit adaptation rates and retention were identical regardless of the time of day.

Significance and Claims
The paper claims that daily fluctuations in motor adaptation do not stem from a general deficit in learning capacity or a change in the isolated efficiency of explicit or implicit systems. Instead, the time of day selectively influences the interaction and coordination between these two processes during the early phase of adaptation.

The authors argue that the morning deficit arises from a state-dependent disruption in explicit strategic control, characterized by directional instability and inconsistency, which likely interferes with the efficient coordination required between explicit and implicit systems. In contrast, the afternoon appears to offer a functional brain state—potentially linked to increased frontoparietal connectivity and arousal—that facilitates the stable generation of explicit strategies and their effective integration with implicit recalibration.

The study concludes that the timing of practice shapes not only the speed of adaptation but specifically how explicit and implicit learning processes are coordinated. This finding highlights the potential importance of scheduling motor rehabilitation and training sessions at optimal times of day to maximize the efficiency of early adaptive learning.

The Morning Fog vs. The Afternoon Spark

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