NeuroMat - Research Center for Neuromathematics

The participant was blindfolded. As the Experiment 2 started, he was sitting comfortably and recalled all instructions.
“An evaluation will be made with a cotton swab. I will touch some regions of your body and you must tell me what you are feeling”.
Soon enough he touched his chest with the left hand to indicate he felt something there.
He thought: “how does the sensation feels like?” Recalling the instructions, a few examples came to his mind.
“pressure, vibration, pricking, burning, squeezing, touch, itch, cold…”
- Yes. - he said according to the instructions, indicating he felt something.
- Where?
- Right here. Something pricking my chest.
- Ok! Let me mark it with the pencil…good, there you go. Now, let’s move on.
This was 833 days after surgery, the injured arm resting on a pillow, the other pointing whenever he felt something.
In total, 81 points where stimulated, of which 48 evoked correctly placed sensations and 27 evoked the so-called RS.

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Referred sensation (RS) is described as “the sensation evoked in the skin areas other than the stimulated region”. It is common in people after severe peripheral injury and there are a few possible explanations.

Some people with the Brachial Plexus Injury (BPI) have also reported experiences of RS. This set of nerves communicates with the brain information from our arms: sensations, movements, postures, etc. It helps us identify objects, perceive temperatures and pain, coordinate motor control and so on.

The mission of NeuroMat’s initiative ABRAÇO is to welcome and guide patients who have suffered BPI, so as families and health professionals. Thanks to ABRAÇO network, this cooperation also made viable studies to improve our comprehension of BPI-related issues such as this one.
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Schmaedeke and colleagues’ preprint (2024; see Ref. 1) report two experiments designed to mapping RS in Traumatic Brachial Plexus Injury patients. The fictional scene that introduced our post was inspired by real data and passages from the paper.

In the first experiment, 12 participants underwent a referred sensation screening. The procedure consists of skin stimulation in areas distributed across upper limbs, neck, and face. The second one was performed with the Semmes-Weinstein monofilament technique in 3 patients that have reported RS before (two of them during Experiment 1). “The protocol was adapted from that used in amputees to map the sensation of the amputated limb after surgical targeted sensory reinnervation”, the authors detail (p. 4).

Importantly, all subjects had a motorcycle accident that led to complete left BPI. Hence, part of the effort of ABRAÇO is to disseminate knowledge about this correlation, since more than 80% of the injuries are due to motorcycle accidents.
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This was the first study to map systematically the RS in patients with Traumatic Brachial Plexus Injury. A possible explanation for the phenomenon involves how cortical sensorimotor regions reorganize themselves after the surgery, where specific nerves are transferred to replace those damaged in the affected area, perhaps allowing patients to retrieve some of the functions in the area.

The large amount of sensory fibers present in the donor nerve my undergo reinnervation, resulting in a sort of cross-communication. Also, “after nerve repair, nerve fibers can also grow misdirected, achieving the wrong, non-intended skin regions”.

One of the patients was assessed three times over 6.3 years. Notably, “it is possible to see a scattering of RS over the course of time”. Although the study states its limitations regarding the small sample of patients, these insights collaborate to expanding our understanding on referred sensation and possible explanations to the phenomenon.
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Learn more about ABRAÇO in our website: https://abraco.numec.prp.usp.br .
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Blindfolded | The “Black Box of Science” series

References:
1. Schmaedeke, A. C.; Erthal, F. S.; Vargas, C. D.; Ramalho, B. L. Mapping Referred Sensation in Traumatic Brachial Plexus Injury Patients. meRxiv preprint. DOI: https://doi.org/10.1101/2024.02.19.23297564

Página inicial | ABRAÇO A missão da iniciativa ABRAÇO é acolher e orientar pacientes que sofreram uma lesão traumática do plexo braquial e seus familiares, oferecer treinamento e capacitação para profissionais interessados e divulgar pesquisa em desenvolvimento sobre a lesão e suas consequências funcionais.

The second episode of the 4th season of the podcast A Matemática do Cérebro, by CEPID NeuroMat, has been released today. In this episode, host Felipe Parlato talks with NeuroMat researchers Cláudia Domingues Vargas and Paulo Cabral-Passos about the Goalkeeper's Game, a research tool designed and developed by NeuroMat to study how our brain detects patterns.

They discuss an experiment that focused on the participants' response times while playing the game. The podcast is available on all major audio streaming platforms, podcast aggregators, and YouTube. Coming soon to the official website.

Listen here:

Árvores de contexto, futebol e o Jogo do Goleiro - A Matemática do Cérebro O Jogo do Goleiro foi idealizado e desenvolvido no NeuroMat a partir de 2014, inspirado pela Copa do Mundo que acontecia no Brasil naquele ano. Disponível em...

Gliotransmitters | The “Black Box of Science” series

The student was impressed when he left the lab. He had been interested in brain research for a long time. Still, he learned way more in the last hour than he could have imagined.

The EEG part felt like a sci-fi movie, even though he had watched hours of videos. At the end of the session, after the researcher explained her goals and the logic behind the task, he took the opportunity to ask some questions while she removed electrodes and gel residue from his hair.

It was just impressive how experimental procedures like that one, in which the participant played the goalkeeper game, could contribute to a more detailed understanding of the human brain.

What he didn't imagine was that, on his way out of the building, he would pass through a door -- a regular one with nothing special to catch his attention -- but a door of another laboratory, another world: no EEGs inside, no electrodes and gel, no goalkeeper game. Instead of a shielded room, isolated from acoustic and electrical noise, this one contains a very special computer. A supercomputer.

There, the neurons are not approached by sensitive electrodes. From individual cells to multi-layered neural networks, several elements and complex systems are explored via simulations.

Where cells cannot be illustrated out of EEG data, mathematical models put us one step ahead. Let’s briefly abstract ourselves from that fictional scene.
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As part of NeuroMat projects, Bezerra and Roque published in 2024 a preprint in which they report insights from a computational model of an astrocyte (see Ref. 1). We talked about these star-shaped cells before (see Ref. 2). Besides being all around in the brain, they are also active, responding to neurotransmitters and supporting cognitive function.

However, their role in the system seems to go beyond sustaining the life and work of neurons. Researches have suggested that astrocytes may support neural synchronization (see Ref. 3), plasticity, working memory, and even social behavior.

The belief that such glial cells would be mostly focused on sustaining neurons is partly due to the fact that they don’t talk to each other via electrical signaling, as neurons do. While neurons use neurotransmitters, glial cells have their own language: gliotransmitters. Interestingly, the complexity of astrocytes makes it difficult to experimentally study how they are able to operate in several different ways using the same mechanism.

Bezerra and Roque (2024) offer us an example of how computational neuroscience can put us one step ahead in the task of raising plausible answers to this type of question. They present a model that can be used to simulate astrocytes from different brain regions and with distinct types of response.

They report that glutamate, dopamine and the cell’s morphology can determine the type of Ca2+ signal triggered. That means diversity may emerge from the same mechanism depending on the way these variables are expressed.
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The power of computational science to inform the field with insights and prolific models has been crucial for knowledge construction. Previous models have several variables and parameters, making it difficult to study the astrocyte response diversity. This simulation shows, as we have also mentioned before, that simplification matters a lot in science construction (see Ref. 4).
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Perhaps the student didn’t know the exact experiment he participated in benefited from models simulated in the laboratory next door. As Bezerra and Roque clarify, “difficulties can be avoided with mathematical models”.

Given that, sometimes our next step may only be possible when the path is enlightened by computational tools.
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References:
1. Bezerra & Roque (2024). Diverse Calcium Signaling in Astrocytes: Insights from a Computational Model. bioRxiv preprint. DOI: https://doi.org/10.1101/2024.07.03.601899
2. NeuroMat (2026) - “The Brain’s Dark Matter | The “Black-Box of Science” Series", Facebook post. https://www.facebook.com/share/p/1AtTs7BkCo/
3. Sardinha,et al. (2017) Astrocytic signaling supports hippocampal–prefrontal theta synchronization and cognitive function. Glia 65(12), 1944–1960 DOI: https://pubmed.ncbi.nlm.nih.gov/28885722/
4. NeuroMat (2026) - “Innovation via simplification | The “Black-Box of Science” Series", Facebook post. https://www.facebook.com/share/p/1JhHrywiQ1/

Full preprint text available here:
https://www.researchgate.net/publication/382057387_Diverse_Calcium_Signaling_in_Astrocytes_Insights_from_a_Computational_Model

(PDF) Diverse Calcium Signaling in Astrocytes: Insights from a Computational Model PDF | Astrocytes are complex cells that influence a variety of brain functions and behaviors. They are active cells that show a sharp increase in... | Find, read and cite all the research you need on ResearchGate

CODING

Criticality in neuroscience: when neurons are poised near a phase transition. Such a state has been formulated as the Critical Brain Hypothesis, whose resulting benefits would include optimal computational performance for complex tasks—which is worth our attention when our goal is to explain the architecture of the brain.

Let’s say we want to figure out how neuronal architecture affects this condition. The first thing an experienced researcher would probably do: check whether someone else has already done that. In this case, Rusch, Kinouchi, and Roque report such a study as they performed in NeuroMat (2025; see Ref. 1). We read the paper. Let’s say that we are also impressed with the results and their implications. What do we do next?

One option may be particularly beneficial in terms of scientific progress: reproducing the same study. The good news is that many challenges we’ve discussed in our last post (see Ref. 2) would not apply to this case: we have access to the code.

So, back to the paper,
let’s not start from the beginning.
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The “Code availability” section is down there, right before the References. It brings a link to “the source codes that support the findings of this study”. The page (Ref. 3) has everything the researcher needs to rerun the simulation.

“This repository has source codes in the Fortran 95 language used to simulate hierarchical modular network topologies and their dynamics”, it says. Each file contains the coding lines that mirror the logic of the study.

“ER_HM_NET.f95”, for example, generates a “network with neuron modules randomly and sparsely connected”. The next one also creates such a structure, this time “with neuron modules randomly connected with the same number of neighbors.”
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When the researchers ask “How do biological networks tune themselves?” and “How can a neuronal network reach and stay near a critical region regardless of perturbations?”, a step-by-step simulation emerges as a plausible method that may result in plausible answers.

Rusch, Kinouchi, and Roque considered Hierarchical Modular networks with three distinct types of connectivity between neurons within the same module”, then them examined which one would be the best fit for the task of maintaining the brain’s operation close to critical points.

“We show that sparse modular architectures—particularly those based on random and regular connectivity—more effectively sustain critical dynamics across multiple hierarchical levels”, the authors report. Their conclusions themselves are sustained by the argument of open science: code availability, which strengthens science reliability.
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Simulations quite often put us one step ahead of experimentation. Reasonably, it becomes even more impactful when they allow pairs to learn from one another’s elucidative study and reproduce their pioneering steps.

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Coding | The “Black Box of Science” series
References:
1.Rusch, F.R., Kinouchi, O. & Roque, A.C. (2025). Influence of topology on the critical behavior of hierarchical modular neuronal networks. Commun Phys 8, 168 https://doi.org/10.1038/s42005-025-02074-5

2. NeuroMat (2026) - “Collaborating from home | The “Black-Box of Science” Series", Facebook post. https://www.facebook.com/share/p/1DtDqF9fcm/

3. Rusch, F.R., Kinouchi, O. & Roque, A.C. (2025) Critical behavior – Codes repository. Available at https://github.com/ruschh/Critical_Behavior_HM-Net

Influence of topology on the critical behavior of hierarchical modular neuronal networks - Communications Physics Critical brain hypothesis states that neuronal networks in the brain operate close to criticality. This study demonstrates the importance of the hierarchical and modular structure of neuron connections in maintaining criticality: modules with sparsely connected neurons can sustain critical activity....

AWARD

Aluno da Pós-Graduação do IME-USP recebe menção honrosa em congresso internacional O ex-aluno de doutorado do Programa de Pós-Graduação em Probabilidade e Estatística do Instituto de Matemática e Estatística da USP (IME-USP), Magno Tairone de Freitas Severino, foi agraciado com uma menção honrosa por sua tese

Collaborating from home | The “Black Box of Science” series

The participant is alone. This time, she’s at the office. It’s lunch time, she’s back before most of her colleagues. The computer is on, she puts on her headphones, but they’re muted, so as her phone. She just wants to reduce external noise and concentrate on the task. A friend told her it was challenging, kind of funny.

After receiving a link to a form, she inserts information about her gender, age, educational level and so on, then clicks on ‘Submit’. In a few moments, a second email: a link to the Goalkeeper Game.

Here's a setup where the researcher can’t actually make sure the participant sits in a comfortable chair and pays attention. The analysis does work, though. We’ll get there.
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Nowadays, those interested in neuroscience can quickly find a lot of content resulting from centuries of scientific work. If a grad student desires to become a researcher, they soon get familiar with the science publishing world of papers, dissertations, theses, books, etc.. With enough study and practice, they are able to dissect these documents and explore its less popular corners, such as the “Supplementary Information” page, henceforth SI.

The simple fact is that, as we discussed in our last post (See Ref. 2), science deeply relies on reproducibility. Checking results is crucial for many reasons and sustains science credibility. Therefore, scientists need access to detailed information about experimental design and procedures — which nowadays might be described with higher quality in an additional report, such as the SI.

Some black boxes are open access. Let us see what’s inside this one — and, more importantly, why exactly they are so important.

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Back to our participant. They could be at home, in a café, a square, or even at the university. As usually explained in the invitation, those willing to participate just need a computer with internet access and a quiet place with no distractions to collaborate. Those conditions, of course, vary depending on goals, methods, measures, subject groups, etc.
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“Due to the COVID19 pandemic, we opted to perform remote data collection”, state Hernández and colleagues in the Supplementary Information page of “Probabilistic prediction and context tree identification in the Goalkeeper game” (2024). Addressing “two related issues on the learning of probabilistic sequences of events”, they report a study where participants could collaborate remotely by playing the web version of the game.

Those guiding questions arose after previous studies. In this paper, they analyzed participants’ response times in search of answers. The measure — grouped by individual performances — was also useful to solve the challenge of establishing a relatively controlled environment outside the lab, in the absence of the investigators themselves.

“Explicit instructions were provided regarding the importance of avoiding distractions”, we read in the SI. The goal was to exclude participants “affected by variable compliance, environmental distractions and other potential factors inherent to the remote context”. This way, Hernández and colleagues found a balance between control of variables and contextual limitations.

Methodologically speaking, that meant not using data from a specific group: “goalkeepers displaying a negative slope in the estimated regression line”. In other words, it was assumed that participants would learn patterns to some degree and, at some point, whether improve their performance or, at least, maintain it.

A pre-analysis showed decreased performances, suggesting that some have disengaged in the game or got distracted. Based on this exclusion criterion, these results were not considered for the main analysis.
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The study conducted by Noslen Hernández, Claudia Vargas, Antonio Galves, … report evidence that subjects take into account their own past choices while still learning the statistical model that generates the pattern of kicks, then “consider only the past choices of the kicker” once they have learned.

One could question, indeed, the criteria for grouping the data. In the spirit of our initial discussion, this could be solved in scientific terms: a new hypothesis, new experiments, a reproduction of this one. Replication. Here’s exactly where transparency means a lot: with well-described design and procedures, choices and criteria, raw and processed data, science construction becomes more collaborative, efficient, and democratic.
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Remote experiments have become more viable, even though they won’t make labs less necessary. Benefits might include saving time and resources, while other precautions demand attention and planning.

Now, let us know: what remote method do you think will become popular in the near future?

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References:
1. Hernández et al. (2024). Probabilistic prediction and context tree identification in the Goalkeeper game. Sci Rep 14, 15467. https://doi.org/10.1038/s41598-024-66009-w

2. NeuroMat (2026) - “Research project management | The “Black-Box of Science” Series", Facebook post. https://www.facebook.com/share/p/1MuuQ619We/

3. The Goalkeeper Game, by NeuroMat. https://neuromat.numec.prp.usp.br/goalkeeper-game/

Probabilistic prediction and context tree identification in the Goalkeeper game - Scientific Reports In this article we address two related issues on the learning of probabilistic sequences of events. First, which features make the sequence of events generated by a stochastic chain more difficult to predict. Second, how to model the procedures employed by different learners to identify the structur...

CALL FOR PAPERS

You are cordially invited to contribute to the Special Issue of Stochastic Processes and Applications, « Probabilistic processes and their applications: from linguistics to neuroscience, passing through Non-Markovianness and Context Tree Models. A tribute to Antonio Galves. »

This special issue aims to collect articles that showcase recent progress across the many topics Antonio Galves has addressed throughout his rich and important scientific career. Topics include context tree models and selection; interacting and/or non-Markovian chains of variable memory, models of language acquisition, models of learning, modeling of spiking neurons and EEG data; metastability and perfect simulation in stochastic processes; modeling of EEG data; perfect simulation.

You can find more information about this issue on the dedicated webpage

https://www.sciencedirect.com/special-issue/10C888SK3GJ

The call for papers is open, and the submission deadline is December 31, 2026. You can submit your paper as soon as it is ready via the journal's editorial system.

www.sciencedirect.com

The fourth season of the podcast A Matemática do Cérebro, by CEPID NeuroMat, has been released today. In the first episode, host Felipe Parlato sits down with NeuroMat researchers Cláudia Domingues Vargas and Fernando Najman to discuss the Statistical Brain research line.
The episode focuses on a study that used musical beats to understand how our brains detect patterns and predict the occurrence of sound stimuli. The podcast is available on all major audio streaming platforms and podcast aggregators, and coming soon to YouTube.
Listen here:

podcast.numec.prp.usp.br

NEUROMAT SEMINAR

Next Wednesday, March 25, at 2:00 pm, Miguel Abadi - Departamento de Estatística – IME - USP, will give a talk in our seminar.

The title and the abstract are the following:

Title: Metastability and Multiscale Extinction Time on a Finite System of Interacting Stochastic Chains

Abstract: We investigate the metastability and extinction time of a finite discrete- time system composed of a large number of interacting components. The system is Markovian with respect to the potential profiles of the components, which are simultaneously subject to leakage and gain effects. We show that the only invariant measure is the null configuration and that it is reached in finite time. Additionally, the system exhibits a metastable state and a metastable barrier, which governs the timescale of the system’s lifetime. We identify a critical parameter, below which the extinction time is independent of system size. Above this critical value, the extinction time depends on the number of components, exhibiting infinitely many scaling behaviors governed by a nontrivial relationship among leakage, gain, and system size.

Electrodes are spread in a specific configuration around her head. For this EEG experiment, researchers adopted the traditional 10-20 system (see Ref. 2). The participant, as usual, sits in a comfortable chair. For forty minutes, she performs her role in this fragment of science construction.

She was instructed to relax. Try not to move too much, pay attention. Listen, read, click to answer. At some point, she feels a little sleepy in the silence of the lab with dim lights, but soon enough large letters on the screen announce: THAT’S IT! THE EXPERIMENT IS OVER. THANK YOU FOR PARTICIPATING!

A few more minutes to remove the electrodes, to clean her hair. A short conversation — questions, doubts, comments, curiosities. Thank you so much. Have a good day.

After she leaves the laboratory and walks past the Institute of Mathematics, she wonders what’s next for the researchers. Are they now doing some data analysis? What happens between one experiment and another?
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Immediately after the experiment, some researchers double-check the data integrity. Hardware and software problems do happen, so as issues related to the participant’s behavior. Perhaps they misunderstood the instructions; perhaps they slept during the fMRI procedures. It happens.

Hence, it is often useless to do so in the presence of the participant, since it would not be possible to rerun the experiment now that they know the task — and there is no benefit in sharing this frustration. The right amount of good-quality data demands patience.

That said, managing the data and the research project itself demands proper tools, a challenge that is not so widely known. The picture of scientists dividing their time between theory, experiments, and analysis overshadows a significant part of their work: documenting and managing the research process as a whole.

The impact in terms of reproducibility is huge — and, hence, for a transparent, democratic science.
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“Despite the remarkable advances made in the Neuroinformatics field in recent years, there is still a lack of open-source computational tools to cope with the heterogeneity and volume of neuroscientific data and the related metadata”, state Ruiz-Olazar and colleagues in their paper that introduces “The Neuroscience Experiments System (NES) -- a software tool to manage experimental data and its provenance”, (2022; see Ref. 1).

The problem was addressed by NeuroMat and resulted on the development of this open-source tool to assist neuroscientists. As the authors explain in the paper, “NES is a Web system that offers a user-friendly interface, allowing quick learning”. Crucially, “[i]ts data model combines several proposals from the scientific community”, which means common challenges and solutions have been taken into account.

Reproducibility is a core science principle, which comes along with the need for data reuse. Here, a specific challenge faced by neuroscientists is the quantity and variety of information. That demands a type of database suitable for the task. After all, replicating results can be challenging, sometimes even impossible, in the absence of detailed information on experimental design and procedures.

Again, citing Ruiz-Olazar and colleagues: “These platforms should allow scientists to examine the data and metadata and know exactly how these were obtained, as well as how the experiment was performed”. To tackle the problem, NES adopts a modular structure with functionalities that cover:
- Participants;
- Experiments;
- Questionnaires;
- Research organization;
- Data export.

Besides, NES meets the needs of both laboratories and research groups, since it contains an role-based control access (RBAC) approach. This way, each user has specific roles and permissions defined by the admin.

Currently, one interesting use case is the “Brachial Plexus Injury Database” (see Ref. 3), where researchers from the institutions involved are using NES to collect, store and manage data registered mainly from EEG and behavioral experiments, and information colected from clinical questionnaires.
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Tools like NES are critical for a scientific field more transparent and effective, since advances rely heavily on transparency and reproduction. You can find more informations in the references below. Now, let us know your thoughts on the relation between the scientific tools you adopt and the fostering of an open science culture!
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Research project management | The “Black Box of Science” series

References:

1. Ruiz-Olazar et al. (2022) - The Neuroscience Experiments System (NES)–A Software Tool to Manage Experimental Data and Its Provenance https://www.frontiersin.org/journals/neuroinformatics/articles/10.3389/fninf.2021.768615/full

2. “10-20 system (EEG)”, Wikipedia entry. Accessed in feb/2026. https://en.wikipedia.org/wiki/10%E2%80%9320_system_(EEG)

3. Brachial Plexus Injury Database – NeuroMat Open Database Web Portal. Accessed in feb/2026. https://neuromatdb.numec.prp.usp.br/experiments/brachial-plexus-injury-database/

Neuroscience Experiments Database This project intends to create a database able to store data of diverse provenance in adult traumatic brachial plexus injury (TBPI) and its surgical reconstruction. This initiative shall allow identifying functional markers related to clinical improvement.

Science construction is not linear. Unpredicted results can be as informative as confirmed hypotheses, even though they often go unnoticed. Therefore, one must keep an eye on controversies and how they develop in order to disentangle apparently contradictory results.

Sometimes, the answer to transforming inconsistencies into new, fruitful hypotheses may be right at hand.
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“Unlike a simple finger action such as thumb flexion”, explain Moraes and colleagues, “the performance of a complex manual task as a handgrip may lead to corticospinal modulation of intrinsic and extrinsic muscles, even without changes in their length” (2023; see Ref. 1). Human’s motor control demands a complex arrangement of neural systems and physical elements, where the Central Nervous System is the responsible for the functional synergy.

Thanks to it, typical humans can walk, grab things, dance, climb, talk. Still, describing and explaining this cognitive ability is not a trivial task.
Some previous studies have presented seemingly inconsistent results. While some findings have pointed to remote corticospinal modulation effects on different muscles in our hands and forearms, others have reported no such effects in adjacent hand muscles.

This inconsistency, after careful analysis, fostered insights that culminated in the above-mentioned paper. Perhaps the appearance of a remote corticospinal modulation depends on certain conditions. In other words,
– divergence –
may suggest that this specific neural modulation occurs in at least 2 distinct ways in different contexts.

There was a window for a better understanding of “(...) the interplay between the neural control of handgrip and the mechanical properties of muscle tissue under different conditions” (Morais et al., 2023). In the study, the researchers assessed corticospinal excitability of different muscles at rest and during a submaximal handgrip strength task.

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Fourteen right-handed subjects participated in the experiment that involved a dynamometer to measure maximum handgrip strength in various wrist postures. Measures were taken using surface Electromyographic (sEMG) combined with Transcranial Magnetic Stimulation (TMS) to assess corticospinal excitability.
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As expected, such a study feeds the discussion with new questions. In the authors’ words, “although extrinsic and intrinsic hand muscles exhibit overlapping cortical representations and partially share the same innervation, they can be modulated differently depending on the biomechanical constraints”.

It is worth mentioning the possible advantages for clinical application and sports performance. Patients recovering from wrist injuries or surgeries, for example, can benefit from therapeutic approaches that adopt postures that facilitate the corticospinal pathway as a strategy to regain handgrip capacity.

In this case, we gained a better understanding of “recruitment patterns and functional synergies”, which can directly benefit clinical work in rehabilitation and sports performance. It’s a reminder that divergence is part of the dialogue in science. We can see many more examples when we look at our past.
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Do you have a favorite contradiction that has driven scientific innovation? Let us know!
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Divergence | The “Black Box of Science” series

References:
1. Moraes et al. (2023) - Effect of muscle length in a handgrip task on corticomotor excitability of extrinsic and intrinsic hand muscles under resting and submaximal contraction conditions. Scandinavian journal of medicine & science in sports, 33(12), 2524–2533.

Effect of muscle length in a handgrip task on corticomotor excitability of extrinsic and intrinsic hand muscles under resting and submaximal contraction conditions The neurophysiological mechanisms underlying muscle force control for different wrist postures still need to be better understood. To further elucidate these mechanisms, the present study aimed to in...