Evidence map›Paper›PMID 34623400›Full record

ArticleBrain : a journal of neurology2021

Volitional control of individual neurons in the human brain.

Kramay Patel, Chaim N Katz, Suneil K Kalia, Milos R Popovic, Taufik A Valiante

Open access · bronzeAbstract read
In one paragraph

Article in Brain : a journal of neurology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.2field-weighted citation impact, top 23% of its field
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

6 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Article
  3. Closed-loop fMRI at the mesoscopic scale of columns and layers: Can we do it and why would we want to?Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
    Article
  4. Article
  5. Neuromuscular control: from a biomechanist's perspective.Frontiers in sports and active living · 2023
    Review
  6. Cognitive Control as a Multivariate Optimization Problem.Journal of cognitive neuroscience · 2022
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Kramay PatelKrembil Brain Institute, Toronto Western Hospital (TWH), Toronto, Ontario M5T 1M8, Canada.ORCID 0000-0002-5174-2309
Chaim N KatzKrembil Brain Institute, Toronto Western Hospital (TWH), Toronto, Ontario M5T 1M8, Canada.
Suneil K KaliaKrembil Brain Institute, Toronto Western Hospital (TWH), Toronto, Ontario M5T 1M8, Canada.
Milos R PopovicKrembil Brain Institute, Toronto Western Hospital (TWH), Toronto, Ontario M5T 1M8, Canada.
Taufik A ValianteKrembil Brain Institute, Toronto Western Hospital (TWH), Toronto, Ontario M5T 1M8, Canada.
University of Toronto · CAUniversity Health Network · CA

Funding

Neuronal mechanisms of human episodic memoryU01NS103792 · NINDS · CEDARS-SINAI MEDICAL CENTER · PI MAMELAK, ADAM NATHANIEL, RUTISHAUSER, UELI · 2017 to 2019
$3.5M
NINDS NIH HHS U01 NS103792
6 · The paper itself

Abstract

Brain-machine interfaces allow neuroscientists to causally link specific neural activity patterns to a particular behaviour. Thus, in addition to their current clinical applications, brain-machine interfaces can also be used as a tool to investigate neural mechanisms of learning and plasticity in the brain. Decades of research using such brain-machine interfaces have shown that animals (non-human primates and rodents) can be operantly conditioned to self-regulate neural activity in various motor-related structures of the brain. Here, we ask whether the human brain, a complex interconnected structure of over 80 billion neurons, can learn to control itself at the most elemental scale-a single neuron. We used the unique opportunity to record single units in 11 individuals with epilepsy to explore whether the firing rate of a single (direct) neuron in limbic and other memory-related brain structures can be brought under volitional control. To do this, we developed a visual neurofeedback task in which participants were trained to move a block on a screen by modulating the activity of an arbitrarily selected neuron from their brain. Remarkably, participants were able to volitionally modulate the firing rate of the direct neuron in these previously uninvestigated structures. We found that a subset of participants (learners), were able to improve their performance within a single training session. Successful learning was characterized by (i) highly specific modulation of the direct neuron (demonstrated by significantly increased firing rates and burst frequency); (ii) a simultaneous decorrelation of the activity of the direct neuron from the neighbouring neurons; and (iii) robust phase-locking of the direct neuron to local alpha/beta-frequency oscillations, which may provide some insights in to the potential neural mechanisms that facilitate this type of learning. Volitional control of neuronal activity in mnemonic structures may provide new ways of probing the function and plasticity of human memory without exogenous stimulation. Furthermore, self-regulation of neural activity in these brain regions may provide an avenue for the development of novel neuroprosthetics for the treatment of neurological conditions that are commonly associated with pathological activity in these brain structures, such as medically refractory epilepsy.

Indexed as

AdultBrainBrain-Computer InterfacesElectrocorticographyFemaleHumansLearningMaleMiddle AgedNeurofeedbackNeuronsVolitionbrain–machine interfacesepilepsyinstrumental conditioninglimbicneurofeedback

Identifiers

PMID34623400
PMCPMC8719845
OpenAlexW3201858881

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.