Study suggests human brain optimally weights information during learning

May 8, 2017 by Christopher Packham, Medical Xpress report
Credit: Wikimedia Commons

(Medical Xpress)—The human brain's capacity for learning is adaptable to a variety of conditions. When the environment changes repeatedly and constantly, learning is difficult, because the brain automatically seeks patterns in incoming information. This requires weighting prior knowledge and incoming data according to reliability.

Recently, two researchers in France proposed that that brain assigns levels of confidence to both new and prior pieces of information by algorithmically evaluating the reliability of knowledge, and conducted an experiment to verify it. They have published the results of their study in the Proceedings of the National Academy of Sciences.

Twenty-one participants conducted a learning task while the researchers scanned them via fMRI. Subjects were presented visual and auditory stimuli in alternated sessions. The subjects experienced stable periods during which the order of the stimuli was constant, and they were able to assign high levels of confidence to the likelihood that a particular stimulus would be presented next. However, at random intervals chosen to avoid lengthy stable periods, the order of stimuli changed.

The researchers paused the sequence at semi-regular intervals and asked the subjects to report their confidence on a four-point scale with a dedicated button. It's important that before the experiment, the subjects were fully informed about the task structure and the process for generating the sequences of stimuli. The performances of the subjects were compared to that of an "ideal observer," an optimised Bayseian model that optimally estimates the likelihood of the current hidden transition probabilities.

The study determined that humans possess a sense of confidence in learned material that is remarkably similar to the "ideal observer" model. The researchers write, "We propose that learning approaches optimality in humans because it shares two features of the optimal algorithm: It relies on a sense of confidence that serves as a weighting factor to balance prior estimates and new observations; and confidence is organized hierarchically, taking into account higher-order factors such as volatility."

The fMRI scans indicated that a confidence-based statistical algorithm for auditory and visual sequences is hosted in the inferior frontal sulcus. The main effect of confidence that the researchers observed were fMRI signals in this brain region that increased as confidence decreased. They also looked for fMRI effects of surprise, another important factor in the learning process. They observed these signals across several areas, but notably also in the inferior frontal sulcus.

Previous learning studies have demonstrated that environmental volatility leads to a decrease in confidence that is strikingly similar to the ideal observer algorithm. And studies have also revealed that drops in boost learning, perhaps resetting the learning process altogether, priming the to seek new patterns. The researchers note that the study shows that "the performs better than classical learning algorithms predict, and indeed makes near-optimal use of all the available evidence when updating its internal model."

Explore further: Learning in the absence of external feedback

More information: Brain networks for confidence weighting and hierarchical inference during probabilistic learning. PNAS 2017 ; published ahead of print April 24, 2017, DOI: 10.1073/pnas.1615773114

Abstract
Learning is difficult when the world fluctuates randomly and ceaselessly. Classical learning algorithms, such as the delta rule with constant learning rate, are not optimal. Mathematically, the optimal learning rule requires weighting prior knowledge and incoming evidence according to their respective reliabilities. This "confidence weighting" implies the maintenance of an accurate estimate of the reliability of what has been learned. Here, using fMRI and an ideal-observer analysis, we demonstrate that the brain's learning algorithm relies on confidence weighting. While in the fMRI scanner, human adults attempted to learn the transition probabilities underlying an auditory or visual sequence, and reported their confidence in those estimates. They knew that these transition probabilities could change simultaneously at unpredicted moments, and therefore that the learning problem was inherently hierarchical. Subjective confidence reports tightly followed the predictions derived from the ideal observer. In particular, subjects managed to attach distinct levels of confidence to each learned transition probability, as required by Bayes-optimal inference. Distinct brain areas tracked the likelihood of new observations given current predictions, and the confidence in those predictions. Both signals were combined in the right inferior frontal gyrus, where they operated in agreement with the confidence-weighting model. This brain region also presented signatures of a hierarchical process that disentangles distinct sources of uncertainty. Together, our results provide evidence that the sense of confidence is an essential ingredient of probabilistic learning in the human brain, and that the right inferior frontal gyrus hosts a confidence-based statistical learning algorithm for auditory and visual sequences.

Related Stories

Learning in the absence of external feedback

April 6, 2016
Rewards act as external factors that influence and reinforce learning processes. Researchers from Charité - Universitätsmedizin Berlin have now been able to show that the brain can produce its own learning signals in cases ...

The brain sets a unique learning rate for everything we do, by self-adjusting to the environment

April 19, 2017
Each time we get feedback, the brain is hard at work updating its knowledge and behavior in response to changes in the environment; yet, if there's uncertainty or volatility in the environment, the entire process must be ...

Our brain uses statistics to calculate confidence, make decisions

May 4, 2016
The directions, which came via cell phone, were a little garbled, but as you understood them: "Turn left at the 3rd light and go straight; the restaurant will be on your right side." Ten minutes ago you made the turn. Still ...

Study demonstrates how humans navigate through doorways and not into walls

April 28, 2017
(Medical Xpress)—You walk into a wedding reception at a hotel. To your left, you see the entrance to the ballroom. To the right, there's an enormous painting of an evergreen forest. Behind you is the exit to the hotel lobby. ...

Dopamine neurons factor ambiguity into predictions enabling us to 'win big and win often'

March 9, 2017
In the struggle of life, evolution rewards animals that master their circumstances, especially when the environment changes fast. If there is a recipe for success, it is not: savor your victories when you are fortunate to ...

In gauging and correcting errors, brain plays confidence game, new research shows

July 19, 2016
The confidence in our decision-making serves to both gauge errors and to revise our approach, New York University neuroscientists have found. Their study offers insights into the hierarchical nature of how we make choices ...

Recommended for you

Brain liquefaction after stroke is toxic to surviving brain: study

February 20, 2018
Scientists have known for years that the brain liquefies after a stroke. If cut off from blood and oxygen for a long enough period, a portion of the brain will die, slowly morphing from a hard, rubbery substance into liquid ...

Therapeutic antibodies protected nerve–muscle connections in a mouse model of Lou Gehrig's disease

February 20, 2018
Amyotrophic lateral sclerosis (ALS), also known as Lou Gehrig's disease, causes lethal respiratory paralysis within several years of diagnosis. There are no effective treatments to slow or halt this devastating disease. Mouse ...

Brain immune system is key to recovery from motor neuron degeneration

February 20, 2018
The selective demise of motor neurons is the hallmark of Lou Gehrig's disease, also known as amyotrophic lateral sclerosis (ALS). Yet neurologists have suspected there are other types of brain cells involved in the progression ...

Every experience that the brain perceives is unique

February 20, 2018
Neuronal activity in the prefrontal cortex represents every experience as "novel." The neurons adapt their activity accordingly, even if the new experience is very similar to a previous one. That is the main finding of a ...

Brain aging may begin earlier than expected

February 20, 2018
Physicists have devised a new method of investigating brain function, opening a new frontier in the diagnoses of neurodegenerative and ageing related diseases.

Electrical implant reduces 'invisible' symptoms of man's spinal cord injury

February 19, 2018
An experimental treatment that sends electrical currents through the spinal cord has improved "invisible" yet debilitating side effects for a B.C. man with a spinal cord injury.

0 comments

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.