summary: A new study reveals that people with schizophrenia and depression struggle to make optimal use of information in the learning process.
Using EEG and advanced computer modeling, researchers found that these patients placed greater weight on less important information, leading to suboptimal decision-making. Reduced flexibility in processing new information was particularly evident in feedback management for future actions.
The findings suggest that the cognitive limitations of schizophrenia and depression may be addressed by targeted treatments that focus on these specific learning disabilities.
Important facts:
- Patients with schizophrenia and depression have impaired learning processes, overvalue less important information, and struggle to make decisions based on feedback.
- In this study, we used EEG and computer modeling to demonstrate a reduction in the neural representation of reward expectations in these patients.
- This research may pave the way for developing more targeted treatment strategies to improve daily functioning in individuals with these mental health disorders.
sauce: Otto von Guericke University of Magdeburg
People with schizophrenia and depression have difficulty making optimal use of new information when learning. During the learning process, both patient groups give more weight to less important information, resulting in less-than-ideal decisions.
This was the result of several months of research conducted by a team led by neuroscientist M.D., Ph.D. Markus Ullsperger from the Otto von Guericke University Magdeburg Institute of Psychology conducted the study in collaboration with colleagues from the university’s Clinic of Psychiatry and Psychotherapy and the German Center for Mental Health.
Using electroencephalography (EEG) and complex mathematical computer modeling, the research team showed that learning disabilities in patients with depression and schizophrenia are caused by reduced/decreased flexibility in using new information. discovered.
This study just brain The title is “Transdiagnostic, inflexible learning dynamics explain deficits in depression and schizophrenia.”
“People with depression and schizophrenia often suffer from cognitive limitations,” says Dr. Hans Kirschner, lead author of the study. For example, they find it difficult to understand complex information, learn, plan, and generalize situations.
“In particular, deficiencies in using feedback from the past to manage future behavior pose fundamental problems for those affected.”
Dr Tillman Klein, a neuropsychologist and psychotherapist, added that these cognitive limitations are extremely troubling for affected patient groups and have a strong impact on treatment outcomes.
“The better we understand these disorders and their causes, the more we can design forms of treatment, such as functional training, to be more specific and targeted in the long term.”
To examine whether the psychological and neural mechanisms that lead to cognitive limitations are the same across different mental disorders, the scientists studied patients diagnosed with severe depressive disorder and schizophrenia; A control group consisting of:
Subjects were repeatedly presented on a screen with images of animals associated with high or low probabilities of reward or punishment, i.e., positive or negative feedback.
Subjects had to decide whether to bet on the animal and win or lose with 10 points. If you didn’t bet, you didn’t win or lose anything, but you will see what would have happened if you had chosen to bet.
Dr. Kirshner explains the test setup: “During the experiment, the participants’ objective was to find out whether it was worth betting and therefore the risk of loss associated with it, or whether losses could be avoided by not betting.”
“This process is a bit like a game of roulette,” explains the neuroscientist. “If you bet, you either win or lose. Even without betting, you can see where the little ball is going and speculate about what would have happened if you had bet.
“What was different about our study was that participants were actually able to learn, because over time, animals were on average more likely to be rewarded or more likely to be punished. Begin to understand that you can always bet on that animal and therefore maximize your profits by either getting a win or minimizing your losses. ”
According to Kirschner, optimal learning in this task means that subjects pay more attention to the feedback at the beginning of the learning process: whether the animal wins or loses.
“Once an animal senses a chance of winning, it will ignore misleading feedback. For example, a photo that would normally be likely to lose may sometimes win.”
Healthy control participants did just this, but a group of patients suffering from depression or schizophrenia were more affected by randomly occurring errors.
“Imagine a basketball player throwing a ball into a basket,” continues Dr. Kirshner. “Poor players rarely score and are not selected for the team. Even if they don’t score every time, good players score frequently and are therefore selected for the team. However, in this study, neither patient group But if you make a bad shot, you’ll be replaced with a better player.”
EEG shows reduced neuronal representations of reward expectation in both patient groups.
“This means that a good basketball player’s scoring rate is not stored well in the brain, and gets overwritten more quickly if the player occasionally fails to score.”
In summary, Dr. Kirschner explains that this study expands the team’s knowledge about the cognitive limitations of patients diagnosed with schizophrenia or depression. “In particular, he was able to mathematically describe complex learning mechanisms on computers. He was also able to demonstrate the benefits of computer models, which he sought to implement in the form of simulations.”
This made it possible to simulate learning behaviors that are difficult to predict and compare them to participants’ behavior in specific tasks.
“With this approach, [the] In the future, we will be able to quantify and characterize learning disabilities in more nuanced ways. And a deeper understanding of these deficiencies can help guide us to further develop existing treatments for depression and schizophrenia in a more targeted manner.
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We hope that in the future our research will benefit patients with learning disabilities and help them cope better in everyday life. ”
About this mental health and learning research news
author: Katharina Vorwerk
sauce: Otto von Guericke University of Magdeburg
contact: Katharina Vorwerk – Otto von Guericke University of Magdeburg
image: Image credited to Neuroscience News
Original research: Open access.
“Transdiagnostic, inflexible learning dynamics explain deficits in depression and schizophreniaWritten by Hans Kirschner et al. brain
abstract
Transdiagnostic, inflexible learning dynamics explain deficits in depression and schizophrenia
Deficits in reward learning are a core symptom of many mental disorders. Recent studies suggest that such learning deficits result from a reduced ability to use reward history to guide behavior, but the neurocomputational mechanisms by which these deficits emerge remain unclear. Furthermore, limited research has adopted transdiagnostic approaches to investigate whether the psychological and neural mechanisms that cause learning disabilities are common to different forms of psychopathology.
To provide insight into this issue, we investigated stochastic reward learning in patients diagnosed with major depressive disorder (n = 33) or schizophrenia (n = 24) and 33 healthy controls by combining computational modeling and single-trial EEG regression. In our task, participants had to integrate the reward history of a stimulus to decide whether it was worth betting on. Adaptive learning in this task is achieved by a dynamic learning rate that is maximal when a particular stimulus is encountered for the first time and decays as stimulus repetition increases. Ideally, therefore, choice preferences would stabilize during the learning process and become less susceptible to misleading information.
We show that both patient groups exhibit hypersensitive learning (i.e., less decline in learning rate) and evidence of reduced learning dynamics that make their choices susceptible to misleading feedback. Additionally, there was an approach bias characteristic of schizophrenia and an increased sensitivity to counterfactual feedback (factual losses and counterfactual wins) characteristic of depression. Inflexible learning in both patient groups was accompanied by changes in neural processing, with expectations not being tracked in either patient group.
Thus, taken together, our results provide evidence that reduced trial-by-trial learning dynamics reflect convergence deficits across depression and schizophrenia. Additionally, we identified disability-specific learning difficulties.