The gene PTEN has emerged as one of the most significant autism risk genes. Variations in this gene are found in a significant proportion of people with autism who also exhibit brain overgrowth. Researchers at the Max Planck Florida Institute for Neuroscience have discovered how loss of this gene rewires circuits and alters behavior, leading to increased fear learning and anxiety in mice – core traits seen in ASD.

PTEN has been linked to alterations in the function of inhibitory neurons in the development of ASD. The researchers focused on the changes in the central lateral amygdala driven by loss of PTEN in a critical neuronal population – somatostatin-expressing inhibitory neurons. They found that deleting PTEN specifically in these interneurons disrupted local inhibitory connectivity in the amygdala by roughly 50% and reduced the strength of the remaining inhibitory connections.

This diminished connectivity between inhibitory connections within the amygdala was contrasted by an increase in the strength of excitatory inputs received from the basolateral amygdala, a nearby brain region that relays emotionally-relevant sensory information to the amygdala. Behavioral analysis demonstrated that this imbalance in neural signaling was linked to heightened anxiety and increased fear learning, but not alterations in social behavior or repetitive behavior traits commonly observed in ASD.

The results confirm that PTEN loss in this specific cell type is sufficient to induce specific ASD-like behaviors and provide one of the most detailed maps to date of how local inhibitory networks in the amygdala are affected by genetic variations associated with neurological disorders. Importantly, the altered circuitry did not affect all ASD-relevant behaviors – social interactions remained largely intact – suggesting that PTEN-related anxiety and fear behaviors may stem from specific microcircuit changes.

By teasing out the local circuitry underlying specific traits, researchers hope to differentiate the roles of specific microcircuits within the umbrella of neurological disorders, which may one day help in developing targeted therapeutics for specific cognitive and behavioral characteristics. In future studies, they plan to evaluate these circuits in different genetic models to determine if these microcircuit alterations are convergent changes that underlie heightened fear and anxiety expression across diverse genetic profiles.

The field of neuroscience has made significant strides in understanding the complex mechanisms behind Alzheimer’s disease. A recent study by researchers at the University of California San Diego School of Medicine offers a glimmer of hope for those affected by this debilitating condition. By developing a gene therapy that targets the root cause of Alzheimer’s, these scientists may have found a way to not only slow down but also potentially reverse memory loss.

Alzheimer’s disease is a progressive disorder that affects millions worldwide. It occurs when abnormal proteins build up in the brain, leading to the death of brain cells and declines in cognitive function and memory. While existing treatments can manage symptoms, they do little to halt or reverse the progression of the disease. This new gene therapy, however, promises to address the underlying issue by influencing the behavior of brain cells themselves.

The researchers conducted their study using mice as models for human Alzheimer’s patients. They found that delivering the treatment at the symptomatic stage of the disease preserved hippocampal-dependent memory – a critical aspect of cognitive function often impaired in Alzheimer’s patients. Moreover, the treated mice had a similar pattern of gene expression compared to healthy mice of the same age, suggesting that the treatment has the potential to alter diseased cells and restore them to a healthier state.

While further studies are required to translate these findings into human clinical trials, this gene therapy offers a unique and promising approach to mitigating cognitive decline and promoting brain health. As researchers continue to refine and develop this technology, we may soon see a future where Alzheimer’s patients can experience a significant reversal of memory loss – a truly remarkable prospect that could revolutionize the way we understand and treat this devastating disease.

The human brain is incredibly skilled at solving complicated problems. One reason for this is that humans can break down complex tasks into manageable subtasks that are easy to solve one at a time. This strategy helps us handle obstacles easily, as shown by the example of going out for coffee, where we can revise how we get out of the building without changing the other steps.

While there’s a great deal of behavioral evidence demonstrating humans’ skill at these complicated tasks, it’s been difficult to devise experimental scenarios that allow precise characterization of the computational strategies used to solve problems. A new study by MIT researchers has successfully modeled how people deploy different decision-making strategies to solve a complicated task – in this case, predicting how a ball will travel through a maze when the ball is hidden from view.

The human brain cannot perform this task perfectly because it’s impossible to track all possible trajectories in parallel, but the researchers found that people can perform reasonably well by flexibly adopting two strategies known as hierarchical reasoning and counterfactual reasoning. The researchers were also able to determine the circumstances under which people choose each of those strategies.

“Weak humans are capable of doing is breaking down the maze into subsections, and then solving each step using relatively simple algorithms,” says Mehrdad Jazayeri, a professor of brain and cognitive sciences at MIT. “When we don’t have the means to solve a complex problem, we manage by using simpler heuristics that get the job done.”

The researchers recruited about 150 human volunteers to participate in the study and evaluated how accurately they could estimate timespans of several hundred milliseconds. For each participant, the researchers created computational models that could predict the patterns of errors that would be seen for that participant if they were running parallel simulations, using hierarchical reasoning alone, counterfactual reasoning alone, or combinations of the two reasoning strategies.

The researchers compared the subjects’ performance with the models’ predictions and found that for every subject, their performance was most closely associated with a model that used hierarchical reasoning but sometimes switched to counterfactual reasoning. This suggests that instead of tracking all possible paths that the ball could take, people broke up the task into smaller subtasks, picked the direction in which they thought the ball turned at the first junction, and continued to track the ball as it headed for the next turn.

If the timing of the next sound they heard wasn’t compatible with the path they had chosen, they would go back and revise their first prediction – but only some of the time. Switching back to the other side represents a shift to counterfactual reasoning, which requires people to review their memory of the tones that they heard.

The researchers found that people decided whether to go back or not based on how good they believed their memory to be. “People rely on counterfactuals to the degree that it’s helpful,” Jazayeri says. “People who take a big performance loss when they do counterfactuals avoid doing them. But if you’re someone who’s really good at retrieving information from the recent past, you may go back to the other side.”

The research was funded by various organizations, including the Lisa K. Yang ICoN Fellowship, the Friends of the McGovern Institute Student Fellowship, and the National Science Foundation Graduate Research Fellowship.

By slightly varying the amount of memory impairment programmed into the models, the researchers also saw hints that the switching of strategies appears to happen gradually, rather than at a distinct cut-off point. They are now performing further studies to try to determine what is happening in the brain as these shifts in strategy occur.