New research reveals that “infantile amnesia” – the forgetting of memories formed during early infancy – is both reversible and preventable

Neuroscientists have discovered a fascinating connection between the retention of early life memories and brain developmental trajectories associated with autism [Wednesday 8^th November 2023].

Most of us remember little of our experiences from before two years of age. This form of memory loss, termed “infantile amnesia” refers to the seemingly complete loss of episodic and autobiographical memories formed during early life. The research team at Trinity College Dublin investigated how infantile amnesia is affected by forms of autism. 

The maternal immune response, sparked into life in response to infection during pregnancy, is known to contribute to the cause of autism in both humans and mice. The Trinity neuroscientists report for the first time that this altered brain state also prevents the usual loss of memories formed during infancy. 

Using a mouse model the team behind this discovery showed that exposure to maternal immune activation, where inflammation is artificially induced during pregnancy in the absence of infection in order to alter offspring brain development, acts as a safeguard against developmental memory loss in early life by impacting the way specialist memory cells (engrams) in the brain function.

Furthermore, the study revealed that memories normally forgotten from infancy can be permanently reinstated if the correct memory engrams are activated in adults (in these experiments they used an “optogenetics” approach, which uses light to trigger specific neural pathways linked to the memory engrams of interest). These findings imply that infantile amnesia stems from a retrieval deficiency, as early childhood memories are still stored in the adult brain but cannot normally be accessed through natural recall.

Dr Tomás Ryan, Associate Professor in Trinity’s School of Biochemistry and Immunology and the Trinity College Institute of Neuroscience, is senior author of the article that has been published today in the leading international journal, Science Advances.

Dr Ryan emphasised the significance of these findings stating:

“Infantile amnesia is possibly the most ubiquitous yet underappreciated form of memory loss in humans and mammals. Despite its widespread relevance, little is known about the biological conditions underpinning this amnesia and its effect on the engram cells that encode each memory. As a society, we assume infant forgetting is an unavoidable fact of life, so we pay little attention to it.”

“These new findings suggest that immune activation during pregnancy results in an altered brain state that alters our innate, yet reversible ‘forgetting switches’ that determine whether the forgetting of infant memories will occur. This research holds significant implications for enhancing our comprehension of memory and forgetting across child development, as well as overall cognitive flexibility in the context of autism.” 

Lead author of the study, Dr Sarah Power, who completed her PhD research in Dr Ryan’s team (now a postdoctoral researcher at the Max Planck Institute for Human Development  in Berlin, Germany), said:

“Our brains’ early developmental trajectories seem to affect what we remember or forget as we move through infancy. We now hope to investigate in more detail how development affects the storage and retrieval of early childhood memories, which could have a number of important knock-on impacts from both an educational and a medical perspective.”

This study marks a major milestone in developmental memory research by shedding light on the connection between the retention of early childhood memories and maternal immune responses associated with Autism spectrum disorder (ASD). It also emphasises the adaptability of brain function in response to environmental challenges across embryonic and early postnatal development. 

A toddler plays a bubble-popping game as part of a 10-minute tablet app that can greatly aid in screening children for autism. CREDIT Duke University

Researchers at Duke University have demonstrated an app driven by AI that can run on a tablet to accurately screen for autism in children by measuring and weighing a variety of distinct behavioral indicators.

Called SenseToKnow, the app delivers scores that evaluate the quality of the data analyzed, the confidence of its results and the probability that the child tested is on the autism spectrum. The results are fully interpretable, meaning that they spell out exactly which of the behavioral indicators led to its conclusions and why.

This ability gives health care providers detailed information on what to look for and consider in children referred for full assessments and intervention. SenseToKnow’s ease of use and lack of hardware limitations, combined with its demonstrated accuracy across sex, ethnicity and race, could help eliminate known disparities in early autism diagnosis and intervention by allowing autism screening to take place in any setting, even in the child’s own home.

The results appear online October 2 in the journal Nature Medicine.

“Autism is characterized by many different behaviors, and not all children on the spectrum display all of them equally, or at all,” said Geraldine Dawson, director of the Duke Center for Autism and Brain Development, who is a co-senior author on the study. “This screening tool captures a wide range of behaviors that more accurately reflect the complexity and variability found in autism.”

Recent research has shown promising results from tracking children’s eye movements in response to specially designed movies that can help diagnose autism in a clinical setting. SenseToKnow, the researchers say, detects a wider range of behaviors such as facial expression, gaze patterns, head movements and blink rate. It also incorporates an on-screen bubble-popping game to assess motor movement and skills, as delays in motor skills are one of the earliest signs of autism.

The app uses almost every sensor in the tablet’s arsenal to measure and characterize the child’s response without the need for any sort of calibration or special equipment. It then uses AI to analyze the child’s responses to predict how likely it is that the child will be diagnosed with autism.

“The AI we’ve built compares each child’s biomarkers to how indicative they are of autism at a population level,” said Sam Perochon, a PhD student working in the laboratory of Guillermo Sapiro, the James B. Duke Distinguished Professor of Electrical and Computer Engineering and co-senior author of the study. “This allows the tool to capture behaviors other screening tests might miss and also report on which biomarkers were of the most interest and most predictive for that particular child.”

The AI tool is able to provide scores for both the quality of data that the app was able to capture as well as its level of confidence in its own analysis—both of which, the researchers believe, are a novel feature.

“This is an important aspect for a health care provider to know, just like they would need to know if a blood test did not have a big enough sample to produce reliable results,” said Matias Di Martino, assistant research professor of electrical and computer engineering at Duke, who co-led the analysis of the study with Sapiro and Perochon.

In the study, SenseToKnow was administered to 475 children during a pediatric well-child visit, 49 of whom were subsequently diagnosed with autism and 98 with developmental delay without autism. The app showed 87.8% sensitivity for detecting autism, meaning it correctly identified most children with the condition. Its specificity—the percentage of children without autism who screened negative—was 80.8%.

Overall, participants who screened positive for autism using the app had a 40.6% probability of subsequently being diagnosed with the condition. In comparison, only about 15% of children who screen positive using the standard parent questionnaire are later diagnosed with autism. Combining the app with the standard questionnaire boosted the probability of a positive screen resulting in later diagnosis to 63.4% — meaning fewer children are falling through the cracks.

The American Academy of Pediatrics recommends that every toddler be screened for autism at 18 and 24 months. However, concerns have been raised that current screening methods that rely solely on parent reporting are missing children. Girls and children of color, in particular, are often missed.

SenseToKnow’s ability to detect autism was similar across children of different sexes, races and ethnicities.  While the researchers do not envision the digital screening tool replacing parent reporting, they believe it is important to augment the subjective questionnaire with objective tools to help close the gap.

“Just like when any patient goes to their doctor, the doctor listens to them describe what they are experiencing, but they also use thermometers and other objective tests to provide additional information to guide next steps and referrals for further evaluation,” Dawson said. “Such objective tests have been missing for autism.”

The researchers are currently conducting a study in which parents deliver the app at home. They hope that the app will also be useful for measuring a child’s progress within an early intervention program as well as to studying the effectiveness of such programs.

“There is a wide range of expertise amongst health care providers in knowing and being able to recognize all the potential signs of a child being on the autism spectrum,” Dawson said. “This app could help clinicians focus on the areas in which the child needs help, as well as identify areas of strength.”