Atypical cognitive training-induced learning and brain plasticity and their relation to insistence on sameness in children with autism
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eLife assessment
This is an important study on learning strategy differences in autism vs typically developing controls. The study identifies similar learning rates but different learning strategies. The evidence provided by the authors is convincing, relying on well-done tasks and fMRI analyses.
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Abstract
Children with autism spectrum disorders (ASDs) often display atypical learning styles; however, little is known regarding learning-related brain plasticity and its relation to clinical phenotypic features. Here, we investigate cognitive learning and neural plasticity using functional brain imaging and a novel numerical problem-solving training protocol. Children with ASD showed comparable learning relative to typically developing children but were less likely to shift from rule-based to memory-based strategy. While learning gains in typically developing children were associated with greater plasticity of neural representations in the medial temporal lobe and intraparietal sulcus, learning in children with ASD was associated with more stable neural representations. Crucially, the relation between learning and plasticity of neural representations was moderated by insistence on sameness, a core phenotypic feature of ASD. Our study uncovers atypical cognitive and neural mechanisms underlying learning in children with ASD, and informs pedagogical strategies for nurturing cognitive abilities in childhood autism.
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Author Response
Reviewer #1 (Public Review):
“Liu et al present a very interesting manuscript investigating whether there are distinct mechanisms of learning in children with ASD. What they found was that children with ASD showed comparable learning to typically developing children, but that there was a difference in learning strategy, with less plasticity and more stable learning representations in children with ASD. In other words, children with ASD showed similar learning performance to typically developing children but were more likely to use different learning rules to get there. Interestingly greater fMRI-measured brain plasticity was associated with learning gains in typically developing children, whereas more stable (less plasticity) neural patterns were associated with learning gains in autistic children. This was mediated …
Author Response
Reviewer #1 (Public Review):
“Liu et al present a very interesting manuscript investigating whether there are distinct mechanisms of learning in children with ASD. What they found was that children with ASD showed comparable learning to typically developing children, but that there was a difference in learning strategy, with less plasticity and more stable learning representations in children with ASD. In other words, children with ASD showed similar learning performance to typically developing children but were more likely to use different learning rules to get there. Interestingly greater fMRI-measured brain plasticity was associated with learning gains in typically developing children, whereas more stable (less plasticity) neural patterns were associated with learning gains in autistic children. This was mediated by insistence on sameness (from the RRIB) in the ASD group. This is a good paper, well reasoned and with strong methods.”
We appreciate the positive comments from the reviewer.
1.1) “The biggest issue is related to subject numbers...With n=35 it is only possible to make a generalized statement about autism.”
Thank you for this comment. Although the sample size in the current study was modest, we would like to note that acquiring high-quality behavioral and brain imaging data at multiple time points a is a challenge in children with ASD. The current training study with unique longitudinal behavioral and brain imaging data provides an unprecedented opportunity to investigate the potentially atypical training-induced learning and brain plasticity in children with ASD relative to TD peers. To our knowledge, the present longitudinal sample is largest of its kind in studies of neurocognitive function in children with ASD. We have acknowledged these points in the revised Discussion section (Page 15), including the following statement:
“First, larger sample sizes are required to further characterize heterogeneous patterns of atypical learning and whether the findings can be generalized to a broader ASD population.” (Page 15)
1.2) “[Another] issue is related to [heterogeneity of autism-related findings]. For example, take the following statement from the results: "while most TD children used the memory-based strategy most frequently following training, nearly half of the children with ASD used rule-based strategies most frequently for trained problems." Is this the heterogeneity of autism at play, or the noisiness of the task and measures?
We hypothesize that group differences in changes in strategy use following training are due to atypical learning style or high level of inter-individual differences, i.e., greater heterogeneity, in autism, rather than noisiness of the measures. This hypothesis is based on the fact that we used the same tasks before and after training and a standardized training protocol across the two groups, which (i) allowed us to systemically examine atypical learning of these tasks in children with ASD compared to TD children and (ii) provided ecologically valid measures. This design minimized potential differences in measurement error between the two groups. We have clarified these points in the revised Introduction section (Page 4), including the following statement: “Crucially, we employed identical tasks before and after training and a standardized training protocol across the two groups. This approach enabled systemic analysis of learning in children with ASD relative to TD children.” (Page 4)
1.3) “Conceptually, is it realistic to expect a unitary learning strategy in all of autism?
We agree with the sentiment expressed by the reviewer, and indeed this notion led to the hypothesis that our study was to test. We hypothesized that children with ASD would not show a unitary learning strategy at this stage of development examined. Our results reveal that a disproportionate number of children with ASD use a rule-based strategy, reflecting atypical learning styles.
1.4) “Lastly, the task itself can only be solved in a subset of autistic children and therefore presents a limited view of the condition.”
We thank the reviewer for this important point and agree that additional studies tailored to more severely affected children with ASD are required for a more comprehensive characterization of learning in children with autism.
Reviewer #2 (Public Review):
“Overall, the authors sought to determine whether children with autism spectrum disorder (ASD) or typical development (TD) would both benefit from a 5-day intervention designed to improve numerical problem-solving. They were particularly interested in how learning across training would be associated with pre-post intervention changes in brain activity, measured with functional magnetic resonance imaging (fMRI). They also examined whether brain-behavior associations driven by learning might be moderated by a classic cognitive inflexibility symptom in ASD ("insistence on sameness"). The study is reasonably well-powered, uses a 5-day evidence-based intervention, and uses a multivariate correlation-based metric for examining neuroplastic changes that may be less susceptible to random variation over time than conventional mass univariate fMRI analyses. The study did have some weaknesses that draw into question the specific claims made based on the present set of analyses, as well as limit the generalizability of the findings to the significant proportion of individuals with ASD that are outside of the normative range of general cognitive functioning. The study also found minimal evidence for transfer between trained and untrained mathematical problems, limiting enthusiasm for the intervention itself. The majority of the authors' claims were rooted in the data and the team was generally able to accomplish their aims. I am sensitive to the fact that one of the main limitations I noted would have significant ethical implications-i.e. NOT offering potentially beneficial numerical training to children randomized to a sham or control group. I think the authors' work will represent a welcome addition to a growing corpus of studies showing similar neuropsychological test performance across several cognitive domains (e.g. learning, memory, proactive cognitive control, etc.) in ASD and TD. However, these relatively preserved cognitive functions still appear to be implemented by unique neural systems and demonstrate unique correlations to clinical symptoms in youth with ASD relative to TD, which may have implications for both educational and clinical contexts.
We thank the reviewer for the positive feedback and helpful suggestions.
Reviewer #3 (Public Review):
“Liu and colleagues examined learning and brain plasticity in neurotypical children and children with autism. The main findings include autistic children relying more on rule-based versus memory-based learning strategies, altered associations between learning gains and brain plasticity in children with autism, and insistence on sameness as a moderator between brain plasticity and learning in autism. Although the sample size is limited in this study, the findings provide a significant contribution to the field. The major strengths of this paper include an extensive pre and post training protocol, a detailed methods section, rationale behind the study, investigation of a potential moderator of learning gains and neural plasticity, and investigation of "neural plasticity" in association to learning in autism. Weaknesses of the study include a small sample size, and some missing information/analyses from the study. The authors laid out four clear aims of the study. They investigated these aims and the analytic approaches were appropriate. The paper included significant findings toward better understanding the mechanisms underlying differences in learning strategies and behavior in children diagnosed with autism spectrum disorder. This holds significant value in educational and classroom settings. Further, the investigation of a potential moderator of learning gains and neural plasticity provides a potential mechanism to improve the relationship. Overall, this is a significant contribution to the field. The autism literature is limited in understanding differences in learning styles and the underlying neural mechanisms of these differences.”
We thank the reviewer for the positive comments and detailed suggestions.
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eLife assessment
This is an important study on learning strategy differences in autism vs typically developing controls. The study identifies similar learning rates but different learning strategies. The evidence provided by the authors is convincing, relying on well-done tasks and fMRI analyses.
-
Reviewer #1 (Public Review):
Liu et al present a very interesting manuscript investigating whether there are distinct mechanisms of learning in children with ASD. What they found was that children with ASD showed comparable learning to typically developing children, but that there was a difference in learning strategy, with less plasticity and more stable learning representations in children with ASD. In other words, children with ASD showed similar learning performance to typically developing children but were more likely to use different learning rules to get there. Interestingly greater fMRI-measured brain plasticity was associated with learning gains in typically developing children, whereas more stable (less plasticity) neural patterns were associated with learning gains in autistic children. This was mediated by insistence on …
Reviewer #1 (Public Review):
Liu et al present a very interesting manuscript investigating whether there are distinct mechanisms of learning in children with ASD. What they found was that children with ASD showed comparable learning to typically developing children, but that there was a difference in learning strategy, with less plasticity and more stable learning representations in children with ASD. In other words, children with ASD showed similar learning performance to typically developing children but were more likely to use different learning rules to get there. Interestingly greater fMRI-measured brain plasticity was associated with learning gains in typically developing children, whereas more stable (less plasticity) neural patterns were associated with learning gains in autistic children. This was mediated by insistence on sameness (from the RRIB) in the ASD group.
This is a good paper, well reasoned and with strong methods. The biggest issue is related to subject numbers and possibly the conceptualization of ASD. With n=35 it is only possible to make a generalized statement about autism. For example, take the following statement from the results: "while most TD children used the memory-based strategy most frequently following training, nearly half of the children with ASD used rule-based strategies most frequently for trained problems." Is this the heterogeneity of autism at play, or the noisiness of the task and measures? Conceptually, is it realistic to expect a unitary learning strategy in all of autism? Lastly, the task itself can only be solved in a subset of autistic children and therefore presents a limited view of the condition.
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Reviewer #2 (Public Review):
- Overall, the authors sought to determine whether children with autism spectrum disorder (ASD) or typical development (TD) would both benefit from a 5-day intervention designed to improve numerical problem-solving. They were particularly interested in how learning across training would be associated with pre-post intervention changes in brain activity, measured with functional magnetic resonance imaging (fMRI). They also examined whether brain-behavior associations driven by learning might be moderated by a classic cognitive inflexibility symptom in ASD ("insistence on sameness").
- The study is reasonably well-powered, uses a 5-day evidence-based intervention, and uses a multivariate correlation-based metric for examining neuroplastic changes that may be less susceptible to random variation over time than …
Reviewer #2 (Public Review):
- Overall, the authors sought to determine whether children with autism spectrum disorder (ASD) or typical development (TD) would both benefit from a 5-day intervention designed to improve numerical problem-solving. They were particularly interested in how learning across training would be associated with pre-post intervention changes in brain activity, measured with functional magnetic resonance imaging (fMRI). They also examined whether brain-behavior associations driven by learning might be moderated by a classic cognitive inflexibility symptom in ASD ("insistence on sameness").
- The study is reasonably well-powered, uses a 5-day evidence-based intervention, and uses a multivariate correlation-based metric for examining neuroplastic changes that may be less susceptible to random variation over time than conventional mass univariate fMRI analyses.
- The study did have some weaknesses that draw into question the specific claims made based on the present set of analyses, as well as limit the generalizability of the findings to the significant proportion of individuals with ASD that are outside of the normative range of general cognitive functioning. The study also found minimal evidence for transfer between trained and untrained mathematical problems, limiting enthusiasm for the intervention itself.
- The majority of the authors' claims were rooted in the data and the team was generally able to accomplish their aims. I am sensitive to the fact that one of the main limitations I noted would have significant ethical implications-i.e. NOT offering potentially beneficial numerical training to children randomized to a sham or control group.
- I think the authors' work will represent a welcome addition to a growing corpus of studies showing similar neuropsychological test performance across several cognitive domains (e.g. learning, memory, proactive cognitive control, etc.) in ASD and TD. However, these relatively preserved cognitive functions still appear to be implemented by unique neural systems and demonstrate unique correlations to clinical symptoms in youth with ASD relative to TD, which may have implications for both educational and clinical contexts.
-
Reviewer #3 (Public Review):
Liu and colleagues examined learning and brain plasticity in neurotypical children and children with autism. The main findings include autistic children relying more on rule-based versus memory-based learning strategies, altered associations between learning gains and brain plasticity in children with autism, and insistence on sameness as a moderator between brain plasticity and learning in autism. Although the sample size is limited in this study, the findings provide a significant contribution to the field.
The major strengths of this paper include an extensive pre and post training protocol, a detailed methods section, rationale behind the study, investigation of a potential moderator of learning gains and neural plasticity, and investigation of "neural plasticity" in association to learning in autism.
Wea…
Reviewer #3 (Public Review):
Liu and colleagues examined learning and brain plasticity in neurotypical children and children with autism. The main findings include autistic children relying more on rule-based versus memory-based learning strategies, altered associations between learning gains and brain plasticity in children with autism, and insistence on sameness as a moderator between brain plasticity and learning in autism. Although the sample size is limited in this study, the findings provide a significant contribution to the field.
The major strengths of this paper include an extensive pre and post training protocol, a detailed methods section, rationale behind the study, investigation of a potential moderator of learning gains and neural plasticity, and investigation of "neural plasticity" in association to learning in autism.
Weaknesses of the study include a small sample size, and some missing information/analyses from the study.
The authors laid out four clear aims of the study. They investigated these aims and the analytic approaches were appropriate.
The paper included significant findings toward better understanding the mechanisms underlying differences in learning strategies and behavior in children diagnosed with autism spectrum disorder. This holds significant value in educational and classroom settings. Further, the investigation of a potential moderator of learning gains and neural plasticity provides a potential mechanism to improve the relationship. Overall, this is a significant contribution to the field.
The autism literature is limited in understanding differences in learning styles and the underlying neural mechanisms of these differences.
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