Investigating the Role of Individual Differences in Adherence to Cognitive Training.

Consistent with research across several domains, intervention adherence is associated with desired outcomes. Our study investigates adherence, defined by participants' commitment to, persistence with, and compliance with an intervention's regimen, as a key mechanism underlying cognitive training effectiveness. We examine this relationship in a large and diverse sample comprising 4,775 adults between the ages of 18 and 93. We test the predictive validity of individual difference factors, such as age, gender, cognitive capability (i.e., fluid reasoning and working memory), grit, ambition, personality, self-perceived cognitive failures, socioeconomic status, exercise, and education on commitment to and persistence with a 20-session cognitive training regimen, as measured by the number of sessions completed. Additionally, we test the relationship between compliance measures: (i) spacing between training sessions, as measured by the average time between training sessions, and (ii) consistency in the training schedule, as measured by the variance in time between training sessions, with performance trajectories on the training task. Our data suggest that none of these factors reliably predict commitment to, persistence with, or compliance with cognitive training. Nevertheless, the lack of evidence from the large and representative sample extends the knowledge from previous research exploring limited, heterogenous samples, characterized by older adult populations. The absence of reliable predictors for commitment, persistence, and compliance in cognitive training suggests that nomothetic factors may affect program adherence. Future research will be well served to examine diverse approaches to increasing motivation in cognitive training to improve program evaluation and reconcile the inconsistency in findings across the field.

Characterizing Attention Resource Capacity in Autism: A Multiple Object Tracking Study.

The extant literature aimed at characterizing attentional capability in autistics has presented inconsistent findings. This inconsistency and uncertainty may be the product of different theoretical and methodological approaches used to define attention in autism. In the current study, we investigate whether the allocation of attentional resources to task demands, and attention resource capacity, differs between autistics with no comorbid attention-deficit diagnosis (n = 55) and age-matched neurotypicals (n = 55). We compared differences in capacity and the allocation of resources by manipulating attentional load in a Multiple Object-Tracking (MOT) task, a robust, versatile, and ecological measure of selective, sustained, and distributed attention. While autistics demonstrated lower MOT performance, this difference disappeared when we accounted for fluid reasoning intelligence. Additionally, the similarity in the trend of MOT performance at increasing levels of attentional load between autistics and neurotypicals suggests no differences in the allocation of attentional resources to task demands. Taken together, our study suggests that higher-order cognitive abilities, such as intelligence, should be considered when characterizing attention across the autistic population in research. Similarly, our findings highlight the importance of considering cognitive competence when assessing attentional capabilities in autistic individuals, which could have significant implications for clinical diagnosis, treatment, and support.

Distinctive patterns of Multiple Object-Tracking performance trajectories in youth with deficits in attention, learning, and intelligence.

There is a significant overlap in symptomology between individuals with deficits in attention and learning, which is explained by the co-dependent dynamic between the two cognitive constructs. Within this dynamic, attentional resources are allocated to salient stimuli while learning mechanisms distinguish relevant from irrelevant information. Moreover, individuals with deficits in higher-order cognition (i.e., intelligence) can demonstrate difficulties in attention and learning. The Multiple Object-Tracking (MOT) task is a sensitive and versatile measure of attention that has characterized individual differences in attention as a function of higher-order cognition. Exploiting the traditional MOT task's ability to characterize the allocation of attentional resources to task demands, the current study compared learning exhibited on an attention-based task across neurodevelopmental conditions defined by deficits in attention (attention-deficit/hyperactivity disorder; ADHD), learning (specific learning disorder; SLD), and intelligence (intellectual developmental disorder; IDD). Children and adolescents (N = 101) completed 15 sessions on a Multiple Object-Tracking (MOT) task where performance trajectories were analyzed using latent growth curve modeling and conditioned by the presence of ADHD, SLD, or IDD while controlling for performance on a separate measure of attention, age, and sex. The sample, characterized by below-average IQ and problematic levels of attention, exhibited an effect of learning on MOT. However, individuals with an IDD diagnosis demonstrated decreased baseline MOT capability while ADHD and SLD profiles exhibited decreased slopes, relative to other neurodevelopmental conditions. Taken together, the results demonstrate distinct linear performance trajectories between neurodevelopmental conditions defined by deficits in attention, learning, and intelligence. The current study provides additional evidence to repurpose the traditional MOT task as a descriptor of attention and discusses alternative uses for the paradigm. Overall, these results suggest an eclectic approach that considers attention, learning, and higher-order cognition when diagnosing ADHD, SLD, or IDD.

Development of static and dynamic perception for luminance- and texture-defined information from school-ages to adulthood.

Few studies have assessed the visual development of static and dynamic information processing at different levels of processing during typical development from the school-age years to adulthood. The implication of non-visual factors on visual development, such as cognitive (e.g., IQ) and attentional abilities, has yet to be systematically assessed with regard to spanning such a large age range. To address these voids, 203 typically-developing participants (aged 6 to 31 years) identified the orientation or direction of a static or moving grating defined by either luminance- or texture-contrast. An adaptive staircase procedure was used to measure contrast sensitivity in all four conditions. Cognitive (Wechsler IQ) and attentional ability (CPT-3) were also measured for all participants. Different developmental rates of contrast sensitivity were found between static and dynamic conditions when defined by more complex, texture-defined information, with the difference in sensitivity starting after the age of 9.71 years. However, static and dynamic profiles for luminance-defined information developed similarly with age. In addition, IQ did not correlate with nor predict the sensitivity across any condition. These results suggest age significantly explains the variance in the developmental profiles of contrast sensitivity above and beyond non-visual factors such as IQ and the CPT-3 attentional scores. Moreover, the neural pathways processing static and dynamic visual information continue to develop through late childhood and adolescence for the processing of texture-defined information only.

Category learning in autism: Are some situations better than others?

Autism is diagnosed according to atypical social-communication and repetitive behaviors. However, autistic individuals are also distinctive in the high variability of specific abilities such as learning. Having been characterized as experiencing great difficulty with learning, autistics have also been reported to learn spontaneously in exceptional ways. These contrasting accounts suggest that some situations may be better than others for learning in autism. We tested this possibility using a probabilistic category learning task with four learning situations differing either in feedback intensity or information presentation. Two learning situations compared high- versus low-intensity feedback, while two other learning situations without external feedback compared isolated sequentially presented information versus arrays of simultaneously presented information. We assessed the categorization and generalization performance of 54 autistic and 52 age-matched typical school-age children after they learned in different situations. We found that children in both groups were able to learn and generalize novel probabilistic categories in all four learning situations. However, across and within groups, autistic children were advantaged by simultaneously presented information while typical children were advantaged by high-intensity feedback when learning. These findings question some common aspects of autism interventions (e.g., frequent intense feedback, minimized simplified information), and underline the importance of improving our current understanding of how and when autistics learn optimally. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Assessing the feasibility of a classroom-based visual attention training program targeting academics for students with extremely low IQ.

BACKGROUND: This feasibility study investigated the viability of implementing a cognitive-based training program (NeuroTracker) and assessing its potential effects on academic performance for adolescents with extremely low IQ. METHODS: Twenty-six adolescents aged between 11 and 16 years with a Wechsler-based IQs in the extremely low range (MIQ = 56.00, SDIQ = 13.89) completed 15 training sessions on either the NeuroTracker or an active control task; math and reading performance were assessed using clinically validated instruments before and after training. Recruitment and retention rates, adherence, and properties of the academic measures were assessed. RESULTS: All recruited participants completed 15 training sessions within a 6-week period. Eighty-three percent of participants meeting initial inclusion criteria completed all stages of the study from baseline to post-intervention assessments. Some limitations of the academic measures were identified. CONCLUSIONS: Results suggest that implementing NeuroTracker as a classroom-based intervention and using clinically validated outcome measures is feasible with this population.

Multiple object-tracking isolates feedback-specific load in attention and learning.

Feedback is beneficial for learning. Nevertheless, it remains unclear whether (i) feedback draws attentional resources when integrated and (ii) the benefits of feedback for learning can be demonstrated using an attention-based task. We therefore (i) isolated feedback-specific load from task-specific load via individual differences in attention resource capacity and (ii) examined the effect of trial-by-trial feedback (i.e., present vs. absent) on learning a multiple object-tracking (MOT) paradigm. We chose MOT because it is a robust measure of attention resource capacity. In Study 1 participants tracked one (i.e., lowest attentional load condition) through four target items (i.e., highest load condition) among eight total items. One group (n = 32) received trial-by-trial feedback whereas the other group (n = 32) did not. The absence of feedback resulted in better MOT performance compared with the presence of feedback. Moreover, the difference in MOT capability between groups increased as the task-specific attentional load increased. These findings suggest that feedback integration requires attentional resources. Study 2 examined whether the absence (n = 19) or presence (n = 19) of feedback affects learning on the same MOT task across four testing days. When holding task-specific load constant, improvement in MOT was greater with feedback than without. Although this study is the first to isolate feedback-specific load in attention with MOT, more evidence is needed to demonstrate how the benefits of feedback translate to improvement on an attention-based task. These findings encourage future research to further explore the interaction between feedback, attention and learning.

Training with a three-dimensional multiple object-tracking (3D-MOT) paradigm improves attention in students with a neurodevelopmental condition: a randomized controlled trial.

The efficacy of attention training paradigms is influenced by many factors, including the specificity of targeted cognitive processes, accuracy of outcome measures, accessibility to specialized populations, and adaptability to user capability. These issues are increasingly significant when working with children diagnosed with neurodevelopmental conditions that are characterized by attentional difficulties. This study investigated the efficacy of training attention in students with neurodevelopmental conditions using a novel three-dimensional Multiple Object-Tracking (3D-MOT) task. All students (ages 6-18 years) performed the Conners Continuous Performance Task (CPT-3) as a baseline measure of attention. They were then equally and randomly assigned to one of three groups: a treatment group, (3D-MOT); an active control group (visual strategy/math-based game, 2048); and a treatment as usual group. Students were trained on their respective tasks for a total of 15 training sessions over a five-week period and then reassessed on the CPT-3. Results showed that post-training CPT-3 performance significantly improved from baseline for participants in the treatment group only. This improvement indicates that training with 3D-MOT increased attentional abilities in students with neurodevelopmental conditions. These results suggest that training attention with a non-verbal, visual-based task is feasible in a school setting and accessible to atypically developing students with attentional difficulties.