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Bottom-Up Problem-Solving in Autistic Adults: A Unique Cognitive Strength, Not a Learned Behavior

Updated: Mar 10

By Tim Aiello, MA, LPC, NCC, ADHD-CCSP, ASDCS

Clinical Director, Myndset Therapeutics


Introduction: What Is Bottom-Up Problem-Solving?

Problem-solving is a fundamental aspect of cognition, shaping how individuals interpret and interact with the world. In cognitive psychology, two primary approaches define how information is processed:


  • Top-down processing, where the brain applies pre-existing knowledge, schemas, and expectations to interpret new information. This approach dominates neurotypical cognition.


  • Bottom-up processing, where raw sensory input is gathered first, and broader patterns emerge only after enough data is accumulated (Kveraga et al., 2007).


As an AuDHD therapist specializing in ADHD, Autism, and AuDHD in adults, I have consistently observed that Autistic individuals default to bottom-up problem-solving—analyzing individual details before recognizing broader concepts. This is not simply a behavioral preference; rather, it is a fundamental neurological difference that defines how Autistic individuals perceive, process, and interact with their environment.


Bottom-Up Processing in Autism: A Neurological Foundation, Not a Learned Behavior

Many assume that cognitive styles, including bottom-up versus top-down thinking, are shaped by learning or personal preference. However, research confirms that bottom-up processing in Autism is not a learned strategy—it is hardwired into the Autistic brain.


1. Differences in Brain Connectivity and Predictive Coding

One of the leading theories explaining bottom-up dominance in Autism is the Predictive Coding Theory. Neurotypical brains rely on strong top-down predictions—meaning they use past experiences to “fill in” missing information, making sense of the world efficiently (Friston et al., 2013).


In contrast, Autistic brains rely more on raw sensory input and struggle with prediction-based processing (Van de Cruys et al., 2014). This results in:


  • Analyzing every piece of incoming data as new, rather than filtering information through mental templates.

  • Intense focus on details, heightened pattern recognition, and difficulty generalizing information.

  • Sensory overload and struggles with ambiguity due to reduced suppression of irrelevant details.


2. Structural Differences in Brain Regions Linked to Perception and Decision-Making

Autistic individuals often process information differently because of unique structural differences in their brains. Research using fMRI scans has identified two key patterns:


  • Increased local connectivity: Autistic brains show stronger connections within specific regions, meaning that detailed, focused thinking happens more efficiently in isolated areas (Belmonte et al., 2004). This heightened connectivity allows for deep focus, strong pattern recognition, and an ability to notice small details that others might miss. However, it can also make shifting attention or integrating different types of information more difficult.

  • Reduced long-range connectivity: The connections between distant brain regions are weaker, making it harder to integrate multiple sources of information at once (Pellicano & Burr, 2012). This can lead to challenges with forming quick generalizations, big-picture thinking, and prioritization. Instead of automatically recognizing an overall pattern, an Autistic individual may focus on each individual piece of information separately before slowly constructing a larger understanding.


For example, when solving a problem, a neurotypical person might quickly apply a general rule or previous experience to reach a conclusion (top-down thinking). An Autistic individual, on the other hand, may analyze every single detail of the situation before arriving at a conclusion (bottom-up thinking). This process can be more time-consuming but often results in greater accuracy, especially in areas that require careful attention to detail.


These structural differences help explain why many Autistic individuals excel in fields that demand precision and deep analytical thinking, such as mathematics, engineering, and research, while facing challenges in environments that require quick decision-making or rapid generalization of information.


3. Increased Sensory Processing and Reduced Perceptual Filtering

Autistic individuals often process more raw sensory input than neurotypicals, leading to heightened sensory perception (Robertson & Baron-Cohen, 2017).


  • Bottom-up processing means Autistic individuals absorb details before synthesizing them into broader concepts.

  • Unlike neurotypicals, who filter out “irrelevant” sensory information, Autistic people process nearly all incoming stimuli, making every detail significant.


🔹 Example: A neurotypical person might glance at a forest and instantly recognize it as “a wooded area,” filtering out individual trees and textures. An Autistic person, however, may process every tree, shadow, sound, and texture before forming the broader concept of “forest.”


How Bottom-Up Problem-Solving Manifests in Autistic Adults

Because Autistic individuals process the world from the ground up, their problem-solving strategies differ from neurotypical approaches.


1. Learning and Comprehension: Concrete First, Abstract Later

Autistic learners often struggle with abstract concepts until they have enough real-world, sensory, or experiential data to support them (Muth et al., 2014).


🔹 Example: If learning a scientific theory, an Autistic student may need to see multiple specific experiments and results before understanding the overarching concept, rather than absorbing a general explanation first.


2. Communication: Literal Thinking and Data Processing

Autistic individuals process language in a highly detailed and literal way due to bottom-up cognition (Happé & Frith, 2006).


🔹 Example: A neurotypical person might hear “It’s raining cats and dogs” and automatically recognize it as an idiom. An Autistic person might first process it literally, assessing its logical feasibility, before recalling it as a common expression.


3. Work and Analytical Strengths: Pattern Recognition and Deep Focus

Autistic individuals often excel in careers that require detail-oriented problem-solving, pattern recognition, and logic-driven analysis (Baron-Cohen et al., 2009).


🔹 Example: An Autistic forensic analyst may detect minute inconsistencies in crime scene data that others overlook because they process raw information instead of filtering it through cognitive shortcuts.


Challenges of Bottom-Up Processing in Daily Life

While bottom-up problem-solving provides strengths, it also presents real-world challenges, especially in environments designed for top-down thinkers.


  • Difficulty with vague instructions: Abstract or high-level directives can feel overwhelming.

  • Struggles with prioritization: Because all details seem equally important, choosing what to focus on can be difficult.

  • Analysis paralysis: Excessive time spent processing details may delay decision-making.

  • Sensory overload: Processing too much raw data without filtering can be exhausting.


🔹 Example: An Autistic person planning a vacation may hyper-focus on every detail—weather patterns, train schedules, baggage policies—without stepping back to create a simple, overarching travel plan.


Supporting Bottom-Up Thinkers

Since bottom-up processing is neurological, not behavioral, effective strategies should accommodate Autistic cognition rather than impose neurotypical expectations.


Provide Clear, Concrete Information First: Instead of vague instructions, offer specific steps.


Allow Extra Processing Time: Bottom-up thinkers often need more time to synthesize data.


Encourage Strength-Based Work: Careers in research, analysis, engineering, and IT often suit bottom-up processors.


Use Visual Supports and Examples: Many Autistic individuals benefit from visual learning tools and real-world examples.


Conclusion: Bottom-Up Processing as a Cognitive Strength

Bottom-up problem-solving is not a deficiency—it is a cognitive style shaped by the neurological structure of the Autistic brain. While it poses challenges in a top-down world, it also offers unparalleled strengths in detail-oriented analysis, deep focus, and pattern recognition.


By recognizing and supporting bottom-up processing, rather than attempting to “fix” it, we can create environments where Autistic adults thrive on their own terms.

At Myndset Therapeutics, we honor the neurodivergent brain and provide therapy that empowers Autistic and AuDHD individuals to navigate life in ways that align with their natural cognition.



References

1. Baron-Cohen, S., Ashwin, E., Ashwin, C., Tavassoli, T., & Chakrabarti, B. (2009). "Talent in autism: Hyper-systemizing, pattern detection, and attention to detail." Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1522), 1377-1383. https://doi.org/10.1098/rstb.2008.0337

2. Belmonte, M. K., Allen, G., Beckel-Mitchener, A., Boulanger, L. M., Carper, R. A., & Webb, S. J. (2004). "Autism and abnormal development of brain connectivity." The Journal of Neuroscience, 24(42), 9228-9231. https://doi.org/10.1523/JNEUROSCI.3340-04.2004

3. Demetriou, E. A., Lampit, A., Quintana, D. S., Naismith, S. L., & Whitehouse, A. J. O. (2019). "Executive function in autism spectrum disorder: A meta-analysis." Autism Research, 12(4), 538-555. https://doi.org/10.1002/aur.2087

4. Friston, K. J., Lawson, R., & Frith, C. D. (2013). "On hyperpriors and hypopriors: Comment on Pellicano and Burr." Trends in Cognitive Sciences, 17(1), 1-2. https://doi.org/10.1016/j.tics.2012.11.003

5. Happé, F., & Frith, U. (2006). "The weak coherence account: Detail-focused cognitive style in autism spectrum disorders." Journal of Autism and Developmental Disorders, 36(1), 5-25. https://doi.org/10.1007/s10803-005-0039-0

6. Kveraga, K., Boshyan, J., & Bar, M. (2007). "The proactive brain: Memory for predictions." Philosophical Transactions of the Royal Society B: Biological Sciences, 364(1521), 1235-1243. https://doi.org/10.1098/rstb.2007.0026

7. Mottron, L., Dawson, M., Soulières, I., Hubert, B., & Burack, J. (2006). "Enhanced perceptual functioning in autism: An update, and eight principles of autistic perception." Journal of Autism and Developmental Disorders, 36(1), 27-43. https://doi.org/10.1007/s10803-005-0040-7

8. Muth, A., Hönekopp, J., & Falter, C. M. (2014). "Visuo-spatial performance in autism: A meta-analysis." Journal of Autism and Developmental Disorders, 44(12), 3245-3263. https://doi.org/10.1007/s10803-014-2188-5

9. Pellicano, E., & Burr, D. (2012). "When the world becomes ‘too real’: A Bayesian explanation of autistic perception." Trends in Cognitive Sciences, 16(10), 504-510. https://doi.org/10.1016/j.tics.2012.08.009

10. Robertson, C. E., & Baron-Cohen, S. (2017). "Sensory perception in autism." Nature Reviews Neuroscience, 18(11), 671-684. https://doi.org/10.1038/nrn.2017.112

11. Van de Cruys, S., Evers, K., Van der Hallen, R., Van Eylen, L., Boets, B., de-Wit, L., & Wagemans, J. (2014). "Precise minds in uncertain worlds: Predictive coding in autism." Psychological Review, 121(4), 649-675. https://doi.org/10.1037/a0037665

12. Zwaigenbaum, L., Bryson, S., & Garon, N. (2013). "Early identification of autism spectrum disorders." Behavioral Neuroscience, 127(5), 628-642. https://doi.org/10.1037/a0033768

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