First a shoutout to MacArthur Genius Grant given to Keivan Staussun at Frist Center.
Next a Nobel in Chemistry.
Disability and Multilingualism
The approach, shaped by clinicians who advised speaking only English to autistic children, paradoxically led to a loss of cultural identity rather than the inclusive exposure that neurotypical children might receive.
Read Full Article at unesco.org...
Weak Central Coherence Theory
The Weak Central Coherence Theory (WCC) of autism, proposed by Uta Frith in the late 1980s and further developed by others, is a cognitive theory that attempts to explain some of the characteristic features of autism. The theory posits that autistics tend to process information in a detail-focused manner, often at the expense of global or contextual processing.
Key Components of WCC Theory:
- Detail-Focused Processing:
- Autistics are more likely to focus on the individual components of a stimulus rather than integrating these components into a coherent whole. This is sometimes referred to as "local processing" or "piecemeal processing.” Eg: notice the specific features of a face, like the shape of the nose or the color of the eyes, rather than perceiving the face as a unified whole.
- Reduced Global Processing:
- The theory suggests that there is a relative weakness in processing global or contextual information. This means that autistics might have challenges in seeing the "big picture" or understand the context in which details fit.
- For example, they might have difficulty understanding the main idea of a story or the overall mood of a social situation because they are focused on specific details.
Implications of Weak Central Coherence:
- Cognitive Strengths:
- The detailed-oriented processing style can lead to strengths in tasks that require attention to detail, such as certain types of puzzles, mathematical problems, or tasks involving pattern recognition.
- Autistics may excel in fields that value precision and attention to minute details.
- Social and Communication Challenges:
- Difficulty in integrating social cues and contextual information can contribute to challenges in social communication and understanding. For instance, recognizing social subtleties or understanding non-literal language (such as idioms or sarcasm) can be difficult.
- Problems with central coherence might also affect understanding narratives, jokes, and metaphors that rely on context.
- Perceptual and Sensory Processing:
- Some research suggests that weak central coherence is related to atypical sensory processing seen in autism, where individuals might have heightened or diminished sensitivity to sensory input.
- This can manifest as either an intense focus on specific sensory details or difficulty in filtering out irrelevant sensory information.
What do LLM's know?
Listened to a very interesting lecture today at SfN. by LA Paul.
Got me thinking about belief systems.
Belief Systems in Humans and LLMs.
While LLMs can produce outputs that seem aligned with certain perspectives or mimic human belief-based reasoning, they do not possess beliefs in the true sense. The distinction lies in the lack of consciousness, subjective experience, and intentional reflection. Instead, LLMs generate text based on patterns they have learned, without the internal state that would constitute holding beliefs. What may look like a belief system is merely a complex simulation, an echo of the data from which they were trained.
Do we need to update our belief systems to better understand LLM?
To better understand LLMs, humans may need to update their belief systems and frameworks, shifting away from traditional notions of intelligence, understanding, and knowledge. This means recognizing the statistical, context-based nature of LLM outputs, reframing how we think about AI capabilities, and addressing the ethical considerations that arise from their use. These changes can help foster a more accurate and nuanced understanding of what LLMs are, how they work, and what their role can be in our lives and society.
- Reframing Concepts of Intelligence: People often equate intelligence with understanding, leading to misconceptions about AI. LLMs simulate understanding based on learned patterns, not conscious thought, so recognizing this distinction helps prevent overestimating their abilities.
- Redefining Knowledge: Unlike human knowledge, LLMs work through statistical associations. Viewing them as tools for generating information rather than sources of human-like knowledge helps set realistic expectations.
- Context in Outputs: Humans tend to attribute intention to LLMs, but their outputs depend on context and training data. Focusing on this can clarify that their responses reflect patterns, not intentions.
- Recognizing LLM Limits: LLMs can mimic expertise but cannot verify facts or produce original thoughts. Differentiating fluency from factuality helps maintain a critical perspective on AI-generated content.
- Adopting Ethical Perspectives: As LLMs become more prevalent, it's important to address biases and responsibility for their outputs. Recognizing the societal impact of AI helps frame it beyond just a technical tool.
- Developing Communication Strategies: Effective use of LLMs requires skill in prompting and understanding their strengths. Clear communication about their capabilities helps prevent misunderstandings about AI’s nature.
Autistic Inertia
Autism Lexicon: Autistic Inertia
Autistic inertia refers to the difficulty some autistic individuals experience in initiating or terminating tasks, linked to neurobiological factors affecting cognitive flexibility, task switching, and motor planning.
PlainSpeak: Autistic inertia describes the challenges that autistic people may face in starting or stopping activities, often needing extra effort or support due to differences in brain function
Read in More Detail about Autistic Inertia
Emotionality Paradigm
An emotionality paradigm refers to an experimental framework or set of tasks designed to study how individuals perceive, process, and respond to emotional stimuli. These paradigms typically involve presenting participants with stimuli that elicit emotions, such as images, sounds, or videos of facial expressions, emotional words, or scenarios that convey different emotional states (e.g., fear, joy, anger, disgust). Researchers use these paradigms to investigate aspects of emotional processing, including recognition of emotions, emotional regulation, attention to emotional cues, and the impact of emotions on decision-making or behavior.
In the context of neuroscience or psychology, emotionality paradigms might be used alongside techniques like EEG, fMRI, or behavioral tasks to observe the neural correlates of emotional processing or assess how emotional responses differ across populations, such as in autism or anxiety disorders. For example, a task might involve showing a participant an image of a fearful face and measuring their brain response or reaction time to assess how quickly and accurately they process the emotion.
In PlainSpeak (Lay Language)
An emotionality paradigm is a way for researchers to study how people react to and process emotions. In these studies, participants are shown things that cause emotional reactions, like pictures, sounds, or videos showing different feelings such as happiness, fear, or anger. The goal is to understand how people recognize emotions, how they manage or control their emotions, and how emotions affect their thoughts or decisions.
In brain research, these tasks might be done while tracking brain activity using tools like EEG or fMRI, which help see how the brain processes emotions. These studies are often used to compare how people with different conditions, like autism or anxiety, respond to emotional situations. For example, a task might show a picture of a scared face, and researchers would measure how fast or accurately someone notices or reacts to that emotion.
Autism Cares Act 2024 Reauthorization
Key Highlights of the Autism CARES Act of 2024:
https://www.congress.gov/bill/118th-congress/senate-bill/4762/text
Reauthorization and Amendments:
These funding priorities aim to support comprehensive research, early detection, intervention, and coordination of services for individuals with autism spectrum disorder
Reauthorization and Amendments:
- The bill reauthorizes programs and research related to autism under the Public Health Service Act until 2029.
- It includes amendments to improve the language and scope of existing provisions, such as changing "culturally competent" to "culturally and linguistically appropriate."
- Extends the program's authorization to 2029.
- Updates terminology to be more inclusive and accurate.
- Emphasizes culturally and linguistically appropriate services.
- Expands the scope to include both screening and diagnostic services.
- Promotes research on evidence-based practices and interventions.
- Requires a report on the need for developmental-behavioral pediatricians and the feasibility of expanding training programs.
- Requires annual summaries and biennial updates on activities.
- Extends the committee's authorization to 2029.
- Updates the timeline for required reports to 2024.
- Adds a requirement for a report on young adults with autism transitioning to adulthood.
- Expands research areas to include psychiatry, psychology, gerontology, and other relevant fields.
- Requires the NIH Director to consider the various needs of individuals with autism, including co-occurring conditions.
- Mandates an annual budget estimate for autism research initiatives.
- Allows the Secretary of Health and Human Services to provide training and technical assistance on using federal funds for communication tools for individuals with autism.
- Requires an annual report on the technical assistance provided and advancements in communication tools.
- Developmental Disabilities Surveillance and Research: $28,100,000 annually for fiscal years 2025 through 2029.
- Autism Education, Early Detection, and Intervention: $56,344,000 annually for fiscal years 2025 through 2029.
- Interagency Autism Coordinating Committee and Related Activities: $306,000,000 annually for fiscal years 2025 through 2029.
These funding priorities aim to support comprehensive research, early detection, intervention, and coordination of services for individuals with autism spectrum disorder
Caught Between Tears and Stoicism
A story worth telling— not because it is exceptional for a disabled person to feel pride, but because it is an ordinary human experience. And that, in itself, is enough.
Read Full Article at
=======
Comment
Beautifully written and very wise, Hari! I will also share it with my students.
An Evolving Landscape of Autism Research
AI and Technology in Autism
- 2020s: Artificial intelligence (AI) and machine learning are applied to analyze large datasets in autism research, identifying biomarkers and developing early detection algorithms.
Biomedical Research
2000s: Gastrointestinal Issues and the Gut-Brain Axis: Studies link GI issues to behavioral changes in autism, leading to research on the gut-brain connection and its impact on autism symptoms.
2014-2018: Endocannabinoid System: Research reveals its role in regulating mood and stress in autism, leading to trials exploring CBD as a treatment for anxiety and sensory sensitivities.
2016: Immune System and Neuroinflammation: Research finds links between immune system irregularities and autism, with some individuals displaying elevated inflammatory markers.
2017: Microglia and Inflammation Research: Studies on microglia (the brain’s immune cells) suggest that increased activation may contribute to autism traits through neuroinflammation.
2019: Microbiome and Gut-Brain Research: Research on the gut microbiome shows that differences in gut bacteria may influence autism symptoms, prompting interest in probiotic treatments.
2019-2021: Nutritional and Metabolic Research: Research explores nutritional deficiencies and metabolic dysfunction in autism, leading to interest in dietary supplements and other nutritional interventions.
2020s: Precision Medicine Approaches: The rise of precision medicine leads to personalized autism treatments tailored to individual genetic, biological, and environmental profiles.
Mental Health
2010s: Autism and Anxiety: Studies show that anxiety is one of the most common co-occurring conditions in autism, particularly linked to sensory sensitivities and social challenges.
2020s: Depression and Suicide Research reveals high rates of depression and suicidal ideation among autistic individuals, leading to calls for targeted mental health interventions.
2010s: Autism and Anxiety: Studies show that anxiety is one of the most common co-occurring conditions in autism, particularly linked to sensory sensitivities and social challenges.
2020s: Depression and Suicide Research reveals high rates of depression and suicidal ideation among autistic individuals, leading to calls for targeted mental health interventions.
Co-occurring Conditions
2014: High Prevalence of Co-occurring Conditions: Studies reveal that 70-80% of autistic individuals have co-occurring conditions like anxiety, depression, ADHD, or epilepsy, emphasizing the need for integrated care.
2014: High Prevalence of Co-occurring Conditions: Studies reveal that 70-80% of autistic individuals have co-occurring conditions like anxiety, depression, ADHD, or epilepsy, emphasizing the need for integrated care.
Aging and Lifespan Research
2010: Shift Toward Aging Research: Research begins focusing on the aging process in autistic adults, identifying accelerated aging and increased physical and mental health conditions.
2015: Aging in Autistic Adults: Studies show that older autistic adults face increased physical health issues like mobility problems and early cognitive decline.
2016: Premature Mortality in Autism: Research reveals a higher risk of premature mortality in autistic individuals due to co-occurring conditions and limited healthcare access.
2019: Social Isolation and Mental Health in Older Adults: Studies highlight loneliness, depression, and anxiety in older autistic adults, prompting calls for better social support.
2020s: Aging, Mental Health, and Physical Health: Research shifts to focus on employment, independent living, and healthcare for aging autistic individuals, emphasizing the need for lifelong supports.
2023: Neurodegenerative Diseases and Autism: Emerging research suggests that older autistic individuals may be at higher risk for neurodegenerative diseases, prompting preventive healthcare strategies.
Motor Function and Movement Disorders
1980s-1990s: Recognition of motor impairments in autism, such as coordination issues and fine motor skill difficulties.
2000s: Movement and Motor Stereotypies: Motor stereotypies, such as hand-flapping and rocking, are studied as part of sensorimotor integration and self-regulation in autism.
2011: Motor Planning and Dyspraxia: Research reveals that many autistic individuals struggle with motor planning and dyspraxia, affecting both fine and gross motor tasks.
2015: Cerebellar and Motor Function: Neuroimaging reveals cerebellar abnormalities in autistic individuals, linking them to difficulties with motor coordination and balance.
2016: Gait and Balance in Autism: Studies show that many autistic individuals have atypical gait patterns and balance issues, which affect daily functioning.
2018: Motor Skills and Social Communication: Research highlights a link between motor skills and social communication, suggesting that improving motor coordination can also enhance social abilities.
2020s: Movement Disorder Subtypes: Research identifies subtypes of motor dysfunction in autism, including parkinsonism and proprioceptive challenges, adding depth to motor-related autism research.
Genetic and Neurological Research
1977: Genetic Link Discovered: Twin studies by Folstein and Rutter reveal a strong genetic component to autism, marking the beginning of autism genetics research.
1980s: Brain Differences Identified: Neuroimaging shows structural differences in the amygdala, frontal cortex, and cerebellum, regions related to social interaction and motor coordination.
2007: Autism Genome Project identifies several genetic mutations, emphasizing the heterogeneous nature of autism and its complex genetics.
2011: Synaptic Pruning: Research finds that impaired pruning in autistic individuals may lead to excess neural connections, contributing to sensory overload.
2015: CRISPR and Genetic Editing: The introduction of CRISPR/Cas9 gene-editing technology provides new insights into autism by allowing the study of genetic mutations and considering potential treatments.
2018: Epigenetics research shows how environmental factors influence gene expression, adding complexity to the genetic understanding of autism.
Sensory Processing Research
1990s: Sensory Processing Differences: Researchers recognize sensory processing differences (hypersensitivity or hyposensitivity) as a hallmark of autism, leading to sensory-based therapies to manage anxiety and stress.
2000s: Sensory Integration Therapy emerges as a common approach to help autistics respond better to sensory input, using activities such as swinging, climbing, and deep pressure to improve sensory regulation.
2000s: Sensory Overload and Environmental Factors: Studies explore how sensory overload in environments like schools and workplaces contributes to anxiety and meltdowns. Creating sensory-friendly environments with dim lighting and noise reduction improves functioning.
2010s: Sensory Over-responsivity and Brain Connectivity: Over-responsivity to sensory stimuli is linked to atypical brain connectivity, showing hyperconnectivity in sensory processing areas, which results in overwhelming responses to stimuli like loud noises or bright lights.
2010s: Sensory Subtypes in Autism: Researchers identify sensory subtypes, including over-responsive, under-responsive, and sensory-seeking behaviors, acknowledging the diversity in sensory processing challenges.
2018: Sensory Processing and Mental Health: Research highlights the connection between sensory processing differences and mental health conditions, such as anxiety and depression, especially in relation to sensory overload contributing to social withdrawal and stress.
2020s: Sensory Processing and Social Communication: Findings suggest that sensory processing differences directly impact social communication in autism. Sensory overload may interfere with social interactions, prompting sensory-informed social skills interventions.
2020s: Wearable Sensory Devices: Wearable devices, such as noise-cancelling headphones and compression garments, help autistic individuals manage sensory overload in daily settings.
Technology and Autism
2010s: Assistive Technology for Communication [still lagging terribly]
2020s: AI and Virtual Reality (VR): applied in autism research, particularly in social skills training, allowing autistic individuals to practice social interactions in controlled settings.
Autism and Employment
2010s: Employment Challenges: Research reveals widespread unemployment and underemployment among autistic adults, leading to the development of neurodiversity hiring programs at major companies like SAP and Microsoft.
2020s: Inclusive Work Environments: Studies focus on creating inclusive work environments, showing that autistic employees can thrive with the right accommodations and mentorship.
Social Cognition Research
1980s: Theory of Mind (ToM): Research introduces mindblindness in autistic individuals, suggesting difficulty understanding others’ thoughts and feelings (Theory of Mind deficits).
1990s: Executive Function and Social Challenges: Studies explore how executive function deficits (e.g., planning, flexibility) affect social cognition, leading to challenges in managing social situations.
2000s: Empathy Research: Researchers distinguish between cognitive empathy (understanding others’ perspectives) and affective empathy (sharing others’ emotions), with cognitive empathy being impaired but affective empathy often intact.
2010s: Mirror Neuron Research: Mirror neuron dysfunction is studied as a potential cause of difficulties with social imitation and understanding others' actions in autism.
2017: Social Skills Training: Social skills training programs target social cognition deficits, such as recognizing emotions and understanding social cues, improving social functioning.
2018: Social Cognition and Cognitive Flexibility: Research shows that autistic individuals process social information differently, leading to interventions focused on cognitive flexibility and social interaction.
2020s: Social Motivation Theory: Social motivation theory suggests that reduced motivation for social interactions, rather than an inability to understand social cues, contributes to autism’s social challenges.
Early Identification and Intervention
1990s-2000s: Early Screening: Advances in early screening tools, enable earlier detection and more effective interventions.
2010s: Early Behavioral Interventions: Research on early interventions ABA, Early Start Denver Model (ESDM), and Pivotal Response Training (PRT).
Autistic Women and Gender Differences
2010s: Autism in Females: Research revealing that many autistic women and girls are underdiagnosed due to masking behaviors.
2020s: Late Diagnosis in Women: Studies emphasize the need for gender-sensitive diagnostic criteria and appropriate supports for these individuals.
2010-20s: Nonbinary Individuals: Studies emphasize the need for gender-sensitive diagnostic criteria. Researchers find that nonbinary and transgender autistic individuals are also often underdiagnosed or misdiagnosed, as their experiences may not align with traditional diagnostic frameworks.
Family and Caregiver Research
2000s: Family Impact: Research highlights the emotional, financial, and logistical burdens faced by families and caregivers of autistic individuals, calling for family-centered support services.
2000s: Sibling Research: Studies explore the experiences of siblings of autistic individuals, prompting the development of support groups and resources for siblings.
Neurodiversity and Self-Advocacy
2010s: Rise of the Neurodiversity Movement: The neurodiversity movement led by autistic self-advocates promotes the view of autism as a natural variation of human experience, leading to a strengths-based approach to autism research.
2020s: Advocacy and Policy Changes: push for more inclusive research practices and participatory models, making autistic individuals co-creators of research.
Subscribe to:
Posts (Atom)