The SfN experience

 Was at the Society for Neuroscience Conference from Oct 4-9. 

Largest neuroscience conference in the world with 22K attendees and 3K exhitors. A mix of overwhelm and awe. 

2 poster sessions navigated - a 2 hr long one during the Early Career Session linked to my TPDA award and another 4hr one under Cross Modal Processing in Humans Session









 


Temporal ventriloquism

Temporal ventriloquism is a phenomenon where the timing of one sensory modality, such as vision, influences the perception of timing in another modality, like sound. In multisensory integration research, temporal ventriloquism is explored through tasks where auditory and visual stimuli are presented slightly out of sync, but the brain often perceives them as occurring simultaneously or closer together in time. Researchers aim to understand how the brain resolves conflicting sensory information and determines which sensory input to prioritize in order to create a coherent perception of the environment.

In temporal ventriloquism tasks, participants might be asked to judge whether a sound and a visual flash are occurring at the same time, even when their timing is slightly offset. The extent to which vision can alter auditory perception—or vice versa—is key to understanding how the brain integrates sensory inputs. This task is particularly valuable in studying sensory processing in autism, where atypical multisensory integration is often reported.

In autism research, there is growing interest in how temporal ventriloquism might differ from typical sensory integration patterns. Autistic individuals may exhibit less flexibility in how sensory inputs are combined, potentially leading to difficulties in processing complex environments where timing discrepancies between senses occur. Studies have shown that autistics often rely more heavily on one sense over others, which might contribute to challenges in tasks like temporal ventriloquism (Noel et al., 2018). Understanding these differences in temporal processing can offer insights into sensory sensitivities and the broader challenges related to perception in autism.

PlainSpeak. In Plain Language for the Lay Audience

Temporal ventriloquism is when the brain tricks us into thinking that sounds and visuals are happening at the same time, even if they’re slightly out of sync. Imagine you see a light flash and hear a beep that’s just a little delayed, but your brain adjusts and makes you think they’re perfectly in sync. This is how the brain works to keep everything feeling smooth and connected across different senses.

In experiments, researchers test this by showing people lights and playing sounds that are a bit off in timing. They ask participants to judge if they think the sounds and visuals happened together. What’s interesting is that the brain can often ignore these small timing differences and make everything seem like it’s happening at once.

For autistic people, the way the brain handles sensory inputs like this might work a little differently. Some studies suggest that autistic individuals may have a harder time combining sounds and visuals when they’re slightly out of sync, which could be related to sensory sensitivities or challenges in processing multiple types of information at once. Understanding these differences could help explain why certain environments feel overwhelming for autistic individuals.

NSF GRFP New Fellows Welcome Event

"Keep making excellence a Priority" 


Vandy is racking it in this year

First a shoutout to  MacArthur Genius Grant given to Keivan  Staussun at Frist Center.

Next a Nobel in Chemistry.



https://www.dailycal.org/2018/04/12/compulsion-complexity



 

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:

  1. 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.
  2. 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:

  1. 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.
  2. 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.
  3. 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.


 

Cut off from the people you belong - even if you are surrounded by other people

 https://time.com/6551520/loneliness-autism-essay/ 



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.