The Uncomfortable Truth Behind a Comforting Word

In the world of scientific research, words carry weight. They shape perceptions, influence emotions, and sometimes, soften the harsh realities of the work being done. One such word is "sacrifice," a term often used to describe the killing of animals, particularly rats, after they have been subjected to various experiments in the name of research. But what does "sacrifice" really mean in this context, and why does it seem to make everyone feel better about a process that is fundamentally unsettling?

The Comforting Illusion of Sacrifice

The word "Sacrifice" is imbued with noble connotations. It suggests an offering, a giving up of something valuable for a greater good. In religious and historical contexts, sacrifices are seen as acts of devotion, acts that are often rewarded with blessings or benefits. In the laboratory, however, the use of "sacrifice" to describe the euthanization of lab rats serves a different purpose—it sanitizes the act, masking the uncomfortable truth of what is actually happening.

The Reality Behind the Term

In research settings, rats are often subjected to a variety of procedures. These can include surgeries, injections, and exposure to drugs or other substances, all in the pursuit of scientific knowledge. After these procedures, the animals are typically euthanized. The term "sacrifice" is used to describe this final act. But let's be clear: the rats are not voluntarily giving up their lives for the greater good. They are being killed because their continued existence is no longer deemed necessary or beneficial for the study.

Making Everyone Feel Better

Using the word "sacrifice" helps researchers, lab technicians, and the public feel better about the process. It creates a psychological buffer, a way to cope with the ethical dilemmas inherent in animal research. By framing the killing as a sacrifice, it suggests that the act is justified, that it is part of a noble quest for knowledge and human advancement. This linguistic choice helps to ease the guilt and moral discomfort that might otherwise accompany the act of ending an animal's life.

The Irony and Ethical Implications

The irony is palpable. While the term "sacrifice" suggests a willing, even heroic act, the reality is one of imposed death following a period of often stressful and painful experimentation. This discrepancy raises important ethical questions. Are we too quick to accept this euphemism without questioning the underlying practices? Does the term "sacrifice" allow us to avoid confronting the moral complexities of animal research?

Perhaps it is time to reconsider our language and the comfort it provides. Transparency in research practices, including the language we use, is crucial. Instead of relying on euphemisms, we should strive for honesty about what happens to animals in research settings. This might involve using more straightforward terms like "euthanize" or "kill" to describe the end of an animal's life in the lab.

Integrating Positive Psychology and Autism.

 I'm published in a journal article. https://doi.org/10.1089/aut.2024.38246.pw

This is my first academic publication

(hope many more to come)

Shrouded Weight

A veil of sorrow surrounds me.
What is the expectation of me?
Disability is a weight indeed.

Uncertain Fate

Will I be allowed to strive and thrive

Or always be left just barely alive?
Staying afloat, with hope so thin,
Struggling each day, just to survive within.

Overwhelmed

I feel overwhelmed today
Waves of doubt come crashing in.
Waiting on undefined academic expectations, I'm supposed to meet
Disability adds weight to my limbs,
And anxiety skyrockets within.

Crimson Fridays

 Feeling end of semester pressure #gradschool

If Blue is for Monday, then I assign Crimson for Friday

CRIMSON FRIDAYS

Check out my other poetry on this blog or on YouTube. 

A Jest for the Best

https://youtu.be/BXGY6PCxuM4

Find my poetry on my YouTube Channel

Attribution Errors

Attribution errors, also known as attribution biases, are cognitive biases that affect how individuals interpret and explain the behavior of themselves and others. These biases involve making inaccurate or biased judgments about the causes of behaviors, often by attributing them to dispositional (internal) factors or situational (external) factors. One common attribution error is the fundamental attribution error (FAE), which occurs when people tend to overemphasize dispositional factors and underestimate situational factors when explaining the behavior of others. For instance, if someone witnesses a colleague being late to work, they might attribute it to the colleague's laziness or lack of punctuality (dispositional), while ignoring the possibility that the colleague might have encountered traffic or had an emergency (situational).

Another attribution error is the actor-observer bias, which relates to the tendency for individuals to attribute their own behavior to situational factors (e.g., "I was late because of traffic") but attribute the behavior of others to dispositional factors (e.g., "They were late because they're always irresponsible"). This bias highlights the differing perspectives people have when explaining their own actions versus the actions of others, often giving themselves the benefit of the doubt while judging others more critically. Understanding attribution errors is essential because they can lead to misunderstandings and conflicts in interpersonal relationships and can affect how individuals perceive and interact with others. Recognizing these biases can help people become more empathetic and make more accurate judgments about the behaviors and motivations of those around them.

p-value

p-value for the layman

Statistics can often feel like a labyrinth of complex numbers and jargon. In the world of statistics, p-values are your compass. While the concept may seem a bit abstract at first, p-values are like a traffic light for your scientific discoveries, guiding you to proceed with caution or giving you the green light to embrace a new understanding of the world.

What is a p-value?

At its core, a p-value is a number that helps us determine the significance of an observation or result in statistical analysis. Imagine you've conducted an experiment or a survey, and you want to know if your findings are meaningful or just a result of chance. The p-value is your guide.

The Role of Probability

To grasp p-values, you need to understand the concept of probability. Think of it as a measure of how likely something is to happen. In statistics, we often want to know the probability of observing certain data if there's no real effect or difference. This is where p-values come into play.

Hypotheses: The Foundation

In any scientific study, you start with two hypotheses: the null hypothesis (H0) and the alternative hypothesis (H1). The null hypothesis represents the idea that there's no significant effect or difference, while the alternative hypothesis suggests the opposite – that there is a significant effect or difference.


The Experiment and the Data

You gather your data, conduct your analysis, and calculate a test statistic, which quantifies the difference between your observed data and what you would expect under the null hypothesis. This test statistic follows a particular distribution, like the normal distribution for many common statistical tests.

The P-Value's Revelation

Here's the moment of truth: the p-value tells you the probability of obtaining a test statistic as extreme as, or more extreme than, the one you calculated if the null hypothesis is true. In simpler terms, it answers the question: "How likely is it that my observed results are just due to random chance?"

Interpreting P-Values

Now, the key interpretation comes into play. If your p-value is small, typically less than 0.05 (but it can vary depending on the field), it suggests that your observed results are unlikely to have occurred by chance alone. This is your green light to reject the null hypothesis and accept that you've found something significant.

Conversely, if your p-value is large (greater than 0.05), it indicates that your observed results are quite likely to be explained by random chance, and you should stick with the null hypothesis.

It's Not Absolute Proof

One crucial thing to understand is that p-values don't provide absolute proof or disproof. They offer a level of evidence, but they can't tell you the size of an effect or whether it's practically meaningful. They merely guide you in determining if your results are statistically significant.

The Decerebrate Cat Walking Experiment

 

In the realm of scientific exploration, certain experiments push boundariesin ways not acceptable by modern ethical standards. One such experiment involves decerebrate cats (popular in the 1940-50s and not done anymore), but which shed light on locomotion,

The Decerebrate Cat Walking Experiment: The video showcases a decerebrate cat walking on a treadmill at varying speeds, revealing three distinct gait patterns.  Decerebrate cats have had their cerebral cortex removed, leaving the brainstem intact. Essentially the cat was paralyzed as its spinal cord didn't talk to its brain anymore which means there was not enough muscle tone to keep the body upright; so researched used a harness to hold the weight of the body. 

Locomotion was initiated by sensory input of the limbs on the moving thredmill.

The primary goal of these experiments was to explore the extent of the brain's involvement in controlling movement. At what level in the brain is behavior (locomotion) controlled.  Researchers aimed to test the idea that much of locomotion control might be inherent to an animal's biomechanics, rather than relying heavily on conscious brain commands. 

Findings:

• Minimal Brain Control: during locomotion, especially in activities like walking, trotting, or running, minimal control comes from the brain itself. Instead, the experiments suggest that a significant portion of locomotion control is achieved through biomechanical and morphological features of the animal's body.
• Biomechanical Design: The experiments support the concept of passive dynamic locomotion, which proposes that animals are capable of controlling their movements efficiently by taking advantage of their natural biomechanical structure.

These findings have broad implications, from improving prosthetics and exoskeletons to advancing neural interface technology and rehabilitation practices, ultimately benefiting individuals with paralysis and advancing our understanding of locomotion in both animals and machines.

The real reason for brains

Fascinating Ted Talk. 

 

Phrenology according to Gall. A Historical Curiosity

 

The 18th century consensus on the brain was steeped in ancient beliefs that depicted it as an formless mass governing bodily functions. Franz Josef Gall, challenged this orthodoxy: the brain wasn't a mere lump of flesh but the very seat of our mental faculties, with distinct regions governing specific functions. This revolutionary idea laid the foundation for what we now recognize as "phrenology." While Gall's phrenological theories have been largely discredited in modern neuroscience, his work marked a significant shift in the study of the brain.  Gall's work also contributed to the development of techniques for brain mapping and the understanding of cognitive processes.

Landing himself in plenty of hot water. 
The prevailing view of the era was dominated by religious or philosophical beliefs rather than empirical research. Gall's ideas  challenged long-held beliefs about the nature of the mind and the brain and landed in a lot of hot water. 

His beliefs were seen as a direct challenge to established religious doctrines, suggesting that human behavior and personality were products of physical attributes, not divine intervention. This incurred the wrath of religious authorities who deemed phrenology heretical. In 1805, Gall was banned from practicing phrenology in Prussia by the Prussian government, which considered his ideas subversive and potentially dangerous. He was eventually expelled from Prussia but that did not deter him from promoting phrenology elsewhere. He continued to travel and lecture about his theories in other European countries, where phrenology gained a following and influence, particularly in France and the UK.

And the hot water was not just religions, but also social. Phrenology also had practical implications, as some individuals and organizations began using it for character assessment in various contexts, such as education and employment. This raised ethical and legal questions about the fairness and validity of making judgments about people based on phrenological assessments.

Gall's  garnered both acclaim and criticism from his contemporaries. One notable figure was Johann Spurzheim, Gall's collaborator and rival, who further popularized phrenology and took it to international audiences. Another contemporary of interest is Marie-Jean-Pierre Flourens, a French physiologist who advocated for a more holistic view of brain function, emphasizing the importance of the brain as a whole rather than isolated "organs." Other scientific peers cast doubts upon his theories, criticizing the lack of empirical evidence and the inherently subjective nature of his observations. Phrenology, in their eyes, was more pseudoscience than genuine scientific inquiry. 

Gall's Neuroanatomy Diagram: A Window into the Mind
Gall's most notable contribution was his intricate neuroanatomy diagram, which depicted the brain as a series of localized faculties or organs, each responsible for a particular aspect of personality or behavior. The size of these organs corresponded to a person's character traits and abilities. Obviously this is quite incredulous by today's standards - a historical curiousity. 

• Firmness (in frontal lobe) Development of this area in the frontal lobe was associated with determination, willpower, and the ability to persevere in the face of challenges.
• Immortality: linked to religious and moral tendencies, as well as a sense of spirituality.
• Veneration (Parietal Love): related to feelings of respect, admiration, and reverence for authority figures or ideals
• Destructiveness (in lower back of brain): aggressive and combative behaviors, as well as a propensity for violence.
• Benevolence (frontal love): linked to kindness, empathy, and a compassionate nature.
• Acquisitiveness (forehead): desire for material wealth and possessions.
• Wit (Frontal Lobe):  responsible for humor, quick thinking, and cleverness.
• Love of Offspring (back of brain):linked to parental instincts and the love and care of one's children.
• Secretiveness (Upper back of brain): associated with the tendency to keep secrets and be discreet.
• Self-Esteem (upper back of head): related to self-confidence, pride, and a sense of self-worth.

1. 
   

Null but Noteworthy Results

[Concepts in Research] 

Unearthing Hidden Gems: The Power of Null but Noteworthy Results. 

We live in a world obsessed with "success" and "results," where everyone craves those flashy headlines and dazzling breakthroughs. But there is also that captivating realm of science where the unsung heroes of research reside: the "Null but Noteworthy" results!

Picture this: scientists, huddled in labs, fervently running experiments, only to be met with a lack of statistically significant findings. It's when scientists don't get that big "Eureka!" moment they hoped for, meaning their experiments didn't yield any jaw-dropping, statistically significant results. 

In the world of research, null results are sometimes brushed aside like yesterday's news. But here's the kicker – they still have a story to tell.  Imagine you're digging for treasure, and instead of finding gold, you stumble upon ancient artifacts that offer a glimpse into an unknown civilization. Those artifacts might not be shiny, but they are undoubtedly noteworthy!

Our pursuit of knowledge should never be solely about finding "yes" or "no" answers. Embracing "Null but Noteworthy" results sparks curiosity, opening doors to entirely new avenues of inquiry. Like a maze with countless paths, these unassuming results may hold the key to groundbreaking revelations.

By acknowledging and sharing these seemingly modest findings, researchers foster an environment of honesty and integrity in science. No more sweeping those "unsuccessful" studies under the rug! It's time to celebrate the courage it takes to publish these results and the potential they have to refine our understanding of the world.

I think we need to remember that in a universe brimming with complexity, not every puzzle piece fits perfectly – and that's okay! These "Null but Noteworthy" results serve as guideposts for future investigations, leading us towards answers that might have otherwise remained hidden.

So, the next time you stumble upon a study with lackluster headlines, pause for a moment and give it a chance. Embrace the power of "Null but Noteworthy" - you never know what intriguing revelations might lie beneath the surface.

Stay curious, stay bold, and let's celebrate the beauty of scientific exploration in all its forms! 🧠

Low Crohbach's Alpha

[Concepts in Research Statistical Analysis] 

In psychological and social sciences research, Cronbach's alpha is often used as a measure of internal consistency, which reflects how closely related a set of items are as a group. 

The alpha coefficient ranges in value from 0 to 1 and can be used to describe the reliability of factors extracted from dichotomous (that is, questions with two possible answers) and/or multi-point formatted questionnaires or scales. 

A high value of alpha (usually 0.7 or above) is taken as an indication that the items measure an underlying (or latent) construct. In other words, it indicates that the scale or test has good internal consistency and that the items within the scale reliably measure the same construct. 

If the Cronbach's alpha is low (below 0.7, and especially below 0.6), it suggests that the items in the scale may not be measuring the same construct; they could be disparate and not well related. For instance, if you have a low alpha for the specific subscale, it suggests that the questions intended to measure that subscale may not be working well together to accurately and reliably assess extraversion in your sample. 

However, a low alpha doesn't necessarily mean your measure is "bad." It could be that your measure is multidimensional (i.e., measuring multiple factors) rather than unidimensional. In addition, alpha is sensitive to the number of items in a scale; scales with fewer items can result in a lower alpha. Further, sometimes scales designed to cover a broad concept may naturally have a lower alpha. 

ie, a low alpha can be an indicator to check your scale or test more thoroughly to understand whether all items are appropriate for your construct and your population. It may also signal the need for additional scales or tests to ensure you're capturing all aspects of a construct.

Schrödinger's cat

Schrödinger's cat is a thought experiment in quantum mechanics, proposed by the physicist Erwin Schrödinger in 1935. The experiment was designed to illustrate the paradoxical nature of quantum mechanics and the uncertainty principle.

In the thought experiment, a cat is placed in a sealed box along with a radioactive substance, a Geiger counter, and a poison. If the Geiger counter detects a radioactive decay, it will trigger the poison and the cat will die. However, according to quantum mechanics, the radioactive decay is in a superposition of states, both decayed and not decayed, until it is observed. Therefore, until the box is opened and the radioactive decay is observed, the cat is considered to be both alive and dead, in a superposition of states.

The thought experiment is often used to illustrate the concept of superposition and the idea that a quantum system can exist in multiple states simultaneously. It also highlights the role of observation and measurement in quantum mechanics, and the idea that the act of observation can collapse a superposition into a definite state.

The uncertainty principle

The uncertainty principle is a fundamental concept in quantum mechanics, which states that it is impossible to simultaneously know the exact position and momentum of a particle with absolute certainty. This means that the more precisely we know the position of a particle, the less precisely we can know its momentum, and vice versa.

The uncertainty principle was first formulated by Werner Heisenberg in 1927 and is often expressed mathematically as: Δx * Δp >= h/4π, where Δx is the uncertainty in the position of the particle, Δp is the uncertainty in its momentum, and h is Planck's constant.

The uncertainty principle has important implications for the behavior of subatomic particles, as it means that they cannot be precisely described or predicted in the same way that macroscopic objects can be. Instead, quantum mechanics uses probabilistic descriptions to predict the behavior of particles, based on the wave function that describes the probability distribution of the particle's position and momentum.

The uncertainty principle also has broader implications for our understanding of the nature of reality, as it challenges our intuition and classical conceptions of how the world works. It has become a central concept in modern physics and has led to the development of many important technologies, including the scanning tunneling microscope and the laser.

Uncertainty and Autism -  A Quantum Perspective 

POM 101

I completed the Protection of Minors Training this morning. 

Why is this important - while a majority of students are not-minors,  universities do cross path with thousands of children each year with all the programs they run., ~50K kids/year at Vandy, per the training. 

Apparently 1:10 kids get abused (median age 9) but only 38% disclose and 90% perpetrators are known to the child. Types of abuse include physical, sexual, neglect and emotional. 

When it comes to abuse, most just focus on the physical or sexual parts. I want to address childhood "abuse" in the context of disabled kids who are also subject to endless rounds of emotional abuse and neglect all through childhood. It's terribly unreported, not even acknowledged, and we carry lifelong emotional scars well into adulthood. 

Here is a small example: Throughout my special education years in elementary I was moved around multiple classrooms, sometimes are many as 4 in the course of one school year. How is that not emotional abuse by teachers who openly did not want me in their classrooms and resentful of my presence. How does that make a small child feel. How it is that the very people we are supposed to trust to nurture and support us (the 98% of folks we are surrounded by), end up as the perpetuators of lifelong emotional trauma for us. 

Last Lecture

As a graduating senior I got to attend a college tradition, a very motivational, Last Lecture by Astrophysics professor, Alexei Filipenko of the exploding supernova and black holes fame. Berkeley has all these amazing faculty who are just so interesting and engaging to listen to. You are just swept away when listening to them. For instance, when Prof Filippenko explains hawking radiation in class, he comes dressed as a black hole, and scatters shiny candy around class. And of course his t-shirt says, Dark Energy is the new black.

It was a lovely last lecture that led us through his personal journey, and his work, which was quite incredible to hear as well as motivational. He really focused on how how endless curiosity led him to where he is today.

The late Carl Sagan had said there were three important characteristics we needed, kindness, kindness and kindness. Professor Filippenko added empathy and curiosity to that list.

Oh, and the picture on the bottom is a quote from Socrates which says Education is the kindling of a flame, not the filling of a vessel. I think back to what Swami says about character being the end of education.

Journey to Stats and R

So Begins Stats2 and R

rrrrrrrr,,,,

 

Mental Health and Autism @Synchrony

I got to present on the urgent need for Mental Health Standards of Care for Autism at the Synchrony 2019 Conference