Complexity Theory sub topic: Thoughts and Nonlinearity

We know that nonlinearity is small actions creating large impacts.
Questions to consider:

1. What is the most reduced state of an action?
2. How small can action be and still create an effect?
3. Can intention/thought alone make an impact or create effect?
4. Does thought need to be measurable to be considered an "Action"?
5. Is thought scalable or cumulative?
6. Can a complex system be created from thought?
7. Can positive and negative feedback loops be created from thought?

Have you ever had an experience of someone thinking about you. and you received a sensation (impact) Question: how did that happen?

BASIC INFO
Thoughts are not directly measurable as a physical object with qualities like mass or volume, but their neural correlates and effects can be scientifically measured. Neuroscientists can track the brain activity that occurs when a person is thinking.
The Science of Measuring Thoughts

• Neural Activity: Thoughts are fundamentally the result of electrochemical signals moving between neurons in the brain. While the thought itself isn't the neuron, it's the pattern and process of this activity, similar to how a pattern on a carpet has no mass, but the threads do.
• Brain Imaging Techniques:
• fMRI (Functional Magnetic Resonance Imaging): This non-invasive tool measures changes in blood flow and oxygen consumption in specific brain regions, indicating where increased neural activity is occurring during thought processes.
• EEG (Electroencephalography): EEG measures electrical activity in the brain through electrodes placed on the scalp, allowing researchers to observe the timing and patterns of brain waves associated with different mental states and thoughts.
• Single-Neuron Recording: In specific neurosurgery cases with awake patients, doctors can measure the activity of single neurons to see which ones "light up" in response to specific stimuli (e.g., a picture of a face or a name), demonstrating highly specific neural correlates for individual concepts.
• Psychological and Behavioral Metrics: Psychologists can measure thoughts indirectly through:
• Self-reports: Asking people to describe their thoughts (used by Freud as "free association").
• Reaction times: Measuring how long it takes to make a decision or respond to a stimulus to infer the speed of cognitive processing.
• Performance on tasks: Evaluating memory, problem-solving, and reasoning abilities through systematic experimentation.
• Quantifying Thoughts: Researchers have developed methods to identify and even estimate the number of thoughts people have per day (ranging from 6,200 to 70,000 in different studies) and the rate at which the brain processes information (around 10 bits per second for conscious thought).
• Physical Effects: Thoughts have measurable effects on the body, such as changes in heart rate, blood pressure, and hormone levels, which can be objectively tracked.

Summary
While you can't put a "thought" on a scale or directly point to it in the physical world, its underlying physical manifestations and effects are highly measurable. The subjective experience of a thought remains a challenge to fully quantify, but the objective, physical processes in the brain that generate it can be studied scientifically with a variety of advanced tools

Electrical activity of the brain and nonlinearity
The electrical activity of the brain is fundamentally rooted in nonlinearity, which is essential for its complex functions, information processing, and dynamic behavior. Neurons function as nonlinear units, and brain activity, from individual cell firing to large-scale network interactions, exhibits characteristics that cannot be described by simple linear models.
Key Aspects of Nonlinearity in Brain Electrical Activity

• Nonlinear Neuronal Firing Patterns: Individual neurons fire in nonlinear patterns; their output is not directly proportional to their input in a simple linear fashion. The all-or-none nature of action potentials (spikes) is a classic example of a sharp, nonlinear transition.
• Complex Cognitive Processes: Nonlinear patterns in neural signals are often associated with more complex cognitive functions. The brain's ability to switch flexibly between different cognitive states (e.g., wakefulness, sleep, attention) is a result of these nonlinear dynamics.
• Emergence of Rhythms and Oscillations: Nonlinear interactions between neurons and neural populations lead to the emergence of various brain waves and oscillations (e.g., alpha, gamma rhythms). These rhythms are crucial for synchronized communication across different brain regions and cognitive processes like memory.
• Information Integration and Broadcasting: Theories of consciousness, such as the Global Neuronal Workspace theory, propose that conscious access involves a nonlinear "cortical ignition" or global broadcast of information across widespread frontoparietal networks. This "ignition" represents an all-or-none transition in brain state.
• Dynamic Systems Behavior: The brain is best understood as a complex, non-linear dynamic system.
• Attractors and Phase Transitions: The brain's activity can be described by "attractors" in phase space, which represent stable patterns of activity associated with specific behaviors or mental states.
• State Changes: The transitions between these attractors (e.g., from an awake state to sleep, or focusing attention) are often abrupt and non-linear, not gradual.
• Neuroimaging Implications: The relationship between neural activity and the signals measured by tools like fMRI is also non-linear. The coupling between neuronal activity and the resulting hemodynamic response (blood flow changes) involves non-linear effects, such as a threshold before a significant change is observed. This necessitates the use of complex, nonlinear tools for accurate data analysis and modeling.
• Cross-frequency Coupling: Communication between different neuronal populations often involves coupling between oscillations of different frequencies, a fundamentally nonlinear phenomenon that allows for complex information transfer.

In essence, nonlinearity provides the rich, complex dynamics and flexible state changes that define a functioning brain. Standard linear analysis tools alone are insufficient to fully capture and understand these intricate processes.
Exercise:

1. Close your eyes and think of a positive word for 60 seconds. Now open your eyes and each person go around the room and share the first word you think of
2. Repeat the above thinking of a negative word.
   Discuss results
   Final question:
   How can what we know about thoughts and nonlinearity be applied to a complex system?