Chemical Signaling in the Brain, what is that:

Chemical Signaling in the Brain, what is that:

“CONSULT A PSYCHIATRIST”

Chemical signaling in the brain refers to how brain cells (neurons) communicate with each other using neurotransmitters — chemical messengers that transmit signals across synapses, the small gaps between neurons.

Here’s a breakdown of the process:

1. Neurotransmitter Release

  • When a neuron fires an electrical impulse (action potential), it reaches the axon terminal.
  • This causes vesicles (tiny sacs) filled with neurotransmitters to fuse with the membrane and release their contents into the synaptic cleft.

2. Synaptic Transmission

  • The neurotransmitters cross the synaptic gap and bind to receptors on the postsynaptic neuron (the receiving cell).
  • This binding can either:
  • Excite the neuron (making it more likely to fire),
  • Or inhibit it (making it less likely to fire).

3. Signal Termination

Once the neurotransmitters have done their job, the signal is stopped in several ways:

  • Reuptake: The neurotransmitter is reabsorbed into the presynaptic neuron.
  • Enzymatic degradation: Enzymes break down the neurotransmitter.
  • Diffusion: It drifts away from the synaptic gap.

Key Neurotransmitters

Neurotransmitter Function Motivation, reward, movement Mood, sleep, appetite Learning, memory, muscle activation Main inhibitory neurotransmitter Main excitatory neurotransmitter Alertness, arousal, stress response

Why It Matters

Chemical signaling is central to everything the brain does, from thinking and feeling to moving and sleeping. Dysfunction in this system might be linked to conditions like:

  • Depression 
  • Schizophrenia
  • Parkinson’s disease 
  • Anxiety disorders 

Shervan K Shahhian

Psychopharmacology, what is it exactly:

“CONSULT A PSYCHIATRIST”

Psychopharmacology, what is it exactly:

Psychopharmacology is the scientific study of how drugs affect mood, behavior, cognition, and mental processes. It combines knowledge from psychology, neuroscience, pharmacology, and psychiatry.

Key Aspects of Psychopharmacology:

Drug Effects on the Brain:

  • Studies how drugs interact with the central nervous system (CNS).
  • Focuses on neurotransmitters like dopamine, serotonin, norepinephrine, GABA, and glutamate.

Types of Psychoactive Drugs:

  • Antidepressants
  • Antipsychotics
  • Anxiolytics
  • Stimulants
  • Mood stabilizers

Therapeutic Uses:

  • Treating mental health disorders such as depression, anxiety, schizophrenia, bipolar disorder, and ADHD.

Side Effects & Tolerability:

  • Includes understanding adverse effects, tolerance, dependence, and withdrawal.

Individual Differences:

  • Effects can vary based on their medical history, genetics, metabolism, age, sex, and psychological state.

Mechanisms of Action:

  • Explores how drugs alter neural pathways, receptor sensitivity, and chemical signaling in the brain.

Why It Matters:

Psychopharmacology is crucial in clinical psychology, psychiatry, and mental health treatment, helping professionals tailor medication plans to improve patient outcomes while minimizing side effects.

Shervan K Shahhian

Attribution Theory, what is it:

Attribution Theory, what is it:
Attribution Theory is a psychological framework that explains how people interpret and assign causes to behavior - either their own or others’. Developed primarily by Fritz Heider and later expanded by Harold Kelley and Bernard Weiner, it helps us understand why someone behaved a certain way.
Core Idea:

People try to make sense of behavior by attributing it to internal or external causes.
Two Main Types of Attribution:

Internal (Dispositional) Attribution
The behavior is due to the person’s personality, traits, motives, or choices.
Example: “She failed the exam because she’s lazy.”

External (Situational) Attribution
The behavior is caused by outside circumstances or the environment.
Example: “She failed the exam because the test was too hard.”

Key Models:

Heider’s Theory (1958):
We are “naive psychologists” trying to understand others’ behavior through cause-and-effect.

Kelley’s Covariation Model (1967):
 People make attributions by considering:
Consensus: Do others behave the same way?
Distinctiveness: Is this behavior unusual for the person?
Consistency: Does this behavior happen repeatedly?

Weiner’s Attribution Theory (1986):
 Focused on achievement and motivation and categorized causes along three dimensions:
Locus (internal vs. external)
Stability (stable vs. unstable over time)
Controllability (controllable vs. uncontrollable)

Why It Matters:

Attribution shapes how we judge others, react emotionally, and decide how to act. For instance:
In education, teachers’ attributions about student performance affect expectations and feedback.
In relationships, how we explain a partner’s actions can increase or reduce conflict.
In mental health, people who attribute negative events to internal, stable, and uncontrollable causes may be more prone to depression.

Shervan K Shahhian

Self-Serving Bias:

Self-Serving Bias:

Self-Serving Bias is a common cognitive bias where people tend to attribute their successes to internal factors (like their own abilities or efforts) and their failures to external factors (like bad luck or other people).

Examples:

  • Success: “I aced the test because I’m smart and studied hard.”
  • Failure: “I failed the test because the teacher made it too hard.”

Purpose:

Self-serving bias helps protect self-esteem and reduce feelings of guilt or failure. It acts as a psychological defense mechanism.

Downsides:

  • Can lead to overconfidence
  • Inhibits learning from mistakes
  • May cause conflicts in relationships if one always blames others

In Psychology:

It’s studied in attribution theory, which explores how people explain the causes of behavior and events.

Shervan K Shahhian

Loss Aversion in Prospect Theory:

Loss Aversion in Prospect Theory:

Loss aversion is a key concept in Prospect Theory, developed by Daniel Kahneman and Amos Tversky, which describes how people make decisions under conditions of risk and uncertainty.

Definition of Loss Aversion:

Loss aversion refers to the tendency for people to strongly prefer avoiding losses over acquiring equivalent gains. In other words, losing $100 feels more painful than the pleasure of gaining $100.

In the Context of Prospect Theory:

  • Value function is steeper for losses than for gains.
  • This means the psychological impact of a loss is roughly twice as powerful as a gain of the same size.
  • The function is also:
  • Concave for gains → risk-averse when gaining.
  • Convex for losses → risk-seeking when losing.

Example:

  • Gain scenario: You’re given the choice between:
  • A sure gain of $500
  • A 50% chance to gain $1,000
     → Most people choose the sure gain (risk-averse in gains).
  • Loss scenario: You’re given the choice between:
  • A sure loss of $500
  • A 50% chance to lose $1,000
     → Most people take the gamble (risk-seeking in losses).

Why It Matters:

  • It helps explain why people hold on to losing stocks (to avoid realizing a loss).
  • It influences consumer behavior, insurance decisions, negotiations, and more.
  • It’s a core departure from classical economics, which assumes rational, utility-maximizing behavior.

Shervan K Shahhian

Framing Effect:

Framing Effect:

The Framing Effect is a type of cognitive bias where the way information is presented (the “frame”) significantly influences decision-making and judgment.

Definition:

People react differently to the same information depending on how it is framed — either positively (gain frame) or negatively (loss frame).

 Classic Example:

Imagine this medical scenario:

  • Option A: “200 people will be saved.”
  • Option B: “There is a one-third chance that all 600 people will be saved, and a two-thirds chance that no one will be saved.”

Now reframe it negatively:

  • Option A: “400 people will die.”
  • Option B: “There is a one-third chance that no one will die, and a two-thirds chance that all 600 will die.”

Though the outcomes are logically identical, people tend to choose:

  • Option A in the positive frame (to avoid loss),
  • Option B in the negative frame (to take risks to avoid sure loss).

Why It Happens:

  • Influenced by emotions, not just logic.
  • We’re more sensitive to losses than gains (related to loss aversion in Prospect Theory).

In Psychology and Real Life:

  • Advertising: “95% fat-free” sounds better than “5% fat.”
  • Medicine: “Survival rate is 90%” sounds more reassuring than “10% die.”
  • Politics: “Tax relief” vs. “tax cut for the rich.”

How to Overcome It:

  • Reframe the situation yourself to see both gain and loss perspectives.
  • Slow down decision-making, especially when stakes are high.
  • Focus on facts and long-term outcomes, not just immediate impressions.

Shervan K Shahhian

Hindsight Bias:

Hindsight Bias:

Hindsight Bias—often referred to as the “I-knew-it-all-along” effect—is a cognitive bias where people perceive past events as having been more predictable than they actually were. After an event has occurred, individuals often believe they could have foreseen the outcome, even if there was little or no way to predict it beforehand.


Key Features of Hindsight Bias:

  • Distorts memory: People misremember their previous predictions or beliefs to align with what actually happened.
  • Overestimates predictability: It gives the illusion that events were obvious or inevitable.
  • Affects learning: It can prevent people from analyzing situations objectively or learning from mistakes, as they believe they “knew it all along.”

Why It Happens:

  1. Cognitive Dissonance Reduction: We prefer consistency in our thoughts and beliefs. Believing we “knew it all along” reduces internal conflict.
  2. Narrative Construction: Our minds seek to make sense of events by forming coherent stories after they happen.
  3. Outcome Knowledge Influences Judgments: Knowing the result changes how we interpret earlier information.

Examples:

  • In sports: After a team wins, fans claim, “I knew they were going to win,” even if they had doubts beforehand.
  • In investing: After a stock crashes, people say, “It was obvious the bubble would burst.”
  • In relationships: After a breakup, someone might claim, “I always knew it wouldn’t last.”

How to Avoid It:

  • Keep a record of predictions or decisions (e.g., journals or decision logs).
  • Be aware of the bias—knowing about it can reduce its influence.
  • Encourage perspective-taking—consider what other outcomes seemed possible at the time.
  • Shervan K Shahhian

Bandwagon Effect:

Bandwagon Effect — Explained Simply:

The bandwagon effect is a type of cognitive bias where people tend to adopt beliefs, behaviors, or trends simply because many others are doing it — like “jumping on the bandwagon.”

Key Characteristics:
Conformity: People align with the group to fit in or avoid standing out.

Popularity-driven: The more popular something becomes, the more likely others are to join.

Not based on logic or personal evaluation: People may ignore their own beliefs or facts.

Examples:
Fashion: Wearing a certain brand because “everyone at school is wearing it.”

Politics: Supporting a candidate just because they’re leading in the polls.

Social Media Trends: Sharing a viral meme or opinion just because it’s trending.

Why It Happens:
Desire for social acceptance.

Fear of missing out (FOMO).

Trust in the “wisdom of the crowd.”

Risks:
Can lead to poor decisions.

Encourages groupthink.

Discourages critical thinking or individual analysis.

Shervan K Shahhian

Omission Bias:

Omission Bias:

Omission bias is a type of cognitive bias where people tend to judge harmful actions as worse or more morally wrong than equally harmful inactions (omissions), even when the outcomes are the same or worse. In other words, we often perceive harm caused by doing something as more blameworthy than harm caused by doing nothing.

Example:
Action: A doctor gives a patient a treatment that causes harmful side effects.
Omission: The doctor withholds a treatment that could have prevented harm, resulting in the patient getting worse.
Even if both lead to the same negative outcome, many people would judge the action (giving the harmful treatment) more harshly than the inaction (withholding the treatment), due to omission bias.

Why It Happens:
It feels less responsible to “let something happen” than to “make something happen.”
People tend to associate guilt more with direct actions than with passive choices.
Risk aversion — doing nothing feels “safer.”
In Real Life:
Medical decisions: Doctors may avoid aggressive treatments due to fear of causing harm, even if inaction is riskier.
Sports: A referee may avoid making a controversial call, thinking not acting is more “neutral.”
Ethics: In moral dilemmas, people often prefer omissions over actions, even when the outcomes are morally equal.
Shervan K Shahhian

Ethical Use of AI in Mental Health:

Ethical Use of AI in Mental Health:

The ethical use of AI in mental health is a growing concern and responsibility, given AI’s expanding role in diagnosis, therapy, and mental wellness support.

Here are the key ethical considerations:

  1. Privacy & Confidentiality
    Issue: AI systems process sensitive personal data.
    Ethical Priority: Data must be encrypted, anonymized, and stored securely.
    Example: A chatbot collecting users’ emotional states should never store data without informed consent.
  2. Informed Consent
    Issue: Users may not understand how their data is used or what the AI can do.
    Ethical Priority: Transparent communication about what the AI system does, its limits, and data usage.
    Example: A user interacting with an AI therapist must be made aware that it’s not a human and that it cannot provide emergency help.
  3. Transparency & Explainability
    Issue: Black-box AI decisions can be hard to interpret.
    Ethical Priority: Systems should explain how they arrive at diagnoses or recommendations.
    Example: An AI that flags depression risk must clearly outline the indicators it used.
  4. Bias & Fairness
    Issue: AI can inherit or amplify biases present in training data.
    Ethical Priority: Use diverse, representative datasets and regularly audit AI for bias.
    Example: Mental health AI tools must be tested across different races, genders, and cultures to ensure equity.
  5. Accuracy & Reliability
    Issue: Misdiagnosis or faulty advice can have serious consequences.
    Ethical Priority: AI tools should be evidence-based and clinically validated.
    Example: Before an AI tool suggests PTSD risk, it must be tested under peer-reviewed protocols.
  6. Human Oversight
    Issue: Overreliance on AI could replace necessary human judgment.
    Ethical Priority: AI should augment, not replace, mental health professionals.
    Example: AI can screen for symptoms, but only a licensed therapist should provide treatment plans.
  7. Emergency Handling
    Issue: AI can’t intervene during a crisis.
    Ethical Priority: Clear protocols must direct users in danger to human help or crisis services.
    Example: If a user expresses suicidal ideation, the system should provide hotlines or alert professionals (if consented).
  8. Accessibility & Digital Divide
    Issue: Not everyone has equal access to AI tools.
    Ethical Priority: Ensure tools are accessible to marginalized, rural, or low-income populations.
    Example: AI-based therapy apps should work on low-bandwidth devices and be offered in multiple languages.
    Conclusion
    AI in mental health holds promise, but it must be ethically designed, transparently deployed, and always accountable to human values. Collaboration with ethicists, psychologists, technologists, and affected communities is essential.

Shervan K Shahhian