Neuroscience: Brain Function and Bayesian Coding
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Questions and Answers

What influences how the brain perceives and reacts to environmental stimuli?

  • The type of sensory information received
  • The level of physical fitness of the individual
  • The presence of crowd noise
  • The person's motivation and end goal (correct)

Which area of the brain helps maintain attention on primary goals while filtering distractions?

  • Visual cortex
  • Anterior cingulate cortex (ACC) (correct)
  • Cerebellum
  • Amygdala

What triggers the release of dopamine in the motivation system during goal-directed behavior?

  • Negative feedback from performance
  • The noise from the environment
  • The expectation of a reward (correct)
  • Interaction with teammates

What is the term used when the brain receives unexpected sensory information that contradicts its predictions?

<p>Prediction error (A)</p> Signup and view all the answers

What process involves the brain generating models of the world and refining them with sensory input?

<p>Probabilistic inference (D)</p> Signup and view all the answers

Why does the brain prioritize unexpected irregularities in a scene?

<p>As a mechanism to prepare for surprises (D)</p> Signup and view all the answers

What happens when individuals begin new activities according to the content?

<p>The brain learns from mistakes to improve future predictions (C)</p> Signup and view all the answers

How does the brain react to stimuli that it perceives as statistically irregular?

<p>It enhances focus and attention on those stimuli (C)</p> Signup and view all the answers

What happens to the probability density function when the prior belief is completely wrong?

<p>The amplitude of the probability density function decreases. (A)</p> Signup and view all the answers

How does the brain update its prior model based on new information?

<p>It updates the prior probability with Bayesian inference. (B)</p> Signup and view all the answers

Which of the following best describes the Bayesian brain?

<p>It is a probability machine that updates predictions. (C)</p> Signup and view all the answers

What does Bayes theorem help the brain compute?

<p>The updated probability of something being true. (A)</p> Signup and view all the answers

What does long-term potentiation (LTP) primarily increase in the postsynaptic cell?

<p>The probability of receptor activation (A)</p> Signup and view all the answers

In novel situations, which aspect of sensory perception is emphasized more?

<p>Reliance on visual stimulus. (B)</p> Signup and view all the answers

What happens during long-term depression (LTD) in the context of neurotransmission?

<p>The same amount of glutamate activates the postsynaptic cell less (B)</p> Signup and view all the answers

What role do action potentials play when perceiving a painful stimulus?

<p>They serve as prediction errors to update models. (A)</p> Signup and view all the answers

How does the brain generate models of the outside world?

<p>By reasoning based on sensory stimuli and experiences (A)</p> Signup and view all the answers

How do prior beliefs influence the brain's predictions?

<p>They enable flexible adjustments based on new information. (B)</p> Signup and view all the answers

What is a critical function of the brain when processing sensory information?

<p>Anticipating relevant information based on intended actions (B)</p> Signup and view all the answers

What does a very low probability density function indicate about the certainty of the prediction?

<p>It suggests greater variability in the predicted outcome. (A)</p> Signup and view all the answers

Why is probability reasoning important in how the brain processes information?

<p>It helps the brain predict and prepare for likely sensory stimuli (C)</p> Signup and view all the answers

Which statement correctly contrasts LTP and LTD?

<p>LTP strengthens synaptic responses, whereas LTD weakens them (C)</p> Signup and view all the answers

What misconception about the brain's processing of sensory information has been updated?

<p>The brain solely reacts to stimuli after receiving them (D)</p> Signup and view all the answers

How does the brain use previous experiences to predict future stimuli?

<p>By prioritizing certain sensory inputs based on context (C)</p> Signup and view all the answers

How does the brain utilize its understanding of statistical regularities?

<p>To create predictions for future events based on likely occurrences. (C)</p> Signup and view all the answers

What philosophical question is raised regarding human perception of reality?

<p>Do we perceive true reality or a combination of reality and expectation? (C)</p> Signup and view all the answers

What is the thermal grill illusion an example of?

<p>An instance of the brain misinterpreting sensory information. (A)</p> Signup and view all the answers

According to Gestalt theory, how do humans perceive visual information?

<p>By imposing a structured interpretation on what they see. (B)</p> Signup and view all the answers

What does the area under a probability density function curve always equal?

<p>1 (D)</p> Signup and view all the answers

What phenomenon explains why the brain may fill in gaps in visual perception?

<p>The brain's dislike for unstructured input. (A)</p> Signup and view all the answers

How does human upbringing affect perception according to the provided content?

<p>It influences how events are perceived based on previous experiences. (A)</p> Signup and view all the answers

What type of stimuli does the brain combine to create a painful sensation in the thermal grill illusion?

<p>Cold and warm stimuli affecting the same nerve pathways. (D)</p> Signup and view all the answers

What is the primary role of nociceptors in relation to pain perception?

<p>To send prediction errors to the brain. (A)</p> Signup and view all the answers

How does the brain conserve energy when processing sensory information?

<p>By only processing prediction errors. (B)</p> Signup and view all the answers

What does the term 'posterior' refer to in Bayesian brain theory?

<p>The likelihood of sensory signals being true based on evidence. (B)</p> Signup and view all the answers

What is the significance of the equation involving likelihood, prior knowledge, and marginal probability?

<p>It is used to calculate the updated probability in Bayesian analysis. (A)</p> Signup and view all the answers

How does Bayesian computation in the brain influence learning?

<p>By continuously updating priors to improve predictions. (B)</p> Signup and view all the answers

In the context of medical diagnosis, what does Bayesian analysis help determine?

<p>The probability of a patient having a disease given a positive test result. (D)</p> Signup and view all the answers

What happens to the posterior probability after each iteration of the Bayesian process?

<p>It becomes the new prior in subsequent calculations. (C)</p> Signup and view all the answers

Which best describes the overall goal of the brain's predictive coding?

<p>To minimize the discrepancies between expected and received sensory inputs. (A)</p> Signup and view all the answers

What is the primary function of memory according to the content?

<p>To predict future events through learned patterns (A)</p> Signup and view all the answers

What do prediction errors signify in the context of neuronal activity?

<p>The difference between actual and predicted outcomes (D)</p> Signup and view all the answers

Which neurotransmitter is primarily associated with excitatory responses in sensory neurons?

<p>Glutamate (A)</p> Signup and view all the answers

How do inhibitory neurotransmitters affect prediction processes in the brain?

<p>They oppose excitatory signals leading to cancellation (A)</p> Signup and view all the answers

Which term describes the difference in height between prior knowledge and posterior knowledge?

<p>Accuracy (C)</p> Signup and view all the answers

What is the role of descending pathways in sensory processing?

<p>To provide feedback from higher cognitive centers (A)</p> Signup and view all the answers

How do EPSPs and IPSPs interact in the neuronal processing of information?

<p>They can cancel each other out to modulate overall activity (C)</p> Signup and view all the answers

Which of the following statements is true regarding the function of sensory neurons?

<p>They bring in information from the environment and initiate responses (A)</p> Signup and view all the answers

Flashcards

Synaptic Probability

The chance of a receptor being activated by a specific amount of neurotransmitter. A higher probability means a stronger signal.

Long-Term Potentiation (LTP)

The process of strengthening a synapse by increasing the likelihood of receptor activation with the same amount of neurotransmitter.

Long-Term Depression (LTD)

The process of weakening a synapse by decreasing the likelihood of receptor activation with the same amount of neurotransmitter.

Active Anticipation

The brain's ability to anticipate incoming sensory information based on previous experiences and the intended goal of actions.

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Brain Models of the World

The brain creates models of the world based on sensory inputs to make predictions about future events.

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Active Search for Sensory Information

A process where the brain actively searches for specific sensory information that it expects to find based on its anticipation of events.

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Brain's Predictive Nature

The brain is constantly generating predictions about the sensory world based on its models and prior experience.

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Brain's Statistical Reasoning

The brain's interpretation of sensory input takes into account the most statistically likely stimuli that could have caused the current response.

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Active Brain Prediction

The brain actively anticipates and predicts future events to optimize actions towards achieving goals. This involves processing sensory information and updating internal models.

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Generative Models

Our brain constructs models of the world based on sensory data and continuously refines them to better predict and adapt to the environment.

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Surprising Events

The brain focuses attention on unexpected or surprising events to quickly identify and adapt to changes in the environment. It's like a detective seeking out irregularities.

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Prediction Error

The brain's prediction error mechanism highlights unexpected events, triggering attention to novel situations to better understand and learn from them.

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Brain Learning

The process of the brain learning from mistakes and applying that knowledge to improve future actions or predictions.

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Probabilistic Inference

The brain's ability to infer probabilities based on sensory information and past experiences, allowing it to make predictions about future events.

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Attention and Filtering

The brain's ability to filter out irrelevant information while maintaining focus on the primary goal.

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Motivation and Reward

The brain's reward system plays a key role in motivating behavior by releasing dopamine, which is associated with pleasure and anticipation.

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Brain's probabilistic model

Our brains use statistical models to make predictions about future events, similar to how a neural network would analyze data. These predictions are based on past experiences and learned information.

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Brain's interpretation of reality

The brain interprets sensory information by imposing structure and order, even when the world is chaotic. It fills in gaps and makes assumptions to create a meaningful perception of reality.

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Brain's perception influenced by learning

The brain's interpretation of reality is heavily influenced by what we have previously learned and experienced. Our childhood experiences and accumulated knowledge shape our perception of the world.

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Illusions and reality perception

Illusions demonstrate how our brains do not always perceive reality accurately. They highlight the brain's tendency to create interpretations based on expectations and assumptions.

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Thermal grill illusion

The thermal grill illusion demonstrates how our brains can perceive pain even when there is no actual painful stimulus. This is due to the brain's interpretation of conflicting sensory information.

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Gestalt theory

Gestalt theory emphasizes that the brain is not passive in perceiving the world. Instead, we actively organize and interpret sensory information to create a meaningful whole.

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Probability density function (PDF)

The probability of an event occurring can be represented by a bell-shaped curve called a probability density function (PDF). The area under the curve always equals 1.

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Brain's predictive capacity

The brain attempts to make sense of sensory information and predict the most likely outcome based on past experiences and learned information.

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Energy-Efficient Processing

The brain prioritizes processing only unexpected sensory information, minimizing energy expenditure by ignoring predicted stimuli.

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Posterior Probability

The probability of a hypothesis being true given the available evidence, constantly updated by the brain to refine its understanding of the world.

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Bayes' Theorem

A mathematical formula that calculates the posterior probability based on prior knowledge and new evidence.

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Prior Knowledge

The brain's existing understanding of the world based on prior experiences and learning.

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Bayesian Learning

The process of updating the brain's generative model based on new information and feedback, leading to improved predictions.

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Predictive Coding

The brain's ability to learn and adapt its generative models to better predict the future outcomes of events.

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Prior Belief

A mental model representing our expectations about how the world works in a specific situation. It influences how we perceive and react to events.

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Probability Density Function

A statistical measure representing the likelihood of an event occurring. It's a way to quantify how likely something is to happen.

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Prior Belief Updating

Updating existing knowledge based on new information. This process allows us to refine our understanding of the world.

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Bayesian Inference

The use of probability calculations to make predictions about the future based on past observations and new information.

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Bayesian Brain

The brain's ability to learn and improve by constantly adjusting its internal models based on experience.

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Reliance On Visual Stimulus In Novel Situations

The brain's tendency to rely more on visual information when encountering a novel situation.

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Minimizing Prediction Errors

The smaller the difference between the predicted outcome and the actual outcome, the more accurate the prediction. This difference is known as the prediction error.

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Descending Predictions

The brain uses descending pathways from higher cognitive centers to send predictions to lower sensory processing areas.

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Ascending Sensory Input

Sensory neurons bring information from the external world to the brain. This information is processed through ascending pathways.

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Neuronal Ensembles

These are groups of neurons that work together to process specific sensory information. They act as checkpoints for sensory input.

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Precision of Prediction

The width of the probability density function represents how precise the brain's prediction is.

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Accuracy of Prediction

The difference between the predicted outcome and the actual outcome reflects the accuracy of the prediction.

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Excitatory vs. Inhibitory

Excitatory neurotransmitters, like glutamate, cause depolarization of neurons, while inhibitory neurotransmitters, like GABA and enkephalin, cause hyperpolarization.

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Study Notes

Brain Function and Probabilistic Neuronal Coding

  • The brain uses probabilities and probabilistic neuronal coding, where postsynaptic cells reason about the probability of input from presynaptic cells.
  • Long-term potentiation (LTP) increases the probability of a receptor being activated by the same amount of glutamate.
  • Conversely, long-term depression (LTD) decreases this probability.
  • The brain generates models of the external world to predict likely sensory inputs.
  • This prediction-based approach allows the brain to anticipate and react rather than passively responding.
  • Active anticipation, a more likely hypothesis, suggests the brain actively searches for and anticipates information relevant to goals.
  • Perception is guided not only by current sensory data, but also by expectations and prior knowledge.

Bayesian Brain Hypothesis

  • The brain uses Bayesian inference to make predictions about the future.
  • The Bayesian brain constantly updates its internal model of the world based on sensory input and prior knowledge.
  • This model allows for predictions about future events and efficient processing of sensory information.
  • Bayesian inference updates probabilities based on new data.
  • The brain's goal is to minimize prediction errors by adjusting its models in response to new information.

Predictive Coding

  • The brain predicts sensory input based on its internal models.
  • Prediction errors (differences between predicted and actual input) are used to update the internal model.
  • This process allows the brain to efficiently process sensory information and focus on relevant details.
  • This is an energy-efficient method of processing information, reducing computational demands.

Neuronal Ensembles

  • The brain uses ensembles of neurons—groups of neurons working together—for information processing and prediction.
  • Neuronal ensembles are affected by long-term potentiation (LTP) and long-term depression (LTD), strengthening or weakening connections between neurons.
  • Learning involves adjusting these connections to improve predictions about future stimuli.
  • These ensembles are essential for encoding various types of information.

Importance of Prediction

  • The brain's predictive mechanisms allow for rapid adjustments to changing environments.
  • Our ability to anticipate events is crucial for survival.
  • Prediction allows efficient use of sensory information and optimizes response time.
  • The ability to predict future events results in more adaptive behaviors.

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Brain Function and Probabilistic Neuronal Coding PDF

Description

Explore the fascinating concepts of brain function, probabilistic neuronal coding, and the Bayesian Brain hypothesis. This quiz delves into how the brain uses probabilities to anticipate sensory inputs and make predictions about the future. Test your understanding of long-term potentiation, long-term depression, and the brain's modeling of the external world.

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