how does decisions link to future actions
experiences retrieved from memory leads to decision leads to future actions
what is the prediction choice outcome loop
- start with goal that we want to achieve
- if there are several options, how to achieve the goal, we make predictions about the outcome of different options
- we then form a decision and make appropriate actions that should get us closer to our goal
- the result of these actions will be an action outcome that we observe
- this outcome will be subjected to internal monitoring processes where we evaluate, if our decision and the corresponding actions have actually achieved our goal. if we havent reached our goal our brain generates a prediction error
- the results of this monitoring process, the prediction error, can be used to update our memory based on the experience we have just made. this updated memory content can then be used to make more precise predictions
what is the criteria for decision making
- avoid harm
- minimize; costs of time, effort, missed opportunities
- maximise reward
- we need to make predictions of possible decision outcomes to optimise our decision making process
- we rely on memory content to make predictions
what factors are considered before making a decision
- difficulty of the action
- probability
- how valuable is the possible reward at this moment
- missed opportunities
what are some biases in decision making
- stick with the same option you have chosen before
- choosing certain gains over gambles
- choosing gambles over certain losses
- temporal discounting
what is temporal discounting
choosing immediate rewards over future rewards unless benefits are made explicit
what are the different levels of decision making
- simple perceptual decisions
- more complex decision
what is the perceptual decision task
- random dot motion task
- monkey maintains fixation
- random dots are presented
- certain percentage of dots moves coherently, other dots move randomly
- when monkey detects main motion direction - eye movement corresponding to target
- noisy sensory signal is converted into discrete motor act
accumulating evidence in perceptual decisions
neuronal recordings in monkeys suggest that this is what is happening in the brain during perceptual decision making tasks
- when the stimulus, consisting of random moving dots, is presented, neurons that are tuned to detect specific motion direction will start to fire
- the more dots are moving in a given direction coherently, the stronger these corresponding motion detector neurons will fire
- firing rate will increase as more evidence for a given motion is being accumulated
- the more dots move in one direction, the stronger the evidence for this direction
- evidence accumulation curve is steeper and reaches threshold faster
what do studies suggest about evidence accumulation
Studies suggest that evidence accumulation always increases up to a certain threshold. When this threshold is reached a decision will be made in line with the evidence leading to a corresponding action, i.e. if the evidence accumulation curve for the left motion direction reaches this threshold first, the monkey will decide to make a left-sided response.
If the evidence accumulation curve for a right motion direction would reach this threshold first, the monkey would decide to make a right-sided response.
what happens to the evidence accumulation curve when stimulus is quite noisy
evidence accumulation curve would reach the decision threshold closer in time and sometimes would lead to incorrect decisions, if the accumulation process for the less dominant direction meets the decision threshold first
what are the 3 stages of perceptual decision making
- detection of sensory evidence; what are the alternatives that can be detected
- integration of evidence over time - because evidence is noisy
- checking if the threshold has been reached - if so elicit appropriate action - if not accumulate more evidence
where does evidence accumulation take place
- brain areas responsible for encoding the relevant feature
- parietal and dorsal prefrontal cortex
- recent evidence; sensorimotor areas representing possible actions, accumulate evidence as well
homogenous model and evidence accumulation
all relevant neurons become active at the same time
heterogenous model and evidence accumulation
- neurons dont become active at the same time, but there are early responding neurons that become active quickly and pass on activity to other neurons. this creates a wave of activity in the network. the accumulated evidence in the network then reflect when the decision threshold will be reached
- by having both neurons that react fast to incoming new info and those neurons that react in a more sustained way over longer periods of time, the memory of accumulated evidence can be both flexible and durable
mental maps in decision making
- decision making processes rely on internal models of the current task; experiences need to be organised in internal models or mental maps
historical roots of mental maps
- edward tolman
- rats experiencing a spatial maze
- the shortest path to the goal was blocked so rat had to go all the way round
- if path was unblocked later, the rats quickly realised they could take a shortcut and go directly from A to B to reach the goal quicker
- the rats seem to have positions A and B encoded as being close together in space, although they had never experienced going from A to B
- the rats had encoded transitive relations of the different locations in the maze and had used this information to build a mental map of the maze
- this mental map informed their decision at first intersection to go straight ahead instead of taking the path they had been trained on
mental maps and problem solving
problems can be described as a series of decisions
- problem - then decide - anticipate outcome - what needs to be done in what order
- sequence of steps could be represented as a mental map
what did kaplan et al suggest about cognitive maps
- we have different cognitive maps for different tasks
what is a cognitive map for a specific task called
state space
- different state spaces for different tasks
what is the state space representation
- gird-like or map like representation of all the decision points along the way from the original problem to the task
- while working towards the goal we move across the state space along these decision points
- the point that reflects, which decision we are currently facing is our hidden state
- at different points where decisions are required, we perform mental explorations before we make a decision
what is hidden state in state space representation
our position within the current task
what is mental exploration in the state space representation
evaluation of potential outcomes for different choices
what did elston and wallis find about space state representations
state space representations provide the context for a given situation and the need for given context to inform the subjective evaluation of rewards
- the hippocampus is well positioned to generate cognitive maps because it encodes both spatial contexts as well as temporal contexts
- the hippocampus is connected to the orbito and medial frontal cortex which has been associated with representation of subjective values and rewards
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emotion46
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sex differences33
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methods50
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methods77
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alzheimer's62
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neurodegenerative disorders44
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schizophrenia56
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decision making42
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anxiety disorders27
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introduction to learning12
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classical conditioning21
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instrumental conditioning37
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numbers and counting17
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time15
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theory of conditioning19
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pavlovian and instrumental interactions56
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categorisation39
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successes of rescorla-wagner model69
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attention55
