cMadan :: the personal website of Christopher R Madan

Research Interests

I am primarily interested in how people learn and retrieve associations for information that is more 'important' (e.g., emotional or rewarded). Some specific aspects of this are: (1) How does memory for items influence memory for associations? (2) How does 'self-important' information affect our ability to learn associations? (3) How can reward learning influence implicit and explicit memory? (4) What processes can underly interactions between item-memory and association-memory? (5) What neural mechanisms can contribute to associative learning?

In everyday life, it is not enough to just remember individual items, such as the names of people at a social gathering. Rather, you also need to remember how the items are related, through associations between items; for example: which of the individuals are couples. Manipulations of word properties that yield better memory for items – such as imageability (how conducive a word is to imagery; Paivio, 1971), word frequency (how common a word is in the English language; Gregg, 1976), emotionality (how emotionally arousing a word is; Rubin & Friendly, 1986), and reward value (how rewarding a word is within a particular context; Estes, 1966) – have been found to increase performance on tests of item-memory. However, how these word properties effect memory for associations has been unclear, e.g., a pair of high-frequency items vs. low-frequency, cued recall performance could be due to item-memory or association-memory. I am interested in how item properties can influence association-memory.

Do we form better associations involving important items or do we simply remember these items better? Emotionality and reward value are both properties that affect how a memory is relevant in individual’s everyday life. Emotional events are recalled better than neutral events, and in turn, more rewarding events should be remembered better than lower rewarded events. However, direct associations between emotional items have never been looked at systematically in order to study item versus association effects in terms of relevance of the learned material. However, unlike simple manipulations of imageability and word frequency, emotionality and reward value are both more complex properties and are remembered better because of their self-important characteristincs. Additionally, Emotionality is measured in two separable dimensions/measures: arousal and valence. Arousal refers to how exciting/calming an emotional item or event is; while valence is a rating of the emotional event in terms of positive/negative (pleasing/displeasing) value (Bradley & Lang, 1994; Russell, 1980). Both emotionality and reward value can be used strongly in opposing directions, such as in the case of 'taboo' words. I am interested in how these two manipulations affect memory performance.

Like emotionality, reward value should influence memory for information. Items that have a higher reward value should be remembered better. However, unlike emotion, reward values are not constant and can vary over time. Classical conditioning in psychology and reinforcement learning in computer science both provide us with methods to investigate how reward values are learned (Rescorla & Wagner, 1972; Sutton & Barto, 1998). I am interested in using models of reward learning to help explain variability in memory performance for items that vary in reward value.

One way to better understand how memory works is to implement mathematical models to represent how the human brain may store information for later retrieval. Some examples of memory models include the matrix model (Anderson, 1970; Humphreys, Bain, & Pike, 1989), TODAM (Murdock, 1982), and SAM (Raajimakers & Shiffrin, 1981). Of particular interest are modeling representations of paired-associate learning.

Experimental psychology approaches to memory can show us what types of items and associations are remembered better than others. Mathematical psychology can provide some insight as to what mechanisms may underly observed behavioural patterns and help us predict new results. However, neuroimaging is essential if we want empirical evidence of how the brain actually processes information differently that results in better memory for one set of items than another.




	Research Interests I am primarily interested in how people learn and retrieve associations for information that is more 'important' (e.g., emotional or rewarded). Some specific aspects of this are: (1) How does memory for items influence memory for associations? (2) How does 'self-important' information affect our ability to learn associations? (3) How can reward learning influence implicit and explicit memory? (4) What processes can underly interactions between item-memory and association-memory? (5) What neural mechanisms can contribute to associative learning? In everyday life, it is not enough to just remember individual items, such as the names of people at a social gathering. Rather, you also need to remember how the items are related, through associations between items; for example: which of the individuals are couples. Manipulations of word properties that yield better memory for items – such as imageability (how conducive a word is to imagery; Paivio, 1971), word frequency (how common a word is in the English language; Gregg, 1976), emotionality (how emotionally arousing a word is; Rubin & Friendly, 1986), and reward value (how rewarding a word is within a particular context; Estes, 1966) – have been found to increase performance on tests of item-memory. However, how these word properties effect memory for associations has been unclear, e.g., a pair of high-frequency items vs. low-frequency, cued recall performance could be due to item-memory or association-memory. I am interested in how item properties can influence association-memory. Do we form better associations involving important items or do we simply remember these items better? Emotionality and reward value are both properties that affect how a memory is relevant in individual’s everyday life. Emotional events are recalled better than neutral events, and in turn, more rewarding events should be remembered better than lower rewarded events. However, direct associations between emotional items have never been looked at systematically in order to study item versus association effects in terms of relevance of the learned material. However, unlike simple manipulations of imageability and word frequency, emotionality and reward value are both more complex properties and are remembered better because of their self-important characteristincs. Additionally, Emotionality is measured in two separable dimensions/measures: arousal and valence. Arousal refers to how exciting/calming an emotional item or event is; while valence is a rating of the emotional event in terms of positive/negative (pleasing/displeasing) value (Bradley & Lang, 1994; Russell, 1980). Both emotionality and reward value can be used strongly in opposing directions, such as in the case of 'taboo' words. I am interested in how these two manipulations affect memory performance. Like emotionality, reward value should influence memory for information. Items that have a higher reward value should be remembered better. However, unlike emotion, reward values are not constant and can vary over time. Classical conditioning in psychology and reinforcement learning in computer science both provide us with methods to investigate how reward values are learned (Rescorla & Wagner, 1972; Sutton & Barto, 1998). I am interested in using models of reward learning to help explain variability in memory performance for items that vary in reward value. One way to better understand how memory works is to implement mathematical models to represent how the human brain may store information for later retrieval. Some examples of memory models include the matrix model (Anderson, 1970; Humphreys, Bain, & Pike, 1989), TODAM (Murdock, 1982), and SAM (Raajimakers & Shiffrin, 1981). Of particular interest are modeling representations of paired-associate learning. Experimental psychology approaches to memory can show us what types of items and associations are remembered better than others. Mathematical psychology can provide some insight as to what mechanisms may underly observed behavioural patterns and help us predict new results. However, neuroimaging is essential if we want empirical evidence of how the brain actually processes information differently that results in better memory for one set of items than another.