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Analogical Inference An Investigation of the Functioning of the Hippocampus in Relational Learning Using fmri William Gross Anthony Greene Today I am going to talk to you about a new task we designed to elucidate how the hippocampus represents context-dependent associations

Hippocampal Dependent Tasks Conscious Memory Context-Dependent Memory Historically, there have been two main perspectives on hippocampal dependent tasks, conscious memories, and context-dependent memories. Here we are interested in the context-dependent perspective.

Hippocampal Dependent Tasks Cannot be solved by attending to only one stimulus Negative Patterning (exclusive-or) A+ B+ AB- Transitive Inference A+ B- B+ C- C+ D- D+ E- B? D? Transverse Patterning A+ B- B+ C- C+ A- Here are a few examples of the most prototypical types of tasks I am referring to. The letters you see here represent arbitrary stimuli. As you can see, in each of these three tasks, it is not possible to solve the entire task by simply attending to single stimuli. Rather, the subject must learn each of the stimuli relative to one another.

Hippocampal Theories Configural Association Theory (Sutherland and Rudy, 1989) Relational Theory (Eichenbaum and Cohen, 2001) Our study focuses on the differences between two current, prominent theories in the literature which attempt to explain the hippocampal contribution to these types of tasks, configural association theory, which was originally proposed by Sutherland and Rudy in 1989, and relational theory, proposed by Eichenbaum and Cohen.

Configural Association Theory A+ B+ Negative Patterning Model + + + Task cannot be solved by simple weights Requires a middle layer AB- A B (Sutherland and Rudy, 1989) Configural theory uses negative patterning as its prototypical task. You ll notice it isn t possible to create a two-layer computational model to solve this task. No weighting scheme can respond correctly to both the elemental items while withholding responses from their combination

Configural Association Theory A+ B+ AB- Negative Patterning Model A + - + AB + + + B Task cannot be solved by simple weights Requires a middle layer (Sutherland and Rudy, 1989) A middle layer is required to modulate the responses to the single items. When these items are presented in combination, this middle layer, which represents the specific configuration of stimuli, will be able to correctly inhibit the response. This is the role the hippocampus serves in configural theory. It modulates the simple, elemental strategy, by allowing configurations of stimuli to gain associative values independent of their constituent stimuli.

Relational Theory Abstract Relations (Eichenbaum and Cohen, 2001) Transitive Inference A+ B- B+ C- C+ D- D+ E- Relational theory is similar in many ways to configural theory, but describes the hippocampus as learning rules rather than specific configurations of stimuli. Relational theory s prototypical task is transitive inference, displayed again here. While configural theory would argue this task is solved by the hippocampus associating individual configurations with their correct response,...

Relational Theory Abstract Relations (Eichenbaum and Cohen, 2001) A > B > C > D > E Transitive Inference A+ B- B+ C- C+ D- D+ E- B? D > means choose over... relational theory would say the hippocampus detects and represents internally consistent relationships which are able to synthesize all of the seemingly contradictory pairs together, into a global hierarchy, like the one shown here. This theory not only offers a method for learning the stimuli simultaneously, but allows for inferential solution to novel stimuli, for example, responding to the novel pair B>D, which can be easily derived from the above hierarchy

Transverse Patterning Relational Theory Configural Theory A C >>> B A+ B- B+ C- [ A B ] [ B C ] [ C A ] A+ B+ C+ (Henke, et al, 1997) C+ A- While these theories are similar, they have distinctly different predictions of how the hippocampus would solve the Transverse Patterning task. Configural theory predicts that the hippocampus would create separate atomic representations for the individual configurations of stimuli which are then associated with the appropriate response. Relational theory, on the other hand, predicts that the hippocampus only creates representations of the relationships between the stimuli. The representations of the stimuli themselves are subserved by cortical processes. Superficially, both of these theories would predict hippocampal involvement in similar behavioral tasks.

Differences? Flexibility Configural Theory: Discriminations bound to stimuli Relational Theory: Relationships independent of stimuli The primary distinction between the two theories is the extent of flexibility afforded by the hippocampus. In configural theory, the discriminations learned by the hippocampus are bound to the stimuli in which they were learned. On the other hand, relational theory, with its abstract rules, allows for much more flexible use of the stimuli.

The AI Task Are subjects able to apply the rules of a hippocampal system (e.g., Transverse Patterning) to another analogous system? So this distinction led me to design the current task. We wanted to test the flexibility of the hippocampal system in humans to see whether human subjects would be able to apply the rules of one hippocampal task to another in an analogous way. In this case I decided to use transverse patterning as our base task.

The AI Task I II A > B X > Y B > C Y > Z C > A Z? X > means choose over Here is a conceptual diagram of the task. The left column, as you can see, is a full transverse patterning. The right column is a second transverse patterning, with different stimuli, however it is incomplete; we do not train the final pair. Our question was whether subjects would use the analogy provided to them by the similar abstract relationships and complete the transverse patterning.

Predictions I II A > B X > Y B > C Y > Z C > A Z? X Control subjects (II only) will overwhelmingly choose X > Z If experimental subjects use a... configural strategy, X > Z relational strategy, Z > X Our specific predictions were as follows. Control subjects -- subjects who are never shown the first transverse patterning -- should overwhelmingly choose X > Z. This is because of the simple inference created by X > Y and Y > Z. If the experimental subjects, who see both sets, are using a configural strategy, they should also choose X > Z. Because if they are not learning through abstract rules, learning the first transverse patterning should not interfere with the second pairs, which are composed of perceptually different stimuli. If, however, subjects are using a relational strategy, they should be able to use the first transverse patterning as an analogy for the second pairs since they are similar in their abstract relationships, and should, at least in part, choose Z > X.

Stimuli Faces taken from a 1954 local high school yearbook Screened for recognizability and low nameability The stimuli we used were faces taken from a local high school yearbook. We chose faces because they are very easily learned, but are difficult to describe in verbal terms (trying to avoid conscious solutions).

Methods Simple instructions Each pair was repeated 75 times per block 75 fixation crosses were randomly mixed into each block Pictures displayed for 1750ms; feedback displayed for 250ms Block Pairs Presented 1 A > B X > Y J > K 2 B > C Y > Z L > M 3 C > A A > B B > C 4 Z > X X > Y Y > Z * * no feedback presented These are the methods we used. The only instructions given to subjects before the experiment was to choose one of the faces and learn from feedback which face is correct. We displayed the faces for 1750ms, followed by feedback for 250ms. This was adjusted in piloting to be slightly faster than is comfortable for subjects to reduce the probability of conscious solutions to the task. Every pair was repeated 75 times within a block. Each of these 3 stimuli listed here were then randomly intermixed along with 75 fixation crosses. This added up to approximately 10 minutes per block. These specific methods were designed in this way in anticipation of taking this task into an fmri scanner. You ll notice in the first 2 blocks we trained subjects on the first two tiers of both the first and second transverse patternings. We also added the non-overlapping pairs J>K and L>M to keep the length of blocks consistent and to provide fmri contrasts. The 3rd block then trains the complete first TP, followed by the 4th block, which presents the complete second TP, but without feedback. You ll notice that we never reinforce a response to ZX. Our main dependent measure, then, was subjects choice on the ZX pair.

Here is an example of the task. You re looking at one of the fixation crosses now +

Subjects were then presented with two faces, each face representing a letter in the previous schemas.

Correct Subjects are then given feedback on whether they were correct or incorrect in their choice.

Hippocampal Specificity Avoid conscious mechanisms (e.g., verbal syllogism) (Greene, et al, 2001) Because we wanted to exclude, as much as we could, the contributions of other systems, for example verbal mechanisms, we attempted to train the task implicitly. To verify the task was being performed implicitly, we debriefed all of the subjects after the experiment and none of them reported to us using explicit strategies for the solution of the ZX pair or reported explicitly noticing two sets of analogous stimuli.

Training Pair Accuracy Proportion Correct 1 0.75 0.5 0.25 0 AB XY JK BC YZ LM AB BC CA 1 2 3 Training Block; Pair Here are the results for the first 3 blocks of the task. You can easily see that performance in the first two blocks of training is near ceiling. Third block performance, as expected, is reduced. Notice that along with low performance on the CA pair, performance on the AB and BC drops indicating subjects are reorganizing relationships. This drop in performance, as well as the fmri data I will show you, suggest that this block is where the majority of the hippocampal processing is occuring

Proportion Correct 1.00 0.75 0.50 0.25 0.00 Block 3, C > A Accuracy 1 11 21 31 41 51 61 71 C > A Trial Number (10-trial moving average) (Greene, et al, 2001) This graph shows the third block performance again by trial number. You will notice subjects begin choosing A>C, the logical conclusion based upon the previous two pairs A>B and B>C. It is important to note that they did not reach ceiling as over-training has been shown previously to be related to awareness.

Z > X Results Proportion Z > X 1 0.75 0.5 0.25 0 XY YZ ZX Pair Type Here we have the results for our critical pair of interest, Z>X in the fourth block. Experimental subjects chose Z>X at approximately 60%. Control subjects are not shown because they all consistently responded X>Z, as was expected. To better interpret these results I ve also included the distribution of scores for the ZX pair.

Z > X Results Proportion Z > X 1 0.75 0.5 0.25 0 XY YZ ZX Pair Type Proportion of Subjects Histogram of Z > X Responses 1 0.75 0.5 0.25 0 0 0.25 0.5 0.75 1 Proportion Z > X Experimental Control From this histogram, you can see the 60% is actually the average of a bimodal distribution. Approximately 75% of experimental subjects chose the analogy Z>X consistently, while 0% of control subjects did. We take this as strong evidence that introducing the transverse patterning analogue is affecting performance on a perceptually dissimilar task.

Block Pairs Presented 1 A > B X > Y J > K 2 B > C Y > Z L > M 3 C > A A > B B > C 4 Z > X X > Y Y > Z Arbitrary fmri Units 3.50 2.63 1.75 0.88 0-0.88 TP Test Training 0 1 2 3 4 5 6 7 TRs (2s) Here is a quick glimpse at what we are working on now. These data are preliminary, but you can see we have found a strong response in the posterior left hippocampus to processing during transverse patterning. The two IRFs are activation during the transverse patterning pairs versus the premise pairs it was based on in the first two blocks (as pictured in the table). These results then support the claim that transverse patterning is in fact hippocampal in humans. This is critical to the validity of our previous argument.

Block Pairs Presented 1 A > B X > Y J > K 2 B > C Y > Z L > M 3 C > A A > B B > C 4 Z > X X > Y Y > Z Arbitrary fmri Units 3.25 1.63 0-1.63-3.25-4.88-6.50 TP Test Training 0 1 2 3 4 5 6 7 TRs (2s) We also observed and anterior hippocampal activation. Because of the nature of this activation, we think this may be due to activation during fixations and therefore is less easily interpreted.

Conclusions The fmri findings support the hippocampal nature of Transverse Patterning The behavioral findings suggest Transverse Patterning is learned flexibly These findings support Relational Theory These data thus provide evidence that, at least, configural theory cannot be a fully accurate representation of how the hippocampus processes stimuli. We presented fmri data which supports the claim that transverse patterning is hippocampal. We have also shown that stimuli in perceptually distinct hippocampal tasks can interfere with one another. According our current interpretation, this cannot be explained by configural theory. Relational theory, however, would predict precisely the results we found, that relationships are learned abstractly and therefore can be applied to many different types of stimuli.

Future Directions Continue in fmri scanner Explore the specific contribution of the hippocampus to Transverse Patterning Explore the role of the hippocampus in performing Analogical Inference Run with lesioned rats Quickly, our next step is to finish running this task in an fmri scanner to explore more specifically the hippocampal contributions to Transverse Patterning. We would also like to explore the Analogical Inference task itself as another form of hippocampal task. We make this prediction because of the similarity of Analogical Inference to other forms of inference, like transitive inference, which are hippocampal dependent. Finally, we have considered running a version of this task in lesioned rats to be able to compare our results more directly with the rat literature.

Acknowledgments Stephen Rao Anna Berg Maria Welch