Impaired spatial and non-spatial configural learning in patients with hippocampal pathology

Abstract

The hippocampus has been proposed to play a critical role in memory through its unique ability to bind together the disparate elements of an experience. This hypothesis has been widely examined in rodents using a class of tasks known as "configural" or "non-linear", where outcomes are determined by specific combinations of elements, rather than any single element alone. On the basis of equivocal evidence that hippocampal lesions impair performance on non-spatial configural tasks, it has been proposed that the hippocampus may only be critical for spatial configural learning. Surprisingly few studies in humans have examined the role of the hippocampus in solving configural problems. In particular, no previous study has directly assessed the human hippocampal contribution to non-spatial and spatial configural learning, the focus of the current study. Our results show that patients with primary damage to the hippocampus bilaterally were similarly impaired at configural learning within both spatial and non-spatial domains. Our data also provide evidence that residual configural learning can occur in the presence of significant hippocampal dysfunction. Moreover, evidence obtained from a post-experimental debriefing session suggested that patients acquired declarative knowledge of the underlying task contingencies that corresponded to the best-fit strategy identified by our strategy analysis. In summary, our findings support the notion that the hippocampus plays an important role in both spatial and non-spatial configural learning, and provide insights into the role of the medial temporal lobe (MTL) more generally in incremental reinforcement-driven learning.

Fig. 1

Experimental design: subjects were instructed to play the role of a weather forecaster, and try to learn over the course of the experiment how different “patterns” of shapes on the screen were associated with one of two outcomes, sun or rain (see Section 2). Each one of the eight patterns was associated with an outcome in a deterministic fashion (i.e. with 100% probability). In patterns 1–4, the position of the triangle determines the outcome (in this example, although the allocation of shapes to outcomes was changed between subjects). Hence when the triangle appears on the left, the outcome is sun regardless of the shape present in the centre. When the triangle appears on the right, the outcome is always rain. In patterns 5–8, specific shape–shape pairings determine the outcome, with the position of the square being irrelevant. Hence, square together with star is associated with sun, regardless of the position of the square. Conversely, square together with ellipse is always associated with rain. Trials could therefore be divided conceptually into those involving learning of spatial (patterns 1–4), as opposed to non-spatial (patterns 5–8), configural associative information.

Fig. 2

Structural MRI scans: coronal sections through the MRI brain scans of each patient, where the damaged hippocampi are indicated by white arrows. Note P01's scan is a FLAIR image, while the other scans are T1 images.

Fig. 3

Performance of amnesic patients and control subjects, collapsed across condition (spatial or non-spatial). Each block consisted of 50 trials, with presentation of each of the eight patterns occurring pseudorandomly (see Section 2). Error bars reflect standard error of the mean (S.E.M.).

Fig. 4

Performance of amnesic patients and control subjects plotted for each condition separately (spatial, non-spatial). (A) Performance of the six control subjects. Error bars are not shown since comparison of performance in spatial and non-spatial conditions is within-subjects. (B) Performance of the four amnesic patients.

Fig. 5

Performance of amnesic patients divided into two groups according to strategy (optimal or sub-optimal). (A) Average performance of optimal strategy patients (P01 and P04). These patients adopted a configural associative strategy (see Section 3/Section 2 for details of strategy analysis) and performed relatively well on the task (average performance during last three blocks: 80%, S.D. 2.9). (B) Average performance of sub-optimal strategy patients (P02 and P03). These patients performed relatively poorly (average performance during last three blocks: 62.7%, S.D. 5.6), failing to adopt a configural strategy and using at best an elemental (i.e. single shape) strategy. The use of this elemental strategy naturally results in superior performance in the non-spatial, as compared to the spatial, condition, although this difference was not statistically significant.

Fig. 6

Performance of the amnesic patients with the data for each plotted separately. (A) P01, (B) P02, (C) P03, (D) P04.