Rhinal and hippocampal contributions to spontaneous inter-item binding and verbal memory recall: Evidence from temporal lobe epilepsy.

The medial temporal lobes (MTL) play a prominent role in associative memory processing. Still, it is unclear to what extent specific structures within the MTL sub-serve distinct aspects of associative memory. Here, the role of the MTL in forming spontaneous associations in a "naturalistic" setting is investigated applying a word-list memory test not presenting items in an associative fashion. This allows for the differential investigation of item recall and associative binding. Participants included patients with medial temporal lobe epilepsy (mTLE, n = 79) and healthy controls (n = 58). Memory performance in a verbal list-learning paradigm was analyzed by (1) inter-trial repetitions ("binding", i.e., number of word-pairs consistently recalled over two consecutive trials), and (2) single item recall. In patients, behavioral results were correlated with rhinal cortex and hippocampal volumetric data. Results showed that binding was specifically diminished for patients with mTLE during learning and delayed recall. Moreover, binding predicted behavioral differences in item recall. Notably, hippocampal volumes were correlated with item recall during delayed recall, whereas rhinal cortex volumes were correlated with binding during learning. Our results provide evidence that diminished verbal memory in patients with mTLE at least partly can be attributed to functional reductions in spontaneous inter-trial stimulus binding. Moreover, they demonstrate a process-dependent functional dissociation between rhinal cortex and hippocampus for verbal encoding and recall: While the rhinal cortex is mainly engaged in detecting novel associations, the hippocampus primarily subserves consolidation and recall of associations between stimuli. Our study thus advances current models of the sub-specialization of MTL structures and offers novel evidence that memory formation in the MTL is mediated by associative item-processing, even when stimuli are not presented in an associative fashion per se. Thus, our results provide valuable qualitative insights into mechanisms of memory formation and memory failures in patients with MTL dysfunctions.

Thought experiment: Decoding cognitive processes from the fMRI data of one individual.

Cognitive processes, such as the generation of language, can be mapped onto the brain using fMRI. These maps can in turn be used for decoding the respective processes from the brain activation patterns. Given individual variations in brain anatomy and organization, analyzes on the level of the single person are important to improve our understanding of how cognitive processes correspond to patterns of brain activity. They also allow to advance clinical applications of fMRI, because in the clinical setting making diagnoses for single cases is imperative. In the present study, we used mental imagery tasks to investigate language production, motor functions, visuo-spatial memory, face processing, and resting-state activity in a single person. Analysis methods were based on similarity metrics, including correlations between training and test data, as well as correlations with maps from the NeuroSynth meta-analysis. The goal was to make accurate predictions regarding the cognitive domain (e.g. language) and the specific content (e.g. animal names) of single 30-second blocks. Four teams used the dataset, each blinded regarding the true labels of the test data. Results showed that the similarity metrics allowed to reach the highest degrees of accuracy when predicting the cognitive domain of a block. Overall, 23 of the 25 test blocks could be correctly predicted by three of the four teams. Excluding the unspecific rest condition, up to 10 out of 20 blocks could be successfully decoded regarding their specific content. The study shows how the information contained in a single fMRI session and in each of its single blocks can allow to draw inferences about the cognitive processes an individual engaged in. Simple methods like correlations between blocks of fMRI data can serve as highly reliable approaches for cognitive decoding. We discuss the implications of our results in the context of clinical fMRI applications, with a focus on how decoding can support functional localization.