Decoding information in the human hippocampus: a user's guide

Multi-voxel pattern analysis (MVPA), or 'decoding', of fMRI activity has gained popularity in the neuroimaging community in recent years. MVPA differs from standard fMRI analyses by focusing on whether information relating to specific stimuli is encoded in patterns of activity across multiple voxels. If a stimulus can be predicted, or decoded, solely from the pattern of fMRI activity, it must mean there is information about that stimulus represented in the brain region where the pattern across voxels was identified. This ability to examine the representation of information relating to specific stimuli (e.g., memories) in particular brain areas makes MVPA an especially suitable method for investigating memory representations in brain structures such as the hippocampus. This approach could open up new opportunities to examine hippocampal representations in terms of their content, and how they might change over time, with aging, and pathology. Here we consider published MVPA studies that specifically focused on the hippocampus, and use them to illustrate the kinds of novel questions that can be addressed using MVPA. We then discuss some of the conceptual and methodological challenges that can arise when implementing MVPA in this context. Overall, we hope to highlight the potential utility of MVPA, when appropriately deployed, and provide some initial guidance to those considering MVPA as a means to investigate the hippocampus

The Interaction of Learning Speed and Memory Interference: When Fast is Bad

Research on individual differences in speed of learning has suggested that forgetting rates could be different for fast and slow learners. Studies have shown either no difference or slower forgetting over time for fast learners. The present study extends this area of research by investigating the possibility that fast and slow learning are differentially vulnerable to interference. Based on neural network models and the encoding variability hypothesis, two novel hypotheses were built and tested in two experiments by a paired-associates task. The hypotheses suggested that fast learning will be more prone to interference when similarity of the learning material is high. Hence, an interaction of learning speed and interference (i.e., similarity) was predicted. Experiment 1 (N = 22) compared retention of Chinese characters for fast and slow learning (both subject and item-specific speed) by manipulating similarity (high vs. low) of the characters learned. Results of Experiment 1 were inconclusive. Experiment 2 (N = 21) had the same basic design as Experiment 1, but included a number of procedural improvements. Interactions in the predicted direction were found both when comparing learning speed between subjects as well as for item-specific speed. However, only the interaction of between-subjects learning speed and similarity was significant. A joint analysis, including data from both experiments, yielded significant interactions for both subject speed and item-specific speed, indicating that the lack of a significant interaction of item-specific speed and similarity in Experiment 2 was probably due to the low sample size. The findings are discussed in relation to previous research on individual differences in learning speed and forgetting

Content representation in the human medial temporal lobe

The transformation of sensory inputs into complex memory representations is fundamental to human experience; yet, little is known about how this crucial process is achieved. When you meet your friend at the new cafe in town, what part of the brain encodes this novel scene into long term memory? What part encoded your friend’s favorite t-shirt, so that the sight of it gives you a feeling of familiarity rather than surprise? It is well-established that the medial temporal lobe (MTL) is crucial to both processes, but the MTL is not a single homogeneous region. In fact, it is composed of several anatomically distinct subregions including hippocampus, perirhinal cortex (PRC) and parahippocampal cortex (PHC). However, the computations performed by each subregion to encode individual events is still unclear. The present research tests the central hypothesis that different forms of event content are transformed into memory by distinct subregions within the MTL. A critical barrier in the study of content representation thus far has been its focus on comparing univariate peak activations in a region to different stimulus materials. To go beyond this limited approach, we employed multivariate statistical analyses that takes into account how event content is represented by distributed activity in MTL subregions. First, we examine the content-specific contributions of MTL subregions to episodic encoding and retrieval. Then, we demonstrate how these distributed representations support memory-based prediction to resolve ambiguities in our environment.Neuroscienc

Cognitive boundary signals in the human medial temporal lobe shape episodic memory representation

While experience unfolds continuously, memories are organized as a set of discrete events that bind together the “where”, “when”, and “what” of episodic memory. This segmentation of continuous experience is thought to be facilitated by the detection of salient environmental or cognitive events. However, the underlying neural mechanisms and how such segmentation shapes episodic memory representations remain unclear. We recorded from single neurons in the human medial temporal lobe while subjects watched videos with different types of embedded boundaries and were subsequently evaluated for memories of the video contents. Here we show neurons that signal the presence of cognitive boundaries between subevents from the same episode and neurons that detect the abstract separation between different episodes. The firing rate and spike timing of these boundary-responsive neurons were predictive of later memory retrieval accuracy. At the population level, abrupt neural state changes following boundaries predicted enhanced memory strength but impaired order memory, capturing the behavioral tradeoff subjects exhibited when recalling episodic content versus temporal order. Successful retrieval was associated with reinstatement of the neural state present following boundaries, indicating that boundaries structure memory search. These findings reveal a neuronal substrate for detecting cognitive boundaries and show that cognitive boundary signals facilitate the mnemonic organization of continuous experience as a set of discrete episodic events

Neural Oscillations as Representations

We explore the contribution made by oscillatory, synchronous neural activity to representation in the brain. We closely examine six prominent examples of brain function in which neural oscillations play a central role, and identify two levels of involvement that these oscillations take in the emergence of representations: enabling (when oscillations help to establish a communication channel between sender and receiver, or are causally involved in triggering a representation) and properly representational (when oscillations are a constitutive part of the representation). We show that even an idealized informational sender-receiver account of representation makes the representational status of oscillations a non-trivial matter, which depends on rather minute empirical details

Neural Oscillations as Representations

We explore the contribution made by oscillatory, synchronous neural activity to representation in the brain. We closely examine six prominent examples of brain function in which neural oscillations play a central role, and identify two levels of involvement that these oscillations take in the emergence of representations: enabling (when oscillations help to establish a communication channel between sender and receiver, or are causally involved in triggering a representation) and properly representational (when oscillations are a constitutive part of the representation). We show that even an idealized informational sender-receiver account of representation makes the representational status of oscillations a non-trivial matter, which depends on rather minute empirical details

Distinct replay signatures for prospective decision-making and memory preservation

Theories of neural replay propose that it supports a range of functions, most prominently planning and memory consolidation. Here, we test the hypothesis that distinct signatures of replay in the same task are related to model-based decision-making (“planning”) and memory preservation. We designed a reward learning task wherein participants utilized structure knowledge for model-based evaluation, while at the same time had to maintain knowledge of two independent and randomly alternating task environments. Using magnetoencephalography and multivariate analysis, we first identified temporally compressed sequential reactivation, or replay, both prior to choice and following reward feedback. Before choice, prospective replay strength was enhanced for the current task-relevant environment when a model-based planning strategy was beneficial. Following reward receipt, and consistent with a memory preservation role, replay for the alternative distal task environment was enhanced as a function of decreasing recency of experience with that environment. Critically, these planning and memory preservation relationships were selective to pre-choice and post-feedback periods, respectively. Our results provide support for key theoretical proposals regarding the functional role of replay and demonstrate that the relative strength of planning and memory-related signals are modulated by ongoing computational and task demands