Sarah Brown-Schmidt

The Necessity of the Hippocampus for Statistical Learning

Converging evidence points to a role for the hippocampus in statistical learning, but open questions about its necessity remain. Evidence for necessity comes from Schapiro and colleagues who report that a single patient with damage to hippocampus and broader medial temporal lobe cortex was unable to discriminate new from old sequences in several statistical learning tasks. The aim of the current study was to replicate these methods in a larger group of patients who have either damage localized to hippocampus or broader medial temporal lobe damage, to ascertain the necessity of the hippocampus in statistical learning. Patients with hippocampal damage consistently showed less learning overall compared with healthy comparison participants, consistent with an emerging consensus for hippocampal contributions to statistical learning. Interestingly, lesion size did not reliably predict performance. However, patients with hippocampal damage were not uniformly at chance and demonstrated above-chance performance in some task variants. These results suggest that hippocampus is necessary for statistical learning levels achieved by most healthy comparison participants but significant hippocampal pathology alone does not abolish such learning.

Memory and Common Ground Processes in Language Use

During communication, we form assumptions about what our communication partners know and believe. Information that is mutually known between the discourse partners-their common ground-serves as a backdrop for successful communication. Here we present an introduction to the focus of this topic, which is the role of memory in common ground and language use. Two types of questions emerge as central to understanding the relationship between memory and common ground, specifically questions having to do with the representation of common ground in memory, and the use of common ground during language processing.

Memory for conversation and the development of common ground

Efficient conversation is guided by the mutual knowledge, or common ground, that interlocutors form as a conversation progresses. Characterized from the perspective of commonly used measures of memory, efficient conversation should be closely associated with item memory—what was said—and context memory—who said what to whom. However, few studies have explicitly probed memory to evaluate what type of information is maintained following a communicative exchange. The current study examined how item and context memory relate to the development of common ground over the course of a conversation, and how these forms of memory vary as a function of one’s role in a conversation as speaker or listener. The process of developing common ground was positively related to both item and context memory. In addition, content that was spoken was remembered better than content that was heard. Our findings illustrate how memory assessments can complement language measures by revealing the impact that basic conversational processes have on memory for what has been discussed. By taking this approach, we show that not only does the process of forming common ground facilitate communication in the present, but it also promotes an enduring record of that event, facilitating conversation into the future.

Hippocampal Contributions to Language Use and Processing

Recent advances in understanding the functionality of the human hippocampus has led to a number of proposals for how hippocampus may support a range of cognitive abilities beyond memory. Building on these advances, we offered a new account of the memory-language interface [Duff and Brown-Schmidt (Front Hum Neurosci 6:69, 2012)]. We proposed that the same processes by which the hippocampal declarative memory system creates and flexibly integrates representations across diverse sources in the formation of new memories, and maintains representations on-line to be evaluated and used in service of behavioral performance, are the same processes necessary for the flexible use and on-line processing of language. This proposal leads to a set of testable predictions and hypotheses about how language and memory work together and argues that efforts to examine the relationship between memory and language are best served by broad-scope approaches that include the study of a range of communicative activities, including those that are characteristic of everyday language use. In this chapter we review the evidence for hippocampal contributions to language use across communicative phenomena (e.g., semantic representation, gesture, perspective-taking) and a range of language related processes (e.g., on-line processing, statistical learning). The present represents a time of tremendous potential for discovery and progress in the study of memory and language and for more representative, biologically plausible, and ecologically valid investigations of memory-and-language-in-use in every-day life.

Knowledge and Learning of Verb Biases in Amnesia

HighlightsPatients with amnesia use verb bias on‐line to interpret syntactic ambiguity.Previously learned probabilistic verb‐structure mappings are hippocampal‐independent.Patients and controls fail to learn new biases from verb‐structure co‐occurrences.Role of hippocampal memory in continuous updating of verb biases is equivocal. &NA; Verb bias—the co‐occurrence frequencies between a verb and the syntactic structures it may appear with—is a critical and reliable linguistic cue for online sentence processing. In particular, listeners use this information to disambiguate sentences with multiple potential syntactic parses (e.g., Feel the frog with the feather.). Further, listeners dynamically update their representations of specific verbs in the face of new evidence about verb‐structure co‐occurrence. Yet, little is known about the biological memory systems that support the use and dynamic updating of verb bias. We propose that hippocampal‐dependent declarative (relational) memory represents a likely candidate system because it has been implicated in the flexible binding of relational co‐occurrences and in statistical learning. We explore this question by testing patients with severe and selective deficits in declarative memory (anterograde amnesia), and demographically matched healthy participants, in their on‐line interpretation of ambiguous sentences and the ability to update their verb bias with experience. We find that (1) patients and their healthy counterparts use existing verb bias to successfully interpret on‐line ambiguity, however (2) unlike healthy young adults, neither group updated these biases in response to recent exposure. These findings demonstrate that using existing representations of verb bias does not necessitate involvement of the declarative memory system, but leave open the question of whether the ability to update representations of verb‐specific biases requires hippocampal engagement.

Expanding the language network: Domain-specific hippocampal recruitment during high-level linguistic processing

Language processing requires us to encode linear relations between acoustic forms and map them onto hierarchical relations between meaning units. Such relational binding of linguistic elements might recruit the hippocampus given its engagement by similar operations in other cognitive domains. Historically, hippocampal engagement in online language use has received little attention because patients with hippocampal damage are not aphasic. However, recent studies have found that these patients exhibit language impairments when the demands on flexible relational binding are high, suggesting that the hippocampus does, in fact, contribute to linguistic processing. A fundamental question is thus whether language processing engages domain-general hippocampal mechanisms that are also recruited across other cognitive processes or whether, instead, it relies on certain language-selective areas within the hippocampus. To address this question, we conducted the first systematic analysis of hippocampal engagement during comprehension in healthy adults (n=150 across three experiments) using fMRI. Specifically, we functionally localized putative “language-regions” within the hippocampus using a language comprehension task, and found that these regions (i) were selectively engaged by language but not by six non-linguistic tasks; and (ii) were coupled in their activity with the cortical language network during both “rest” and especially story comprehension, but not with the domain-general “multiple-demand (MD)” network. This functional profile did not generalize to other hippocampal regions that were localized using a non-linguistic, working memory task. These findings suggest that some hippocampal mechanisms that maintain and integrate information during language comprehension are not domain-general but rather belong to the language-specific brain network. Significance statement According to popular views, language processing is exclusively supported by neocortical mechanisms. However, recent patient studies suggest that language processing may also require the hippocampus, especially when relations among linguistic elements have to be flexibly integrated and maintained. Here, we address a core question about the place of the hippocampus in the cognitive architecture of language: are certain hippocampal operations language-specific rather than domain-general? By extensively characterizing hippocampal recruitment during language comprehension in healthy adults using fMRI, we show that certain hippocampal subregions exhibit signatures of language specificity in both their response profiles and their patterns of activity synchronization with known functional regions in the neocortex. We thus suggest that the hippocampus is a satellite constituent of the language network.

Autoregressive Generalized Linear Mixed Effect Models with Crossed Random Effects: An Application to Intensive Binary Time Series Eye-Tracking Data

As a method to ascertain person and item effects in psycholinguistics, a generalized linear mixed effect model (GLMM) with crossed random effects has met limitations in handing serial dependence across persons and items. This paper presents an autoregressive GLMM with crossed random effects that accounts for variability in lag effects across persons and items. The model is shown to be applicable to intensive binary time series eye-tracking data when researchers are interested in detecting experimental condition effects while controlling for previous responses. In addition, a simulation study shows that ignoring lag effects can lead to biased estimates and underestimated standard errors for the experimental condition effects.

How We Remember Conversation: Implications in Legal Settings

Memory for the content of our conversations reflects two partially conflicting demands. First, to be an effective participant in a conversation, we use our memory to follow its trajectory, to keep track of unresolved details, and to model the intentions and knowledge states of our partners. Second, to effectively remember a conversation, we need to recall the gist of what was said, by whom, and in what context. These two sets of demands are often different in their content and character. In this article, we review what is known about distant memory for conversations, focusing on issues that have particular relevance for legal contexts. We highlight evidence likely to be of importance in legal contexts, including estimates of how much information can be recalled, the quantity and types of errors that are likely to be made, and the situational factors that shape memory for conversation. The biases we see in distant memory for a conversation reflect in part the interplay of the conflicting demands that conversation places upon us.