Semantic Search as Pattern Completion across a Concept

Differential relational memory impairment in temporal lobe epilepsy

OBJECTIVE

Temporal lobe epilepsy (TLE) is typically associated with pathology of the hippocampus, a key structure involved in relational memory, including episodic, semantic, and spatial memory processes. While it is widely accepted that TLE-associated hippocampal alterations underlie memory deficits, it remains unclear whether impairments relate to a specific cognitive domain or multiple ones.

METHODS

We administered a recently validated task paradigm to evaluate episodic, semantic, and spatial memory in 24 pharmacoresistant TLE patients and 50 age- and sex-matched healthy controls. We carried out two-way analyses of variance to identify memory deficits in individuals with TLE relative to controls across different relational memory domains, and used partial least squares correlation to identify factors contributing to variations in relational memory performance across both cohorts.

RESULTS

Compared to controls, TLE patients showed marked impairments in episodic and spatial memory, with mixed findings in semantic memory. Even when additionally controlling for age, sex, and overall cognitive function, between-group differences persisted along episodic and spatial domains. Moreover, age, diagnostic group, and hippocampal volume were all associated with relational memory behavioral phenotypes.

SIGNIFICANCE

Our behavioral findings show graded deficits across relational memory domains in people with TLE, which provides further insights into the complex pattern of cognitive impairment in the condition.

Disrupting dorsal hippocampus impairs category learning in rats

Categorization requires a balance of mechanisms that can generalize across common features and discriminate against specific details. A growing literature suggests that the hippocampus may accomplish these mechanisms by using fundamental mechanisms like pattern separation, pattern completion, and memory integration. Here, we assessed the role of the rodent dorsal hippocampus (HPC) in category learning by combining inhibitory DREADDs (Designer Receptors Exclusively Activated by Designer Drugs) and simulations using a neural network model. Using touchscreens, we trained rats to categorize distributions of visual stimuli containing black and white gratings that varied along two continuous dimensions. Inactivating the dorsal HPC impaired category learning and generalization, suggesting that the rodent HPC plays an important role during categorization. Hippocampal inactivation had no effect on a control discrimination task that used identical trial procedures as the categorization tasks, suggesting that the impairments were specific to categorization. Model simulations were conducted with variants of a neural network to assess the impact of selective deficits on category learning. The hippocampal inactivation groups were best explained by a model that injected random noise into the computation that compared the similarity between category stimuli and existing memory representations. This model is akin to a deficit in mechanisms of pattern completion, which retrieves similar memory representations using partial information.

The shared and unique neural correlates of personal semantic, general semantic, and episodic memory

One of the most common distinctions in long-term memory is that between semantic (i.e., general world knowledge) and episodic (i.e., recollection of contextually specific events from one's past). However, emerging cognitive neuroscience data suggest a surprisingly large overlap between the neural correlates of semantic and episodic memory. Moreover, personal semantic memories (i.e., knowledge about the self and one's life) have been studied little and do not easily fit into the standard semantic-episodic dichotomy. Here, we used fMRI to record brain activity while 48 participants verified statements concerning general facts, autobiographical facts, repeated events, and unique events. In multivariate analysis, all four types of memory involved activity within a common network bilaterally (e.g., frontal pole, paracingulate gyrus, medial frontal cortex, middle/superior temporal gyrus, precuneus, posterior cingulate, angular gyrus) and some areas of the medial temporal lobe. Yet the four memory types differentially engaged this network, increasing in activity from general to autobiographical facts, from autobiographical facts to repeated events, and from repeated to unique events. Our data are compatible with a component process model, in which declarative memory types rely on different weightings of the same elementary processes, such as perceptual imagery, spatial features, and self-reflection.

Specifying a relationship between semantic and episodic memory in the computation of a feature-based familiarity signal using MINERVA 2

Approaches to modeling episodic recognition memory often imply a separability from semantic memory insofar as an implicit tabula rasa (i.e., blank slate) assumption is apparent in many simulations. This is evident in the common practice of having new test probes correspond to zero memory traces in the store while old test probes correspond to traces representing instances of items' occurrence on a study list. However, in list-learning studies involving word lists, none of the test items would actually correspond to zero items in the person's memory, as all of the test words are generally known to participants, whether old or new. By focusing on a list-learning recognition phenomenon that likely results from feature-based familiarity detection and necessarily involves a role of preexisting knowledge in its mechanisms-the semantic-feature-based recognition without cued recall phenomenon-we show how incorporating preexisting knowledge into the MINERVA 2 model enables it to simulate previously shown empirical patterns with this phenomenon. The simulation patterns reported here raise new theoretical implications worth further exploration, such as the extent to which the variances change in the signal versus the noise distribution when preexisting knowledge is present versus absent in the simulations.

Sleep reduces the semantic coherence of memory recall: An application of latent semantic analysis to investigate memory reconstruction

Sleep is thought to help consolidate hippocampus-dependent memories by reactivating previously encoded neural representations, promoting both quantitative and qualitative changes in memory representations. However, the qualitative nature of changes to memory representations induced by sleep remains largely uncharacterized. In this study, we investigated how memories are reconstructed by hypothesizing that semantic coherence, defined as conceptual relatedness between statements of free-recall texts and quantified using latent semantic analysis (LSA), is affected by post-encoding sleep. Short naturalistic videos of events featuring six animals were presented to 115 participants who were randomly assigned to either 12- or 24-h delay groups featuring sleep or wakefulness. Participants' free-recall responses were analyzed to test for an effect of sleep on semantic coherence between adjacent statements, and overall. The presence of sleep reduced both forms of semantic coherence, compared to wakefulness. This change was robust and not due to shifts in conciseness or repetitiveness with sleep. These findings support the notion that sleep-dependent consolidation qualitatively changes the features of reconstructed memory representations by reducing semantic coherence.

Varying demands for cognitive control reveals shared neural processes supporting semantic and episodic memory retrieval

The categorisation of long-term memory into semantic and episodic systems has been an influential catalyst for research on human memory organisation. However, the impact of variable cognitive control demands on this classical distinction remains to be elucidated. Across two independent experiments, here we directly compare neural processes for the controlled versus automatic retrieval of semantic and episodic memory. In a multi-session functional magnetic resonance imaging experiment, we first identify a common cluster of cortical activity centred on the left inferior frontal gyrus and anterior insular cortex for the retrieval of both weakly-associated semantic and weakly-encoded episodic memory traces. In an independent large-scale individual difference study, we further reveal a common neural circuitry in which reduced functional interaction between the identified cluster and ventromedial prefrontal cortex, a default mode network hub, is linked to better performance across both memory types. Our results provide evidence for shared neural processes supporting the controlled retrieval of information from functionally distinct long-term memory systems.

Making sense of the world around us often requires flexible access to information from both semantic and episodic memory systems. Here, the authors show that controlled retrieval from functionally distinct long-term memory stores is supported by shared neural processes in the human brain.

Concept formation as a computational cognitive process

Hippocampus and entorhinal cortex form cognitive maps that represent relations among memories within a multidimensional space. While these relational maps have long been proposed to contribute to episodic memory, recent work suggests that they also support concept formation by representing relevant features for discriminating among related concepts. Cognitive maps may be refined by medial prefrontal cortex, which selects dimensions to represent based on their behavioral relevance. Hippocampal pattern completion, which is critical for retrieval of episodic memories, may also contribute to generalization of existing concepts to new exemplars. Navigation within hippocampal cognitive maps, which is guided by grid coding in entorhinal cortex, may contribute to imagination through recombination of event elements or concept features.