Expanding the Language Network: Direct Contributions from the Hippocampus

The hippocampus supports the representation of abstract concepts: Implications for the study of recognition memory

Words, unlike images, are symbolic representations. The associative details inherent within a word's meaning and the visual imagery it generates, are inextricably connected to the way words are processed and represented. It is well recognised that the hippocampus associatively binds components of a memory to form a lasting representation, and here we show that the hippocampus is especially sensitive to abstract word processing. Using fMRI during recognition, we found that the increased abstractness of words produced increased hippocampal activation regardless of memory outcome. Interestingly, word recollection produced hippocampal activation regardless of word content, while the parahippocampal cortex was sensitive to concreteness of word representations, regardless of memory outcome. We reason that the hippocampus has assumed a critical role in the representation of uncontextualized abstract word meaning, as its information-binding ability allows the retrieval of the semantic and visual associates that, when bound together, generate the abstract concept represented by word symbols. These insights have implications for research on word representation, memory, and hippocampal function, perhaps shedding light on how the human brain has adapted to encode and represent abstract concepts.

Finding the Words: How Does the Aging Brain Process Language? A Focused Review of Brain Connectivity and Compensatory Pathways

As people age, there is a natural decline in cognitive functioning and brain structure. However, the relationship between brain function and cognition in older adults is neither straightforward nor uniform. Instead, it is complex, influenced by multiple factors, and can vary considerably from one person to another. Reserve, compensation, and maintenance mechanisms may help explain why some older adults can maintain high levels of performance while others struggle. These mechanisms are often studied concerning memory and executive functions that are particularly sensitive to the effects of aging. However, language abilities can also be affected by age, with changes in production fluency. The impact of brain changes on language abilities needs to be further investigated to understand the dynamics and patterns of aging, especially successful aging. We previously modeled several compensatory profiles of language production and lexical access/retrieval in aging within the Lexical Access and Retrieval in Aging (LARA) model. In the present paper, we propose an extended version of the LARA model, called LARA-Connectivity (LARA-C), incorporating recent evidence on brain connectivity. Finally, we discuss factors that may influence the strategies implemented with aging. The LARA-C model can serve as a framework to understand individual performance and open avenues for possible personalized interventions.

Bridging the Chasm Between Cognitive Representations and Formal Structures of Linguistic Meanings

This paper aims to show that properties of cognitive/conceptual representations and formal-logical structures of linguistic meaning can be inter-translated, recast, transformed into one another, and so united together, even though cognitive/conceptual representations and formal-logical structures of linguistic meaning are apparently distinct in ontology and divergent in their form or character. While cognitive/conceptual representations are ultimately rooted in sensory-motor systems, formal-logical structures of linguistic meaning are abstractions detached from and independent of the actualized world. This paper sketches out the foundations of how representations of linguistic meaning in terms of cognitive/conceptual structures in Cognitive/Conceptual Semantics can be unified with those in terms of formal-logical structures in Formal Semantics. This is done by recasting cognitive/conceptual representations in terms of formal-logical structures of linguistic meaning and re-encoding formal-logical structures of linguistic meaning in terms of cognitive/conceptual representations. Then, these two types of semantic representations, thus shown representationally equivalent, will be related to a series of derivations across levels in neuronal networks and dynamics. The general discussion on unifying cognitive/conceptual representations of linguistic meaning with formal-logical structures is contextualized within the broader context of theorizing in cognitive science.

Speech decoding using cortical and subcortical electrophysiological signals

Introduction

Language impairments often result from severe neurological disorders, driving the development of neural prosthetics utilizing electrophysiological signals to restore comprehensible language. Previous decoding efforts primarily focused on signals from the cerebral cortex, neglecting subcortical brain structures' potential contributions to speech decoding in brain-computer interfaces.

Methods

In this study, stereotactic electroencephalography (sEEG) was employed to investigate subcortical structures' role in speech decoding. Two native Mandarin Chinese speakers, undergoing sEEG implantation for epilepsy treatment, participated. Participants read Chinese text, with 1-30, 30-70, and 70-150 Hz frequency band powers of sEEG signals extracted as key features. A deep learning model based on long short-term memory assessed the contribution of different brain structures to speech decoding, predicting consonant articulatory place, manner, and tone within single syllable.

Results

Cortical signals excelled in articulatory place prediction (86.5% accuracy), while cortical and subcortical signals performed similarly for articulatory manner (51.5% vs. 51.7% accuracy). Subcortical signals provided superior tone prediction (58.3% accuracy). The superior temporal gyrus was consistently relevant in speech decoding for consonants and tone. Combining cortical and subcortical inputs yielded the highest prediction accuracy, especially for tone.

Discussion

This study underscores the essential roles of both cortical and subcortical structures in different aspects of speech decoding.

Gesture, spatial cognition and the evolution of language

Human communication displays a striking contrast between the diversity of languages and the universality of the principles underlying their use in conversation. Despite the importance of this interactional base, it is not obvious that it heavily imprints the structure of languages. However, a deep-time perspective suggests that early hominin communication was gestural, in line with all the other Hominidae. This gestural phase of early language development seems to have left its traces in the way in which spatial concepts, implemented in the hippocampus, provide organizing principles at the heart of grammar. This article is part of a discussion meeting issue 'Face2face: advancing the science of social interaction'.

Word Learning as a Window to Memory and Rehabilitation Outcomes in Traumatic Brain Injury

PURPOSE

The purpose of this viewpoint is to advocate for increased study of word learning abilities and word learning interventions in traumatic brain injury (TBI).

METHOD

We describe the word learning process and the unique opportunities afforded by studying each component and stage. Building on discussions at the 2022 International Cognitive-Communication Disorders Conference, we describe how word learning may underlie a variety of functional outcomes after TBI, making it a promising target for rehabilitation. Finally, we discuss principles that may guide study in this critical area to advance outcomes after TBI for children and adults.

RESULTS

Word learning is a dynamic and iterative process taking place over time and in multiple stages. Thus, studying word learning affords the opportunity to parse the relative contributions of multiple memory systems to different phases and components of the process. However, single-timepoint designs are insufficient to capture the full word learning process, which occurs over time and across contexts. Word learning also presents an opportunity to assess the contributions of behavioral and lifestyle factors (e.g., sleep and exercise) to different memory phases. Understanding these interactions could drive clinical interventions aimed at improving memory through manipulable external behaviors.

CONCLUSIONS

Word learning is key to success in functional spheres across the life span. The importance of words to daily life remains after TBI, even as the memory systems that support word learning are disrupted. The empirical study of word learning and rehabilitation of word learning deficits in TBI presents a promising new direction in understanding the breadth of neurogenic cognitive-communication disorders and an opportunity to explore a potential driver of functional outcome and impactful rehabilitation target.

Baseline structural imaging correlates of treatment outcomes in semantic variant primary progressive aphasia

Semantic variant primary progressive aphasia (svPPA) is a neurodegenerative disorder characterized by a loss of semantic knowledge in the context of anterior temporal lobe atrophy (left > right). Core features of svPPA include anomia and single-word comprehension impairment. Despite growing evidence supporting treatment for anomia in svPPA, there is a paucity of research investigating neural mechanisms supporting treatment-induced gains and generalization to untrained items. In the current study, we examined the relation between the structural integrity of brain parenchyma (tissue inclusive of gray and white matter) at pre-treatment and treatment outcomes for trained and untrained items in a group of 19 individuals with svPPA who completed lexical retrieval treatment. Two structural neuroimaging approaches were used: an exploratory, whole-brain, voxel-wise approach and an a priori region of interest (ROI) approach. Based on previous research, bilateral temporal (inferior, middle, and superior temporal gyri), parietal (supramarginal and angular gyri), frontal (inferior and middle frontal gyri) and medial temporal (hippocampus and parahippocampal gyri) ROIs were selected from the Automated Anatomical Labeling (AAL) atlas. Analyses revealed improved naming of trained items and generalization to untrained items following treatment, providing converging evidence that individuals with svPPA can benefit from treatment for anomia. Better post-treatment naming accuracy was associated with the structural integrity of inferior parietal cortex and the hippocampus. Specifically, improved naming of trained items was related to the left supramarginal (phonological processing) and angular gyri (phonological and semantic processing), and improved naming of trained and untrained items was related to the left hippocampus (episodic, context-based memory). Future research should examine treatment outcomes in relation to pre-treatment functional and structural connectivity as well as changes in network dynamics following speech-language intervention to further elucidate the neural mechanisms underlying treatment response in svPPA and related disorders.

Clinical Features, Brain-Structure Changes, and Cognitive Impairment in Basal Ganglia Infarcts: A Pilot Study

Introduction

Stroke has been considered to raise the risk of dementia in several studies, but the relationship between brain structural changes and poststroke cognitive impairment (PSCI) is unclear.

Methods

In this study, 23 PSCI patients with basal ganglia infarcts after 2 weeks and 29 age-matched controls underwent magnetic resonance imaging measuring cortical thickness and volume changes, as well as neuropsychological tests. CI was derived from a performance score <1.5 standard deviations for normally distributed scores. We compared Z scores in different cognitive domains and cortical thickness and volumes in two groups. Multiple linear regressions were used to investigate the relationship between cortical thickness and volumes and neuropsychological tests.

Results

A majority of PSCI patients were in their 50s (55.19±8.52 years). PSCI patients exhibited significantly decreased Z scores in multiple domains, such as memory, language, visuomotor speed, and attention/executive function. The volumes of the middle posterior corpus callosum, middle anterior corpus callosum, and hippocampus in PSCI patients were markedly lower than controls. The thickness of the right inferior temporal cortex and insula were significantly smaller than controls. It found that the reduced right hippocampus was related to executive dysfunction. Hippocampus dysfunction may be involved in language impairment (p<0.05) in PSCI patients with basal ganglia infarcts.

Conclusion

These findings demonstrated that brain structure changed after ischemic stroke, and different gray-matter structural changes could lead to specific cognitive decline in PSCI patients with basal ganglia infarcts. Atrophy of the right hippocampus potentially serves as an imaging marker of early executive function of PSCI.

Language Impairment in Children of Mothers with Gestational Diabetes, Preeclampsia, and Preterm Delivery: Current Hypothesis and Potential Underlying Mechanisms : Language Impartment and Pregnancy Complications

Many conditions may impair or delay language development, including socioeconomic status, parent's education, or intrauterine environment. Accordingly, increasing evidence has described that pregnancy complications, including gestational diabetes mellitus (GDM), preeclampsia, and preterm delivery, are associated with the offspring's impaired neurodevelopment. Since language is one of the high brain functions, alterations in this function are another sign of neurodevelopment impairment. How these maternal conditions may generate language impairment has yet to be entirely understood. However, since language development requires adequate structural formation and function/connectivity of the brain, these processes must be affected by alterations in maternal conditions. However, the underlying mechanisms of these structural alterations are largely unknown. This manuscript critically analyzes the literature focused on the risk of developing language impairment in children of mothers with GDM, preeclampsia, and preterm delivery. Furthermore, we highlight potential underlying molecular mechanisms associated with these alterations, such as neuroinflammatory and metabolic and cerebrovascular alterations.

Dataset of Speech Production in intracranial.Electroencephalography

Speech production is an intricate process involving a large number of muscles and cognitive processes. The neural processes underlying speech production are not completely understood. As speech is a uniquely human ability, it can not be investigated in animal models. High-fidelity human data can only be obtained in clinical settings and is therefore not easily available to all researchers. Here, we provide a dataset of 10 participants reading out individual words while we measured intracranial EEG from a total of 1103 electrodes. The data, with its high temporal resolution and coverage of a large variety of cortical and sub-cortical brain regions, can help in understanding the speech production process better. Simultaneously, the data can be used to test speech decoding and synthesis approaches from neural data to develop speech Brain-Computer Interfaces and speech neuroprostheses.

Measurement(s)	Brain activity
Technology Type(s)	Stereotactic electroencephalography
Sample Characteristic - Organism	Homo sapiens
Sample Characteristic - Environment	Epilepsy monitoring center
Sample Characteristic - Location	The Netherlands

Language reorganization in patients with left-hemispheric gliomas is associated with increased cortical volume in language-related areas and in the default mode network

BACKGROUND

Language function may reorganize to overcome focal impairment; however, the relation between functional and structural changes in patients with brain tumors remains unclear. We investigated the cortical volume of atypical language dominant (AD) patients with left frontal-insular high-grade (HGG) and low-grade glioma (LGG). We hypothesized atypical language being associated with areas of increased cortical volume in the right hemisphere, including language areas homologues.

METHODS

Patient were recruited following the criteria: left frontal-insular glioma; functional MRI and 3DT1-weighted images; no artifacts. We calculated an hemispheric language laterality index (LI), defined as: AD if LI < .2; left-dominant (LD) if LI ≥ .2. We measured cortical volume in three voxel-based morphometry (VBM) analyses: total AD vs. LD patients; AD vs. LD in HGG; AD vs. LD in LGG. We repeated the analysis in AD vs. LD healthy controls (HC). A minimum threshold of t > 2 and corrected p < .025 (Bonferroni) was employed.

RESULTS

We recruited 119 patients (44LGG, 75HGG). Hemispheric LI demonstrated 64/119AD and 55/119LD patients. The first VBM analysis demonstrated significantly increased cortical volume in AD patients in the right inferior frontal gyrus (IFG), right superior temporal gyrus (STG), right insula, right fusiform gyrus (FG), right precentral gyrus, right temporal-parietal junction, right posterior cingulate cortex (PCC), right hippocampus, right- and left cerebellum. AD patients with HGG showed the same areas of significantly increased cortical volume. AD patients with LGG displayed significantly increased cortical volume in right IFG, right STG, right insula, right FG, right anterior cingulate cortex, right PCC, right dorsal-lateral prefrontal cortex. HC showed no significant results.

CONCLUSION

Right-sided (atypical) language activations in patients with left-hemispheric gliomas are associated with areas of increased cortical volume. Additionally, default mode network nodes showed greater cortical volume in AD patients regardless of the tumor grade, supporting the idea of these cortices participating in the development of language plasticity.

The role of the hippocampus in statistical learning and language recovery in persons with post stroke aphasia

Although several studies have aimed for accurate predictions of language recovery in post stroke aphasia, individual language outcomes remain hard to predict. Large-scale prediction models are built using data from patients mainly in the chronic phase after stroke, although it is clinically more relevant to consider data from the acute phase. Previous research has mainly focused on deficits, i.e., behavioral deficits or specific brain damage, rather than compensatory mechanisms, i.e., intact cognitive skills or undamaged brain regions. One such unexplored brain region that might support language (re)learning in aphasia is the hippocampus, a region that has commonly been associated with an individual's learning potential, including statistical learning. This refers to a set of mechanisms upon which we rely heavily in daily life to learn a range of regularities across cognitive domains. Against this background, thirty-three patients with aphasia (22 males and 11 females, M = 69.76 years, SD = 10.57 years) were followed for 1 year in the acute (1-2 weeks), subacute (3-6 months) and chronic phase (9-12 months) post stroke. We evaluated the unique predictive value of early structural hippocampal measures for short-term and long-term language outcomes (measured by the ANELT). In addition, we investigated whether statistical learning abilities were intact in patients with aphasia using three different tasks: an auditory-linguistic and visual task based on the computation of transitional probabilities and a visuomotor serial reaction time task. Finally, we examined the association of individuals' statistical learning potential with acute measures of hippocampal gray and white matter. Using Bayesian statistics, we found moderate evidence for the contribution of left hippocampal gray matter in the acute phase to the prediction of long-term language outcomes, over and above information on the lesion and the initial language deficit (measured by the ScreeLing). Non-linguistic statistical learning in patients with aphasia, measured in the subacute phase, was intact at the group level compared to 23 healthy older controls (8 males and 15 females, M = 74.09 years, SD = 6.76 years). Visuomotor statistical learning correlated with acute hippocampal gray and white matter. These findings reveal that particularly left hippocampal gray matter in the acute phase is a potential marker of language recovery after stroke, possibly through its statistical learning ability.

Neural network based successor representations to form cognitive maps of space and language

How does the mind organize thoughts? The hippocampal-entorhinal complex is thought to support domain-general representation and processing of structural knowledge of arbitrary state, feature and concept spaces. In particular, it enables the formation of cognitive maps, and navigation on these maps, thereby broadly contributing to cognition. It has been proposed that the concept of multi-scale successor representations provides an explanation of the underlying computations performed by place and grid cells. Here, we present a neural network based approach to learn such representations, and its application to different scenarios: a spatial exploration task based on supervised learning, a spatial navigation task based on reinforcement learning, and a non-spatial task where linguistic constructions have to be inferred by observing sample sentences. In all scenarios, the neural network correctly learns and approximates the underlying structure by building successor representations. Furthermore, the resulting neural firing patterns are strikingly similar to experimentally observed place and grid cell firing patterns. We conclude that cognitive maps and neural network-based successor representations of structured knowledge provide a promising way to overcome some of the short comings of deep learning towards artificial general intelligence.

Cross-linguistic differences in case marking shape neural power dynamics and gaze behavior during sentence planning

Languages differ in how they mark the dependencies between verbs and arguments, e.g., by case. An eye tracking and EEG picture description study examined the influence of case marking on the time course of sentence planning in Basque and Swiss German. While German assigns an unmarked (nominative) case to subjects, Basque specifically marks agent arguments through ergative case. Fixations to agents and event-related synchronization (ERS) in the theta and alpha frequency bands, as well as desynchronization (ERD) in the alpha and beta bands revealed multiple effects of case marking on the time course of early sentence planning. Speakers decided on case marking under planning early when preparing sentences with ergative-marked agents in Basque, whereas sentences with unmarked agents allowed delaying structural commitment across languages. These findings support hierarchically incremental accounts of sentence planning and highlight how cross-linguistic differences shape the neural dynamics underpinning language use.

Oscillatory and Aperiodic Neural Activity Jointly Predict Language Learning

Memory formation involves the synchronous firing of neurons in task-relevant networks, with recent models postulating that a decrease in low-frequency oscillatory activity underlies successful memory encoding and retrieval. However, to date, this relationship has been investigated primarily with face and image stimuli; considerably less is known about the oscillatory correlates of complex rule learning, as in language. Furthermore, recent work has shown that nonoscillatory (1/ƒ) activity is functionally relevant to cognition, yet its interaction with oscillatory activity during complex rule learning remains unknown. Using spectral decomposition and power-law exponent estimation of human EEG data (17 females, 18 males), we show for the first time that 1/ƒ and oscillatory activity jointly influence the learning of word order rules of a miniature artificial language system. Flexible word-order rules were associated with a steeper 1/ƒ slope, whereas fixed word-order rules were associated with a shallower slope. We also show that increased theta and alpha power predicts fixed relative to flexible word-order rule learning and behavioral performance. Together, these results suggest that 1/ƒ activity plays an important role in higher-order cognition, including language processing, and that grammar learning is modulated by different word-order permutations, which manifest in distinct oscillatory profiles.

Understanding Language Reorganization With Neuroimaging: How Language Adapts to Different Focal Lesions and Insights Into Clinical Applications

When the language-dominant hemisphere is damaged by a focal lesion, the brain may reorganize the language network through functional and structural changes known as adaptive plasticity. Adaptive plasticity is documented for triggers including ischemic, tumoral, and epileptic focal lesions, with effects in clinical practice. Many questions remain regarding language plasticity. Different lesions may induce different patterns of reorganization depending on pathologic features, location in the brain, and timing of onset. Neuroimaging provides insights into language plasticity due to its non-invasiveness, ability to image the whole brain, and large-scale implementation. This review provides an overview of language plasticity on MRI with insights for patient care. First, we describe the structural and functional language network as depicted by neuroimaging. Second, we explore language reorganization triggered by stroke, brain tumors, and epileptic lesions and analyze applications in clinical diagnosis and treatment planning. By comparing different focal lesions, we investigate determinants of language plasticity including lesion location and timing of onset, longitudinal evolution of reorganization, and the relationship between structural and functional changes.

The influence of estradiol and progesterone on neurocognition during three phases of the menstrual cycle: Modulating factors

Estradiol is an ovarian steroid hormone that peaks shortly before ovulation and significantly affects various brain regions and neurotransmitter systems, with similar and differential effects with progesterone, another ovarian hormone. Studies investigating the neurocognitive processes during the menstrual cycle have focused on the early follicular phase (EFP) characterized by low estradiol and progesterone levels and the mid-luteal phase (MLP) with high estradiol and progesterone levels. However, most studies have failed to include the ovulatory phase, characterized by high estradiol and low progesterone levels. Given the various hormonal changes in the menstrual cycle, we revisited studies suggesting that the menstrual cycle did not affect verbal and spatial abilities and observed that many contain mixed results. Comparing these studies makes it possible to identify relevant modulating factors, such as sample size, participant age, accurate selection of days for testing, asymmetrical practice effects, genetic polymorphisms, and task difficulty. More robust findings are related to improved mental rotation capacity during EFP with challenging tasks and differences in brain activation among menstrual cycle phases during the execution of spatial and verbal tasks. During MLP, less robust findings were observed, possibly modulated by the complex effects of the two hormones on the brain. In conclusion, we propose that it is crucial to include all three menstrual cycle phases and consider these modulating factors to avoid confounding findings.

Effects of Linguistic Distance on Second Language Brain Activations in Bilinguals: An Exploratory Coordinate-Based Meta-Analysis

In this quantitative meta-analysis, we used the activation likelihood estimation (ALE) approach to address the effects of linguistic distance between first (L1) and second (L2) languages on language-related brain activations. In particular, we investigated how L2-related networks may change in response to linguistic distance from L1. Thus, we examined L2 brain activations in two groups of participants with English as L2 and either (i) a European language (European group, n = 13 studies) or (ii) Chinese (Chinese group, n = 18 studies) as L1. We further explored the modulatory effect of age of appropriation (AoA) and proficiency of L2. We found that, irrespective of L1-L2 distance-and to an extent-irrespective of L2 proficiency, L2 recruits brain areas supporting higher-order cognitive functions (e.g., cognitive control), although with group-specific differences (e.g., the insula region in the European group and the frontal cortex in the Chinese group). The Chinese group also selectively activated the parietal lobe, but this did not occur in the subgroup with high L2 proficiency. These preliminary results highlight the relevance of linguistic distance and call for future research to generalize findings to other language pairs and shed further light on the interaction between linguistic distance, AoA, and proficiency of L2.

Working Memory and Language Contribution to Verbal Learning and Memory in Drug-Resistant Unilateral Focal Temporal Lobe Epilepsy

We aimed to investigate the working memory (WM) and language separate contributions to verbal learning and memory in patients with unilateral drug-resistant temporal lobe epilepsy (drTLE); additionally, we explored the mediating role of WM on the relationship between the number of antiepileptic drugs (AEDs) and short-term verbal memory. We retrospectively enrolled 70 patients with left (LTLE; n = 44) and right (RTLE; n = 26) drTLE. About 40 similar (age and education) healthy controls were used to determine impairments of groups at WM, language (naming and verbal fluency), and verbal learning and memory (five trials list-learning, story memory-immediate recall). To disentangle the effect of learning from the short-term memory, we separately analyzed performances at the first trial, last trial, and delayed-recall list-learning measures, in addition to the total learning capacity (the sum of the five trials). Correlation and regression analyses were used to assess the contribution of potential predictors while controlling for main clinical and demographic variables, and ascertain the mediating role of WM. All patients were impaired at WM and story memory, whereas only LTLE showed language and verbal learning deficits. In RTLE, language was the unique predictor for the most verbal learning performances, whereas WM predicted the results at story memory. In LTLE, WM was the sole predictor for short-term verbal learning (list-learning capacity; trial 1) and mediated the interaction between AED number and the performance at these measures, whereas language predicted the delayed-recall. Finally, WM confounded the performance at short-term memory in both groups, although at different measures. WM is impaired in drTLE and contributes to verbal memory and learning deficits in addition to language, mediating the relationship between AED number and short-term verbal memory in LTLE. Clinicians should consider this overlap when interpreting poor performance at verbal learning and memory in drTLE.

Missing links: The functional unification of language and memory (L∪M)

The field of neurocognition is currently undergoing a significant change of perspective. Traditional neurocognitive models evolved into an integrative and dynamic vision of cognitive functioning. Dynamic integration assumes an interaction between cognitive domains traditionally considered to be distinct. Language and declarative memory are regarded as separate functions supported by different neural systems. However, they also share anatomical structures (notably, the inferior frontal gyrus, the supplementary motor area, the superior and middle temporal gyrus, and the hippocampal complex) and cognitive processes (such as semantic and working memory) that merge to endorse our quintessential daily lives. We propose a new model, "L∪M" (i.e., Language/union/Memory), that considers these two functions interactively. We fractionated language and declarative memory into three fundamental dimensions or systems ("Receiver-Transmitter", "Controller-Manager" and "Transformer-Associative" Systems), that communicate reciprocally. We formalized their interactions at the brain level with a connectivity-based approach. This new taxonomy overcomes the modular view of cognitive functioning and reconciles functional specialization with plasticity in neurological disorders.

Accelerated intermittent theta-burst stimulation broadly ameliorates symptoms and cognition in Alzheimer's disease: A randomized controlled trial

BACKGROUND

Deficits in associative memory (AM) are the earliest and most prominent feature of Alzheimer's disease (AD) and demonstrate a clear cause of distress for patients and their families.

OBJECTIVE

The present study aimed to determine AM enhancements following accelerated intermittent theta-burst stimulation (iTBS) in patients with AD.

METHODS

In a randomized, double-blind, sham-controlled design, iTBS was administered to the left dorsolateral prefrontal cortex (DLPFC) of patients with AD for 14 days. Measurements included AM (primary outcome) and a comprehensive neuropsychological battery. Patients were evaluated at baseline, following the intervention (week 2), and 8 weeks after treatment cessation (week 10).

RESULTS

Sixty patients with AD were initially enrolled; 47 completed the trial. The active group displayed greater AM improvements compared with the sham group at week 2 (P = 0.003), which was sustained at week 10. Furthermore, higher Mini-Mental State Examination (MMSE) scores at baseline were associated with greater AM improvements at weeks 2 and 10. For the independent iTBS group, this correlation predicted improvements in AM (P < 0.001) and identified treatment responders with 92% accuracy. Most of the neuropsychological tests were markedly improved in the active group. In particular, the Montreal Cognitive Assessment and MMSE in the active group increased by 2.8 and 2.3 points, respectively, at week 2, while there was no marked change in the sham group.

CONCLUSION

In the present study, accelerated iTBS of the DLPFC demonstrated an effective and well-tolerated complementary treatment for patients with AD, especially for individuals with relatively high MMSE scores.

Why language survives as the dominant communication tool: A neurocognitive perspective

By focusing on the contributions of subcortical structures, our commentary suggests that the functions of the hippocampus underlying "displacement," a feature enabling humans to communicate things and situations that are remote in space and time, make language more effective at social bonding. Based on the functions of the basal ganglia and hippocampus, evolutionary trajectory of the subcomponents of music and language in different species will also be discussed.

Did Dog Domestication Contribute to Language Evolution?

Different factors seemingly account for the emergence of present-day languages in our species. Human self-domestication has been recently invoked as one important force favoring language complexity mostly via a cultural mechanism. Because our self-domestication ultimately resulted from selection for less aggressive behavior and increased prosocial behavior, any evolutionary or cultural change impacting on aggression levels is expected to have fostered this process. Here, we hypothesize about a parallel domestication of humans and dogs, and more specifically, about a positive effect of our interaction with dogs on human self-domestication, and ultimately, on aspects of language evolution, through the mechanisms involved in the control of aggression. We review evidence of diverse sort (ethological mostly, but also archeological, genetic, and physiological) supporting such an effect and propose some ways of testing our hypothesis.

Interactive mapping of language and memory with the GE2REC protocol

Previous studies have highlighted the importance of considering cognitive functions from a dynamic and interactive perspective and multiple evidence was brought for a language and memory interaction. In this study performed with healthy participants, we present a new protocol entitled GE2REC that interactively accesses the neural representation of language-and-memory network. This protocol consists of three runs related to each other, providing a link between tasks, in order to assure an interactive measure of linguistic and episodic memory processes. GE2REC consists of a sentence generation (GE) in the auditory modality and two recollecting (2REC) memory tasks, one recognition performed in the visual modality, and another one recall performed in the auditory modality. Its efficiency was evaluated in 20 healthy volunteers using a 3T MR imager. Our results corroborate the ability of GE2REC to robustly activate fronto-temporo-parietal language network as well as temporal mesial, prefrontal and parietal cortices in encoding during sentence generation and recognition. GE2REC is useful because it: (a) requires simultaneous and interactive language-and-memory processes and jointly maps their neural basis; (b) explores encoding and retrieval, managing to elicit activation of mesial temporal structures; (c) is easy to perform, hence being suitable for more restrictive settings, and (d) has an ecological dimension of tasks and stimuli. GE2REC may be useful for studying neuroplasticity of cognitive functions, especially in patients with temporal lobe epilepsy who show reorganization of both language and memory networks. Overall, GE2REC can provide valuable information in terms of the practical foundation of exploration language and memory interconnection.

Reconfiguration dynamics of a language-and-memory network in healthy participants and patients with temporal lobe epilepsy

Current theoretical frameworks suggest that human behaviors are based on strong and complex interactions between cognitive processes such as those underlying language and memory functions in normal and neurological populations. We were interested in assessing the dynamic cerebral substrate of such interaction between language and declarative memory, as the composite function, in healthy controls (HC, N = 19) and patients with temporal lobe epilepsy (TLE, N = 16). Our assumption was that the language and declarative memory integration is based on a language-and-memory network (LMN) that is dynamic and reconfigures according to task demands and brain status. Therefore, we explored two types of LMN dynamics, a state reconfiguration (intrinsic resting-state compared to extrinsic state assessed with a sentence recall task) and a reorganization of state reconfiguration (TLE compared to HC). The dynamics was evaluated in terms of segregation (community or module detection) and integration (connector hubs). In HC, the level of segregation was the same in both states and the mechanism of LMN state reconfiguration was shown through module change of key language and declarative memory regions with integrative roles. In TLE patients, the reorganization of LMN state reconfiguration was reflected in segregation increase and extrinsic modules that were based on shorter-distance connections. While lateral and mesial temporal regions enabled state reconfiguration in HC, these regions showed reduced flexibility in TLE. We discuss our results in a connectomic perspective and propose a dynamic model of language and declarative memory functioning. We claim that complex and interactive cognitive functions, such as language and declarative memory, should be investigated dynamically, considering the interaction between cognitive networks.

Does rehearsal matter? Left anterior temporal alpha and theta band changes correlate with the beneficial effects of rehearsal on working memory

Rehearsal during working memory (WM) maintenance is assumed to facilitate retrieval. Less is known about how rehearsal modulates WM delay activity. In the present study, 44 participants completed a Sternberg Task with either intact novel scenes or phase-scrambled scenes, which had similar color and spatial frequency but lacked semantic content. During the rehearsal condition participants generated a descriptive label during encoding and covertly rehearsed during the delay period. During the suppression condition participants did not generate a label during encoding and suppressed (repeated "the") during the delay period. This was easy in the former (novel scenes) but more difficult in the later condition (phase-scrambled scenes) where scenes lacked semantic content. Behavioral performance and EEG delay activity was analyzed as a function of maintenance strategy. Performance during WM revealed a benefit of rehearsal for phase-scrambled but not intact scenes. Examination of the absolute amplitude revealed three underlying sources of activity for rehearsal, including the left anterior temporal (ATL) and left and midline parietal regions. Increases in alpha and theta activity in ATL were correlated with improvement in performance on WM with rehearsal only when labeling was not automatic (e.g., phase-scrambled scenes), which may reflect differences in labeling and rehearsal (i.e., semantic associations vs. shallow labels). We conclude that rehearsal only benefits memory for visual stimuli that lack semantic information, and that this is correlated with changes in alpha and theta rhythms.

The contributions of the left hippocampus and bilateral inferior parietal lobule to form-meaning associative learning

Existing studies have identified crucial roles for the hippocampus and a distributed set of cortical regions (e.g., the inferior parietal cortex) in learning novel words. Nevertheless, researchers have not clearly determined how the hippocampus and cortical regions dynamically interact during novel word learning, especially during form-meaning associative learning. As a method to address this question, we used an online learning paradigm and representational similarity analysis to explore the contributions of the hippocampus and neocortex to form-meaning associative learning. Twenty-nine native Chinese college students were recruited to learn 30 form-meaning pairs, which were repeated 7 times during fMRI scan. Form-meaning associative learning elicited activations in a wide neural network including regions required for word processing (i.e., the bilateral inferior frontal gyrus and the occipitotemporal cortex), regions required for encoding (i.e., the bilateral parahippocampus and hippocampus), and regions required for cognitive control (i.e., the anterior cingulate cortex and dorsolateral prefrontal cortex). More importantly, our study revealed the differential roles of the left hippocampus and bilateral inferior parietal lobule (IPL) in form-meaning associative learning. Specifically, higher pattern similarity in the bilateral IPL in the early learning phase (repetitions 1 to 3) was related to better learning performance, while higher pattern similarity in the left hippocampus in the late learning phase (repetitions 5 to 7) was associated with better learning performance. These findings indicate that the hippocampus and cortical regions (e.g., the IPL) contribute to form-meaning learning in different stages.

Resting-state hippocampal networks related to language processing reveal unique patterns in temporal lobe epilepsy

OBJECTIVE

Patients with temporal lobe epilepsy (TLE) commonly experience a broad range of language impairments. These deficits are thought to arise from repeated seizure activity that damages language regions. However, connectivity between the seizure onset region in the hippocampus and regions related to language processing has rarely been studied, and could also have a strong impact on language function. The purpose of this study was to use resting-state functional connectivity (FC) measures to assess hippocampal network patterns and their relation to language abilities in patients with right TLE (RLTE), left TLE (LTLE), and healthy controls.

METHODS

Presurgical resting-state 3T functional MRI data were acquired from 40 patients with mesial TLE (27 RTLE, 13 LTLE) and 54 controls. The regions of interest were the anterior and posterior bilateral hippocampi and eleven regions grouped by frontal or temporo-parietal locations, including large areas of language-related cortex. FC values were computed with the right/left anterior and posterior hippocampi as the seeds and frontal and temporo-parietal regions as targets. Resting-state lateralization indices were also calculated (LI-Rest), and all FC measures were correlated to neuropsychological language scores and measures related to manifestation of epilepsy including age of onset, duration of disease, monthly seizure frequency, and hippocampal volume.

RESULTS

We found significant group differences between the anterior hippocampi and temporo-parietal regions closest to the seizure focus, in which RTLE and LTLE showed stronger connectivity to their contralateral hippocampus, while controls showed similar connectivity to both hippocampi. In addition, LI-Rest demonstrated significantly more right lateralization in LTLE compared to RTLE for temporo-parietal regions only. In LTLE, we found significant associations between stronger hippocampal network resting-state FC and later age of onset and decreased left anterior hippocampal volume.

SIGNIFICANCE

The results of our study indicate that the presence of TLE impacts hippocampal-temporo-parietal networks relevant to language processing.

Deep Relational Reasoning for the Prediction of Language Impairment and Postoperative Seizure Outcome Using Preoperative DWI Connectome Data of Children With Focal Epilepsy

Prolonged seizures in children with focal epilepsy (FE) may impair language functions and often reoccur after surgical intervention. This study is aimed at developing a novel deep relational reasoning network to investigate whether conventional diffusion-weighted imaging connectome analysis can be improved when predicting expressive and receptive scores of preoperative language impairments and classifying postoperative seizure outcomes (seizure freedom or recurrence) in individual FE children. To deeply reason the dependencies of axonal connections that are sparsely distributed in the whole brain, this study proposes the "dilated CNN + RN", a dilated convolutional neural network (CNN) combined with a relation network (RN). The performance of the dilated CNN + RN was evaluated using whole brain connectome data from 51 FE children. It was found that when compared with other state-of-the-art algorithms, the dilated CNN + RN led to an average improvement of 90.2% and 97.3% in predicting expressive and receptive language scores, and 2.2% and 4% improvement in classifying seizure freedom and seizure recurrence, respectively. These improvements were independent of the prefixed connectome densities. Also, the dilated CNN + RN could provide an explainable artificial intelligence (AI) model by computing gradient-based regression/classification activation maps. This mapping analysis revealed left superior-medial frontal cortex, bilateral hippocampi, and cerebellum as crucial hubs, facilitating important connections that were most predictive of language function and seizure refractoriness after surgery.

The limited role of hippocampal declarative memory in transient semantic activation during online language processing

Recent findings point to a role for hippocampus in the moment-by-moment processing of language, including the use and generation of semantic features in certain contexts. What role the hippocampus might play in the processing of semantic relations in spoken language comprehension, however, is unknown. Here we test patients with bilateral hippocampal damage and dense amnesia in order to examine the necessity of hippocampus for lexico-semantic mapping processes in spoken language understanding. In two visual-world eye-tracking experiments, we monitor eye movements to images that are semantically related to spoken words and sentences. We find no impairment in amnesia, relative to matched healthy comparison participants. These findings suggest, at least for close semantic links and simple language comprehension tasks, a lack of necessity for hippocampus in lexico-semantic mapping between spoken words and simple pictures.

The hippocampal region is necessary for text comprehension and memorization: a combined VBM/DTI study in neuropsychological patients

According to the Construction-Integration model (Kintsch 1988; Kintsch 1998), two forms of representation are activated during the reading and the comprehension of a text: 1) the text base, which includes semantic propositions and 2) the situation model, corresponding to the integration of the information contained in the text to the memories and knowledge of the reader. Functional neuroimaging studies in healthy subjects have shown that the text base is underpinned by frontal regions and lateral temporal regions whereas the situation model would rather depend on the posterior cingulate cortex, the precuneus and other regions depending on the dimension studied. However, the brain regions highlighted so far were only involved in comprehension and not necessary for this cognitive ability. For the first time, we explored the brain structures necessary to understand texts using a combined VBM/DTI approach in neuropsychological patients with whom we obtained comprehension scores (text base and situation model) after the reading of narrative texts. To our great surprise and contrary to our hypotheses, which were based on the results of functional neuroimaging studies, our own results show that it is the hippocampal region that is necessary to activate and memorize/remember the text base and the situation model. The highlighting of a link between the integrity of a portion of the uncinate fasciculus which is well known to play a role in semantic processing and the performance scores of the text base suggests that the hippocampal region is necessary not only for the retrieval of the text base and of the situation model thanks to episodic memory, but also for the activation of the text base during the reading and the comprehension of a text.

White matter pathways underlying Chinese semantic and phonological fluency in mild cognitive impairment

Neuroimaging evidence has suggested that Chinese-language processing differs from that of its alphabetic-language counterparts. However, the underlying white matter pathway correlations between semantic and phonological fluency in Chinese-language processing remain unknown. Thus, we investigated the differences between two verbal fluency tests on 50 participants with amnestic mild cognitive impairment (aMCI) and 36 healthy controls (HC) with respect to five groups (ventral and dorsal stream fibers, frontal-striatal fibers, hippocampal-related fibers, and the corpus callosum) of white matter microstructural integrity. Diffusion spectrum imaging was used. The results revealed a progressive reduction in advantage in semantic fluency relative to phonological fluency from HC to single-domain aMCI to multidomain aMCI. Common and dissociative white matter correlations between tests of the two types of fluency were identified. Both types of fluency relied on the corpus callosum and ventral stream fibers, semantic fluency relied on the hippocampal-related fibers, and phonological fluency relied on the dorsal stream and frontal-striatal fibers. The involvement of bilateral tracts of interest as well as the association with the corpus callosum indicate the uniqueness of Chinese-language fluency processing. Dynamic associations were noted between white matter tract involvement and performance on the two fluency tests in four time blocks. Overall, our findings suggest the clinical utility of verbal fluency tests in geriatric populations, and they elucidate both task-specific and language-specific brain-behavior associations.

Contributions of electrophysiology for identifying cortical language systems in patients with epilepsy

A crucial element of the surgical treatment of medically refractory epilepsy is to delineate cortical areas that must be spared in order to avoid clinically relevant neurological and neuropsychological deficits postoperatively. For each patient, this typically necessitates determining the language lateralization between hemispheres and language localization within hemisphere. Understanding cortical language systems is complicated by two primary challenges: the extent of the neural tissue involved and the substantial variability across individuals, especially in pathological populations. We review the contributions made through the study of electrophysiological activity to address these challenges. These contributions are based on the techniques of magnetoencephalography (MEG), intracerebral recordings, electrical-cortical stimulation (ECS), and the electrovideo analyses of seizures and their semiology. We highlight why no single modality alone is adequate to identify cortical language systems and suggest avenues for improving current practice.

Both activation and deactivation of functional networks support increased sentence processing costs

The research on the neural correlates underlying the language system has gradually moved away from the traditional Broca-Wernicke framework to a network perspective in the past 15 years. Language processing is found to be supported by the co-activation of both core and peripheral brain regions. However, the dynamic co-activation patterns of these brain regions serving different language functions remain to be fully revealed. The present functional magnetic resonance imaging (fMRI) study focused on sentence processing at different syntactic complexity levels to examine how the co-activation of different brain networks will be modulated by increased processing costs. Chinese relative clauses were used to probe the two dimensions of syntactic complexity: embeddedness (left-branching vs. center-embedded) and gap-filler dependency (subject-gap vs. object-gap) using the general linear model (GLM) approach, independent component analysis (ICA) and graph theoretical analysis. In contrast to localized activation revealed by the GLM approach, ICA identified more extensive networks both positively and negatively correlated with the task. We found that the posterior default mode network was anti-correlated to the gap-filler integration costs with increased deactivation for the left-branching object relative clauses compared to subject relative clauses, suggesting the involvement of this network in leveraging the cognitive resources based on the complexity level of the language task. Concurrent activation and deactivation of networks were found to be associated with the higher costs induced by center-embedding and its interaction with gap-filler integration. The graph theoretical analysis further unveiled that center-embeddedness imposed more attentional demand on the subject relative clause, as characterized by its higher degree and strength in the ventral attention network, and higher processing costs of syntactic reanalysis on the object relative clause, as characterized by increased intermodular connections of the language network with other networks. The results suggest that network activation and deactivation profiles are modulated by different dimensions of syntactic complexity to serve the higher demand of creating a coherent semantic representation.

Hippocampus plays a role in speech feedback processing

There is increasing evidence that the hippocampus is involved in language production and verbal communication, although little is known about its possible role. According to one view, hippocampus contributes semantic memory to spoken language. Alternatively, hippocampus is involved in the processing the (mis)match between expected sensory consequences of speaking and the perceived speech feedback. In the current study, we re-analysed functional magnetic resonance (fMRI) data of two overt picture-naming studies to test whether hippocampus is involved in speech production and, if so, whether the results can distinguish between a "pure memory" versus a "prediction" account of hippocampal involvement. In both studies, participants overtly named pictures during scanning while hearing their own speech feedback unimpededly or impaired by a superimposed noise mask. Results showed decreased hippocampal activity when speech feedback was impaired, compared to when feedback was unimpeded. Further, we found increased functional coupling between auditory cortex and hippocampus during unimpeded speech feedback, compared to impaired feedback. Finally, we found significant functional coupling between a hippocampal/supplementary motor area (SMA) interaction term and auditory cortex, anterior cingulate cortex and cerebellum during overt picture naming, but not during listening to one's own pre-recorded voice. These findings indicate that hippocampus plays a role in speech production that is in accordance with a "prediction" view of hippocampal functioning.

Cerebellar Theta and Beta Noninvasive Stimulation Rhythms Differentially Influence Episodic Memory versus Semantic Prediction

The human cerebellum is thought to interact with distributed brain networks to support cognitive abilities such as episodic memory and semantic prediction. Hippocampal and fronto-temporo-parietal networks that respectively support episodic memory versus semantic prediction have been associated with distinct endogenous oscillatory activity frequency bands: theta (∼3-8 Hz) versus beta (∼13-30 Hz) respectively. We sought to test whether it is possible to toggle cerebellar participation in episodic memory versus semantic prediction by noninvasively stimulating with theta versus beta rhythmic transcranial magnetic stimulation. In human subjects of both sexes, cerebellar theta stimulation improved episodic memory encoding but did not influence neural signals of semantic prediction, whereas beta stimulation of the same cerebellar location increased neural signals of semantic prediction but did not influence episodic memory encoding. This constitutes evidence for double dissociation of cerebellar contributions to semantic prediction versus episodic memory based on stimulation rhythm, supporting the hypothesis that the cerebellum can be biased to support these distinct cognitive abilities at the command of network-specific rhythmic activity.SIGNIFICANCE STATEMENT The cerebellum interacts with several distinct large-scale brain networks for cognitive function, but the factors governing selectivity of such interactions for particular functions are not fully understood. We tested the hypothesis that cerebellar contributions to cognition are guided by neural oscillations with function-specific frequency bands. We demonstrated that matching noninvasive stimulation to network-specific frequencies selectively enhanced episodic memory versus semantic prediction. These findings suggest that cerebellar contributions to cognitive networks are selected based on corresponding activity rhythms and could be used to develop cerebellar stimulation interventions for specific neurocognitive impairments.

Theta oscillations support the interface between language and memory

Recent evidence shows that hippocampal theta oscillations, usually linked to memory and navigation, are also observed during online language processing, suggesting a shared neurophysiological mechanism between language and memory. However, it remains to be established what specific roles hippocampal theta oscillations may play in language, and whether and how theta mediates the communication between the hippocampus and the perisylvian cortical areas, generally thought to support language processing. With whole-head magnetoencephalographic (MEG) recordings, the present study investigated these questions with two experiments. Using a violation paradigm, extensively used for studying neural underpinnings of different aspects of linguistic processing, we found increased theta power (4-8 ​Hz) in the hippocampal formation, when participants read a semantically incorrect vs. correct sentence ending. Such a pattern of results was replicated using different sentence stimuli in another cohort of participants. Importantly, no significant hippocampal theta power increase was found when participants read a semantically correct but syntactically incorrect sentence ending vs. a correct sentence ending. These findings may suggest that hippocampal theta oscillations are specifically linked to lexical-semantic related processing, and not general information processing in sentence reading. Furthermore, we found significantly transient theta phase coupling between the hippocampus and the left superior temporal gyrus, a hub area of the cortical network for language comprehension. This transient theta phase coupling may provide an important channel that links the memory and language systems for the generation of sentence meaning. Overall, these findings help specify the role of hippocampal theta in language, and provide a novel neurophysiological mechanism at the network level that may support the interface between memory and language.

Electrocorticography reveals spatiotemporal neuronal activation patterns of verbal fluency in patients with epilepsy

Verbal fluency is commonly used to evaluate cognitive dysfunction in a variety of neuropsychiatric diseases, yet the neurobiology underlying performance of this task is incompletely understood. Electrocorticography (ECoG) provides a unique opportunity to investigate temporal activation patterns during cognitive tasks with high spatial and temporal precision. We used ECoG to study high gamma activity (HGA) patterns in patients undergoing presurgical evaluation for intractable epilepsy as they completed an overt, free-recall verbal fluency task. We examined regions demonstrating changes in HGA during specific timeframes relative to speech onset. Early pre-speech high gamma activity was present in left frontal regions during letter fluency and in bifrontal regions during category fluency. During timeframes typically associated with word planning, a distributed network was engaged including left inferior frontal, orbitofrontal and posterior temporal regions. Peri-Rolandic activation was observed during speech onset, and there was post-speech activation in the bilateral posterior superior temporal regions. Based on these observations in the context of prior studies, we propose a model of neocortical activity patterns underlying verbal fluency.

Altered resting-state functional connectivity in young children at familial high risk for psychotic illness: A preliminary study

Multiple lines of evidence suggest that illness development in schizophrenia and other psychotic disorders predates the first psychotic episode by many years. In this study, we examined a sample of 15 pre-adolescent children, ages 7 through 12 years, who are at familial high-risk (FHR) because they have a parent or sibling with a history of schizophrenia or related psychotic disorder. Using multi-voxel pattern analysis (MVPA), a data-driven fMRI analysis, we assessed whole-brain differences in functional connectivity in the FHR sample as compared to an age- and sex-matched control (CON) group of 15 children without a family history of psychosis. MVPA analysis yielded a single cluster in right posterior superior temporal gyrus (pSTG/BA 22) showing significant group-differences in functional connectivity. Post-hoc characterization of this cluster through seed-to-voxel analysis revealed mostly reduced functional connectivity of the pSTG seed to a set of language and default mode network (DMN) associated brain regions including Heschl's gyrus, inferior temporal gyrus extending into fusiform gyrus, (para)hippocampus, thalamus, and a cerebellar cluster encompassing mainly Crus I/II. A height-threshold of whole-brain p < .001 (two-sided), and FDR-corrected cluster-threshold of p < .05 (non-parametric statistics) was used for post-hoc characterization. These findings suggest that abnormalities in functional communication in a network encompassing right STG and associated brain regions are present before adolescence in at-risk children and may be a risk marker for psychosis. Subsequent changes in this functional network across development may contribute to either disease manifestation or resilience in children with a familial vulnerability for psychosis.

Semantic Memory and the Hippocampus: Revisiting, Reaffirming, and Extending the Reach of Their Critical Relationship

Since Tulving proposed a distinction in memory between semantic and episodic memory, considerable effort has been directed towards understanding their similar and unique features. Of particular interest has been the extent to which semantic and episodic memory have a shared dependence on the hippocampus. In contrast to the definitive evidence for the link between hippocampus and episodic memory, the role of the hippocampus in semantic memory has been a topic of considerable debate. This debate stems, in part, from highly variable reports of new semantic memory learning in amnesia ranging from profound impairment to full preservation, and various degrees of deficit and ability in between. More recently, a number of significant advances in experimental methods have occurred, alongside new provocative data on the role of the hippocampus in semantic memory, making this an ideal moment to revisit this debate, to re-evaluate data, methods, and theories, and to synthesize new findings. In line with these advances, this review has two primary goals. First, we provide a historical lens with which to reevaluate and contextualize the literature on semantic memory and the hippocampus. The second goal of this review is to provide a synthesis of new findings on the role of the hippocampus and semantic memory. With the perspective of time and this critical review, we arrive at the interpretation that the hippocampus does indeed make necessary contributions to semantic memory. We argue that semantic memory, like episodic memory, is a highly flexible, (re)constructive, relational and multimodal system, and that there is value in developing methods and materials that fully capture this depth and richness to facilitate comparisons to episodic memory. Such efforts will be critical in addressing questions regarding the cognitive and neural (inter)dependencies among forms of memory, and the role that these forms of memory play in support of cognition more broadly. Such efforts also promise to advance our understanding of how words, concepts, and meaning, as well as episodes and events, are instantiated and maintained in memory and will yield new insights into our two most quintessentially human abilities: memory and language.

Lesion-Specific Language Network Alterations in Temporal Lobe Epilepsy

BACKGROUND AND PURPOSE

Temporal lobe epilepsy, structural or nonlesional, may negatively affect language function. However, little is known about the lesion-specific influence on language networks. We hypothesized that different epileptogenic lesions are related to distinct alterations in the functional language connectome detected by fMRI.

MATERIALS AND METHODS

One hundred one patients with epilepsy due to mesiotemporal sclerosis (21 left, 22 right), low-grade mesiotemporal tumors (12 left), or nonlesional temporal lobe epilepsy (22 left, 24 right) and 22 healthy subjects performed 3T task-based language fMRI. Task-based activation maps (laterality indices) and functional connectivity analysis (global and connectivity strengths between language areas) were correlated with language scores.

RESULTS

Laterality indices based on fMRI activation maps failed to discriminate among patient groups. Functional connectivity analysis revealed the most extended language network alterations in left mesiotemporal sclerosis (involving the left temporal pole, left inferior frontal gyrus, and bilateral premotor areas). The other patient groups showed less extended but also predominantly ipsilesional network changes compared with healthy controls. Left-to-right hippocampal connectivity strength correlated positively with naming function (P = .01), and connectivity strength between the left Wernicke area and the left hippocampus was linked to verbal fluency scores (P = .01) across all groups.

CONCLUSIONS

Different pathologies underlying temporal lobe epilepsy are related to distinct alterations of the functional language connectome visualized by fMRI functional connectivity analysis. Network analysis allows new insights into language organization and provides possible imaging biomarkers for language function. These imaging findings emphasize the importance of a personalized treatment strategy in patients with epilepsy.

Why Brain Oscillations Are Improving Our Understanding of Language

We explore the potential that brain oscillations have for improving our understanding of how language develops, is processed in the brain, and initially evolved in our species. The different synchronization patterns of brain rhythms can account for different perceptual and cognitive functions, and we argue that this includes language. We aim to address six distinct questions—the What, How, Where, Who, Why, and When questions—pertaining to oscillatory investigations of language. Language deficits found in clinical conditions like autism, schizophrenia and dyslexia can be satisfactorily construed in terms of an abnormal, disorder-specific pattern of brain rhythmicity. Lastly, an eco-evo-devo approach to language is defended with explicit reference to brain oscillations, embracing a framework that considers language evolution to be the result of a changing environment surrounding developmental paths of the primate brain.

Language, Memory, and Mental Time Travel: An Evolutionary Perspective

Language could not exist without memory, in all its forms: working memory for sequential production and understanding, implicit memory for grammatical rules, semantic memory for knowledge, and episodic memory for communicating personal experience. Episodic memory is part of a more general capacity for mental travel both forward and backward in time, and extending even into fantasy and stories. I argue that the generativity of mental time travel underlies the generativity of language itself, and could be the basis of what Chomsky calls I-language, or universal grammar (UG), a capacity for recursive thought independent of communicative language itself. Whereas Chomsky proposed that I-language evolved in a single step well after the emergence of Homo sapiens, I suggest that generative imagination, extended in space and time, has a long evolutionary history, and that it was the capacity to share internal thoughts, rather than the nature of the thoughts themselves, that more clearly distinguishes humans from other species.

Relationship between neuronal network architecture and naming performance in temporal lobe epilepsy: A connectome based approach using machine learning

Impaired confrontation naming is a common symptom of temporal lobe epilepsy (TLE). The neurobiological mechanisms underlying this impairment are poorly understood but may indicate a structural disorganization of broadly distributed neuronal networks that support naming ability. Importantly, naming is frequently impaired in other neurological disorders and by contrasting the neuronal structures supporting naming in TLE with other diseases, it will become possible to elucidate the common systems supporting naming. We aimed to evaluate the neuronal networks that support naming in TLE by using a machine learning algorithm intended to predict naming performance in subjects with medication refractory TLE using only the structural brain connectome reconstructed from diffusion tensor imaging. A connectome-based prediction framework was developed using network properties from anatomically defined brain regions across the entire brain, which were used in a multi-task machine learning algorithm followed by support vector regression. Nodal eigenvector centrality, a measure of regional network integration, predicted approximately 60% of the variance in naming. The nodes with the highest regression weight were bilaterally distributed among perilimbic sub-networks involving mainly the medial and lateral temporal lobe regions. In the context of emerging evidence regarding the role of large structural networks that support language processing, our results suggest intact naming relies on the integration of sub-networks, as opposed to being dependent on isolated brain areas. In the case of TLE, these sub-networks may be disproportionately indicative naming processes that are dependent semantic integration from memory and lexical retrieval, as opposed to multi-modal perception or motor speech production.

Diurnal Cortisol Dynamics, Perceived Stress, and Language Production in Aphasia

Purpose The current study investigated diurnal cortisol dynamics in adults with and without aphasia, along with subjective reports of stress and measures of language production. Dysregulation of cortisol, a common biomarker of stress, is associated with cognitive dysfunction in different clinical populations. However, little is known about the consequences of stress-induced cortisol disturbances for stroke survivors, including those with aphasia. Method Nineteen participants with aphasia and 14 age-matched neurotypical adults were tested. Saliva samples were collected from participants to assess the cortisol awakening response, a marker of the integrity of the hypothalamic-pituitary-adrenal (HPA) axis. Participants also completed 2 subjective stress questionnaires. Language was evaluated using 3 short, picture description narratives, analyzed for discourse (dys)fluency and productivity markers. Results In contrast to neurotypical participants, adults with aphasia did not show the predictable cortisol awakening response. Participants with aphasia also showed an unusual heightened level of cortisol upon awakening. Additionally, neurotypical participants demonstrated an association between intact language performance and the cortisol awakening response, whereas the participants with aphasia did not, although they did perceive the language tasks as stressful. Conclusion This study indicates that the functionality of the HPA axis, as indexed by cortisol, contributes to optimal language performance in healthy adults. The absence of an awakening response among participants with aphasia suggests that stroke leads to dysregulation of the HPA axis, although the degree to which this impairment affects language deficits in this population requires further investigation.

Peptide Sharing Between Viruses and DLX Proteins: A Potential Cross-Reactivity Pathway to Neuropsychiatric Disorders

The present study seeks to determine potential associations between viral infections and neuropsychiatric diseases. To address this issue, we investigated the peptide commonalities between viruses that have been related to psychiatric and neurological disorders—such as rubella, human immunodeficiency virus, and herpesviruses—and human distal-less homeobox (DLX) proteins expressed in developing brain—namely, DLX1, DLX2, DLX5, and DLX6. Peptide matching analyses revealed a high degree of pentapeptide sharing. From an immunological perspective, this overlap is relevant because pentapeptides are endowed with immunogenicity and antigenicity—that is, they are immune determinants. Moreover, infection-induced immune cross-reactions might have functional, spatial, and temporal implications related to the functions and expression patterns of DLX1 and DLX5 in the fetal and adult human brain. In sum, our data support the hypothesis that viral infections may be linked to neuropsychiatric diseases through autoimmune cross-reactions caused by molecular mimicry between viral proteins and brain-specific DLX self-antigens.

Sleep-Dependent Memory Consolidation and Incremental Sentence Comprehension: Computational Dependencies during Language Learning as Revealed by Neuronal Oscillations

We hypothesize a beneficial influence of sleep on the consolidation of the combinatorial mechanisms underlying incremental sentence comprehension. These predictions are grounded in recent work examining the effect of sleep on the consolidation of linguistic information, which demonstrate that sleep-dependent neurophysiological activity consolidates the meaning of novel words and simple grammatical rules. However, the sleep-dependent consolidation of sentence-level combinatorics has not been studied to date. Here, we propose that dissociable aspects of sleep neurophysiology consolidate two different types of combinatory mechanisms in human language: sequence-based (order-sensitive) and dependency-based (order-insensitive) combinatorics. The distinction between the two types of combinatorics is motivated both by cross-linguistic considerations and the neurobiological underpinnings of human language. Unifying this perspective with principles of sleep-dependent memory consolidation, we posit that a function of sleep is to optimize the consolidation of sequence-based knowledge (the when) and the establishment of semantic schemas of unordered items (the what) that underpin cross-linguistic variations in sentence comprehension. This hypothesis builds on the proposal that sleep is involved in the construction of predictive codes, a unified principle of brain function that supports incremental sentence comprehension. Finally, we discuss neurophysiological measures (EEG/MEG) that could be used to test these claims, such as the quantification of neuronal oscillations, which reflect basic mechanisms of information processing in the brain.