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

Hippocampus supports long-term maintenance of language representations: Evidence of impaired collocation knowledge in amnesia

Traditional systems consolidation theories of memory suggest that the role of the hippocampus in maintaining memory representations diminishes over time, with learned information eventually becoming fully independent of the hippocampus. Knowledge of collocations in one's native (L1) language are acquired during development and are solidly acquired by adulthood. Remote semantic knowledge of collocations might therefore be expected to be resistant to hippocampal pathology. Patients with hippocampal damage and severe anterograde amnesia completed two tasks testing English collocation knowledge originally designed for use with English language learners. Patients with hippocampal damage demonstrated impairments in recognition of common English collocations, despite a lifetime of language experience (including postsecondary education) prior to sustaining this damage. These results suggest the hippocampus contributes to the long-term maintenance of linguistic representations and provides a challenge to traditional consolidation views of memory and an extension of newer theories to include a role for the hippocampus in maintaining semantic memory.

Midlife dynamics of white matter architecture in lexical production

We aimed to examine the white matter changes associated with lexical production difficulties, beginning in midlife with increased naming latencies. To delay lexical production decline, middle-aged adults may rely on domain-general and language-specific compensatory mechanisms proposed by the LARA model (Lexical Access and Retrieval in Aging). However, the white matter changes supporting these mechanisms remains largely unknown. Using data from the CAMCAN cohort, we employed an unsupervised and data-driven methodology to examine the relationships between diffusion-weighted imaging and lexical production. Our findings indicate that midlife is marked by alterations in brain structure within distributed dorsal, ventral, and anterior cortico-subcortical networks, marking the onset of lexical production decline around ages 53-54. Middle-aged adults may initially adopt a "semantic strategy" to compensate for lexical production challenges, but this strategy seems compromised later (ages 55-60) as semantic control declines. These insights underscore the interplay between domain-general and language-specific processes in the trajectory of lexical production performance in healthy aging and hint at potential biomarkers for language-related neurodegenerative pathologies.

BOLDly Going Where Few Researchers Have Gone Before-Leveraging Language-Related Hippocampal Activations to Predict Postoperative Memory Decline

Hippocampal Activations Obtained During Language fMRI Tasks: A Complementary Tool for Predicting Postoperative Memory Prognosis Salleles E, Samson S, Denos M, Mere M, Lehericy S, Herlin B, Dupont S. Epilepsy Res . 2024;205:107405. doi: 10.1016/j.eplepsyres . 2024.107405. PMID: 39002388. In medial temporal lobe epilepsy (MTLE), the benefits of surgery must be balanced against the risk of postoperative memory decline. Prediction of postoperative outcomes based on functional magnetic resonance imaging (fMRI) tasks is increasingly common but remains uncertain. The aim of this retrospective study was to determine whether hippocampal activations elicited by fMRI language tasks could enhance or refine memory fMRI in MTLE patient candidates to surgery. Forty-six patients were included: 30 right and 16 left MTLE, mostly with hippocampal sclerosis. Preoperative assessment included neuropsychological tests and fMRI with language (syntactic verbal fluency) and memory tasks (encoding, delayed, and immediate recognition of images of objects). Thirty patients underwent surgery and had neuropsychological evaluations 1 year after surgery. Worsening was defined as a degradation of more than 10% in postoperative forgetting scores compared to preoperative scores in verbal, nonverbal and global memory. Memory fMRI had the best sensitivity with hippocampal activations obtained in 95% of patients, versus 65% with language fMRI. Considering the patients who elicited a hippocampal activation, language fMRI led to 80%, 65% and 85% of correct predictions for respectively global, verbal and nonverbal memory (vs 71%, 64%, and 68% with memory fMRI). Memory and language fMRI predictions outperformed those made by neuropsychological tests. In summary, language fMRI was less sensitive than memory fMRI to elicit hippocampal activations but when it did, the proportion of correct memory predictions was better. Moreover, it proved to be an independent predictive factor regardless of the side of the epileptic focus. Given the ease of setting up a language task in fMRI, we recommend the systematic combination of memory and language tasks to predict the postoperative memory outcome of MTLE patients undergoing epilepsy surgery.

Blood-derived microRNAs are related to cognitive domains in the general population

INTRODUCTION

Blood-derived microRNAs (miRNAs) are potential candidates for detecting and preventing subclinical cognitive dysfunction. However, replication of previous findings and identification of novel miRNAs associated with cognitive domains, including their relation to brain structure and the pathways they regulate, are still lacking.

METHODS

We examined blood-derived miRNAs and miRNA co-expression clusters in relation to cognitive domains, structural magnetic resonance imaging measures, target gene expression, and genetic variants in 2869 participants of a population-based cohort.

RESULTS

Five previously identified and 14 novel miRNAs were associated with cognitive domains. Eleven of these were also associated with cortical thickness and two with hippocampal volume. Multi-omics analysis showed that certain identified miRNAs were genetically influenced and regulated genes in pathways like neurogenesis and synapse assembly.

DISCUSSION

We identified miRNAs associated with cognitive domains, brain regions, and neuronal processes affected by aging and neurodegeneration, making them promising candidate blood-based biomarkers or therapeutic targets of subclinical cognitive dysfunction.

HIGHLIGHTS

We investigated the association of blood-derived microRNAs with cognitive domains. Five previously identified and 14 novel microRNAs were associated with cognition. Eleven cognition-related microRNAs were also associated with cortical thickness. Identified microRNAs were linked to genes associated with neuronal functions. Results provide putative biomarkers or therapeutic targets of cognitive aging.

Hippocampal activations obtained during language fMRI tasks: A complementary tool for predicting postoperative memory prognosis

In medial temporal lobe epilepsy (MTLE), the benefits of surgery must be balanced against the risk of post-operative memory decline. Prediction of postoperative outcomes based on functional magnetic resonance imaging (fMRI) tasks is increasingly common but remains uncertain. The aim of this retrospective study was to determine whether hippocampal activations elicited by fMRI language tasks could enhance or refine memory fMRI in MTLE patients candidates to surgery. Forty-six patients were included: 30 right and 16 left MTLE, mostly with hippocampal sclerosis. Preoperative assessment included neuropsychological tests and fMRI with language (syntactic verbal fluency) and memory tasks (encoding, delayed, and immediate recognition of images of objects). Thirty patients underwent surgery and had neuropsychological evaluations one year after surgery. Worsening was defined as a degradation of more than 10 % in postoperative forgetting scores compared to preoperative scores in verbal, non-verbal and global memory. Memory fMRI had the best sensitivity with hippocampal activations obtained in 95 % of patients, versus 65 % with language fMRI. Considering the patients who elicited an hippocampal activation, language fMRI led to 80 %, 65 % and 85 % of correct predictions for respectively global, verbal and non verbal memory (versus 71 %, 64 % and 68 % with memory fMRI). Memory and language fMRI predictions outperformed those made by neuropsychological tests. In summary, language fMRI was less sensitive than memory fMRI to elicit hippocampal activations but when it did, the proportion of correct memory predictions was better. Moreover, it proved to be an independent predictive factor regardless of the side of the epileptic focus. Given the ease of setting up a language task in fMRI, we recommend the systematic combination of memory and language tasks to predict the post-operative memory outcome of MTLE patients undergoing epilepsy surgery.

Identifying novel data-driven subgroups in congenital heart disease using multi-modal measures of brain structure

Individuals with congenital heart disease (CHD) have an increased risk of neurodevelopmental impairments. Given the hypothesized complexity linking genomics, atypical brain structure, cardiac diagnoses and their management, and neurodevelopmental outcomes, unsupervised methods may provide unique insight into neurodevelopmental variability in CHD. Using data from the Pediatric Cardiac Genomics Consortium Brain and Genes study, we identified data-driven subgroups of individuals with CHD from measures of brain structure. Using structural magnetic resonance imaging (MRI; N = 93; cortical thickness, cortical volume, and subcortical volume), we identified subgroups that differed primarily on cardiac anatomic lesion and language ability. In contrast, using diffusion MRI (N = 88; white matter connectivity strength), we identified subgroups that were characterized by differences in associations with rare genetic variants and visual-motor function. This work provides insight into the differential impacts of cardiac lesions and genomic variation on brain growth and architecture in patients with CHD, with potentially distinct effects on neurodevelopmental outcomes.

Unveiling the cognitive network organization through cognitive performance

The evaluation of cognitive functions interactions has become increasingly implemented in the cognition exploration. In the present study, we propose to examine the organization of the cognitive network in healthy participants through the analysis of behavioral performances in several cognitive domains. Specifically, we aim to explore cognitive interactions profiles, in terms of cognitive network, and as a function of participants' handedness. To this end, we proposed several behavioral tasks evaluating language, memory, executive functions, and social cognition performances in 175 young healthy right-handed and left-handed participants and we analyzed cognitive scores, from a network perspective, using graph theory. Our results highlight the existence of intricate interactions between cognitive functions both within and beyond the same cognitive domain. Language functions are interrelated with executive functions and memory in healthy cognitive functioning and assume a central role in the cognitive network. Interestingly, for similar high performance, our findings unveiled differential organizations within the cognitive network between right-handed and left-handed participants, with variations observed both at a global and nodal level. This original integrative network approach to the study of cognition provides new insights into cognitive interactions and modulations. It allows a more global understanding and consideration of cognitive functioning, from which complex behaviors emerge.

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.

Atypical cortical hierarchy in Aβ-positive older adults and its reflection in spontaneous speech

Abnormal deposition of Aβ amyloid is an early neuropathological marker of Alzheimer's disease (AD), arising long ahead of clinical symptoms. Non-invasive measures of associated early neurofunctional changes, together with easily accessible behavioral readouts of these changes, could be of great clinical benefit. We pursued this aim by investigating large-scale cortical gradients of functional connectivity with functional MRI, which capture the hierarchical integration of cortical functions, together with acoustic-prosodic features from spontaneous speech, in cognitively unimpaired older adults with and without Aβ positivity (total N = 188). We predicted distortions of the cortical hierarchy associated with prosodic changes in the Aβ + group. Results confirmed substantially altered cortical hierarchies and less variability in these in the Aβ + group, together with an increase in quantitative prosodic measures, which correlated with gradient variability as well as digit span test scores. Overall, these findings confirm that long before the clinical stage and objective cognitive impairment, increased risk of cognitive decline as indexed by Aβ accumulation is marked by neurofunctional changes in the cortical hierarchy, which are related to automatically extractable speech patterns and alterations in working memory functions.

Disintegration at the Syntax-Semantics Interface in Prodromal Alzheimer's Disease: New Evidence from Complex Sentence Anaphora in Amnestic Mild Cognitive Impairment (aMCI)

Although diverse language deficits have been widely observed in prodromal Alzheimer's disease (AD), the underlying nature of such deficits and their explanation remains opaque. Consequently, both clinical applications and brain-language models are not well-defined. In this paper we report results from two experiments which test language production in a group of individuals with amnestic Mild Cognitive Impairment (aMCI) in contrast to healthy aging and healthy young. The experiments apply factorial designs informed by linguistic analysis to test two forms of complex sentences involving anaphora (relations between pronouns and their antecedents). Results show that aMCI individuals differentiate forms of anaphora depending on sentence structure, with selective impairment of sentences which involve construal with reference to context (anaphoric coreference). We argue that aMCI individuals maintain core structural knowledge while evidencing deficiency in syntax-semantics integration, thus locating the source of the deficit in the language-thought interface of the Language Faculty.

Modeling the neurocognitive dynamics of language across the lifespan

Healthy aging is associated with a heterogeneous decline across cognitive functions, typically observed between language comprehension and language production (LP). Examining resting-state fMRI and neuropsychological data from 628 healthy adults (age 18-88) from the CamCAN cohort, we performed state-of-the-art graph theoretical analysis to uncover the neural mechanisms underlying this variability. At the cognitive level, our findings suggest that LP is not an isolated function but is modulated throughout the lifespan by the extent of inter-cognitive synergy between semantic and domain-general processes. At the cerebral level, we show that default mode network (DMN) suppression coupled with fronto-parietal network (FPN) integration is the way for the brain to compensate for the effects of dedifferentiation at a minimal cost, efficiently mitigating the age-related decline in LP. Relatedly, reduced DMN suppression in midlife could compromise the ability to manage the cost of FPN integration. This may prompt older adults to adopt a more cost-efficient compensatory strategy that maintains global homeostasis at the expense of LP performances. Taken together, we propose that midlife represents a critical neurocognitive juncture that signifies the onset of LP decline, as older adults gradually lose control over semantic representations. We summarize our findings in a novel synergistic, economical, nonlinear, emergent, cognitive aging model, integrating connectomic and cognitive dimensions within a complex system perspective.

Dose response of transcranial near infrared light stimulation on brain functional connectivity and cognition in older adults-A randomized comparison

Photobiomodulation, also called low-level light therapy, has been reported in animal studies to have an effect on brain activity and cognition. However, studies in humans regarding its effect on cognition and brain functional connectivity, and the required dose threshold for achieving the same have been very limited. We compared the effects of different doses of photobiomodulation (PBM) on cognition and resting state brain functional connectivity in 25 cognitively normal adults aged 55-70 years. They were randomized to a single session of the sham group, "low-dose" and "high-dose" groups receiving NIR light with transcranial fluence of 26 and 52 J/cm2 respectively, and intranasal fluence of 9 and 18 J/cm2 respectively. There was a significant increase in resting state functional connectivity of the left superior frontal gyrus (SFG) with the left planum temporale (PT), p = 0.0016, and with the left inferior frontal gyrus, pars triangularis, p = 0.0235 in the "high-dose" group only compared to the "sham" group. There was also a significant improvement in visual search and processing speed (p = 0.012) in the "high-dose" group. Replication of these findings in an adequately powered randomized sham-controlled study in healthy older adults can pave the way for clinical application of NIRL as a therapeutic modality in patients with Alzheimer's disease.

Episodic Thinking in Alzheimer's Disease Through the Lens of Language: Linguistic Analysis and Transformer-Based Classification

PURPOSE

Episodic memory decline is a hallmark of Alzheimer's disease (AD) and linked to deficits in episodic thinking directed to the future. We addressed the question whether a deficit in episodic thinking can be picked up directly from connected speech and its detection can be automatized.

METHOD

We linguistically classified 2,809 utterances (including embedded clauses in the utterances) from picture descriptions from 70 healthy older controls, 82 people with mild probable AD (pAD), and 46 people with moderate pAD for whether they were episodic, nonepisodic, or "other" (e.g., off-task). Generalized linear regression models were used to investigate how ratios of these categories change in AD, controlling for age, gender, and education. Finally, we applied deep learning technique to explore the feasibility of automating the episodicity analysis.

RESULTS

Decline in episodicity significantly distinguished controls from both mild pAD and moderate pAD. Correlation analysis suggested this decline not to be an effect of age, gender, and education but of cognitive ability. The decline was not compensated by an increase of nonepisodic utterances but mainly of off-task expressions. A transformer-based classifier to explore the possibility of automatizing the classification of episodicity achieved a macro F1 score of 0.913 in the ternary classification.

CONCLUSION

These results show that a loss of episodicity is an early effect in AD that is manifested in spontaneous speech and can be reliably measured by both humans and machines.

When Age Tips the Balance: a Dual Mechanism Affecting Hemispheric Specialization for Language

Aging engenders neuroadaptations, generally reducing specificity and selectivity in functional brain responses. Our investigation delves into the functional specialization of brain hemispheres within language-related networks across adulthood. In a cohort of 728 healthy adults spanning ages 18 to 88, we modeled the trajectories of inter-hemispheric asymmetry concerning the principal functional gradient across 37 homotopic regions of interest (hROIs) of an extensive language network, known as the Language-and-Memory Network. Our findings reveal that over two-thirds of Language-and-Memory Network hROIs undergo asymmetry changes with age, falling into two main clusters. The first cluster evolves from left-sided specialization to right-sided tendencies, while the second cluster transitions from right-sided asymmetry to left-hemisphere dominance. These reversed asymmetry shifts manifest around midlife, occurring after age 50, and are associated with poorer language production performance. Our results provide valuable insights into the influence of functional brain asymmetries on language proficiency and present a dynamic perspective on brain plasticity during the typical aging process.

The functional connectome of 3,4-methyldioxymethamphetamine-related declarative memory impairments

The chronic intake of 3,4-methylenedioxymethamphetamine (MDMA, "ecstasy") bears a strong risk for sustained declarative memory impairments. Although such memory deficits have been repeatedly reported, their neurofunctional origin remains elusive. Therefore, we here investigate the neuronal basis of altered declarative memory in recurrent MDMA users at the level of brain connectivity. We examined a group of 44 chronic MDMA users and 41 demographically matched controls. Declarative memory performance was assessed by the Rey Auditory Verbal Learning Test and a visual associative learning test. To uncover alterations in the whole brain connectome between groups, we employed a data-driven multi-voxel pattern analysis (MVPA) approach on participants' resting-state functional magnetic resonance imaging data. Recent MDMA use was confirmed by hair analyses. MDMA users showed lower performance in delayed recall across tasks compared to well-matched controls with moderate-to-strong effect sizes. MVPA revealed a large cluster located in the left postcentral gyrus of global connectivity differences between groups. Post hoc seed-based connectivity analyses with this cluster unraveled hypoconnectivity to temporal areas belonging to the auditory network and hyperconnectivity to dorsal parietal regions belonging to the dorsal attention network in MDMA users. Seed-based connectivity strength was associated with verbal memory performance in the whole sample as well as with MDMA intake patterns in the user group. Our findings suggest that functional underpinnings of MDMA-related memory impairments encompass altered patterns of multimodal sensory integration within auditory processing regions to a functional heteromodal connector hub, the left postcentral gyrus. In addition, hyperconnectivity in regions of a cognitive control network might indicate compensation for degraded sensory processing.

An explainable machine learning model of cognitive decline derived from speech

INTRODUCTION

Traditional Alzheimer's disease (AD) and mild cognitive impairment (MCI) screening lacks the sensitivity and timeliness required to detect subtle indicators of cognitive decline. Multimodal artificial intelligence technologies using only speech data promise improved detection of neurodegenerative disorders.

METHODS

Speech collected over the telephone from 91 older participants who were cognitively healthy (n = 29) or had diagnoses of AD (n = 30) or amnestic MCI (aMCI; n = 32) was analyzed with multimodal natural language and speech processing methods. An explainable ensemble decision tree classifier for the multiclass prediction of cognitive decline was created.

RESULTS

This approach was 75% accurate overall-an improvement over traditional speech-based screening tools and a unimodal language-based model. We include a dashboard for the examination of the results, allowing for novel ways of interpreting such data.

DISCUSSION

This work provides a foundation for a meaningful change in medicine as clinical translation, scalability, and user friendliness were core to the methodologies.

Highlights

Remote assessments and artificial intelligence (AI) models allow greater access to cognitive decline screening.Speech impairments differ significantly between mild AD, amnestic mild cognitive impairment (aMCI), and healthy controls.AI predictions of cognitive decline are more accurate than experts and standard tools.The AI model was 75% accurate in classifying mild AD, aMCI, and healthy controls.

A reconceptualization of sentence production in post-stroke agrammatic aphasia: the synergistic processing bottleneck model

The language production deficit in post-stroke agrammatic aphasia (PSA-G) tends to result from lesions to the left inferior frontal gyrus (LIFG) and is characterized by a triad of symptoms: fragmented sentences, errors in functional morphology, and a dearth of verbs. Despite decades of research, the mechanisms underlying production patterns in PSA-G have been difficult to characterize. Two major impediments to progress may have been the view that it is a purely morphosyntactic disorder and the (sometimes overzealous) application of linguistic theory without interceding psycholinguistic evidence. In this paper, empirical evidence is examined to present an integrated portrait of language production in PSA-G and to evaluate the assumption of a syntax-specific syndrome. In light of extant evidence, it is proposed that agrammatic language production results from a combination of morphosyntactic, phonomotor, and processing capacity limitations that cause a cumulative processing bottleneck at the point of articulatory planning. This proposed Synergistic Processing Bottleneck model of PSA-G presents a testable framework for future research. The paper ends with recommendations for future research on PSA-G.

Automated Classification of Cognitive Decline and Probable Alzheimer's Dementia Across Multiple Speech and Language Domains

BACKGROUND

Decline in language has emerged as a new potential biomarker for the early detection of Alzheimer's disease (AD). It remains unclear how sensitive language measures are across different tasks, language domains, and languages, and to what extent changes can be reliably detected in early stages such as subjective cognitive decline (SCD) and mild cognitive impairment (MCI).

METHOD

Using a scene construction task for speech elicitation in a new Spanish/Catalan speaking cohort (N = 119), we automatically extracted features across seven domains, three acoustic (spectral, cepstral, and voice quality), one prosodic, and three from text (morpholexical, semantic, and syntactic). They were forwarded to a random forest classifier to evaluate the discriminability of participants with probable AD dementia, amnestic and nonamnestic MCI, SCD, and cognitively healthy controls. Repeated-measures analyses of variance and paired-samples Wilcoxon signed-ranks test were used to assess whether and how performance differs significantly across groups and linguistic domains.

RESULTS

The performance scores of the machine learning classifier were generally satisfactorily high, with the highest scores over .9. Model performance was significantly different for linguistic domains (p < .001), and speech versus text (p = .043), with speech features outperforming textual features, and voice quality performing best. High diagnostic classification accuracies were seen even within both cognitively healthy (controls vs. SCD) and MCI (amnestic and nonamnestic) groups.

CONCLUSION

Speech-based machine learning is powerful in detecting cognitive decline and probable AD dementia across a range of different feature domains, though important differences exist between these domains as well.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.23699733.

The right uncinate fasciculus supports verbal short-term memory in aphasia

Verbal short-term memory (STM) deficits are associated with language processing impairments in people with aphasia. Importantly, the integrity of STM can predict word learning ability and anomia therapy gains in aphasia. While the recruitment of perilesional and contralesional homologous brain regions has been proposed as a possible mechanism for aphasia recovery, little is known about the white-matter pathways that support verbal STM in post-stroke aphasia. Here, we investigated the relationships between the language-related white matter tracts and verbal STM ability in aphasia. Nineteen participants with post-stroke chronic aphasia completed a subset of verbal STM subtests of the TALSA battery including nonword repetition (phonological STM), pointing span (lexical-semantic STM without language output) and repetition span tasks (lexical-semantic STM with language output). Using a manual deterministic tractography approach, we investigated the micro- and macrostructural properties of the structural language network. Next, we assessed the relationships between individually extracted tract values and verbal STM scores. We found significant correlations between volume measures of the right Uncinate Fasciculus and all three verbal STM scores, with the association between the right UF volume and nonword repetition being the strongest one. These findings suggest that the integrity of the right UF is associated with phonological and lexical-semantic verbal STM ability in aphasia and highlight the potential compensatory role of right-sided ventral white matter language tracts in supporting verbal STM after aphasia-inducing left hemisphere insult.

Intraoperative Testing During the Mapping of the Language Cortex

Intracranial lesions, particularly in the language-eloquent areas of the brain, can affect one's speaking ability. Despite advances in surgery, the excision of these lesions can be challenging. Intraoperative neurophysiological monitoring (IONM) during awake craniotomies can help identify language-eloquent areas and minimize postoperative impairments. Preoperative language testing is performed to establish a baseline before intraoperative language testing. This involves subjecting patients to predetermined tasks in the operating room to evaluate their phonological, semantic, and syntactic capabilities. The current state and future directions of intraoperative language testing procedures are discussed in this paper. The most common intraoperative tasks are counting and picture naming. However, some experts recommend utilizing more nuanced tasks that involve regions affected by infrequently occurring tumor patterns. Low-frequency bipolar Penfield stimulation is optimal for language mapping. Exception cases are discussed where awake craniotomies are not feasible. When dealing with multilingual patients, the patient's age of learning and skill level can be accounted for in terms of making informed task choices and mapping techniques to avoid any damage to language areas.

Gait control by the frontal lobe

The frontal lobe is crucial and contributes to controlling truncal motion, postural responses, and maintaining equilibrium and locomotion. The rich repertoire of frontal gait disorders gives some indication of this complexity. For human walking, it is necessary to simultaneously achieve at least two tasks, such as maintaining a bipedal upright posture and locomotion. Particularly, postural control plays an extremely significant role in enabling the subject to maintain stable gait behaviors to adapt to the environment. To achieve these requirements, the frontal cortex (1) uses cognitive information from the parietal, temporal, and occipital cortices, (2) creates plans and programs of gait behaviors, and (3) acts on the brainstem and spinal cord, where the core posture-gait mechanisms exist. Moreover, the frontal cortex enables one to achieve a variety of gait patterns in response to environmental changes by switching gait patterns from automatic routine to intentionally controlled and learning the new paradigms of gait strategy via networks with the basal ganglia, cerebellum, and limbic structures. This chapter discusses the role of each area of the frontal cortex in behavioral control and attempts to explain how frontal lobe controls walking with special reference to postural control.

Unraveling the functional attributes of the language connectome: crucial subnetworks, flexibility and variability

Language processing is a highly integrative function, intertwining linguistic operations (processing the language code intentionally used for communication) and extra-linguistic processes (e.g., attention monitoring, predictive inference, long-term memory). This synergetic cognitive architecture requires a distributed and specialized neural substrate. Brain systems have mainly been examined at rest. However, task-related functional connectivity provides additional and valuable information about how information is processed when various cognitive states are involved. We gathered thirteen language fMRI tasks in a unique database of one hundred and fifty neurotypical adults (InLang [Interactive networks of Language] database), providing the opportunity to assess language features across a wide range of linguistic processes. Using this database, we applied network theory as a computational tool to model the task-related functional connectome of language (LANG atlas). The organization of this data-driven neurocognitive atlas of language was examined at multiple levels, uncovering its major components (or crucial subnetworks), and its anatomical and functional correlates. In addition, we estimated its reconfiguration as a function of linguistic demand (flexibility) or several factors such as age or gender (variability). We observed that several discrete networks could be specifically shaped to promote key functional features of language: coding-decoding (Net1), control-executive (Net2), abstract-knowledge (Net3), and sensorimotor (Net4) functions. The architecture of these systems and the functional connectivity of the pivotal brain regions varied according to the nature of the linguistic process, gender, or age. By accounting for the multifaceted nature of language and modulating factors, this study can contribute to enriching and refining existing neurocognitive models of language. The LANG atlas can also be considered a reference for comparative or clinical studies involving various patients and conditions.

Distinct limbic connectivity in left and right benign mesial temporal lobe epilepsy: Evidence from a resting state functional MRI study

Background

Functional connectivity (FC) studies showed that pharmaco-resistant mesial temporal lobe epilepsy (MTLE) affects not only the limbic system, but also several extra-limbic regions, including areas belonging to resting state networks. Less is known about FC in subjects with benign MTLE (i.e., sensitive to antiseizure medication, bMTLE).

Aim and methods

We evaluated FC of hippocampus and amygdala in subjects with bMTLE, distinguished based on the epileptic focus lateralization. We enrolled 19 patients (10 with left and 9 with right bMTLE) and 10 age-matched healthy subjects. Connectivity was investigated at rest by using a seed-based regression analyses approach with four regions of interest (left and right hippocampus, left and right amygdala). Patients were also tested with a neuropsychological battery and their scores were correlated with fMRI data.

Results and conclusions

Our study documented an asymmetrical disruption of FC in bMTLE, in relation to the side of the focus. Right subjects only exhibited limited altered connections, while left subjects—who performed worse in verbal memory tests—showed a wide bilateral hypoconnectivity of hippocampus and amygdala with areas belonging to language and memory network. The strength of FC between left limbic areas and language and memory network correlated with better performances in verbal memory tests. Moreover, we observed an increased FC with areas of default mode network, more pronounced in left subjects, a possible attempt to compensate cognitive deficit but without effectiveness.

We believe that these findings could help to better characterize bMTLE, in which a dysfunction of limbic connectivity is detectable despite well-controlled epilepsy.

Language learning in aphasia: A narrative review and critical analysis of the literature with implications for language therapy

People with aphasia (PWA) present with language deficits including word retrieval difficulties after brain damage. Language learning is an essential life-long human capacity that may support treatment-induced language recovery after brain insult. This prospect has motivated a growing interest in the study of language learning in PWA during the last few decades. Here, we critically review the current literature on language learning ability in aphasia. The existing studies in this area indicate that (i) language learning can remain functional in some PWA, (ii) inter-individual variability in learning performance is large in PWA, (iii) language processing, short-term memory and lesion site are associated with learning ability, (iv) preliminary evidence suggests a relationship between learning ability and treatment outcomes in this population. Based on the reviewed evidence, we propose a potential account for the interplay between language and memory/learning systems to explain spared/impaired language learning and its relationship to language therapy in PWA. Finally, we indicate potential avenues for future research that may promote more cross-talk between cognitive neuroscience and aphasia rehabilitation.

Disconnection from prediction: A systematic review on the role of right temporoparietal junction in aberrant predictive processing

The right temporoparietal junction (rTPJ) is a brain area that plays a critical role in a variety of cognitive functions. Although different theoretical proposals tried to explain the ubiquitous role of rTPJ, recent evidence suggests that rTPJ may be a fundamental cortical region involved in different kinds of predictions. This systematic review aims to better investigate the potential role of rTPJ under a predictive processing perspective, providing an overview of cognitive impairments in neurological patients as the consequence of structural or functional disconnections or damage of rTPJ. Results confirm the involvement of rTPJ across several tasks and neurological pathologies. RTPJ, via its connections with other brain networks, would integrate diverse information and update internal models of the world. Against traditional views, which tend to focus on distinct domains, we argue that the role of rTPJ can be parsimoniously interpreted as a key hub involved in domain-general predictions. This alternative account of rTPJ role in aberrant predictive processing opens different perspectives, stimulating new hypotheses in basic research and clinical contexts.