Never forget a name: white matter connectivity predicts person memory

Cluster-based analysis of PTSD-Checklist for DSM-5 (PCL-5) in civilians with post-concussive cognitive changes

OBJECTIVE

This study explores the relationship between PTSD symptoms and cognition in patients with persistent post-concussive symptoms (PPCS).

METHODS

Adults with PPCS presenting to a specialized brain injury clinic provided demographic and injury information and completed the PTSD checklist for DSM-5, Generalized Anxiety Disorder Scale-7 (GAD-7) and Patient Health Questionnaire-9 (PHQ-9). The Montreal Cognitive Assessment (MoCA) was used to screen for possible cognitive concerns. Multiple regression analysis (MLR) adjusting for age, sex, mechanism of injury, psychiatric history, number of previous concussions, months since most recent injury, and mental health questionnaire scores was used to determine associations between PTSD and cognition. Binomial logistic regression explored the relationship between domains of the MoCA and PCL-5 scores.

RESULTS

We found a negative correlation between MoCA scores, PCL-5 (ρ=-0.211, p = 0.009) and PHQ-9 (ρ=-0.187, p = 0.021) in patients with PPCS and collinearity of PCL-5 and PHQ-9 scores. Significantly higher Arousal and Reactivity cluster scores within the PCL-5 were associated with poorer scores on naming and abstract tasks on the MoCA.

CONCLUSION

The association between specific PCL-5 clusters and lower MoCA scores may represent a viable target for psychotherapeutic and psychopharmacologic intervention in patients with cognitive changes associated with PPCS.

Global changes in the pattern of connectivity in developmental prosopagnosia

Developmental prosopagnosia is a neurodevelopmental condition characterized by difficulties in recognizing the identity of a person from their face. While current theories of the neural basis of developmental prosopagnosia focus on the face processing network, successful recognition of face identities requires broader integration of neural signals across the whole brain. Here, we asked whether disruptions in global functional and structural connectivity contribute to the face recognition difficulties observed in developmental prosopagnosia. We found that the left temporal pole was less functionally connected to the rest of the brain in developmental prosopagnosia. This was driven by weaker contralateral connections to the middle and inferior temporal gyri, as well as to the medial prefrontal cortex. The pattern of global connectivity in the left temporal pole was also disrupted in developmental prosopagnosia. Critically, these changes in global functional connectivity were only evident when participants viewed faces. Structural connectivity analysis revealed localized reductions in connectivity between the left temporal pole and a number of regions, including the fusiform gyrus, inferior temporal gyrus, and orbitofrontal cortex. Our findings underscore the importance of whole-brain integration in supporting typical face recognition and provide evidence that disruptions in connectivity involving the left temporal pole may underlie the characteristic difficulties of developmental prosopagnosia.

Associative white matter tracts selectively predict sensorimotor learning

Human learning varies greatly among individuals and is related to the microstructure of major white matter tracts in several learning domains, yet the impact of the existing microstructure of white matter tracts on future learning outcomes remains unclear. We employed a machine-learning model selection framework to evaluate whether existing microstructure might predict individual differences in learning a sensorimotor task, and further, if the mapping between tract microstructure and learning was selective for learning outcomes. We used diffusion tractography to measure the mean fractional anisotropy (FA) of white matter tracts in 60 adult participants who then practiced drawing a set of 40 unfamiliar symbols repeatedly using a digital writing tablet. We measured drawing learning as the slope of draw duration over the practice session and measured visual recognition learning for the symbols using an old/new 2-AFC task. Results demonstrated that tract microstructure selectively predicted learning outcomes, with left hemisphere pArc and SLF3 tracts predicting drawing learning and the left hemisphere MDLFspl predicting visual recognition learning. These results were replicated using repeat, held-out data and supported with complementary analyses. Results suggest that individual differences in the microstructure of human white matter tracts may be selectively related to future learning outcomes.

The role of language-related functional brain regions and white matter tracts in network plasticity of post-stroke aphasia

The neural mechanisms underlying language recovery after a stroke remain controversial. This review aimed to summarize the plasticity and reorganization mechanisms of the language network through neuroimaging studies. Initially, we discussed the involvement of right language homologues, perilesional tissue, and domain-general networks. Subsequently, we summarized the white matter functional mapping and remodeling mechanisms associated with language subskills. Finally, we explored how non-invasive brain stimulation (NIBS) promoted language recovery by inducing neural network plasticity. It was observed that the recruitment of right hemisphere language area homologues played a pivotal role in the early stages of frontal post-stroke aphasia (PSA), particularly in patients with larger lesions. Perilesional plasticity correlated with improved speech performance and prognosis. The domain-general networks could respond to increased "effort" in a task-dependent manner from the top-down when the downstream language network was impaired. Fluency, repetition, comprehension, naming, and reading skills exhibited overlapping and unique dual-pathway functional mapping models. In the acute phase, the structural remodeling of white matter tracts became challenging, with recovery predominantly dependent on cortical activation. Similar to the pattern of cortical activation, during the subacute and chronic phases, improvements in language functions depended, respectively, on the remodeling of right white matter tracts and the restoration of left-lateralized language structural network patterns. Moreover, the midline superior frontal gyrus/dorsal anterior cingulate cortex emerged as a promising target for NIBS. These findings offered theoretical insights for the early personalized treatment of aphasia after stroke.

Evidence for the role of affective theory of mind in face-name associative memory

Poor face-name recall has been associated with age-related impairments in cognitive functioning, namely declines in episodic memory and executive control. However, the role of social cognitive function - the ability to remember, process, and store information about others - has been largely overlooked in this work. Extensive work has shown that social and nonsocial cognitive processes rely on unique, albeit overlapping, mechanisms. In the current study, we explored whether social cognitive functioning - specifically the ability to infer other people's mental states (i.e., theory of mind) - facilitates better face-name learning. To do this, a sample of 289 older and young adults completed a face-name learning paradigm along with standard assessments of episodic memory and executive control alongside two theory of mind measures, one static and one dynamic. In addition to expected age differences, several key effects emerged. Age-related differences in recognition were explained by episodic memory, not social cognition. However, age effects in recall were explained by both episodic memory and social cognition, specifically affective theory of mind in the dynamic task. Altogether, we contend that face-name recall can be supported by social cognitive functioning, namely understanding emotions. While acknowledging the influence of task characteristics (i.e., lures, target ages), we interpret these findings in light of existing accounts of age differences in face-name associative memory.

Diffusion tensor imaging helps identify shunt-responsive normal pressure hydrocephalus patients among probable iNPH cohort

The aim of this study was to investigate whether white matter changes as measured by diffusion tensor imaging (DTI) can help differentiate shunt-responsive idiopathic normal pressure hydrocephalus (iNPH) patients from patients with other causes of gait disturbances and/or cognitive decline with ventriculomegaly whose clinical symptoms do not improve significantly after cerebrospinal fluid derivation (non-iNPH). Between 2017 and 2022, 85 patients with probable iNPH underwent prospective preoperative magnetic resonance imaging (MRI) and comprehensive clinical workup. Patients with clinical symptoms of iNPH, positive result on lumbar infusion test, and gait improvement after 120-h lumbar drainage were diagnosed with iNPH and underwent shunt-placement surgery. Fractional anisotropy (FA) and mean diffusivity (MD) values for individual regions of interest were extracted from preoperative MRI, using the TBSS pipeline of FSL toolkit. These FA and MD values were then compared to results of clinical workup and established diagnosis of iNPH. An identical MRI protocol was performed on 13 age- and sex-matched healthy volunteers. Statistically significant differences in FA values of several white matter structures were found not only between iNPH patients and healthy controls but also between iNPH and non-iNPH patients. ROI that showed best diagnostic ability when differentiating iNPH among probable iNPH cohort was uncinate fasciculus, with AUC of 0.74 (p < 0.001). DTI methods of white matter analysis using standardised methods of ROI extraction can help in differentiation of iNPH patients not only from healthy patients but also from patients with other causes of gait disturbances with cognitive decline and ventriculomegaly.

Associative white matter tracts selectively predict sensorimotor learning

Human learning is a complex phenomenon that varies greatly among individuals and is related to the microstructure of major white matter tracts in several learning domains, yet the impact of the existing myelination of white matter tracts on future learning outcomes remains unclear. We employed a machine-learning model selection framework to evaluate whether existing microstructure might predict individual differences in the potential for learning a sensorimotor task, and further, if the mapping between the microstructure of major white matter tracts and learning was selective for learning outcomes. We used diffusion tractography to measure the mean fractional anisotropy (FA) of white matter tracts in 60 adult participants who then underwent training and subsequent testing to evaluate learning. During training, participants practiced drawing a set of 40 novel symbols repeatedly using a digital writing tablet. We measured drawing learning as the slope of draw duration over the practice session and visual recognition learning as the performance accuracy in an old/new 2-AFC recognition task. Results demonstrated that the microstructure of major white matter tracts selectively predicted learning outcomes, with left hemisphere pArc and SLF 3 tracts predicting drawing learning and the left hemisphere MDLFspl predicting visual recognition learning. These results were replicated in a repeat, held-out data set and supported with complementary analyses. Overall, results suggest that individual differences in the microstructure of human white matter tracts may be selectively related to future learning outcomes and open avenues of inquiry concerning the impact of existing tract myelination in the potential for learning.

Significance statement

A selective mapping between tract microstructure and future learning has been demonstrated in the murine model and, to our knowledge, has not yet been demonstrated in humans. We employed a data-driven approach that identified only two tracts, the two most posterior segments of the arcuate fasciculus in the left hemisphere, to predict learning a sensorimotor task (drawing symbols) and this prediction model did not transfer to other learning outcomes (visual symbol recognition). Results suggest that individual differences in learning may be selectively related to the tissue properties of major white matter tracts in the human brain.

The fornix supports episodic memory during childhood

Episodic memory relies on the coordination of widespread brain regions that reconstruct spatiotemporal details of an episode. These topologically dispersed brain regions can rapidly communicate through structural pathways. Research in animal and human lesion studies implicate the fornix-the major output pathway of the hippocampus-in supporting various aspects of episodic memory. Because episodic memory undergoes marked changes in early childhood, we tested the link between the fornix and episodic memory in an age window of robust memory development (ages 4-8 years). Children were tested on the stories subtest from the Children's Memory Scale, a temporal order memory task, and a source memory task. Fornix streamlines were reconstructed using probabilistic tractography to estimate fornix microstructure. In addition, we measured fornix macrostructure and computed free water. To assess selectivity of our findings, we also reconstructed the uncinate fasciculus. Findings show that children's memory increases from ages 4 to 8 and that fornix micro- and macrostructure increases between ages 4 and 8. Children's memory performance across nearly every memory task correlated with individual differences in fornix, but not uncinate fasciculus, white matter. These findings suggest that the fornix plays an important role in supporting the development of episodic memory, and potentially semantic memory, in early childhood.

White matter connectivity in brain networks supporting social and affective processing predicts real-world social network characteristics

Human behavior is embedded in social networks. Certain characteristics of the positions that people occupy within these networks appear to be stable within individuals. Such traits likely stem in part from individual differences in how people tend to think and behave, which may be driven by individual differences in the neuroanatomy supporting socio-affective processing. To investigate this possibility, we reconstructed the full social networks of three graduate student cohorts (N = 275; N = 279; N = 285), a subset of whom (N = 112) underwent diffusion magnetic resonance imaging. Although no single tract in isolation appears to be necessary or sufficient to predict social network characteristics, distributed patterns of white matter microstructural integrity in brain networks supporting social and affective processing predict eigenvector centrality (how well-connected someone is to well-connected others) and brokerage (how much one connects otherwise unconnected others). Thus, where individuals sit in their real-world social networks is reflected in their structural brain networks. More broadly, these results suggest that the application of data-driven methods to neuroimaging data can be a promising approach to investigate how brains shape and are shaped by individuals' positions in their real-world social networks.

Relationship between post-traumatic amnesia and white matter integrity in traumatic brain injury using tract-based spatial statistics

This study used tract-based spatial statistics to examine the relationship between post-traumatic amnesia (PTA) and white matter integrity in patients with a traumatic brain injury (TBI). Forty-seven patients with TBI in the chronic stage and 47 age- and sex-matched normal control subjects were recruited to the study. Correlation coefficients were calculated to observe the relationships among the PTA duration, white matter fractional anisotropy (FA) values, and mini-mental state examination (MMSE) results in the patient group. Both before and after Benjamini–Hochberg (BH) corrections, FA values of 46 of the 48 regions of interests of the patient group were lower than those of the control group. The FA values of column and body of fornix, left crus of fornix, left uncinate fasciculus, right hippocampus part of cingulum, left medial lemniscus, right superior cerebellar peduncle, left superior cerebellar peduncle, and left posterior thalamic radiation (after BH correction: the uncinate fasciculus and right hippocampus part of cingulum) in the patient group were negatively correlated with PTA duration. PTA duration was related to the injury severity of eight neural structures, each of which is involved in the cognitive functioning of patients with TBI. Therefore, PTA duration can indicate injury severity of the above neural structures in TBI patients.

Structural and Functional Changes Are Related to Cognitive Status in Wilson's Disease

Patients with Wilson’s disease (WD) suffer from prospective memory (PM) impairment, and some of patients develop cognitive impairment. However, very little is known about how brain structure and function changes effect PM in WD. Here, we employed multimodal neuroimaging data acquired from 22 WD patients and 26 healthy controls (HC) who underwent three-dimensional T1-weighted, diffusion tensor imaging (DTI), and resting state functional magnetic resonance imaging (RS-fMRI). We investigated gray matter (GM) volumes with voxel-based morphometry, DTI metrics using the fiber tractography method, and RS-fMRI using the seed-based functional connectivity method. Compared with HC, WD patients showed GM volume reductions in the basal ganglia (BG) and occipital fusiform gyrus, as well as volume increase in the visual association cortex. Moreover, whiter matter (WM) tracks of WD were widely impaired in association and limbic fibers. WM tracks in association fibers are significant related to PM in WD patients. Relative to HC, WD patients showed that the visual association cortex functionally connects to the thalamus and hippocampus, which is associated with global cognitive function in patients with WD. Together, these findings suggested that PM impairment in WD may be modulated by aberrant WM in association fibers, and that GM volume changes in the association cortex has no direct effect on cognitive status, but indirectly affect global cognitive function by its aberrant functional connectivity (FC) in patients with WD. Our findings may provide a new window to further study how WD develops into cognitive impairment, and deepen our understanding of the cognitive status and neuropathology of WD.

Revisiting the Functional Anatomy of the Human Brain: Toward a Meta-Networking Theory of Cerebral Functions

For more than one century, brain processing was mainly thought in a localizationist framework, in which one given function was underpinned by a discrete, isolated cortical area, and with a similar cerebral organization across individuals. However, advances in brain mapping techniques in humans have provided new insights into the organizational principles of anatomo-functional architecture. Here, we review recent findings gained from neuroimaging, electrophysiological, as well as lesion studies. Based on these recent data on brain connectome, we challenge the traditional, outdated localizationist view and propose an alternative meta-networking theory. This model holds that complex cognitions and behaviors arise from the spatiotemporal integration of distributed but relatively specialized networks underlying conation and cognition (e.g., language, spatial cognition). Dynamic interactions between such circuits result in a perpetual succession of new equilibrium states, opening the door to considerable interindividual behavioral variability and to neuroplastic phenomena. Indeed, a meta-networking organization underlies the uniquely human propensity to learn complex abilities, and also explains how postlesional reshaping can lead to some degrees of functional compensation in brain-damaged patients. We discuss the major implications of this approach in fundamental neurosciences as well as for clinical developments, especially in neurology, psychiatry, neurorehabilitation, and restorative neurosurgery.

Names and their meanings: A dual-process account of proper-name encoding and retrieval

The ability to pick out a unique entity with a proper name is an important component of human language. It has been a primary focus of research in the philosophy of language since the nineteenth century. Brain-based evidence has shed new light on this capacity, and an extensive literature indicates the involvement of distinct fronto-temporal and temporo-occipito-parietal association cortices in proper-name retrieval. However, comparatively few efforts have sought to explain how memory encoding processes lead to the later recruitment of these distinct regions at retrieval. Here, we provide a unified account of proper-name encoding and retrieval, reviewing evidence that socio-emotional and unitized encoding subserve the retrieval of proper names via anterior-temporal-prefrontal activations. Meanwhile, non-unitized item-item and item-context encoding support subsequent retrieval, largely dependent on the temporo-occipito-parietal cortex. We contend that this well-established divergence in encoding systems can explain how proper names are later retrieved from distinct neural structures. Furthermore, we explore how evidence reviewed here can inform a century-and-a-half-old debate about proper names and the meanings they pick out.

"Need to Know" or the Strong Urge to Find Names of Unique Entities in Acquired Obsessive-Compulsive Disorder

The two forms of obsessive-compulsive disorder (OCD), idiopathic and acquired, have been linked to abnormalities in the fronto-striato-thalamo-cortical circuitry, involving the orbitofrontal cortex, anterior cingulate cortex, thalamus, and striatum. Accumulating evidence indicates that damage to other brain regions (ie, temporal lobes) is also implicated in the pathogenesis of both types of OCD. In addition, some discrete OCD symptoms have received less attention because of their presumed low occurrence and difficultly of categorization. Among these, one intriguing and potentially severe type of obsessive thinking is the so-called "need to know" (NtK), which is a strong urge to access certain information, particularly proper names. In some patients, this monosymptomatic presentation may constitute the major feature of OCD. Here we report the cases of two patients who developed NtK obsessions with tenacious time-consuming, answer-seeking compulsions as the only or more disabling symptomatology in association with malignant tumors involving the right temporal lobe and connected fronto-subcortical circuits.

White matter pathways and social cognition

There is a growing consensus that social cognition and behavior emerge from interactions across distributed regions of the "social brain". Researchers have traditionally focused their attention on functional response properties of these gray matter networks and neglected the vital role of white matter connections in establishing such networks and their functions. In this article, we conduct a comprehensive review of prior research on structural connectivity in social neuroscience and highlight the importance of this literature in clarifying brain mechanisms of social cognition. We pay particular attention to three key social processes: face processing, embodied cognition, and theory of mind, and their respective underlying neural networks. To fully identify and characterize the anatomical architecture of these networks, we further implement probabilistic tractography on a large sample of diffusion-weighted imaging data. The combination of an in-depth literature review and the empirical investigation gives us an unprecedented, well-defined landscape of white matter pathways underlying major social brain networks. Finally, we discuss current problems in the field, outline suggestions for best practice in diffusion-imaging data collection and analysis, and offer new directions for future research.

The Original Social Network: White Matter and Social Cognition

Social neuroscience has traditionally focused on the functionality of gray matter regions, ignoring the critical role played by axonal fiber pathways in supporting complex social processes. In this paper, we argue that research on white matter is essential for understanding a range of topics in social neuroscience, such as face processing, theory of mind, empathy, and imitation, as well as clinical disorders defined by aberrant social behavior, such as prosopagnosia, autism, and schizophrenia. We provide practical advice on how best to carry out these studies, which ultimately will substantially deepen our understanding of the neurobiological basis of social behavior.

Neuroimaging of person perception: A social-visual interface

The visual system is able to extract an enormous amount of socially relevant information from the face, including social categories, personality traits, and emotion. While facial features may be directly tied to certain perceptions, emerging research suggests that top-down social cognitive factors (e.g., stereotypes, social-conceptual knowledge, prejudice) considerably influence and shape the perceptual process. The rapid integration of higher-order social cognitive processes into visual perception can give rise to systematic biases in face perception and may potentially act as a mediating factor for intergroup behavioral and evaluative biases. Drawing on neuroimaging evidence, we review the ways that top-down social cognitive factors shape visual perception of facial features. This emerging work in social and affective neuroscience builds upon work on predictive coding and perceptual priors in cognitive neuroscience and visual cognition, suggesting domain-general mechanisms that underlie a social-visual interface through which social cognition affects visual perception.

White matter structural connectivity and episodic memory in early childhood

Episodic memory undergoes dramatic improvement in early childhood; the reason for this is poorly understood. In adults, episodic memory relies on a distributed neural network. Key brain regions that supporting these processes include the hippocampus, portions of the parietal cortex, and portions of prefrontal cortex, each of which shows different developmental profiles. Here we asked whether developmental differences in the axonal pathways connecting these regions may account for the robust gains in episodic memory in young children. Using diffusion weighted imaging, we examined whether white matter connectivity between brain regions implicated in episodic memory differed with age, and were associated with memory performance differences in 4- and 6-year-old children. Results revealed that white matter connecting the hippocampus to the inferior parietal lobule significantly predicted children's performance on episodic memory tasks. In contrast, variation in the white matter connecting the hippocampus to the medial prefrontal cortex did not relate to memory performance. These findings suggest that structural connectivity between the hippocampus and lateral parietal regions is relevant to the development of episodic memory.