A human memory circuit derived from brain lesions causing amnesia

Heterogenous brain activations across individuals localize to a common network

Task functional magnetic resonance imaging research has generally shielded away from studying individuals due to the low reproducibility. Here, we propose that heterogeneous brain activations across individuals localize to a common network. To test this hypothesis, we use working memory (WM) as our example. First, we showed that discrete-brain-based reproducibility of brain activation during WM across individuals was low. Then, we used activation network mapping (ANM) technique to identify each individual's brain network of WM and found that network-based reproducibility was rather high. Prediction analyses using machine learning algorithms indicated that individual WM networks identified via ANM can predict WM behavioral performance. This predictive ability even outperformed that of brain activations. Our study provides a new explanation on the low reproducibility of brain activations across individuals. The results suggest that ANM can be used to identify individual brain networks of cognitive processes, thus promising broad potential applications.

Mapping lesion-related human aggression to a common brain network

BACKGROUND

Aggression exacts a significant toll on human societies and is highly prevalent among neuropsychiatric patients for which neural mechanisms are unclear and treatment options are limited.

METHODS

Using recently validated lesion network mapping technique, we derived an aggression associated network by analyzing 182 patients who had suffered penetrating head injuries during their service in the Vietnam War. To test whether damage to this lesion-derived network would increase the risk of aggression related neuropsychiatric symptoms, we used the Harvard Lesion Repository (N = 928). To explore potential therapeutic relevance of this network, we used an independent Deep brain stimulation dataset of 25 patients with epilepsy, in which irritability and aggression are known potential side effects.

RESULTS

We found that lesions associated with aggression occurred in many different brain locations but were characterized by a specific brain network defined by functional connectivity to a hub region in the right prefrontal cortex (PFC). This network involves positive connectivity to the ventromedial PFC, dorsolateral PFC, frontal pole, posterior cingulate cortex, anterior cingulate cortex, temporal-parietal junction, and lateral temporal lobe and negative connectivity to the amygdala, hippocampus, insula, and visual cortex. Among all 25 neuropsychiatric symptoms included in the Harvard Lesion Repository, criminality demonstrated the most alignment with our aggression associated network. DBS site connectivity to this same network was associated with increased irritability.

CONCLUSIONS

We conclude that brain lesions associated with aggression map to a specific human brain circuit, and the functionally connected regions in this circuit provide testable targets for therapeutic neuromodulation.

Multimodal neuroimaging to characterize symptom-specific networks in movement disorders

Movement disorders, such as Parkinson's disease, essential tremor, and dystonia, are characterized by their predominant motor symptoms, yet diseases causing abnormal movement also encompass several other symptoms, including non-motor symptoms. Here we review recent advances from studies of brain lesions, neuroimaging, and neuromodulation that provide converging evidence on symptom-specific brain networks in movement disorders. Although movement disorders have traditionally been conceptualized as disorders of the basal ganglia, cumulative data from brain lesions causing parkinsonism, tremor and dystonia have now demonstrated that this view is incomplete. Several recent studies have shown that lesions causing a given movement disorder occur in heterogeneous brain locations, but disrupt common brain networks, which appear to be specific to each motor phenotype. In addition, findings from structural and functional neuroimaging in movement disorders have demonstrated that brain abnormalities extend far beyond the brain networks associated with the motor symptoms. In fact, neuroimaging findings in each movement disorder are strongly influenced by the constellation of patients' symptoms that also seem to map to specific networks rather than individual anatomical structures or single neurotransmitters. Finally, observations from deep brain stimulation have demonstrated that clinical changes, including both symptom improvement and side effects, are dependent on the modulation of large-scale networks instead of purely local effects of the neuromodulation. Combined, this multimodal evidence suggests that symptoms in movement disorders arise from distinct brain networks, encouraging multimodal imaging studies to better characterize the underlying symptom-specific mechanisms and individually tailor treatment approaches.

Cross-regional coordination of activity in the human brain during autobiographical self-referential processing

For the human brain to operate, populations of neurons across anatomical structures must coordinate their activity within milliseconds. To date, our understanding of such interactions has remained limited. We recorded directly from the hippocampus (HPC), posteromedial cortex (PMC), ventromedial/orbital prefrontal cortex (OFC), and the anterior nuclei of the thalamus (ANT) during two experiments of autobiographical memory processing that are known from decades of neuroimaging work to coactivate these regions. In 31 patients implanted with intracranial electrodes, we found that the presentation of memory retrieval cues elicited a significant increase of low frequency (LF < 6 Hz) activity followed by cross-regional phase coherence of this LF activity before select populations of neurons within each of the four regions increased high-frequency (HF > 70 Hz) activity. The power of HF activity was modulated by memory content, and its onset followed a specific temporal order of ANT→HPC/PMC→OFC. Further, we probed cross-regional causal effective interactions with repeated electrical pulses and found that HPC stimulations cause the greatest increase in LF-phase coherence across all regions, whereas the stimulation of any region caused the greatest LF-phase coherence between that particular region and ANT. These observations support the role of the ANT in gating, and the HPC in synchronizing, the activity of cortical midline structures when humans retrieve self-relevant memories of their past. Our findings offer a fresh perspective, with high temporal fidelity, about the dynamic signaling and underlying causal connections among distant regions when the brain is actively involved in retrieving self-referential memories from the past.

Automated Measurement of Cerebral Hemorrhagic Contusions and Outcomes After Traumatic Brain Injury in the TRACK-TBI Study

Importance

Because withdrawal of life-sustaining therapy based on perceived poor prognosis is the most common cause of death after moderate or severe traumatic brain injury (TBI), the accuracy of clinical prognoses is directly associated with mortality. Although the location of brain injury is known to be important for determining recovery potential after TBI, the best available prognostic models, such as the International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) score, do not currently incorporate brain injury location.

Objective

To test whether automated measurement of cerebral hemorrhagic contusion size and location is associated with improved prognostic performance of the IMPACT score.

Design, Setting, and Participants

This prognostic cohort study was performed in 18 US level 1 trauma centers between February 26, 2014, and August 8, 2018. Adult participants aged 17 years or older from the US-based Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) study with moderate or severe TBI (Glasgow Coma Scale score 3-12) and contusions detected on brain computed tomography (CT) scans were included. The data analysis was performed between January 2023 and February 2024.

Exposures

Labeled contusions detected on CT scans using Brain Lesion Analysis and Segmentation Tool for Computed Tomography (BLAST-CT), a validated artificial intelligence algorithm.

Main Outcome and Measure

The primary outcome was a Glasgow Outcome Scale-Extended (GOSE) score of 4 or less at 6 months after injury. Whether frontal or temporal lobe contusion volumes improved the performance of the IMPACT score was tested using logistic regression and area under the receiver operating characteristic curve comparisons. Sparse canonical correlation analysis was used to generate a disability heat map to visualize the strongest brainwide associations with outcomes.

Results

The cohort included 291 patients with moderate or severe TBI and contusions (mean [SD] age, 42 [18] years; 221 [76%] male; median [IQR] emergency department arrival Glasgow Coma Scale score, 5 [3-10]). Only temporal contusion volumes improved the discrimination of the IMPACT score (area under the receiver operating characteristic curve, 0.86 vs 0.84; P = .03). The data-derived disability heat map of contusion locations showed that the strongest association with unfavorable outcomes was within the bilateral temporal and medial frontal lobes.

Conclusions and Relevance

These findings suggest that CT-based automated contusion measurement may be an immediately translatable strategy for improving TBI prognostic models.

Studying the social mind: An updated summary of findings from the Vietnam Head Injury Study

Lesion mapping studies allow us to evaluate the potential causal contribution of specific brain areas to human cognition and complement other cognitive neuroscience methods, as several authors have recently pointed out. Here, we present an updated summary of the findings from the Vietnam Head Injury Study (VHIS) focusing on the studies conducted over the last decade, that examined the social mind and its intricate neural and cognitive underpinnings. The VHIS is a prospective, long-term follow-up study of Vietnam veterans with penetrating traumatic brain injury (pTBI) and healthy controls (HC). The scope of the work is to present the studies from the latest phases (3 and 4) of the VHIS, 70 studies since 2011, when the Raymont et al. paper was published (Raymont et al., 2011). These studies have contributed to our understanding of human social cognition, including political and religious beliefs, theory of mind, but also executive functions, intelligence, and personality. This work finally discusses the usefulness of lesion mapping as an approach to understanding the functions of the human brain from basic science and clinical perspectives.

Increased Cortical Thickness in Alzheimer's Disease

OBJECTIVE

Patients with Alzheimer's disease (AD) have diffuse brain atrophy, but some regions, such as the anterior cingulate cortex (ACC), are spared and may even show increase in size compared to controls. The extent, clinical significance, and mechanisms associated with increased cortical thickness in AD remain unknown. Recent work suggested neural facilitation of regions anticorrelated to atrophied regions in frontotemporal dementia. Here, we aim to determine whether increased thickness occurs in sporadic AD, whether it relates to clinical symptoms, and whether it occur in brain regions functionally connected to-but anticorrelated with-locations of atrophy.

METHODS

Cross-sectional clinical, neuropsychological, and neuroimaging data from the Alzheimer's Disease Neuroimaging Initiative were analyzed to investigate cortical thickness in AD subjects versus controls. Atrophy network mapping was used to identify brain regions functionally connected to locations of increased thickness and atrophy.

RESULTS

AD patients showed increased thickness in the ACC in a region-of-interest analysis and the visual cortex in an exploratory analysis. Increased thickness in the left ACC was associated with preserved cognitive function, while increased thickness in the left visual cortex was associated with hallucinations. Finally, we found that locations of increased thickness were functionally connected to, but anticorrelated with, locations of brain atrophy (r = -0.81, p < 0.05).

INTERPRETATION

Our results suggest that increased cortical thickness in Alzheimer's disease is relevant to AD symptoms and preferentially occur in brain regions functionally connected to, but anticorrelated with, areas of brain atrophy. Implications for models of compensatory neuroplasticity in response to neurodegeneration are discussed. ANN NEUROL 2024;95:929-940.

Identification of Early Hippocampal Dynamics during Recognition Memory with Independent Component Analysis

The hippocampus is generally considered to have relatively late involvement in recognition memory, its main electrophysiological signature being between 400 and 800 ms after stimulus onset. However, most electrophysiological studies have analyzed the hippocampus as a single responsive area, selecting only a single-site signal exhibiting the strongest effect in terms of amplitude. These classical approaches may not capture all the dynamics of this structure, hindering the contribution of other hippocampal sources that are not located in the vicinity of the selected site. We combined intracerebral electroencephalogram recordings from epileptic patients with independent component analysis during a recognition memory task involving the recognition of old and new images. We identified two sources with different responses emerging from the hippocampus: a fast one (maximal amplitude at ∼250 ms) that could not be directly identified from raw recordings and a latter one, peaking at ∼400 ms. The former component presented different amplitudes between old and new items in 6 out of 10 patients. The latter component had different delays for each condition, with a faster activation (∼290 ms after stimulus onset) for recognized items. We hypothesize that both sources represent two steps of hippocampal recognition memory, the faster reflecting the input from other structures and the latter the hippocampal internal processing. Recognized images evoking early activations would facilitate neural computation in the hippocampus, accelerating memory retrieval of complementary information. Overall, our results suggest that the hippocampal activity is composed of several sources with an early activation related to recognition memory.

Targeting Symptom-Specific Networks With Transcranial Magnetic Stimulation

Increasing evidence suggests that the clinical effects of transcranial magnetic stimulation are target dependent. Within any given symptom, precise targeting of specific brain circuits may improve clinical outcomes. This principle can also be extended across symptoms-stimulation of different circuits may lead to different symptom-level outcomes. This may include targeting different symptoms within the same disorder (such as dysphoria vs. anxiety in patients with major depression) or targeting the same symptom across different disorders (such as primary major depression and depression secondary to stroke, traumatic brain injury, epilepsy, multiple sclerosis, or Parkinson's disease). Some of these symptom-specific changes may be desirable, while others may be undesirable. This review focuses on the conceptual framework through which symptom-specific target circuits may be identified, tested, and implemented.

Lesion voxels to lesion networks: The enduring value of the Vietnam Head Injury Study

The Vietnam Head Injury Study has been curated by Dr Jordan Grafman since the 1980s in an effort to study patients with penetrating traumatic brain injuries suffered during the Vietnam War. Unlike many datasets of ischemic stroke lesions, the VHIS collected extraordinarily deep phenotyping and was able to sample lesion locations that are not constrained to typical vascular territories. For decades, this dataset has helped researchers draw causal links between neuroanatomical regions and neuropsychiatric symptoms. The value of the VHIS has only increased over time as techniques for analyzing the dataset have developed and evolved. Tools such as voxel lesion symptom mapping allowed one to relate symptoms to individual brain voxels. With the advent of the human connectome, tools such as lesion network mapping allow one to relate symptoms to connected brain networks by combining lesion datasets with new atlases of human brain connectivity. In a series of recent studies, lesion network mapping has been combined with the Vietnam Head Injury dataset to identify brain networks associated with spirituality, religiosity, consciousness, memory, emotion regulation, addiction, depression, and even transdiagnostic mental illness. These findings are enhancing our ability to make diagnoses, identify potential treatment targets for focal brain stimulation, and understand the human brain generally. Our techniques for studying brain lesions will continue to improve, as will our tools for modulating brain circuits. As these advances occur, the value of well characterized lesion datasets such as the Vietnam Head Injury Study will continue to grow. This study aims to review the history of the Vietnam Head Injury Study and contextualize its role in modern-day localization of neurological symptoms.

Advancing Beyond the Hippocampus to Preserve Cognition for Patients With Brain Metastases: Dosimetric Results From a Phase 2 Trial of Memory-Avoidance Whole Brain Radiation Therapy

Purpose

Recent advances to preserve neurocognitive function in patients treated for brain metastases include stereotactic radiosurgery, hippocampal avoidance whole brain radiation therapy (WBRT), and memantine administration. The hippocampus, corpus callosum, fornix, and amygdala are key neurocognitive substructures with a low propensity for brain metastases. Herein, we report our preliminary experience using a "memory-avoidance" WBRT (MA-WBRT) approach that spares these substructures for patients with >15 brain metastases.

Methods and Materials

Ten consecutive patients treated with MA-WBRT on a phase 2 clinical trial were reviewed. In each patient, the hippocampi, amygdalae, corpus callosum, and fornix were contoured. Patients were not eligible for MA-WBRT if they had metastases in these substructures. A memory-avoidance region was created using a 5-mm volumetric expansion around these substructures. Hotspots were avoided in the hypothalamus and pituitary gland. Coverage of brain metastases was prioritized over memory avoidance dose constraints. Dose constraints for these avoidance structures included a D100% ≤ 9 Gy and D0.03 cm3 ≤ 16 Gy (variation acceptable to 20 Gy). LINAC-based volumetric modulated arc therapy plans were generated for a prescription dose of 30 Gy in 10 fractions.

Results

On average, the memory avoidance structure volume was 37.1 cm3 (range, 25.2-44.6 cm3), occupying 2.5% of the entire whole brain target volume. All treatment plans met the D100% dose constraint, and 8 of 10 plans met the D0.03 cm3 constraint, with priority given to tumor coverage for the remaining 2 cases. Target coverage (D98% > 25 Gy) and homogeneity (D2% ≤ 37.5 Gy) were achieved for all plans.

Conclusions

Modern volumetric modulated arc therapy techniques allow for sparing of the hippocampus, amygdala, corpus callosum, and fornix with good target coverage and homogeneity. After enrollment is completed, quality of life and cognitive data will be evaluated to assess the efficacy of MA-WBRT to mitigate declines in quality of life and cognition after whole brain radiation.

A neural circuit for spatial orientation derived from brain lesions

There is disagreement regarding the major components of the brain network supporting spatial cognition. To address this issue, we applied a lesion mapping approach to the clinical phenomenon of topographical disorientation. Topographical disorientation is the inability to maintain accurate knowledge about the physical environment and use it for navigation. A review of published topographical disorientation cases identified 65 different lesion sites. Our lesion mapping analysis yielded a topographical disorientation brain map encompassing the classic regions of the navigation network: medial parietal, medial temporal, and temporo-parietal cortices. We also identified a ventromedial region of the prefrontal cortex, which has been absent from prior descriptions of this network. Moreover, we revealed that the regions mapped are correlated with the Default Mode Network sub-network C. Taken together, this study provides causal evidence for the distribution of the spatial cognitive system, demarking the major components and identifying novel regions.

Converging diencephalic and hippocampal supports for episodic memory

To understand the neural basis of episodic memory it is necessary to appreciate the significance of the fornix. This pathway creates a direct link between those temporal lobe and medial diencephalic sites responsible for anterograde amnesia. A collaboration with Andrew Mayes made it possible to recruit and scan 38 patients with colloid cysts in the third ventricle, a condition associated with variable fornix damage. Complete fornix loss was seen in three patients, who suffered chronic long-term memory problems. Volumetric analyses involving all 38 patients then revealed a highly consistent relationship between mammillary body volume and the recall of episodic memory. That relationship was not seen for working memory or tests of recognition memory. Three different methods all supported a dissociation between recollective-based recognition (impaired) and familiarity-based recognition (spared). This dissociation helped to show how the mammillary body-anterior thalamic nuclei axis, as well as the hippocampus, is vital for episodic memory yet is not required for familiarity-based recognition. These findings set the scene for a reformulation of temporal lobe and diencephalic amnesia. In this revised model, these two regions converge on overlapping cortical areas, including retrosplenial cortex. The united actions of the hippocampal formation and the anterior thalamic nuclei on these cortical areas enable episodic memory encoding and consolidation, impacting on subsequent recall.

Multiple sclerosis lesions that impair memory map to a connected memory circuit

BACKGROUND

Nearly 1 million Americans are living with multiple sclerosis (MS) and 30-50% will experience memory dysfunction. It remains unclear whether this memory dysfunction is due to overall white matter lesion burden or damage to specific neuroanatomical structures. Here we test if MS memory dysfunction is associated with white matter lesions to a specific brain circuit.

METHODS

We performed a cross-sectional analysis of standard structural images and verbal memory scores as assessed by immediate recall trials from 431 patients with MS (mean age 49.2 years, 71.9% female) enrolled at a large, academic referral center. White matter lesion locations from each patient were mapped using a validated algorithm. First, we tested for associations between memory dysfunction and total MS lesion volume. Second, we tested for associations between memory dysfunction and lesion intersection with an a priori memory circuit derived from stroke lesions. Third, we performed mediation analyses to determine which variable was most associated with memory dysfunction. Finally, we performed a data-driven analysis to derive de-novo brain circuits for MS memory dysfunction using both functional (n = 1000) and structural (n = 178) connectomes.

RESULTS

Both total lesion volume (r = 0.31, p < 0.001) and lesion damage to our a priori memory circuit (r = 0.34, p < 0.001) were associated with memory dysfunction. However, lesion damage to the memory circuit fully mediated the association of lesion volume with memory performance. Our data-driven analysis identified multiple connections associated with memory dysfunction, including peaks in the hippocampus (T = 6.05, family-wise error p = 0.000008), parahippocampus, fornix and cingulate. Finally, the overall topography of our data-driven MS memory circuit matched our a priori stroke-derived memory circuit.

CONCLUSIONS

Lesion locations associated with memory dysfunction in MS map onto a specific brain circuit centered on the hippocampus. Lesion damage to this circuit fully mediated associations between lesion volume and memory. A circuit-based approach to mapping MS symptoms based on lesions visible on standard structural imaging may prove useful for localization and prognosis of higher order deficits in MS.

A Lesion-Derived Brain Network for Emotion Regulation

BACKGROUND

Emotion regulation has been linked to specific brain networks based on functional neuroimaging, but networks causally involved in emotion regulation remain unknown.

METHODS

We studied patients with focal brain damage (N = 167) who completed the managing emotion subscale of the Mayer-Salovey-Caruso Emotional Intelligence Test, a measure of emotion regulation. First, we tested whether patients with lesions to an a priori network derived from functional neuroimaging showed impaired emotion regulation. Next, we leveraged lesion network mapping to derive a de novo brain network for emotion regulation. Finally, we used an independent lesion database (N = 629) to test whether damage to this lesion-derived network would increase the risk of neuropsychiatric conditions associated with emotion regulation impairment.

RESULTS

First, patients with lesions intersecting the a priori emotion regulation network derived from functional neuroimaging showed impairments in the managing emotion subscale of the Mayer-Salovey-Caruso Emotional Intelligence Test. Next, our de novo brain network for emotion regulation derived from lesion data was defined by functional connectivity to the left ventrolateral prefrontal cortex. Finally, in the independent database, lesions associated with mania, criminality, and depression intersected this de novo brain network more than lesions associated with other disorders.

CONCLUSIONS

The findings suggest that emotion regulation maps to a connected brain network centered on the left ventrolateral prefrontal cortex. Lesion damage to part of this network is associated with reported difficulties in managing emotions and is related to increased likelihood of having one of several neuropsychiatric disorders.

Connectome-based modelling of neurodegenerative diseases: towards precision medicine and mechanistic insight

Neurodegenerative diseases are the most common cause of dementia. Although their underlying molecular pathologies have been identified, there is substantial heterogeneity in the patterns of progressive brain alterations across and within these diseases. Recent advances in neuroimaging methods have revealed that pathological proteins accumulate along specific macroscale brain networks, implicating the network architecture of the brain in the system-level pathophysiology of neurodegenerative diseases. However, the extent to which 'network-based neurodegeneration' applies across the wide range of neurodegenerative disorders remains unclear. Here, we discuss the state-of-the-art of neuroimaging-based connectomics for the mapping and prediction of neurodegenerative processes. We review findings supporting brain networks as passive conduits through which pathological proteins spread. As an alternative view, we also discuss complementary work suggesting that network alterations actively modulate the spreading of pathological proteins between connected brain regions. We conclude this Perspective by proposing an integrative framework in which connectome-based models can be advanced along three dimensions of innovation: incorporating parameters that modulate propagation behaviour on the basis of measurable biological features; building patient-tailored models that use individual-level information and allowing model parameters to interact dynamically over time. We discuss promises and pitfalls of these strategies for improving disease insights and moving towards precision medicine.

Neural network process simulations support a distributed memory system and aid design of a novel computer adaptive digital memory test for preclinical and prodromal Alzheimer's disease

OBJECTIVE

Growing evidence supports the importance of learning as a central deficit in preclinical/prodromal Alzheimer's disease. The aims of this study were to conduct a series of neural network simulations to develop a functional understanding of a distributed, nonmodular memory system that can learn efficiently without interference. This understanding is applied to the development of a novel digital memory test.

METHOD

Simulations using traditional feed forward neural network architectures to learn simple logic problems are presented. The simulations demonstrate three limitations: (a) inefficiency, (b) an inability to learn problems consistently, and (c) catastrophic interference when given multiple problems. A new mirrored cascaded architecture is introduced to address these limitations, with support provided by a series of simulations.

RESULTS

The mirrored cascaded architecture demonstrates efficient and consistent learning relative to feed forward networks but also suffers from catastrophic interference. Addition of context values to add the capability of distinguishing features as part of learning eliminates the problem of interference in the mirrored cascaded, but not the feed forward, architectures.

CONCLUSIONS

A mirrored cascaded architecture addresses the limitations of traditional feed forward neural networks, provides support for a distributed memory system, and emphasizes the importance of context to avoid interference. These process models contributed to the design of a digital computer-adaptive word list learning test that places maximum stress on the capability to distinguish specific episodes of learning. Process simulations provide a useful method of testing models of brain function and contribute to new approaches to neuropsychological assessment. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Network Localization of Spontaneous Confabulation

OBJECTIVE

Spontaneous confabulation is a symptom in which false memories are conveyed by the patient as true. The purpose of the study was to identify the neuroanatomical substrate of this complex symptom and evaluate the relationship to related symptoms, such as delusions and amnesia.

METHODS

Twenty-five lesion locations associated with spontaneous confabulation were identified in a systematic literature search. The network of brain regions functionally connected to each lesion location was identified with a large connectome database (N=1,000) and compared with networks derived from lesions associated with nonspecific (i.e., variable) symptoms (N=135), delusions (N=32), or amnesia (N=53).

RESULTS

Lesions associated with spontaneous confabulation occurred in multiple brain locations, but they were all part of a single functionally connected brain network. Specifically, 100% of lesions were connected to the mammillary bodies (familywise error rate [FWE]-corrected p<0.05). This connectivity was specific for lesions associated with confabulation compared with lesions associated with nonspecific symptoms or delusions (FWE-corrected p<0.05). Lesions associated with confabulation were more connected to the orbitofrontal cortex than those associated with amnesia (FWE-corrected p<0.05).

CONCLUSIONS

Spontaneous confabulation maps to a common functionally connected brain network that partially overlaps, but is distinct from, networks associated with delusions or amnesia. These findings lend new insight into the neuroanatomical bases of spontaneous confabulation.

Prediction of behavioral deficits in acute stroke from lesion and structural disconnection mapping

Prediction of behavioral deficits in stroke relies on understanding the distribution of focal damage as well as the distribution of the underlying functional anatomy. Using structural or functional magnetic resonance imaging, previous studies investigated the predictive performance of imaging biomarkers for behavioral deficits in stroke patients. However, only focal lesion information or functional connectivity information alone was used in the modelling, with a small sample size and on a specific behavioral deficit domain. In this study, we investigated the prediction of behavioral deficits in acute stroke using both focal lesion patterns and structural disconnection mapping on a cohort of 551 ischemic stroke patients within one week post symptom onset. Five behavioral deficits domains, including motor, cognitive, visual, somatosensory and coordination deficits, were investigated. A probabilistic map of lesion-induced structural "disconnectome" map was created to estimate the degree of structural disconnection due to lesions. In the predictive modelling, both lesion volume and location and distant structural disconnections were included in combination with the clinical information. The results showed that improved prediction performance was achieved when considering both focal lesion patterns and global lesion-induced structural disconnections for all five behavioral deficits groups. Distinct lesion maps were obtained for each behavioral deficit, providing insights into neurobiological mechanisms of stroke functional impairment.

Functional and structural lesion network mapping in neurological and psychiatric disorders: a systematic review

Background

The traditional approach to studying the neurobiological mechanisms of brain disorders and localizing brain function involves identifying brain abnormalities and comparing them to matched controls. This method has been instrumental in clinical neurology, providing insight into the functional roles of different brain regions. However, it becomes challenging when lesions in diverse regions produce similar symptoms. To address this, researchers have begun mapping brain lesions to functional or structural networks, a process known as lesion network mapping (LNM). This approach seeks to identify common brain circuits associated with lesions in various areas. In this review, we focus on recent studies that have utilized LNM to map neurological and psychiatric symptoms, shedding light on how this method enhances our understanding of brain network functions.

Methods

We conducted a systematic search of four databases: PubMed, Scopus, and Web of Science, using the term "Lesion network mapping." Our focus was on observational studies that applied lesion network mapping in the context of neurological and psychiatric disorders.

Results

Following our screening process, we included 52 studies, comprising a total of 6,814 subjects, in our systematic review. These studies, which utilized functional connectivity, revealed several regions and network overlaps across various movement and psychiatric disorders. For instance, the cerebellum was found to be part of a common network for conditions such as essential tremor relief, parkinsonism, Holmes tremor, freezing of gait, cervical dystonia, infantile spasms, and tics. Additionally, the thalamus was identified as part of a common network for essential tremor relief, Holmes tremor, and executive function deficits. The dorsal attention network was significantly associated with fall risk in elderly individuals and parkinsonism.

Conclusion

LNM has proven to be a powerful tool in localizing a broad range of neuropsychiatric, behavioral, and movement disorders. It holds promise in identifying new treatment targets through symptom mapping. Nonetheless, the validity of these approaches should be confirmed by more comprehensive prospective studies.

Using in vivo functional and structural connectivity to predict chronic stroke aphasia deficits

Focal brain damage caused by stroke can result in aphasia and advances in cognitive neuroscience suggest that impairment may be associated with network-level disorder rather than just circumscribed cortical damage. Several studies have shown meaningful relationships between brain-behaviour using lesions; however, only a handful of studies have incorporated in vivo structural and functional connectivity. Patients with chronic post-stroke aphasia were assessed with structural (n = 68) and functional (n = 39) MRI to assess whether predicting performance can be improved with multiple modalities and if additional variance can be explained compared to lesion models alone. These neural measurements were used to construct models to predict four key language-cognitive factors: (i) phonology; (ii) semantics; (iii) executive function; and (iv) fluency. Our results showed that each factor (except executive ability) could be significantly related to each neural measurement alone; however, structural and functional connectivity models did not explain additional variance above the lesion models. We did find evidence that the structural and functional predictors may be linked to the core lesion sites. First, the predictive functional connectivity features were found to be located within functional resting-state networks identified in healthy controls, suggesting that the result might reflect functionally specific reorganization (damage to a node within a network can result in disruption to the entire network). Second, predictive structural connectivity features were located within core lesion sites, suggesting that multimodal information may be redundant in prediction modelling. In addition, we observed that the optimum sparsity within the regularized regression models differed for each behavioural component and across different imaging features, suggesting that future studies should consider optimizing hyperparameters related to sparsity per target. Together, the results indicate that the observed network-level disruption was predicted by the lesion alone and does not significantly improve model performance in predicting the profile of language impairment.

Spatial navigation and memory: A review of the similarities and differences relevant to brain models and age

Spatial navigation and memory are often seen as heavily intertwined at the cognitive and neural levels of analysis. We review models that hypothesize a central role for the medial temporal lobes, including the hippocampus, in both navigation and aspects of memory, particularly allocentric navigation and episodic memory. While these models have explanatory power in instances in which they overlap, they are limited in explaining functional and neuroanatomical differences. Focusing on human cognition, we explore the idea of navigation as a dynamically acquired skill and memory as an internally driven process, which may better account for the differences between the two. We also review network models of navigation and memory, which place a greater emphasis on connections rather than the functions of focal brain regions. These models, in turn, may have greater explanatory power for the differences between navigation and memory and the differing effects of brain lesions and age.

Further Evidence of Relationship Between Thiamine Blood Level and Cognition in Chronic Alcohol-Dependent Adults: Prospective Pilot Study of an Inpatient Detoxification with Oral Supplementation Protocol

BACKGROUND

The relationship between thiamine blood level (TBL) and cognition remains uncertain including amongst alcohol-dependent persons (ADP) AIM: To evaluate this relationship during protocol-driven inpatient alcohol detoxification treatment including thiamine supplementation (AD+Th) METHODS: Prospective 3-week study with 100 consecutively admitted detoxification-seeking ADP (47.7±11 years-old, 21% females) without superseding comorbidities requiring treatment. TBL and Montreal Cognitive Assessment (MoCA) were measured at admission (t₁, pre-AD+Th) and discharge (t₃, post-AD+Th). Frontal Assessment Battery (FAB) was performed at t₁. AD+Th included abstinence, pharmacological alcohol withdrawal syndrome treatment and oral thiamine supplementation (200 mg/day for 14 days). Regression and mediation analyses assessed TBL-cognition relationships.

RESULTS

We found no cases of Wernicke Encephalopathy (WE) and only one case of thiamine deficiency. Both MoCA and TBL significantly improved across AD+Th (with medium-to-large effect sizes). At t₁, TBL significantly predicted MoCA and FAB sum scores (medium effect sizes; extreme and very strong evidence, respectively). The clear TBL-MoCA association disappeared at t₃. In multivariate regression and mediation analyses exploring key influential factors of cognition (identified by LASSO regression), the TBL-MoCA interactions did not relevantly change at t₁ and t₃. Age, serum transaminases, vitamin D levels, drinking-years and depression score weakly modified the relationship.

CONCLUSION

TBL was a robust predictor of pre-detoxification cognitive impairment, and both TBL and cognition improved significantly during AD+Th (including abstinence) in our ADP population, supporting routine thiamine supplementation for ADP, even those at low WE-risk. TBL-cognition relationship was minimally confounded by age, alcohol-toxicity proxies, mood, and vitamin D levels.

CLINICAL TRIALS REGISTRATION

https://osf.io/b54eh/.

A transdiagnostic network for psychiatric illness derived from atrophy and lesions

Psychiatric disorders share neurobiology and frequently co-occur. This neurobiological and clinical overlap highlights opportunities for transdiagnostic treatments. In this study, we used coordinate and lesion network mapping to test for a shared brain network across psychiatric disorders. In our meta-analysis of 193 studies, atrophy coordinates across six psychiatric disorders mapped to a common brain network defined by positive connectivity to anterior cingulate and insula, and by negative connectivity to posterior parietal and lateral occipital cortex. This network was robust to leave-one-diagnosis-out cross-validation and specific to atrophy coordinates from psychiatric versus neurodegenerative disorders (72 studies). In 194 patients with penetrating head trauma, lesion damage to this network correlated with the number of post-lesion psychiatric diagnoses. Neurosurgical ablation targets for psychiatric illness (four targets) also aligned with the network. This convergent brain network for psychiatric illness may partially explain high rates of psychiatric comorbidity and could highlight neuromodulation targets for patients with more than one psychiatric disorder.

A tripartite view of the posterior cingulate cortex

The posterior cingulate cortex (PCC) is one of the least understood regions of the cerebral cortex. By contrast, the anterior cingulate cortex has been the subject of intensive investigation in humans and model animal systems, leading to detailed behavioural and computational theoretical accounts of its function. The time is right for similar progress to be made in the PCC given its unique anatomical and physiological properties and demonstrably important contributions to higher cognitive functions and brain diseases. Here, we describe recent progress in understanding the PCC, with a focus on convergent findings across species and techniques that lay a foundation for establishing a formal theoretical account of its functions. Based on this converging evidence, we propose that the broader PCC region contains three major subregions - the dorsal PCC, ventral PCC and retrosplenial cortex - that respectively support the integration of executive, mnemonic and spatial processing systems. This tripartite subregional view reconciles inconsistencies in prior unitary theories of PCC function and offers promising new avenues for progress.

Linking Personalized Brain Atrophy to Schizophrenia Network and Treatment Response

BACKGROUND AND HYPOTHESIS

Schizophrenia manifests with marked heterogeneity in both clinical presentation and underlying biology. Modeling individual differences within clinical cohorts is critical to translate knowledge reliably into clinical practice. We hypothesized that individualized brain atrophy in patients with schizophrenia may explain the heterogeneous outcomes of repetitive transcranial magnetic stimulation (rTMS).

STUDY DESIGN

The magnetic resonance imaging (MRI) data of 797 healthy subjects and 91 schizophrenia patients (between January 1, 2015, and December 31, 2020) were retrospectively selected from our hospital database. The healthy subjects were used to establish normative reference ranges for cortical thickness as a function of age and sex. Then, a schizophrenia patient's personalized atrophy map was computed as vertex-wise deviations from the normative model. Each patient's atrophy network was mapped using resting-state functional connectivity MRI from a subgroup of healthy subjects (n = 652). In total 52 of the 91 schizophrenia patients received rTMS in a randomized clinical trial (RCT). Their longitudinal symptom changes were adopted to test the clinical utility of the personalized atrophy map.

RESULTS

The personalized atrophy maps were highly heterogeneous across patients, but functionally converged to a putative schizophrenia network that comprised regions implicated by previous group-level findings. More importantly, retrospective analysis of rTMS-RCT data indicated that functional connectivity of the personalized atrophy maps with rTMS targets was significantly associated with the symptom outcomes of schizophrenia patients.

CONCLUSIONS

Normative modeling can aid in mapping the personalized atrophy network associated with treatment outcomes of patients with schizophrenia.

Multimodal and multidomain lesion network mapping enhances prediction of sensorimotor behavior in stroke patients

Beyond the characteristics of a brain lesion, such as its etiology, size or location, lesion network mapping (LNM) has shown that similar symptoms after a lesion reflects similar dis-connectivity patterns, thereby linking symptoms to brain networks. Here, we extend LNM by using a multimodal strategy, combining functional and structural networks from 1000 healthy participants in the Human Connectome Project. We apply multimodal LNM to a cohort of 54 stroke patients with the aim of predicting sensorimotor behavior, as assessed through a combination of motor and sensory tests. Results are two-fold. First, multimodal LNM reveals that the functional modality contributes more than the structural one in the prediction of sensorimotor behavior. Second, when looking at each modality individually, the performance of the structural networks strongly depended on whether sensorimotor performance was corrected for lesion size, thereby eliminating the effect that larger lesions generally produce more severe sensorimotor impairment. In contrast, functional networks provided similar performance regardless of whether or not the effect of lesion size was removed. Overall, these results support the extension of LNM to its multimodal form, highlighting the synergistic and additive nature of different types of network modalities, and their corresponding influence on behavioral performance after brain injury.

The impact of etiology in lesion-symptom mapping - A direct comparison between tumor and stroke

INTRODUCTION

Lesion-symptom mapping is a key tool in understanding the relationship between brain structures and behavior. However, the behavioral consequences of lesions from different etiologies may vary because of how they affect brain tissue and how they are distributed. The inclusion of different etiologies would increase the statistical power but has been critically debated. Meanwhile, findings from lesion studies are a valuable resource for clinicians and used across different etiologies. Therefore, the main objective of the present study was to directly compare lesion-symptom maps for memory and language functions from two populations, a tumor versus a stroke population.

METHODS

Data from two different studies were combined. Both the brain tumor (N = 196) and stroke (N = 147) patient populations underwent neuropsychological testing and an MRI, pre-operatively for the tumor population and within three months after stroke. For this study, we selected two internationally widely used standardized cognitive tasks, the Rey Auditory Verbal Learning Test and the Verbal Fluency Test. We used a state-of-the-art machine learning-based, multivariate voxel-wise approach to produce lesion-symptom maps for these cognitive tasks for both populations separately and combined.

RESULTS

Our lesion-symptom mapping results for the separate patient populations largely followed the expected neuroanatomical pattern based on previous literature. Substantial differences in lesion distribution hindered direct comparison. Still, in brain areas with adequate coverage in both groups, considerable LSM differences between the two populations were present for both memory and fluency tasks. Post-hoc analyses of these locations confirmed that the cognitive consequences of focal brain damage varied between etiologies.

CONCLUSION

The differences in the lesion-symptom maps between the stroke and tumor population could partly be explained by differences in lesion volume and topography. Despite these methodological limitations, both the lesion-symptom mapping results and the post-hoc analyses confirmed that etiology matters when investigating the cognitive consequences of lesions with lesion-symptom mapping. Therefore, caution is advised with generalizing lesion-symptom results across etiologies.

Mapping lesion, structural disconnection, and functional disconnection to symptoms in semantic aphasia

Patients with semantic aphasia have impaired control of semantic retrieval, often accompanied by executive dysfunction following left hemisphere stroke. Many but not all of these patients have damage to the left inferior frontal gyrus, important for semantic and cognitive control. Yet semantic and cognitive control networks are highly distributed, including posterior as well as anterior components. Accordingly, semantic aphasia might not only reflect local damage but also white matter structural and functional disconnection. Here, we characterise the lesions and predicted patterns of structural and functional disconnection in individuals with semantic aphasia and relate these effects to semantic and executive impairment. Impaired semantic cognition was associated with infarction in distributed left-hemisphere regions, including in the left anterior inferior frontal and posterior temporal cortex. Lesions were associated with executive dysfunction within a set of adjacent but distinct left frontoparietal clusters. Performance on executive tasks was also associated with interhemispheric structural disconnection across the corpus callosum. In contrast, poor semantic cognition was associated with small left-lateralized structurally disconnected clusters, including in the left posterior temporal cortex. Little insight was gained from functional disconnection symptom mapping. These results demonstrate that while left-lateralized semantic and executive control regions are often damaged together in stroke aphasia, these deficits are associated with distinct patterns of structural disconnection, consistent with the bilateral nature of executive control and the left-lateralized yet distributed semantic control network.

New insights into anatomical connectivity along the anterior–posterior axis of the human hippocampus using in vivo quantitative fibre tracking

The hippocampus supports multiple cognitive functions including episodic memory. Recent work has highlighted functional differences along the anterior–posterior axis of the human hippocampus, but the neuroanatomical underpinnings of these differences remain unclear. We leveraged track-density imaging to systematically examine anatomical connectivity between the cortical mantle and the anterior–posterior axis of the in vivo human hippocampus. We first identified the most highly connected cortical areas and detailed the degree to which they preferentially connect along the anterior–posterior axis of the hippocampus. Then, using a tractography pipeline specifically tailored to measure the location and density of streamline endpoints within the hippocampus, we characterised where these cortical areas preferentially connect within the hippocampus. Our results provide new and detailed insights into how specific regions along the anterior–posterior axis of the hippocampus are associated with different cortical inputs/outputs and provide evidence that both gradients and circumscribed areas of dense extrinsic anatomical connectivity exist within the human hippocampus. These findings inform conceptual debates in the field and emphasise the importance of considering the hippocampus as a heterogeneous structure. Overall, our results represent a major advance in our ability to map the anatomical connectivity of the human hippocampus in vivo and inform our understanding of the neural architecture of hippocampal-dependent memory systems in the human brain.

The brain allows us to perceive and interact with our environment and to create and recall memories about our day-to-day lives. A sea-horse shaped structure in the brain, called the hippocampus, is critical for translating our perceptions into memories, and it does so in coordination with other brain regions. For example, different regions of the cerebral cortex (the outer layer of the brain) support different aspects of cognition, and pathways of information flow between the cerebral cortex and hippocampus underpin the healthy functioning of memory.

Decades of research conducted into the brains of non-human primates show that specific regions of the cerebral cortex anatomically connect with different parts of the hippocampus to support this information flow. These insights form the foundation for existing theoretical models of how networks of neurons in the hippocampus and the cerebral cortex are connected. However, the human cerebral cortex has greatly expanded during our evolution, meaning that patterns of connectivity in the human brain may diverge from those in the brains of non-human primates.

Deciphering human brain circuits in greater detail is crucial if we are to gain a better understanding of the structure and operation of the healthy human brain. However, obtaining comprehensive maps of anatomical connections between the hippocampus and cerebral cortex has been hampered by technical limitations. For example, magnetic resonance imaging (MRI), an approach that can be used to study the living human brain, suffers from insufficient image resolution.

To overcome these issues, Dalton et al. used an imaging technique called diffusion weighted imaging which is used to study white matter pathways in the brain. They developed a tailored approach to create high-resolution maps showing how the hippocampus anatomically connects with the cerebral cortex in the healthy human brain. Dalton et al. produced detailed maps illustrating which areas of the cerebral cortex have high anatomical connectivity with the hippocampus and how different parts of the hippocampus preferentially connect to different neural circuits in the cortex. For example, the experiments demonstrate that highly connected areas in a cortical region called the temporal cortex connect to very specific, circumscribed regions within the hippocampus.

These findings suggest that the hippocampus may consist of different neural circuits, each preferentially linked to defined areas of the cortex which are, in turn, associated with specific aspects of cognition. These observations further our knowledge of hippocampal-dependant memory circuits in the human brain and provide a foundation for the study of memory decline in aging and neurodegenerative diseases.

Structural disconnection-based prediction of poststroke depression

Poststroke depression (PSD) is a common complication of stroke. Brain network disruptions caused by stroke are potential biological determinants of PSD but their conclusive roles are unavailable. Our study aimed to identify the strategic structural disconnection (SDC) pattern for PSD at three months poststroke and assess the predictive value of SDC information. Our prospective cohort of 697 first-ever acute ischemic stroke patients were recruited from three hospitals in central China. Sociodemographic, clinical, psychological and neuroimaging data were collected at baseline and depression status was assessed at three months poststroke. Voxel-based disconnection-symptom mapping found that SDCs involving bilateral temporal white matter and posterior corpus callosum, as well as white matter next to bilateral prefrontal cortex and posterior parietal cortex, were associated with PSD. This PSD-specific SDC pattern was used to derive SDC scores for all participants. SDC score was an independent predictor of PSD after adjusting for all imaging and clinical-sociodemographic-psychological covariates (odds ratio, 1.25; 95% confidence interval, 1.07, 1.48; P = 0.006). Split-half replication showed the stability and generalizability of above results. When added to the clinical-sociodemographic-psychological prediction model, SDC score significantly improved the model performance and ranked the highest in terms of predictor importance. In conclusion, a strategic SDC pattern involving multiple lobes bilaterally is identified for PSD at 3 months poststroke. The SDC score is an independent predictor of PSD and may improve the predictive performance of the clinical-sociodemographic-psychological prediction model, providing new evidence for the brain-behavior mechanism and biopsychosocial theory of PSD.

A depression network caused by brain tumours

To systematically analyse and discuss whether suppressive heterogeneous brain tumours (BTs) belong to a common brain network and provide a theoretical basis for identifying BT patients with a high risk of depression and select therapeutic targets for clinical treatment. The PubMed database was systematically searched to obtain relevant case reports, and lesion locations were manually traced to standardised brain templates according to ITK-SNAP descriptive literature. Resting-state functional magnetic resonance imaging data sets were collected from 1,000 healthy adults aged 18-35 years. Each lesion location or functional connectivity area of the lesion network. Connectivity analysis was performed in an MN152 space, and Fisher z-transformation was applied to normalise the distribution of each value in the functional connectivity correlation map, and T maps of each tumour location network were calculated with the T score of individual voxels. This T score indicates the statistical significance of voxelwise connectivity at each tumour location. The lesion networks were thresholded at T = 7, creating binarised maps of brain regions connecting tumour locations, overlaying network maps to identify tumour-sensitive hubs and also assessing specific hubs with other conditional controls. A total of 18 patients describing depression following focal BTs were included. Of these cases, it was reported that depression-related tumours were unevenly distributed in the brain: 89% (16/18) were positively correlated with the left striatum, and the peak of the left striatum lesion network continuously overlapped. The depression-related tumour location was consistent with the tumour suppressor network (89%). These results suggest that sensitive hubs are aligned with specific networks, and specific hubs are aligned with sensitive networks. Brain tumour-related depression differs from acute lesion-related depression and may be related to the mapping of tumours to depression-related brain networks. It can provide an observational basis for the neuroanatomical basis of BT-related depression and a theoretical basis for identifying patients with BTs at high risk of depression and their subsequent clinical diagnosis and treatment.

Convergent gray matter alterations across drugs of abuse and network-level implications: A meta-analysis of structural MRI studies

BACKGROUND

Neuroimaging studies often consider brain alterations linked with substance abuse within the context of individual drugs (e.g., nicotine), while neurobiological theories of addiction emphasize common brain network-level alterations across drug classes. Using emergent meta-analytic techniques, we identified common structural brain alterations across drugs and characterized the functionally-connected networks with which such structurally altered regions interact.

METHODS

We identified 82 articles characterizing gray matter (GM) volume differences for substance users vs. controls. Using the anatomical likelihood estimation algorithm, we identified convergent GM reductions across drug classes. Next, we performed resting-state and meta-analytic functional connectivity analyses using each structurally altered region as a seed and computed whole-brain functional connectivity profiles as the union of both maps. We characterized an "extended network" by identifying brain areas demonstrating the highest degree of functional coupling with structurally impacted regions. Finally, hierarchical clustering was performed leveraging extended network nodes' functional connectivity profiles to delineate subnetworks.

RESULTS

Across drug classes, we identified medial frontal/ventromedial prefrontal, and multiple regions in anterior cingulate (ACC) and insula as regions displaying convergent GM reductions among users. Overlap of these regions' functional connectivity profiles identified ACC, inferior frontal, PCC, insula, superior temporal, and putamen as regions of an impacted extended network. Hierarchical clustering revealed 3 subnetworks closely corresponding to default mode (PCC, angular), salience (dACC, caudate), and executive control networks (dlPFC and parietal).

CONCLUSIONS

These outcomes suggest that substance-related structural brain alterations likely have implications for the functioning of canonical large-scale networks and the perpetuation of substance use and neurocognitive alterations.

Lesions causing post-stroke spasticity localize to a common brain network

Objective

The efficacy of clinical interventions for post-stroke spasticity (PSS) has been consistently unsatisfactory, probably because lesions causing PSS may occur at different locations in the brain, leaving the neuroanatomical substrates of spasticity unclear. Here, we investigated whether heterogeneous lesions causing PSS were localized to a common brain network and then identified the key nodes in this network.

Methods

We used 32 cases of PSS and the Human Connectome dataset (n = 1,000), using a lesion network mapping method to identify the brain regions that were associated with each lesion in patients with PSS. Functional connectivity maps of all lesions were overlaid to identify common connectivity. Furthermore, a split-half replication method was used to evaluate reproducibility. Then, the lesion network mapping results were compared with those of patients with post-stroke non-spastic motor dysfunction (n = 29) to assess the specificity. Next, both sensitive and specific regions associated with PSS were identified using conjunction analyses, and the correlation between these regions and PSS was further explored by correlation analysis.

Results

The lesions in all patients with PSS were located in different cortical and subcortical locations. However, at least 93% of these lesions (29/32) had functional connectivity with the bilateral putamen and globus pallidus. These connections were highly repeatable and specific, as compared to those in non-spastic patients. In addition, the functional connectivity between lesions and bilateral putamen and globus pallidus in patients with PSS was positively correlated with the degree of spasticity.

Conclusion

We identified that lesions causing PSS were localized to a common functional connectivity network defined by connectivity to the bilateral putamen and globus pallidus. This network may best cover the locations of lesions causing PSS. The putamen and globus pallidus may be potential key regions in PSS. Our findings complement previous neuroimaging studies on PSS, contributing to identifying patients with stroke at high risk for spasticity at an early stage, and may point to PSS-specific brain stimulation targets.

A precise language network revealed by the independent component-based lesion mapping in post-stroke aphasia

Brain lesion mapping studies have provided the strongest evidence regarding the neural basis of cognition. However, it remained a problem to identify symptom-specific brain networks accounting for observed clinical and neuroanatomical heterogeneity. Independent component analysis (ICA) is a statistical method that decomposes mixed signals into multiple independent components. We aimed to solve this issue by proposing an independent component-based lesion mapping (ICLM) method to identify the language network in patients with moderate to severe post-stroke aphasia. Lesions were first extracted from 49 patients with post-stroke aphasia as masks applied to fMRI data in a cohort of healthy participants to calculate the functional connectivity (FC) within the masks and non-mask brain voxels. ICA was further performed on a reformatted FC matrix to extract multiple independent networks. Specifically, we found that one of the lesion-related independent components (ICs) highly resembled classical language networks. Moreover, the damaged level within the language-related lesioned network is strongly associated with language deficits, including aphasia quotient, naming, and auditory comprehension scores. In comparison, none of the other two traditional lesion mapping methods found any regions responsible for language dysfunction. The language-related lesioned network extracted with the ICLM method showed high specificity in detecting aphasia symptoms compared with the performance of resting ICs and classical language networks. In total, we detected a precise language network in patients with aphasia and proved its efficiency in the relationship with language symptoms. In general, our ICLM could successfully identify multiple lesion-related networks from complicated brain diseases, and be used as an effective tool to study brain-behavior relationships and provide potential biomarkers of particular clinical behavioral deficits.

Early effect of thrombolysis on structural brain network organisation after anterior‐circulation stroke in the randomized WAKE‐UP trial

The symptoms of acute ischemic stroke can be attributed to disruption of the brain network architecture. Systemic thrombolysis is an effective treatment that preserves structural connectivity in the first days after the event. Its effect on the evolution of global network organisation is, however, not well understood. We present a secondary analysis of 269 patients from the randomized WAKE‐UP trial, comparing 127 imaging‐selected patients treated with alteplase with 142 controls who received placebo. We used indirect network mapping to quantify the impact of ischemic lesions on structural brain network organisation in terms of both global parameters of segregation and integration, and local disruption of individual connections. Network damage was estimated before randomization and again 22 to 36 h after administration of either alteplase or placebo. Evolution of structural network organisation was characterised by a loss in integration and gain in segregation, and this trajectory was attenuated by the administration of alteplase. Preserved brain network organization was associated with excellent functional outcome. Furthermore, the protective effect of alteplase was spatio‐topologically nonuniform, concentrating on a subnetwork of high centrality supported in the salvageable white matter surrounding the ischemic cores. This interplay between the location of the lesion, the pathophysiology of the ischemic penumbra, and the spatial embedding of the brain network explains the observed potential of thrombolysis to attenuate topological network damage early after stroke. Our findings might, in the future, lead to new brain network‐informed imaging biomarkers and improved prognostication in ischemic stroke.

Time to retire the serial Papez circuit: Implications for space, memory, and attention

After more than 80 years, Papez serial circuit remains a hugely influential concept, initially for emotion, but in more recent decades, for memory. Here, we show how this circuit is anatomically and mechanistically naïve as well as outdated. We argue that a new conceptualisation is necessitated by recent anatomical and functional findings that emphasize the more equal, working partnerships between the anterior thalamic nuclei and the hippocampal formation, along with their neocortical interactions in supporting, episodic memory. Furthermore, despite the importance of the anterior thalamic for mnemonic processing, there is growing evidence that these nuclei support multiple aspects of cognition, only some of which are directly associated with hippocampal function. By viewing the anterior thalamic nuclei as a multifunctional hub, a clearer picture emerges of extra-hippocampal regions supporting memory. The reformulation presented here underlines the need to retire Papez serially processing circuit.

Lesion network mapping for symptom localization: recent developments and future directions

PURPOSE OF REVIEW

Focal lesions causing specific neurological or psychiatric symptoms can occur in multiple different brain locations, complicating symptom localization. Here, we review lesion network mapping, a technique used to aid localization by mapping lesion-induced symptoms to brain circuits rather than individual brain regions. We highlight recent examples of how this technique is being used to investigate clinical entities and identify therapeutic targets.

RECENT FINDINGS

To date, lesion network mapping has successfully been applied to more than 40 different symptoms or symptom complexes. In each case, lesion locations were combined with an atlas of human brain connections (the human connectome) to map heterogeneous lesion locations causing the same symptom to a common brain circuit. This approach has lent insight into symptoms that have been difficult to localize using other techniques, such as hallucinations, tics, blindsight, and pathological laughter and crying. Further, lesion network mapping has recently been applied to lesions that improve symptoms, such as tremor and addiction, which may translate into new therapeutic targets.

SUMMARY

Lesion network mapping can be used to map lesion-induced symptoms to brain circuits rather than single brain regions. Recent findings have provided insight into long-standing clinical mysteries and identified testable treatment targets for circuit-based and symptom-based neuromodulation.

Neural substrates of motivational dysfunction across neuropsychiatric conditions: Evidence from meta-analysis and lesion network mapping

Motivational dysfunction constitutes one of the fundamental dimensions of psychopathology cutting across traditional diagnostic boundaries. However, it is unclear whether there is a common neural circuit responsible for motivational dysfunction across neuropsychiatric conditions. To address this issue, the current study combined a meta-analysis on psychiatric neuroimaging studies of reward/loss anticipation and consumption (4308 foci, 438 contrasts, 129 publications) with a lesion network mapping approach (105 lesion cases). Our meta-analysis identified transdiagnostic hypoactivation in the ventral striatum (VS) for clinical/at-risk conditions compared to controls during the anticipation of both reward and loss. Moreover, the VS subserves a key node in a distributed brain network which encompasses heterogeneous lesion locations causing motivation-related symptoms. These findings do not only provide the first meta-analytic evidence of shared neural alternations linked to anticipatory motivation-related deficits, but also shed novel light on the role of VS dysfunction in motivational impairments in terms of both network integration and psychological functions. Particularly, the current findings suggest that motivational dysfunction across neuropsychiatric conditions is rooted in disruptions of a common brain network anchored in the VS, which contributes to motivational salience processing rather than encoding positive incentive values.

Causal mapping of human brain function

Mapping human brain function is a long-standing goal of neuroscience that promises to inform the development of new treatments for brain disorders. Early maps of human brain function were based on locations of brain damage or brain stimulation that caused a functional change. Over time, this approach was largely replaced by technologies such as functional neuroimaging, which identify brain regions in which activity is correlated with behaviours or symptoms. Despite their advantages, these technologies reveal correlations, not causation. This creates challenges for interpreting the data generated from these tools and using them to develop treatments for brain disorders. A return to causal mapping of human brain function based on brain lesions and brain stimulation is underway. New approaches can combine these causal sources of information with modern neuroimaging and electrophysiology techniques to gain new insights into the functions of specific brain areas. In this Review, we provide a definition of causality for translational research, propose a continuum along which to assess the relative strength of causal information from human brain mapping studies and discuss recent advances in causal brain mapping and their relevance for developing treatments.

A brain network for deep brain stimulation induced cognitive decline in Parkinson's disease

Deep brain stimulation is an effective treatment for Parkinson's disease but can be complicated by side-effects such as cognitive decline. There is often a delay before this side-effect is apparent and the mechanism is unknown, making it difficult to identify patients at risk or select appropriate deep brain stimulation settings. Here, we test whether connectivity between the stimulation site and other brain regions is associated with cognitive decline following deep brain stimulation. First, we studied a unique patient cohort with cognitive decline following subthalamic deep brain stimulation for Parkinson's disease (n = 10) where reprogramming relieved the side-effect without loss of motor benefit. Using resting state functional connectivity data from a large normative cohort (n = 1000), we computed connectivity between each stimulation site and the subiculum, an a priori brain region functionally connected to brain lesions causing memory impairment. Connectivity between deep brain stimulation sites and this same subiculum region was significantly associated with deep brain stimulation induced cognitive decline (P < 0.02). We next performed a data-driven analysis to identify connections most associated with deep brain stimulation induced cognitive decline. Deep brain stimulation sites causing cognitive decline (versus those that did not) were more connected to the anterior cingulate, caudate nucleus, hippocampus, and cognitive regions of the cerebellum (PFWE < 0.05). The spatial topography of this deep brain stimulation-based circuit for cognitive decline aligned with an a priori lesion-based circuit for memory impairment (P = 0.017). To begin translating these results into a clinical tool that might be used for deep brain stimulation programming, we generated a 'heat map' in which the intensity of each voxel reflects the connectivity to our cognitive decline circuit. We then validated this heat map using an independent dataset of Parkinson's disease patients in which cognitive performance was measured following subthalamic deep brain stimulation (n = 33). Intersection of deep brain stimulation sites with our heat map was correlated with changes in the Mattis dementia rating scale 1 year after lead implantation (r = 0.39; P = 0.028). Finally, to illustrate how this heat map might be used in clinical practice, we present a case that was flagged as 'high risk' for cognitive decline based on intersection of the patient's deep brain stimulation site with our heat map. This patient had indeed experienced cognitive decline and our heat map was used to select alternative deep brain stimulation parameters. At 14 days follow-up the patient's cognition improved without loss of motor benefit. These results lend insight into the mechanism of deep brain stimulation induced cognitive decline and suggest that connectivity-based heat maps may help identify patients at risk and who might benefit from deep brain stimulation reprogramming.

Lesion network mapping of mania using different normative connectomes

Lesion network mapping is a neuroimaging technique that explores the network of regions functionally connected to lesions causing a common syndrome. The technique uses resting state functional connectivity from large databases of healthy individuals, i.e., connectomes, and has allowed for important insight into the potential network mechanisms underlying several neuropsychiatric disorders. However, concerns regarding reproducibility have arisen, that may be due to the use of different connectomes, with variable MRI acquisition parameters and preprocessing methods. Here, we tested the impact of using different connectomes on the results of lesion network mapping for mania. We found results were reliable and consistent independent of the connectome used.

The anterior thalamic nuclei: core components of a tripartite episodic memory system

Standard models of episodic memory focus on hippocampal-parahippocampal interactions, with the neocortex supplying sensory information and providing a final repository of mnemonic representations. However, recent advances have shown that other regions make distinct and equally critical contributions to memory. In particular, there is growing evidence that the anterior thalamic nuclei have a number of key cognitive functions that support episodic memory. In this article, we describe these findings and argue for a core, tripartite memory system, comprising a 'temporal lobe' stream (centred on the hippocampus) and a 'medial diencephalic' stream (centred on the anterior thalamic nuclei) that together act on shared cortical areas. We demonstrate how these distributed brain regions form complementary and necessary partnerships in episodic memory formation.

The Neuropsychiatric Approach to the Assessment of Patients in Neurology

Neuropsychiatry is a clinical neuroscience specialty focused on the evaluation and treatment of patients who present with symptoms at the intersection of neurology and psychiatry. Neuropsychiatrists assess and manage the cognitive, affective, behavioral, and perceptual manifestations of disorders of the central nervous system. Although fellowship training in behavioral neurology-neuropsychiatry exists in the United States and several other countries internationally, the need for neuropsychiatric expertise greatly outweighs the number of specialists in practice or training. This article serves as a primer for both neurologists and psychiatrists seeking to improve or refresh their knowledge of the neuropsychiatric assessment, including detailing aspects of the history-taking, physical exam, psychometric testing, and associated diagnostic work-up. In doing so, we urge the next generation of neurologists and psychiatrists to take on both the opportunity and challenge to work at the intersection of both clinical neuroscience specialties using an integrated neuropsychiatric perspective.

Association of Infarct Topography and Outcome After Endovascular Thrombectomy in Patients With Acute Ischemic Stroke

BACKGROUND AND OBJECTIVES

The care of patients with large vessel occlusion (LVO) stroke has been revolutionized by endovascular thrombectomy (EVT). While EVT has a large effect size, most patients treated with EVT remain disabled or die within 90 days. A better understanding of outcomes may influence EVT selection criteria, novel therapies, and prognostication. We sought to identify associations between outcomes and brain regions involved in ischemic lesions.

METHODS

For this cohort study, consecutive patients with LVO who were treated with EVT and underwent post-EVT MRI were identified from a tertiary referral center (2011-2019). Acute ischemic lesions were manually segmented from diffusion-weighted imaging and spatially normalized. Individual lesions were parcellated (atlas-defined 94 cortical regions, 14 subcortical nuclei, 20 white matter tracts) and reduced to 10 essential lesion patterns with the use of unsupervised dimensionality reduction techniques. Ninety-day modified Rankin Scale (mRS) score (>2) was modeled via bayesian regression, taking the 10 lesion patterns as inputs and controlling for lesion size, age, sex, acute NIH Stroke Scale (NIHSS) score, alteplase, prior stroke, intracerebral hemorrhage, and good reperfusion (Thrombolysis in Cerebral Infarction 2b-3). In comparative analyses, 90-day mRS score was modeled considering covariates only, and compartment-wise relevances for acute stroke severity and 90-day mRS score were evaluated.

RESULTS

There were 151 patients with LVO identified (age 68 ± 15 years, 52% female). The median NIHSS score was 16 (interquartile range 13-20); 56% had mRS score >2. Lesion locations predictive of 90-day mRS score involved bilateral but left hemispherically more pronounced precentral and postcentral gyri, insular and opercular cortex, and left putamen and caudate (area under the curve 0.91, highest probability density interval [HPDI] covering 90% certainty 0.90-0.92). The lesion location model outperformed the simpler model relying on covariates only (bayesian model comparison of 97% weight to the model with vs 3% weight to the model without lesion location). While lesions affecting subcortical nuclei had the highest relevance for stroke severity (posterior distribution mean 0.75, 90% HPDI 0.256-1.31), lesions affecting white matter tracts had the highest relevance for 90-day mRS score (0.656, 90% HPDI 0.0864-1.12).

DISCUSSION

These data describe the significance for outcomes of specific brain regions involved in ischemic lesions on MRI after EVT. Future work in additional datasets is needed to confirm these granular findings.

A Neural Circuit for Spirituality and Religiosity Derived From Patients With Brain Lesions

BACKGROUND

Over 80% of the global population consider themselves religious, with even more identifying as spiritual, but the neural substrates of spirituality and religiosity remain unresolved.

METHODS

In two independent brain lesion datasets (N₁ = 88; N₂ = 105), we applied lesion network mapping to test whether lesion locations associated with spiritual and religious belief map to a specific human brain circuit.

RESULTS

We found that brain lesions associated with self-reported spirituality map to a brain circuit centered on the periaqueductal gray. Intersection of lesion locations with this same circuit aligned with self-reported religiosity in an independent dataset and previous reports of lesions associated with hyper-religiosity. Lesion locations causing delusions and alien limb syndrome also intersected this circuit.

CONCLUSIONS

These findings suggest that spirituality and religiosity map to a common brain circuit centered on the periaqueductal gray, a brainstem region previously implicated in fear conditioning, pain modulation, and altruistic behavior.

Sex-specific lesion pattern of functional outcomes after stroke

Stroke represents a considerable burden of disease for both men and women. However, a growing body of literature suggests clinically relevant sex differences in the underlying causes, presentations and outcomes of acute ischaemic stroke. In a recent study, we reported sex divergences in lesion topographies: specific to women, acute stroke severity was linked to lesions in the left-hemispheric posterior circulation. We here determined whether these sex-specific brain manifestations also affect long-term outcomes. We relied on 822 acute ischaemic patients [age: 64.7 (15.0) years, 39% women] originating from the multi-centre MRI-GENIE study to model unfavourable outcomes (modified Rankin Scale >2) based on acute neuroimaging data in a Bayesian hierarchical framework. Lesions encompassing bilateral subcortical nuclei and left-lateralized regions in proximity to the insula explained outcomes across men and women (area under the curve = 0.81). A pattern of left-hemispheric posterior circulation brain regions, combining left hippocampus, precuneus, fusiform and lingual gyrus, occipital pole and latero-occipital cortex, showed a substantially higher relevance in explaining functional outcomes in women compared to men [mean difference of Bayesian posterior distributions (men - women) = -0.295 (90% highest posterior density interval = -0.556 to -0.068)]. Once validated in prospective studies, our findings may motivate a sex-specific approach to clinical stroke management and hold the promise of enhancing outcomes on a population level.

Network Localization of Unconscious Visual Perception in Blindsight

OBJECTIVE

Blindsight is a disorder where brain injury causes loss of conscious but not unconscious visual perception. Prior studies have produced conflicting results regarding the neuroanatomical pathways involved in this unconscious perception.

METHODS

We performed a systematic literature search to identify lesion locations causing visual field loss in patients with blindsight (n = 34) and patients without blindsight (n = 35). Resting state functional connectivity between each lesion location and all other brain voxels was computed using a large connectome database (n = 1,000). Connections significantly associated with blindsight (vs no blindsight) were identified.

RESULTS

Functional connectivity between lesion locations and the ipsilesional medial pulvinar was significantly associated with blindsight (family wise error p = 0.029). No significant connectivity differences were found to other brain regions previously implicated in blindsight. This finding was independent of methods (eg, flipping lesions to the left or right) and stimulus type (moving vs static).

INTERPRETATION

Connectivity to the ipsilesional medial pulvinar best differentiates lesion locations associated with blindsight versus those without blindsight. Our results align with recent data from animal models and provide insight into the neuroanatomical substrate of unconscious visual abilities in patients. ANN NEUROL 2022;91:217-224.

Functional neuroanatomy of mania

Mania, the diagnostic hallmark of bipolar disorder, is an episodic disturbance of mood, sleep, behavior, and perception. Improved understanding of the neurobiology of mania is expected to allow for novel avenues to address current challenges in its diagnosis and treatment. Previous research focusing on the impairment of functional neuronal circuits and brain networks has resulted in heterogenous findings, possibly due to a focus on bipolar disorder and its several phases, rather than on the unique context of mania. Here we present a comprehensive overview of the evidence regarding the functional neuroanatomy of mania. Our interpretation of the best available evidence is consistent with a convergent model of lateralized circuit dysfunction in mania, with hypoactivity of the ventral prefrontal cortex in the right hemisphere, and hyperactivity of the amygdala, basal ganglia, and anterior cingulate cortex in the left hemisphere of the brain. Clarification of dysfunctional neuroanatomic substrates of mania may contribute not only to improve understanding of the neurobiology of bipolar disorder overall, but also highlights potential avenues for new circuit-based therapeutic approaches in the treatment of mania.