A two-level model of interindividual anatomo-functional variability of the brain and its implications for neurosurgery

Augmented surgical decision-making for glioblastoma: integrating AI tools into education and practice

Surgical decision-making for glioblastoma poses significant challenges due to its complexity and variability. This study investigates the potential of artificial intelligence (AI) tools in improving "decision-making processes" for glioblastoma surgery. A systematic review of literature identified 10 relevant studies, primarily focused on predicting resectability and surgery-related neurological outcomes. AI tools, especially rooted in radiomics and connectomics, exhibited promise in predicting resection extent through precise tumor segmentation and tumor-network relationships. However, they demonstrated limited effectiveness in predicting postoperative neurological due to dynamic and less quantifiable nature of patient-related factors. Recognizing these challenges, including limited datasets and the interpretability requirement in medical applications, underscores the need for standardization, algorithm optimization, and addressing variability in model performance and then further validation in clinical settings. While AI holds potential, it currently does not possess the capacity to emulate the nuanced decision-making process utilized by experienced neurosurgeons in the comprehensive approach to glioblastoma surgery.

Optimizing spatial specificity and signal quality in fNIRS: an overview of potential challenges and possible options for improving the reliability of real-time applications

The optical brain imaging method functional near-infrared spectroscopy (fNIRS) is a promising tool for real-time applications such as neurofeedback and brain-computer interfaces. Its combination of spatial specificity and mobility makes it particularly attractive for clinical use, both at the bedside and in patients' homes. Despite these advantages, optimizing fNIRS for real-time use requires careful attention to two key aspects: ensuring good spatial specificity and maintaining high signal quality. While fNIRS detects superficial cortical brain regions, consistently and reliably targeting specific regions of interest can be challenging, particularly in studies that require repeated measurements. Variations in cap placement coupled with limited anatomical information may further reduce this accuracy. Furthermore, it is important to maintain good signal quality in real-time contexts to ensure that they reflect the true underlying brain activity. However, fNIRS signals are susceptible to contamination by cerebral and extracerebral systemic noise as well as motion artifacts. Insufficient real-time preprocessing can therefore cause the system to run on noise instead of brain activity. The aim of this review article is to help advance the progress of fNIRS-based real-time applications. It highlights the potential challenges in improving spatial specificity and signal quality, discusses possible options to overcome these challenges, and addresses further considerations relevant to real-time applications. By addressing these topics, the article aims to help improve the planning and execution of future real-time studies, thereby increasing their reliability and repeatability.

The subcortical basis of subjective sleep quality

Study objectives

To assess the association between self-reported sleep quality and cortical and subcortical local morphometry.

Methods

Sleep and neuroanatomical data from the full release of the young adult Human Connectome Project dataset were analyzed. Sleep quality was operationalized with the Pittsburgh Sleep Quality Index (PSQI). Local cortical and subcortical morphometry was measured with subject-specific segmentations resulting in voxelwise thickness measurements for cortex and relative (i.e., cross-sectional) local atrophy measurements for subcortical regions.

Results

Relative atrophy across several subcortical regions, including bilateral pallidum, striatum, and thalamus, was negatively associated with both global PSQI score and sub-components of the index related to sleep duration, efficiency, and quality. Conversely, we found no association between cortical morphometric measurements and self-reported sleep quality.

Conclusions

This work shows that subcortical regions such as the bilateral pallidum, thalamus, and striatum, might be interventional targets to ameliorate self-reported sleep quality.

A common low dimensional structure of cognitive impairment in stroke and brain tumors

INTRODUCTION

Neuropsychological studies infer brain-behavior relationships from focal lesions like stroke and tumors. However, these pathologies impair brain function through different mechanisms even when they occur at the same brain's location. The aim of this study was to compare the profile of cognitive impairment in patients with brain tumors vs. stroke and examine the correlation with lesion location in each pathology.

METHODS

Patients with first time stroke (n = 77) or newly diagnosed brain tumors (n = 76) were assessed with a neuropsychological battery. Their lesions were mapped with MRI scans. Test scores were analyzed using principal component analysis (PCA) to measure their correlation, and logistic regression to examine differences between pathologies. Next, with ridge regression we examined whether lesion features (location, volume) were associated with behavioral performance.

RESULTS

The PCA showed a similar cognitive impairment profile in tumors and strokes with three principal components (PCs) accounting for about half of the individual variance. PC1 loaded on language, verbal memory, and executive/working memory; PC2 loaded on general performance, visuo-spatial attention and memory, and executive functions; and, PC3 loaded on calculation, reading and visuo-spatial attention. The average lesion distribution was different, and lesion location was correlated with cognitive deficits only in stroke. Logistic regression found language and calculation more affected in stroke, and verbal memory and verbal fluency more affected in tumors.

CONCLUSIONS

A similar low dimensional set of behavioral impairments was found both in stroke and brain tumors, even though each pathology caused some specific deficits in different domains. The lesion distribution was different for stroke and tumors and correlated with behavioral impairment only in stroke.

Intraoperative identification of functional brain areas with RGB imaging using statistical parametric mapping: Simulation and clinical studies

Complementary technique to preoperative fMRI and electrical brain stimulation (EBS) for glioma resection could improve dramatically the surgical procedure and patient care. Intraoperative RGB optical imaging is a technique for localizing functional areas of the human cerebral cortex that can be used during neurosurgical procedures. However, it still lacks robustness to be used with neurosurgical microscopes as a clinical standard. In particular, a robust quantification of biomarkers of brain functionality is needed to assist neurosurgeons. We propose a methodology to evaluate and optimize intraoperative identification of brain functional areas by RGB imaging. This consist in a numerical 3D brain model based on Monte Carlo simulations to evaluate intraoperative optical setups for identifying functional brain areas. We also adapted fMRI Statistical Parametric Mapping technique to identify functional brain areas in RGB videos acquired for 12 patients. Simulation and experimental results were consistent and showed that the intraoperative identification of functional brain areas is possible with RGB imaging using deoxygenated hemoglobin contrast. Optical functional identifications were consistent with those provided by EBS and preoperative fMRI. We also demonstrated that a halogen lighting may be particularity adapted for functional optical imaging. We showed that an RGB camera combined with a quantitative modeling of brain hemodynamics biomarkers can evaluate in a robust way the functional areas during neurosurgery and serve as a tool of choice to complement EBS and fMRI.

Development of an educational method to rethink and learn oncological brain surgery in an "a la carte" connectome-based perspective

BACKGROUND

Understanding the structural connectivity of white matter tracts (WMT) and their related functions is a prerequisite to implementing an "a la carte" "connectomic approach" to glioma surgery. However, accessible resources facilitating such an approach are lacking. Here we present an educational method that is readily accessible, simple, and reproducible that enables the visualization of WMTs on individual patient images via an atlas-based approach.

METHODS

Our method uses the patient's own magnetic resonance imaging (MRI) images and consists of three main steps: data conversion, normalization, and visualization; these are accomplished using accessible software packages and WMT atlases. We implement our method on three common cases encountered in glioma surgery: a right supplementary motor area tumor, a left insular tumor, and a left temporal tumor.

RESULTS

Using patient-specific perioperative MRIs with open-sourced and co-registered atlas-derived WMTs, we highlight the critical subnetworks requiring specific surgical monitoring identified intraoperatively using direct electrostimulation mapping with cognitive monitoring. The aim of this didactic method is to provide the neurosurgical oncology community with an accessible and ready-to-use educational tool, enabling neurosurgeons to improve their knowledge of WMTs and to better learn their oncologic cases, especially in glioma surgery using awake mapping.

CONCLUSIONS

Taking no more than 3-5 min per patient and irrespective of their resource settings, we believe that this method will enable junior surgeons to develop an intuition, and a robust 3-dimensional imagery of WMT by regularly applying it to their cases both before and after surgery to develop an "a la carte" connectome-based perspective to glioma surgery.

Oncological and functional neurosurgery: Perspectives for the decade regarding diffuse gliomas

For decades, diffuse glioma (DG) studies mostly focused on oncological considerations, whereas functional outcomes received less attention. Currently, because overall survival has increased in DG, especially in low-grade glioma (overall survival > 15 years), quality of life including neurocognitive and behavioral aspects should be assessed and preserved more systematically, particularly regarding surgery. Indeed, early maximal tumor removal results in greater survival in both high-grade and low-grade gliomas, leading to propose "supra-marginal" resection, with excision of the peritumoral zone in diffuse neoplasms. To minimize functional risks while maximizing the extent of resection, traditional "tumor-mass resection" is replaced by "connectome-guided resection" conducted under awake mapping, taking into account inter-individual brain anatomo-functional variability. A better understanding of the dynamic interplay between DG progression and reactional neuroplastic mechanisms is critical to adapt a personalized multistage therapeutic strategy, with integration of functional neurooncological (re)operation(s) in a multimodal management scheme including repeated medical therapies. Because the therapeutic armamentarium remains limited, the aims of this paradigmatic shift are to predict one/several step(s) ahead glioma behavior, its modifications, and compensatory neural networks reconfiguration over time in order to optimize the onco-functional benefit of each treatment - either in isolation or in combination with others - in human beings bearing a chronic tumoral disease while enjoying an active familial and socio-professional life as close as possible to their expectations. Thus, new ecological endpoints such as return to work should be incorporated into future DG trials. "Preventive neurooncology" might also be envisioned, by proposing a screening policy to discover and treat incidental glioma earlier.

Preoperative language tract integrity is a limiting factor in recovery from aphasia after glioma surgery

Aphasia can occur in a broad range of pathological conditions that affect cortical or subcortical structures. Here we test the hypothesis that white matter integrity of language pathways assessed by preoperative diffusion tensor imaging (DTI) is associated with language performance and its recovery after glioma resection. 27 patients with preoperative DTI were included. Segmentation of the arcuate fascicle (AF), the inferior fronto-occipital fascicle (IFOF), the inferior longitudinal fascicle (ILF), the superior longitudinal fascicle (SLF), and the uncinate fascicle (UF) was performed with a fully-connected neural network (FCNN, TractSeg). Median fractional anisotropy (FA) was extracted from the resulting volumes as surrogate marker for white matter integrity and tested for correlation with clinical parameters. After correction for demographic data and multiple testing, preoperative white matter integrity of the IFOF, the ILF, and the UF in the left hemisphere were independently and significantly associated with aphasia three months after surgery. Comparison between patients with and without aphasia three months after surgery revealed significant differences in preoperative white matter integrity of the left AF (p = 0.021), left IFOF (p = 0.015), left ILF (p = 0.003), left SLF (p = 0.001, p = 0.021, p = 0.043 for respective sub-bundles 1-3), left UF (p = 0.041) and the right AF (p = 0.027). Preoperative assessment of white matter integrity of the language network by time-efficient MRI protocols and FCNN-driven segmentation may assist in the evaluation of postoperative rehabilitation potential in glioma patients.

Anterior transtemporal endoscopic selective amygdalohippocampectomy: a virtual and cadaveric feasibility study

PURPOSE

Selective amygdalohippocampectomy (SelAH) is one of the most common surgical treatments for mesial temporal sclerosis. Microsurgical approaches are associated with the risk of cognitive and visual deficits due to damage to the cortex and white matter (WM) pathways. Our objective is to test the feasibility of an endoscopic approach through the anterior middle temporal gyrus (aMTG) to perform a SelAH.

METHODS

Virtual simulation with MRI scans of ten patients (20 hemispheres) was used to identify the endoscopic trajectory through the aMTG. A cadaveric study was performed on 22 specimens using a temporal craniotomy. The anterior part of the temporal horn was accessed using a tubular retractor through the aMTG after performing a 1.5 cm corticectomy at 1.5 cm posterior to the temporal pole. Then, an endoscope was introduced. SeIAH was performed in each specimen. The specimens underwent neuronavigation-assisted endoscopic SeIAH to confirm our surgical trajectory. WM dissection using Klingler's technique was performed on five specimens to assess WM integrity.

RESULTS

This approach allowed the identification of collateral eminence, lateral ventricular sulcus, choroid plexus, inferior choroidal point, amygdala, hippocampus, and fimbria. SelAH was successfully performed on all specimens, and CT neuronavigation confirmed the planned trajectory. WM dissection confirmed the integrity of language pathways and optic radiations.

CONCLUSIONS

Endoscopic SelAH through the aMTG can be successfully performed with a corticectomy of 15 mm, presenting a reduced risk of vascular injury and damage to WM pathways. This could potentially help to reduce cognitive and visual deficits associated with SelAH.

A Personalized Longitudinal Strategy in Low-Grade Glioma Patients: Predicting Oncological and Neural Interindividual Variability and Its Changes over Years to Think One Step Ahead

Diffuse low-grade glioma (LGG) is a rare cerebral cancer, mostly involving young adults with an active life at diagnosis. If left untreated, LGG widely invades the brain and becomes malignant, generating neurological worsening and ultimately death. Early and repeat treatments for this incurable tumor, including maximal connectome-based surgical resection(s) in awake patients, enable postponement of malignant transformation while preserving quality of life owing to constant neural network reconfiguration. Due to considerable interindividual variability in terms of LGG course and consecutive cerebral reorganization, a multistage longitudinal strategy should be tailored accordingly in each patient. It is crucial to predict how the glioma will progress (changes in growth rate and pattern of migration, genetic mutation, etc.) and how the brain will adapt (changes in patterns of spatiotemporal redistribution, possible functional consequences such as epilepsy or cognitive decline, etc.). The goal is to anticipate therapeutic management, remaining one step ahead in order to select the optimal (re-)treatment(s) (some of them possibly kept in reserve), at the appropriate time(s) in the evolution of this chronic disease, before malignization and clinical worsening. Here, predictive tumoral and non-tumoral factors, and their ever-changing interactions, are reviewed to guide individual decisions in advance based on patient-specific markers, for the treatment of LGG.

Inter-individual variability in dorsal stream dynamics during word production

The current standard model of language production involves a sensorimotor dorsal stream connecting areas in the temporo-parietal junction with those in the inferior frontal gyrus and lateral premotor cortex. These regions have been linked to various aspects of word production such as phonological processing or articulatory programming, primarily through neuropsychological and functional imaging group studies. Most if not all the theoretical descriptions of this model imply that the same network should be identifiable across individual speakers. We tested this hypothesis by quantifying the variability of activation observed across individuals within each dorsal stream anatomical region. This estimate was based on electrical activity recorded directly from the cerebral cortex with millisecond accuracy in awake epileptic patients clinically implanted with intracerebral depth electrodes for pre-surgical diagnosis. Each region's activity was quantified using two different metrics-intra-cerebral evoked related potentials and high gamma activity-at the level of the group, the individual and the recording contact. The two metrics show simultaneous activation of parietal and frontal regions during a picture naming task, in line with models that posit interactive processing during word retrieval. They also reveal different levels of between-patient variability across brain regions, except in core auditory and motor regions. The independence and non-uniformity of cortical activity estimated through the two metrics push the current model towards sub-second and sub-region explorations focused on individualized language speech production. Several hypotheses are considered for this within-region heterogeneity.

Visual working memory recruits two functionally distinct alpha rhythms in posterior cortex

Oscillatory activity in the human brain is dominated by posterior alpha oscillations (8-14 Hz), which have been shown to be functionally relevant in a wide variety of cognitive tasks. Although posterior alpha oscillations are commonly considered a single oscillator anchored at an individual alpha frequency (IAF; ∼10 Hz), previous work suggests that IAF reflects a spatial mixture of different brain rhythms. In this study, we assess whether Independent Component Analysis (ICA) can disentangle functionally distinct posterior alpha rhythms in the context of visual short-term memory retention. Magnetoencephalography (MEG) was recorded in 33 subjects while performing a visual working memory task. Group analysis at sensor level suggested the existence of a single posterior alpha oscillator that increases in power and decreases in frequency during memory retention. Conversely, single-subject analysis of independent components revealed the existence of two dissociable alpha rhythms: one that increases in power during memory retention (Alpha1) and another one that decreases in power (Alpha2). Alpha1 and Alpha2 rhythms were differentially modulated by the presence of visual distractors (Alpha1 increased in power while Alpha2 decreased) and had an opposite relationship with accuracy (positive for Alpha1 and negative for Alpha2). In addition, Alpha1 rhythms showed a lower peak frequency, a narrower peak width, a greater relative peak amplitude and a more central source than Alpha2 rhythms. Together, our results demonstrate that modulations in posterior alpha oscillations during short-term memory retention reflect the dynamics of at least two distinct brain rhythms with different functions and spatiospectral characteristics.Significance statementAlpha oscillations are the most prominent feature of the human brain's electrical activity, and consist of rhythmic neuronal activity in posterior parts of the cortex. Alpha is usually considered a single brain rhythm that changes in power and frequency to support cognitive operations. We here show that posterior alpha entails at least two dissociable rhythms with distinct functions and characteristics. These findings could solve previous inconsistencies in the literature regarding the direction of task-related alpha power/frequency modulations and their relation to cognitive performance. In addition, the existence of two distinct posterior alpha rhythms could have important consequences for the design of neurostimulation protocols aimed at modulating alpha oscillations and subsequently cognition.

Leveraging manifold learning techniques to explore white matter anomalies: An application of the TractLearn pipeline in epilepsy

An accurate description of brain white matter anatomy in vivo remains a challenge. However, technical progress allows us to analyze structural variations in an increasingly sophisticated way. Current methods of processing diffusion MRI data now make it possible to correct some limiting biases. In addition, the development of statistical learning algorithms offers the opportunity to analyze the data from a new perspective. We applied newly developed tractography models to extract quantitative white matter parameters in a group of patients with chronic temporal lobe epilepsy. Furthermore, we implemented a statistical learning workflow optimized for the MRI diffusion data - the TractLearn pipeline - to model inter-individual variability and predict structural changes in patients. Finally, we interpreted white matter abnormalities in the context of several other parameters reflecting clinical status, as well as neuronal and cognitive functioning for these patients. Overall, we show the relevance of such a diffusion data processing pipeline for the evaluation of clinical populations. The "global to fine scale" funnel statistical approach proposed in this study also contributes to the understanding of neuroplasticity mechanisms involved in refractory epilepsy, thus enriching previous findings.

Repeated Awake Surgical Resection(s) for Recurrent Diffuse Low-Grade Gliomas: Why, When, and How to Reoperate?

Early maximal surgical resection is the first treatment in diffuse low-grade glioma (DLGG), because the reduction of tumor volume delays malignant transformation and extends survival. Awake surgery with intraoperative mapping and behavioral monitoring enables to preserve quality of life (QoL). However, because of the infiltrative nature of DLGG, relapse is unavoidable, even after (supra)total resection. Therefore, besides chemotherapy and radiotherapy, the question of reoperation(s) is increasingly raised, especially because patients with DLGG usually enjoy a normal life with long-lasting projects. Here, the purpose is to review the literature in the emerging field of iterative surgeries in DLGG. First, long-term follow-up results showed that patients with DLGG who underwent multiple surgeries had an increased survival (above 17 years) with preservation of QoL. Second, the criteria guiding the decision to reoperate and defining the optimal timing are discussed, mainly based on the dynamic intercommunication between the glioma relapse (including its kinetics and pattern of regrowth) and the reactional cerebral reorganization—i.e., mechanisms underpinning reconfiguration within and across neural networks to enable functional compensation. Third, how to adapt medico-surgical strategy to this individual spatiotemporal brain tumor interplay is detailed, by considering the perpetual changes in connectome. These data support early reoperation in recurrent DLGG, before the onset of symptoms and before malignant transformation. Repeat awake resection(s) should be integrated in a global management including (neo)adjuvant medical treatments, to enhance long-lasting functional and oncological outcomes. The prediction of potential and limitation of neuroplasticity at each step of the disease must be improved to anticipate personalized multistage therapeutic attitudes.

Group-level stability but individual variability of neurocognitive status after awake resections of right frontal IDH-mutated glioma

Awake surgery for low-grade gliomas is currently considered the best procedure to improve the extent of resection and guarantee a "worth living life" for patients, meaning avoiding not only motor but also cognitive deficits. However, tumors located in the right hemisphere, especially in the right frontal lobe, are still rarely operated on in awake condition; one of the reasons possibly being that there is little information in the literature describing the rates and nature of long-lasting neuropsychological deficits following resection of right frontal glioma. To investigate long-term cognitive deficits after awake surgery in right frontal IDH-mutated glioma. We retrospectively analyzed a consecutive series of awake surgical resections between 2012 and 2020 for right frontal IDH-mutated glioma. We studied the patients' subjective complaints and objective neuropsychological evaluations, both before and after surgery. Our results were then put in perspective with the literature. Twenty surgical cases (including 5 cases of redo surgery) in eighteen patients (medium age: 42.5 [range 26-58]) were included in the study. The median preoperative volume was 37 cc; WHO grading was II, III and IV in 70%, 20%, and 10% of cases, respectively. Preoperatively, few patients had related subjective cognitive or behavioral impairment, while evaluations revealed mild deficits in 45% of cases, most often concerning executive functions, attention, working memory and speed processing. Immediate postoperative evaluations showed severe deficits of executive functions in 75% of cases but also attentional deficits (65%), spatial neglect (60%) and behavioral disturbances (apathy, aprosodia/amimia, emotional sensitivity, anosognosia). Four months after surgery, although psychometric z-scores were unchanged at the group level, individual evaluations showed a slight decrease of performance in 9/20 cases for at least one of the following domains: executive functions, speed processing, attention, semantic cognition, social cognition. Our results are generally consistent with those of the literature, confirming that the right frontal lobe is a highly eloquent area and suggesting the importance of operating these patients in awake conditions.

White Matter Tracts and Diffuse Lower-Grade Gliomas: The Pivotal Role of Myelin Plasticity in the Tumor Pathogenesis, Infiltration Patterns, Functional Consequences and Therapeutic Management

For many decades, interactions between diffuse lower-grade glioma (LGG) and brain connectome were neglected. However, the neoplasm progression is intimately linked to its environment, especially the white matter (WM) tracts and their myelin status. First, while the etiopathogenesis of LGG is unclear, this tumor seems to appear during the adolescence, and it is mostly located within anterior and associative cerebral areas. Because these structures correspond to those which were myelinated later in the brain maturation process, WM myelination could play a role in the development of LGG. Second, WM fibers and the myelin characteristics also participate in LGG diffusion, since glioma cells migrate along the subcortical pathways, especially when exhibiting a demyelinated phenotype, which may result in a large invasion of the parenchyma. Third, such a migratory pattern can induce functional (neurological, cognitive and behavioral) disturbances, because myelinated WM tracts represent the main limitation of neuroplastic potential. These parameters are critical for tailoring an individualized therapeutic strategy, both (i) regarding the timing of active treatment(s) which must be proposed earlier, before a too wide glioma infiltration along the WM bundles, (ii) and regarding the anatomic extent of surgical resection and irradiation, which should take account of the subcortical connectivity. Therefore, the new science of connectomics must be integrated in LGG management, based upon an improved understanding of the interplay across glioma dissemination within WM and reactional neural networks reconfiguration, in order to optimize long-term oncological and functional outcomes. To this end, mechanisms of activity-dependent myelin plasticity should be better investigated.

Functional Approaches to the Surgery of Brain Gliomas

In the surgery of gliomas, recent years have witnessed unprecedented theoretical and technical development, which extensively increased indication to surgery. On one hand, it has been solidly demonstrated the impact of gross total resection on life expectancy. On the other hand, the paradigm shift from classical cortical localization of brain function towards connectomics caused by the resurgence of awake surgery and the advent of tractography has permitted safer surgeries focused on subcortical white matter tracts preservation and allowed for surgical resections within regions, such as Broca's area or the primary motor cortex, which were previously deemed inoperable. Furthermore, new asleep electrophysiological techniques have been developed whenever awake surgery is not an option, such as operating in situations of poor compliance (including paediatric patients) or pre-existing neurological deficits. One such strategy is the use of intraoperative neurophysiological monitoring (IONM), enabling the identification and preservation of functionally defined, but anatomically ambiguous, cortico-subcortical structures through mapping and monitoring techniques. These advances tie in with novel challenges, specifically risk prediction and the impact of neuroplasticity, the indication for tumour resection beyond visible borders, or supratotal resection, and most of all, a reappraisal of the importance of the right hemisphere from early psychosurgery to mapping and preservation of social behaviour, executive control, and decision making.Here we review current advances and future perspectives in a functional approach to glioma surgery.

Tackling the Complexity of Lesion-Symptoms Mapping: How to Bridge the Gap Between Data Scientists and Clinicians?

Accurate and predictive lesion-symptoms mapping is a major goal in the field of clinical neurosciences. Recent studies have called for a reappraisal of the results given by the standard univariate voxel-based lesion-symptom mapping technique, emphasizing the need of developing multivariate methods. While the organization of large datasets and their analysis with machine learning (ML) approaches represents an opportunity to increase prediction accuracy, the complexity and dimensionality of the problem remain a major obstacle. Acknowledging the difficulty of inferring individual outcomes from the observation of spatial patterns of lesions, we propose here to base prediction on new individuals on models of brain connectivity, whereby the disruption of a given network predicts the occurrence of selective deficits. Well-suited ML tools are necessary to capture the relevant information from limited datasets and perform reliable inference.

Evolving Landscape of Long Non-coding RNAs in Cerebrospinal Fluid: A Key Role From Diagnosis to Therapy in Brain Tumors

Long non-coding RNAs (lncRNAs) are a type of non-coding RNAs that act as molecular fingerprints and modulators of many pathophysiological processes, particularly in cancer. Specifically, lncRNAs can be involved in the pathogenesis and progression of brain tumors, affecting stemness/differentiation, replication, invasion, survival, DNA damage response, and chromatin dynamics. Furthermore, the aberrations in the expressions of these transcripts can promote treatment resistance, leading to tumor recurrence. The development of next-generation sequencing technologies and the creation of lncRNA-specific microarrays have boosted the study of lncRNA etiology. Cerebrospinal fluid (CSF) directly mirrors the biological fluid of biochemical processes in the brain. It can be enriched for small molecules, peptides, or proteins released by the neurons of the central nervous system (CNS) or immune cells. Therefore, strategies that identify and target CSF lncRNAs may be attractive as early diagnostic and therapeutic options. In this review, we have reviewed the studies on CSF lncRNAs in the context of brain tumor pathogenesis and progression and discuss their potential as biomarkers and therapeutic targets.

The death of localizationism: The concepts of functional connectome and neuroplasticity deciphered by awake mapping, and their implications for best care of brain-damaged patients

Although clinical neurology was mainly erected on the dogma of localizationism, numerous reports have described functional recovery after lesions involving presumed non-compensable areas in an inflexible view of brain processing. Here, the purpose is to review new insights into the functional connectome and the mechanisms underpinning neural plasticity, gained from intraoperative direct electrostimulation mapping and real-time behavioral monitoring in awake patients, combined with perioperative neuropsychological and neuroimaging data. Such longitudinal anatomo-functional correlations resulted in the reappraisal of classical models of cognition, especially by highlighting the dynamic interplay within and between neural circuits, leading to the concept of meta-network (network of networks), as well as by emphasizing that subcortical connectivity is the main limitation of neuroplastic potential. Beyond their contribution to basic neurosciences, these findings might also be helpful for an optimization of care for brain-damaged patients, such as in resective oncological or epilepsy neurosurgery in structures traditionally deemed inoperable (e.g., in Broca's area) as well as for elaborating new programs of functional rehabilitation, eventually combined with transcranial brain stimulation, aiming to change the connectivity patterns in order to enhance cognitive competences following cerebral injury.

The inferior fronto-occipital fascicle: a century of controversies from anatomy theaters to operative neurosurgery

INTRODUCTION

Since its first description in the early 19th century, the inferior frontooccipital fascicle (IFOF) and its anatomo-functional features were neglected in the neuroscientific literature for the last century. In the last decade, the rapid development of in vivo imaging for the reconstruction of white matter (WM) connectivity (i.e., tractography) and the consequent interest in more traditional ex vivo methods (postmortem dissection) have allowed a renewed debate about course, termination territories, anatomical relationships, and functional roles of this fascicle.

EVIDENCE ACQUISITION

We reviewed the main current knowledge concerning the structural and functional anatomy of the IFOF and possible implications in neurosurgical practice.

EVIDENCE SYNTHESIS

The IFOF connects the occipital cortex, the temporo-basal areas, the superior parietal lobule, and the pre-cuneus to the frontal lobe, passing through the ventral third of subinsular WM of the external capsule. This wide distribution of cortical terminations provides multimodal integration between several functional networks, including language, non-verbal semantic processing, object identification, visuo-spatial processing and planning, reading, facial expression recognition, memory and conceptualization, emotional and neuropsychological behavior. This anatomo-functional organization has important implication also in neurosurgical practice, especially when approaching the frontal, insular, temporo-parieto-occipital regions and the ventricular system.

CONCLUSIONS

The IFOF is the most extensive associative bundle of the human connectome. Its multi-layer organization reflects important implications in many aspects of brain functional processing. Accurate awareness of IFOF functional anatomy and integration between multimodal datasets coming from different sources has crucial implications for both neuroscientific knowledge and quality of neurosurgical treatments.

Brain connectomics applied to oncological neuroscience: from a traditional surgical strategy focusing on glioma topography to a meta-network approach

The classical way for surgical selection and planning in cerebral glioma mainly focused on tumor topography. The emerging science of connectomics, which aims of mapping brain connectivity, resulted in a paradigmatic shift from a modular account of cerebral organization to a meta-network perspective. Adaptive behavior is actually mediated by constant changes in interactions within and across large-scale delocalized neural systems underlying conation, cognition, and emotion. Here, to optimize the onco-functional balance of glioma surgery, the purpose is to switch toward a connectome-based resection taking account of both relationships between the tumor and critical distributed circuits (especially subcortical pathways) as well as the perpetual instability of the meta-network. Such dynamic in the neural spatiotemporal integration permits functional reallocation leading to neurological recovery after massive resection in structures traditionally thought as "inoperable." This better understanding of connectome increases benefit/risk ratio of surgery (i) by selecting resection in areas deemed "eloquent" according to a localizationist dogma; (ii), conversely, by refining intraoperative awake cognitive mapping and monitoring in so-called non-eloquent areas; (iii) by improving preoperative information, enabling an optimal selection of intrasurgical tasks tailored to the patient's wishes; (iv) by developing an "oncological disconnection surgery"; (v) by defining a personalized multistep surgical strategy adapted to individual brain reshaping potential; and (vi) ultimately by preserving environmentally and socially appropriate behavior, including return to work, while increasing the extent of (possibly repeated) resection(s). Such a holistic vision of neural processing can enhance reliability of connectomal surgery in oncological neuroscience and may also be applied to restorative neurosurgery.

Individual versus task differences in slow potential generators

Average slow potentials (SPs) can be computed from any voluntary task, minimally involving attention to anticipated stimuli. Their topography when recorded by large electrode arrays even during simple tasks is complex, multifocal, and its generators appear to be equally multifocal and highly variable across subjects. Various sources of noise of course contaminate such averages and must contribute to the topographic complexity. Here, we report a study in which the non-averaged SP band (0 to 1 Hz) was analyzed by independent components (ICA), from 256 channel recordings of 18 subjects, during four task conditions (resting, visual attention, CPT, and Stroop). We intended to verify whether the replicable SP generators (between two separate day sessions) modeled as current density reconstruction on structural MRI sets were individual-specific, and if putative task-related differences were systematic across subjects. Typically, 3 ICA components (out of 10) explained SPs in each task and subject, and their combined generators were highly variable across subjects: although some occipito-temporal and medial temporal areas contained generators in most subjects; the overall patterns were obviously variable, with no single area common to all 18 subjects. Linear regression modeling to compare combined generators (from all ICA components) between tasks and sessions showed significantly higher correlations between the four tasks than between sessions for each task. Moreover, it was clear that no common task-specific areas could be seen across subjects. Those results represent one more instance in which individual case analyses favor the hypothesis of individual-specific patterns of cortical activity, regardless of task conditions. We discuss this hypothesis with respect to results from the beta band, from individual-case fMRI studies, and its corroboration by functional neurosurgery and the neuropsychology of focal lesions.

Functional linguistic specificity of the left frontal aslant tract for spontaneous speech fluency: Evidence from intraoperative language mapping

The left frontal aslant tract (FAT) has been proposed to be relevant for language, and specifically for spontaneous speech fluency. However, there is missing causal evidence that stimulation of the FAT affects spontaneous speech, and not language production in general. We present a series of 12 neurosurgical cases with awake language mapping of the cortex near the left FAT. Tasks for language mapping included the commonly used action picture naming, and sentence completion, tapping more specifically into spontaneous speech. A task dissociation was found in 10 participants: while being stimulated on specific sites, they were able to name a picture but could not complete a sentence. Overlaying of these sites on preoperative white-matter tract reconstructions revealed that in each individual case they were located on cortical terminations of the FAT. This corroborates the language functional specificity of the left FAT as a tract underlying fluent spontaneous speech.

What Direct Electrostimulation of the Brain Taught Us About the Human Connectome: A Three-Level Model of Neural Disruption

For a long time, the relevance of the information provided by direct electrostimulation (DES) for mapping brain functions was debated. Recently, major advances in intraoperative DES for guiding resection of cerebral tumors in awake patients enabled the validation of this method and its increased utilization in basic neurosciences. Indeed, in addition to the cortical stimulation used for many decades in epilepsy surgery, axonal mapping was developed thanks to DES of the white matter tracts, giving original insights into the neural connectivity. Moreover, functional results collected during intrasurgical mapping have been correlated with neuropsychological performances before and after DES-guided resection, and with perioperative neuroimaging data. Thus, it was evidenced that DES offers the unique opportunity to identify both cortical and subcortical structures critical for cerebral functions. Here, the first aim is to propose a three-level model of DES-generated functional disruption, able to explain the behavioral consequences elicited during awake surgery, i.e., (i) DES of an input/output unimodal (e.g., somatosensory or motor) network inducing "positive" responses (as involuntary movement); (ii) DES of a distributed specialized network inducing a within-system disruption leading to specific "negative" disorders (e.g., exclusive language deficit with no other disorders); (iii) DES generating an inter-system disruption leading to more complex behavioral disturbances (e.g., the inability to perform dual-task while each function can be performed separately). Second, in light of this model, original findings gained from DES concerning the human connectome, complementary to those provided by functional neuroimaging (FNI), are reviewed. Further longitudinal multimodal investigations are needed to explore neuroplasticity mechanisms.

Why brain radiation therapy should take account of the individual structural and functional connectivity: Toward an irradiation "à la carte"

Although radiation therapy (RT) is a main treatment of brain tumors, delayed cerebral toxicity may lead to cognitive deteriorations with adverse effects on quality of life. Despite technological advances in RT, the concept of brain connectome has not yet been incorporated in the strategy of irradiation. Because white matter tracts represent the main limitation of neuroplasticity, tumor surgery is increasingly performed with awake cortical-subcortical mapping. Here, the purpose is to reinforce the link between cognitive neurosciences and neurooncology, which is critical for neurosurgeons but also for medical oncologists, especially brain radiation oncologists. The goal is to optimize RT planning by sparing individual critical neural networks. A redefinition of "organs at risk" should be proposed, beyond the few structures (such as brainstem, optic pathway, pituitary gland, hippocampi) which are classically preserved for brain radiation, by considering the structural and functional connectivity in order to evolve toward a RT "à la carte".

No evidence for differences among language regions in their temporal receptive windows

The "core language network" consists of left frontal and temporal regions that are selectively engaged in linguistic processing. Whereas functional differences among these regions have long been debated, many accounts propose distinctions in terms of representational grain-size-e.g., words vs. phrases/sentences-or processing time-scale, i.e., operating on local linguistic features vs. larger spans of input. Indeed, the topography of language regions appears to overlap with a cortical hierarchy reported by Lerner et al. (2011) wherein mid-posterior temporal regions are sensitive to low-level features of speech, surrounding areas-to word-level information, and inferior frontal areas-to sentence-level information and beyond. However, the correspondence between the language network and this hierarchy of "temporal receptive windows" (TRWs) is difficult to establish because the precise anatomical locations of language regions vary across individuals. To directly test this correspondence, we first identified language regions in each participant with a well-validated task-based localizer, which confers high functional resolution to the study of TRWs (traditionally based on stereotactic coordinates); then, we characterized regional TRWs with the naturalistic story listening paradigm of Lerner et al. (2011), which augments task-based characterizations of the language network by more closely resembling comprehension "in the wild". We find no region-by-TRW interactions across temporal and inferior frontal regions, which are all sensitive to both word-level and sentence-level information. Therefore, the language network as a whole constitutes a unique stage of information integration within a broader cortical hierarchy.

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.

Overall survival time prediction for high-grade glioma patients based on large-scale brain functional networks

High-grade glioma (HGG) is a lethal cancer with poor outcome. Accurate preoperative overall survival (OS) time prediction for HGG patients is crucial for treatment planning. Traditional presurgical and noninvasive OS prediction studies have used radiomics features at the local lesion area based on the magnetic resonance images (MRI). However, the highly complex lesion MRI appearance may have large individual variability, which could impede accurate individualized OS prediction. In this paper, we propose a novel concept, namely brain connectomics-based OS prediction. It is based on presurgical resting-state functional MRI (rs-fMRI) and the non-local, large-scale brain functional networks where the global and systemic prognostic features rather than the local lesion appearance are used to predict OS. We propose that the connectomics features could capture tumor-induced network-level alterations that are associated with prognosis. We construct both low-order (by means of sparse representation with regional rs-fMRI signals) and high-order functional connectivity (FC) networks (characterizing more complex multi-regional relationship by synchronized dynamics FC time courses). Then, we conduct a graph-theoretic analysis on both networks for a jointly, machine-learning-based individualized OS prediction. Based on a preliminary dataset (N = 34 with bad OS, mean OS, ~400 days; N = 34 with good OS, mean OS, ~1030 days), we achieve a promising OS prediction accuracy (86.8%) on separating the individuals with bad OS from those with good OS. However, if using only conventionally derived descriptive features (e.g., age and tumor characteristics), the accuracy is low (63.2%). Our study highlights the importance of the rs-fMRI and brain functional connectomics for treatment planning.

Structural Variability Across the Primate Brain: A Cross-Species Comparison

A large amount of variability exists across human brains; revealed initially on a small scale by postmortem studies and, more recently, on a larger scale with the advent of neuroimaging. Here we compared structural variability between human and macaque monkey brains using grey and white matter magnetic resonance imaging measures. The monkey brain was overall structurally as variable as the human brain, but variability had a distinct distribution pattern, with some key areas showing high variability. We also report the first evidence of a relationship between anatomical variability and evolutionary expansion in the primate brain. This suggests a relationship between variability and stability, where areas of low variability may have evolved less recently and have more stability, while areas of high variability may have evolved more recently and be less similar across individuals. We showed specific differences between the species in key areas, including the amount of hemispheric asymmetry in variability, which was left-lateralized in the human brain across several phylogenetically recent regions. This suggests that cerebral variability may be another useful measure for comparison between species and may add another dimension to our understanding of evolutionary mechanisms.

Focal left prefrontal lesions and cognitive impairment: A multivariate lesion-symptom mapping approach

Despite network studies of the human brain have brought consistent evidence of brain regions with diverse functional roles, the neuropsychological approach has mainly focused on the functional specialization of individual brain regions. Relatively few neuropsychological studies try to understand whether the severity of cognitive impairment across multiple cognitive abilities can be related to focal brain injuries. Here we approached this issue by applying a latent variable modeling of the severity of cognitive impairment in brain tumor patients, followed by multivariate lesion-symptom methods identifying brain regions critically involved in multiple cognitive abilities. We observed that lesions in confined left lateral prefrontal areas including the inferior frontal junction produced the most severe cognitive deficits, above and beyond tumor histology. Our findings support the recently suggested integrated albeit modular view of brain functional organization, according to which specific brain regions are highly involved across different sub-networks and subserve a vast range of cognitive abilities. Defining such brain regions is relevant not only theoretically but also clinically, since it may facilitate tailored tumor resections and improve cognitive surgical outcomes.

Surface-Based Spatial Pyramid Matching of Cortical Regions for Analysis of Cognitive Performance

We propose a method to analyze the relationship between the shape of functional regions of the cortex and cognitive measures, such as reading ability and vocabulary knowledge. Functional regions on the cortical surface can vary not only in size and shape but also in topology and position relative to neighboring regions. Standard diffeomorphism-based shape analysis tools do not work well here because diffeomorphisms are unable to capture these topological differences, which include region splitting and merging across subjects. State-of-the-art cortical surface shape analyses compute derived regional properties (scalars), such as regional volume, cortical thickness, curvature, and gyrification index. However, these methods cannot compare the full extent of topological or shape differences in cortical regions. We propose icosahedral spatial pyramid matching (ISPM) of region borders computed on the surface of a sphere to capture this variation in regional topology, position, and shape. We then analyze how this variation corresponds to measures of cognitive performance. We compare our method to other approaches and find that it is indeed informative to consider aspects of shape beyond the standard approaches. Analysis is performed using a subset of 27 test/retest subjects from the Human Connectome Project in order to understand both the effectiveness and reproducibility of this method.

Higher-Order Surgical Questions for Diffuse Low-Grade Gliomas: Supramaximal Resection, Neuroplasticity, and Screening

Diffuse low-grade glioma (DLGG) is a brain neoplasm that migrates within the connectome and that becomes malignant if left untreated. Early and maximal safe surgical resection by means of awake mapping enables a significant improvement of survival and quality of life. Supramaximal functional-based resection seems to prevent DLGG malignant transformation. Neuroplasticity is helpful to remove DLGG in eloquent areas. When radical excision cannot be achieved due to invasion of critical neural networks, cerebral remapping over time may lead to a reoperation with an optimized resection. To discover and treat DLGG earlier, a screening in the general population should be considered.

Beyond Language: Mapping Cognition and Emotion

The use of intraoperative cognitive mapping and monitoring during awake surgery is not new, but this surgical approach has undergone important changes in recent years, especially in the context of low-grade glioma surgery. This rapid development is related to the growing awareness from neurosurgeons that sustaining quality of life in patients with a long-survival expectancy implies assessment and preservation of a range of important functions during surgery, beyond "overt" functions, such as language or motricity. Here we describe the different behavioral paradigms typically used, and how they are selected and modulated to identify and spare critical brain-wide cognitive systems.

Resection of gliomas deemed inoperable by neurosurgeons based on preoperative imaging studies

OBJECTIVE

Maximal safe resection is a primary objective in the management of gliomas. Despite this objective, surgeons and referring physicians may, on the basis of radiological studies alone, assume a glioma to be unresectable. Because imaging studies, including functional MRI, may not localize brain functions (such as language) with high fidelity, this simplistic approach may exclude some patients from what could be a safe resection. Intraoperative direct electrical stimulation (DES) allows for the accurate localization of functional areas, thereby enabling maximal resection of tumors, including those that may appear inoperable based solely on radiological studies. In this paper the authors describe the extent of resection (EOR) and functional outcomes following resections of tumors deemed inoperable by referring physicians and neurosurgeons.

METHODS

The authors retrospectively examined the cases of 58 adult patients who underwent glioma resection within 6 months of undergoing a brain biopsy of the same lesion at an outside hospital. All patients exhibited unifocal supratentorial disease and preoperative Karnofsky Performance Scale scores ≥ 70. The EOR and 6-month functional outcomes for this population were characterized.

RESULTS

Intraoperative DES mapping was performed on 96.6% (56 of 58) of patients. Nearly half of the patients (46.6%, 27 of 58) underwent an awake surgical procedure with DES. Overall, the mean EOR was 87.6% ± 13.6% (range 39.0%–100%). Gross-total resection (resection of more than 99% of the preoperative tumor volume) was achieved in 29.3% (17 of 58) of patients. Subtotal resection (95%–99% resection) and partial resection (PR; < 95% resection) were achieved in 12.1% (7 of 58) and 58.6% (34 of 58) of patients, respectively. Of the cases that involved PR, the mean EOR was 79.4% ± 12.2%. Six months after surgery, no patient was found to have a new postoperative neurological deficit. The majority of patients (89.7%, 52 of 58) were free of neurological deficits both pre- and postoperatively. The remainder of patients exhibited either residual but stable deficits (5.2%, 3 of 58) or complete correction of preoperative deficits (5.2%, 3 of 58).

CONCLUSIONS

The use of DES enabled maximal safe resections of gliomas deemed inoperable by referring neurosurgeons. With rare exceptions, tumor resectability cannot be determined solely by radiological studies.

Paradoxes of evidence-based medicine in lower-grade glioma: To treat the tumor or the patient?

Brain lower-grade gliomas (LGG) usually occur in young adults who enjoy an active life. This tumor has a high risk of malignant transformation resulting in neurologic deterioration and finally death. Early and multistage therapeutic management can increase survival over 10 years. Preservation of functional neural networks and quality of life is crucial. In the era of evidence-based medicine, the issues discussed are those associated with the design, analysis, and clinical application of randomized controlled trials (RCTs) for LGG. RCTs should take account of the following: considerable variability in the natural course of LGG; limited prognostic value of molecular biology at the individual level; large variability of brain organization across patients; technical and conceptual progress of therapies over years; combination or repetition of iterative treatments, taken as a whole and not only in isolation; and long-term consequences on oncologic and functional outcomes. As it is difficult to translate the results of an RCT into benefits for a unique patient with LGG, personalized decisions must be made by considering the tumor behavior, individual pattern of neuroplasticity, and patient needs, and not by administrating a standardized protocol exclusively based on an RCT.

Photogrammetry of the Human Brain: A Novel Method for Three-Dimensional Quantitative Exploration of the Structural Connectivity in Neurosurgery and Neurosciences

BACKGROUND

Anatomic awareness of the structural connectivity of the brain is mandatory for neurosurgeons, to select the most effective approaches for brain resections. Although standard microdissection is a validated technique to investigate the different white matter (WM) pathways and to verify the results of tractography, the possibility of interactive exploration of the specimens and reliable acquisition of quantitative information has not been described. Photogrammetry is a well-established technique allowing an accurate metrology on highly defined three-dimensional (3D) models. The aim of this work is to propose the application of the photogrammetric technique for supporting the 3D exploration and the quantitative analysis on the cerebral WM connectivity.

METHODS

The main perisylvian pathways, including the superior longitudinal fascicle and the arcuate fascicle were exposed using the Klingler technique. The photogrammetric acquisition followed each dissection step. The point clouds were registered to a reference magnetic resonance image of the specimen. All the acquisitions were coregistered into an open-source model.

RESULTS

We analyzed 5 steps, including the cortical surface, the short intergyral fibers, the indirect posterior and anterior superior longitudinal fascicle, and the arcuate fascicle. The coregistration between the magnetic resonance imaging mesh and the point clouds models was highly accurate. Multiple measures of distances between specific cortical landmarks and WM tracts were collected on the photogrammetric model.

CONCLUSIONS

Photogrammetry allows an accurate 3D reproduction of WM anatomy and the acquisition of unlimited quantitative data directly on the real specimen during the postdissection analysis. These results open many new promising neuroscientific and educational perspectives and also optimize the quality of neurosurgical treatments.

Improving surgical outcome for gliomas with intraoperative mapping

INTRODUCTION

Radical glioma resection improves overall survival, both in low-grade and high-grade glial tumors. However, preservation of the quality of life is also crucial. Areas covered: Due to the diffuse feature of gliomas, which invade the central nervous system, and due to considerable variations of brain organization among patients, an individual cerebral mapping is mandatory to solve the classical dilemma between the oncological and functional issues. Because functional neuroimaging is not reliable enough, intraoperative electrical stimulation, especially in awake patients benefiting from a real-time cognitive monitoring, is the best way to increase the extent of resection while sparing eloquent neural networks. Expert commentary: Here, we propose a paradigmatic shift from image-guided resection to functional mapping-guided resection, based on the study of the dynamic distribution of delocalized cortico-subcortical circuits at the individual level, i.e., the investigation of brain connectomics and neuroplastic potential. This surgical philosophy results in an improvement of both oncological outcomes and quality of life. This highlights the need to reinforce the link between glioma surgery and cognitive neurosciences.

Electrical stimulation of the dorsolateral prefrontal cortex impairs semantic cognition

OBJECTIVE

To identify the prefrontal cortical structures causally involved in verbal and nonverbal semantic cognition in both cerebral hemispheres.

METHODS

We retrospectively screened the intraoperative brain mapping data of 584 patients who underwent neurosurgery for neoplastic tumor under local anesthesia with direct cortical electrostimulation. Patients were included if they were right-handed, recently diagnosed with a diffuse low-grade glioma, and had a positive language mapping for verbal (naming task) and nonverbal (visual semantic association task) semantic cognition in the prefrontal cortex (n = 49). Among these, 30 were tested intraoperatively with both the naming and the semantic association tasks, while 19 were tested with the naming task only. Subsequently, each semantic site (n = 85) was plotted individually onto a common stereotaxic space for detailed analyses.

RESULTS

The cortical sites associated with verbal semantic disturbances (n = 45) were distributed in the pars opercularis (n = 14) and pars triangularis (n = 19) of the left inferior frontal gyrus, and left dorsolateral prefrontal cortex (dlPFC, n = 12); only 2 sites were observed in the right dlPFC. In contrast, all but one cortical site associated with nonverbal semantic disturbances were observed in the left dorsolateral cortex (n = 8). In the right hemisphere, the same disturbances were found in the dlPFC (n = 14) and pars opercularis (n = 2).

CONCLUSION

The present study demonstrated the critical role of the dlPFC in the semantic network, and indicated its specific and bilateral involvement in nonverbal semantic cognition in right-handers.

Higher similarity in beta topography between tasks than subjects

We have recently provided evidence for highly idiosyncratic topographic distributions of beta oscillations (as well as slow potentials) across individuals. More recently, by emphasizing the analysis of similarity instead of differences across tasks, we concluded that differences between an attention task and quiet resting may be negligible or at least unsystematic across subjects. Due to the possibility that individual differences could be due to noise in a wide sense or some inherent instability of beta activity, we designed a replication study to explicitly test whether pairs of individuals matched for head size and shape would still present less similar beta topography than each individual between sessions or tasks. We used independent component analysis (ICA) for an exhaustive decomposition of beta activity in a visual attention task and in quiet resting, recorded by 256-channel EEG in 20 subjects, on two separate days. We evaluated whether each ICA component obtained in one task and in one given individual could be explained by a linear regression model based on the topographic patterns of the complementary task (correlation between one component with a linear combination of components from complementary conditions), of the same task in a second session and of a matched individual. Results again showed a high topographic similarity between conditions, as previously seen between reasoning and simple visual attention beta correlates. From an overall number of 16 components representing brain activity obtained for the tasks (out of 60 originally computed where the remaining were considered noise), over 92% could satisfactorily be explained by the complementary task. Although the similarity between sessions was significantly smaller than between tasks on each day, the similarity between sessions was statistically higher than that between subjects in a highly significant way. We discuss the possible biases of group spatial averaging and the emphasis on differences as opposed to similarities, and noise in a wide sense, as the main causes of hardly replicable findings on task-related forms of activity and the inconclusive state of a universal functional mapping of cortical association areas.

Can neuroimaging help aphasia researchers? Addressing generalizability, variability, and interpretability

Neuroimaging studies of individuals with brain damage seek to link brain structure and activity to cognitive impairments, spontaneous recovery, or treatment outcomes. To date, such studies have relied on the critical assumption that a given anatomical landmark corresponds to the same functional unit(s) across individuals. However, this assumption is fallacious even across neurologically healthy individuals. Here, we discuss the severe implications of this issue, and argue for an approach that circumvents it, whereby: (i) functional brain regions are defined separately for each subject using fMRI, allowing for inter-individual variability in their precise location; (ii) the response profile of these subject-specific regions are characterized using various other tasks; and (iii) the results are averaged across individuals, guaranteeing generalizabliity. This method harnesses the complementary strengths of single-case studies and group studies, and it eliminates the need for post hoc "reverse inference" from anatomical landmarks back to cognitive operations, thus improving data interpretability.