Social interactions play a central role in shaping brain function, but neuroscientific research on interactive social behavior has been limited by the restrictions of brain imaging environments. Although a growing body of neuroimaging research situates participants in real-time social interactive contexts, questions remain about the brain systems critical for understanding social interaction. This study addresses three primary questions: 1) Is there a common network of brain regions that underlies diverse forms of social interaction? 2) Are there dissociable brain systems that contribute to different aspects of social interactive behavior? 3) What are the brain networks and cognitive functions associated with the socially interactive brain? We implemented a systematic search of the human neuroimaging literature to find studies involving social interaction - participants were socially engaged and interacted with perceived social partners in real-time - that contrasted against non-socially interactive control conditions. We used coordinate-based meta-analysis (CBMA) of 108 studies to elucidate common social interaction brain regions. We further analyzed subsets of studies to probe social engagement with a human (versus non-human) partner, interactive (versus non-interactive) social contexts, and reciprocal initiating (participant elicits a response from a partner) and responding (to partners actions). Finally, we used the Brainmap and Neurosynth databases to conduct meta-analytic coactivation modeling (MACM) and functional decoding to better characterize the neurocognitive systems associated with social interaction. The overarching CBMA uncovered significant convergence in ten brain areas that cut across different large-scale brain networks. Follow-up analyses suggest that regions of the reward system contribute to perceived social engagement, regions of the ventral attention network are associated with reciprocal interaction, and partially dissociable brain systems relate to initiating and responding behaviors. MACM and functional decoding results suggest that 3-4 overlapping neurocognitive systems underlie social interaction: default mode network (temporoparietal junction, medial prefrontal cortex, precuneus, and cerebellum); lateral frontoparietal regions associated with cognitive control processes; and intermediary midcingulo-insular areas that are associated with reward and emotion. The current study used a data-driven investigation of the neuroimaging literature to advance our understanding of the neural and cognitive systems critical for human social interaction. Our findings suggest that the myriad forms of social interaction may be subserved by a common network of brain areas that traverse multiple neurocognitive systems and adds support to emerging theories proposing the centrality of social interaction in human brain function.
Based on an assumption of movement control optimality in reach-to-grasp movements, we have recently developed a mathematical model of transport-aperture coordination (TAC), according to which the hand-target distance is a function of hand velocity and acceleration, aperture magnitude, and aperture velocity and acceleration (Rand et al. in Exp Brain Res 188:263-274, 2008). Reach-to-grasp movements were performed by young adults under four different reaching speeds and two different transport distances. The residual error magnitude of fitting the above model to data across different trials and subjects was minimal for the aperture-closure phase, but relatively much greater for the aperture-opening phase, indicating considerable difference in TAC variability between those phases. This study's goal is to identify the main reasons for that difference and obtain insights into the control strategy of reach-to-grasp movements. TAC variability within the aperture-opening phase of a single trial was found minimal, indicating that TAC variability between trials was not due to execution noise, but rather a result of inter-trial and inter-subject variability of motor plan. At the same time, the dependence of the extent of trial-to-trial variability of TAC in that phase on the speed of hand transport was sharply inconsistent with the concept of speed-accuracy trade-off: the lower the speed, the larger the variability. Conversely, the dependence of the extent of TAC variability in the aperture-closure phase on hand transport speed was consistent with that concept. Taking into account recent evidence that the cost of neural information processing is substantial for movement planning, the dependence of TAC variability in the aperture-opening phase on task performance conditions suggests that it is not the movement time that the CNS saves in that phase, but the cost of neuro-computational resources and metabolic energy required for TAC regulation in that phase. Thus, the CNS performs a trade-off between that cost and TAC regulation accuracy. It is further discussed that such trade-off is possible because, due to a special control law that governs optimal switching from aperture opening to aperture closure, the inter-trial variability of the end of aperture opening does not affect the high accuracy of TAC regulation in the subsequent aperture-closure phase.
Ultrasound neuromodulation enables to elicit of long-lasting effect on neural activities and behavioral responses across species, including humans. However, the potential biophysical mechanism of ultrasound stimulation to induce neuroplasticity is still unclear. In this study, we developed a miniature, high target-specificity ultrasound neuro-stimulation chip to selectively stimulate subnucleus and investigate the synaptic plasticity induced by ultrasound stimulation in mouse hippocampal slices. The design of the narrow aperture planar interdigital transducers (IDTs) could reach a 1.3-mm acoustic beam to precisely stimulate the presynaptic CA3 neurons. Acoustic long-term potentiation (A-LTP) was induced by the ultrasound neuro-stimulation chip with 1-ms pulsed duration and different acoustic pressures at 100-Hz repetition frequency [100-Hz low-intensity pulsed ultrasound stimulation (LIPUS)] in the CA3 subregion. Synaptic plasticity was measured by the slope of field excitatory postsynaptic potentials (fEPSPs), which were elicited using bipolar electrical stimulation (ES) electrodes in the Schaffer collaterals of CA3 region and recorded in postsynaptic CA1 neurons using extracellular electrodes. The LTP induced by ultrasound was compared to conventional 100-Hz tetanic ES (100-Hz ES). Our results confirmed that ultrasound stimulation of CA3 significantly induces LTP-like synaptic plasticity when the applied acoustic pressure was 1.08 MPa. The success rate of A-LTP and the average weight of synaptic potentiation level were significantly increased with the increment of acoustic pressure. Moreover, A-LTP was mainly due to the mechanical effects of acoustic waves, but not the thermal or cavitation effects. These results demonstrated that the high-precision ultrasound neuro-stimulation chip can selectively modulate the neural activities in the subnuclear brain region to induce synaptic potentiation, clarifying the biophysical mechanism of A-LTP.
Attempts at dynamic reconstruction of the upper eyelid either by neurotization or direct muscle replacement have been scarce. Substitution of the levator palpebrae superioris muscle requires the use of extremely small and pliable structures. As a proof of concept/pilot study, we present a consecutive series of patients who underwent blepharoptosis correction using the neurotized omohyoid muscle graft. Retrospective analysis of patients receiving a neurotized omohyoid muscle graft for levator palpebralis substitution between January and December 2019. Five patients were operated (2 male, 3 female); median age was 35.5 years. Median palpebral aperture was 0 mm and levator function was< 1 mm in all cases. Median denervation time for the levator muscle was 9 years. All surgeries were uneventful, and no postoperative complications were seen. Twelve months after the procedure, all patients presented with adequate palpebral aperture on activation of the spinal nerve. Median palpebral aperture was 6.5 mm Postoperative electromyography revealed muscle contraction when stimulation was applied to the spinal nerve. This study introduces the concept of severe blepharoptosis correction using the omohyoid muscle. We believe that with time and further technical refinements it could become an invaluable tool in eyelid reconstruction surgery.
Ophthalmic associations of West syndrome, a rare clinical triad comprising infantile spasms, a pathognomonic electroencephalogram pattern of paroxysmal activity called hypsarrhythmia and global developmental delay, usually associated with neuro-radiological anomalies, have been sparsely reported. We observed primary concomitant horizontal strabismus, mostly exotropia, and palpebral aperture abnormalities, mostly epicanthal folds, in a large subset of these subjects presenting to our tertiary care pediatric hospital and pediatric ophthalmology services. This was a cross-sectional, observational, hospital-based study designed to descriptively record ophthalmic findings in children with West Syndrome with the aim to establish the array of ophthalmic associations of this condition. One hundred and eighteen consecutive subjects with the diagnosis of West syndrome, referred from the pediatric neurology division to the pediatric ophthalmology division, were recruited prospectively and evaluated comprehensively. Primary concomitant horizontal strabismus (PCHS) was observed in 80/118 (67.79%) patients, exotropia in 58 and esotropia in 22 cases. Patients with PCHS had a significantly earlier age of onset as well as significantly increased number of drugs required to control the spasms as compared to the children without strabismus. 40/80 (50%) subjects of West Syndrome with PCHS demonstrated palpebral aperture anomalies, especially epicanthal folds, significantly more than subjects of WS without PCHS. PCHS along with eyelid and palpebral fissure anomalies are visible phenotypes and thus, very useful ophthalmological clinical biomarkers for early identification of children with increased severity of West Syndrome, which aids the pediatric neurologist toward early management of this life-threatening recalcitrant seizure disorder, while imaging and electro-encephalography evaluation is ongoing.
Similarity analyses between multiple correlation or covariance tables constitute the cornerstone of network neuroscience. Here, we introduce covSTATIS, a versatile, linear, unsupervised multi-table method designed to identify structured patterns in multi-table data, and allow for the simultaneous extraction and interpretation of both individual and group-level features. With covSTATIS, multiple similarity tables can now be easily integrated, without requiring a priori data simplification, complex black-box implementations, user-dependent specifications, or supervised frameworks. Applications of covSTATIS, a tutorial with Open Data and source code are provided. CovSTATIS offers a promising avenue for advancing the theoretical and analytic landscape of network neuroscience.
Deep learning has proven highly effective in various medical imaging scenarios, yet the lack of an efficient distribution platform hinders developers from sharing models with end-users. Here, we describe brainchop, a fully functional web application that allows users to apply deep learning models developed with Python to local neuroimaging data from within their browser. While training artificial intelligence models is computationally expensive, applying existing models to neuroimaging data can be very fast; brainchop harnesses the end user's graphics card such that brain extraction, tissue segmentation, and regional parcellation require only seconds and avoids privacy issues that impact cloud-based solutions. The integrated visualization allows users to validate the inferences, and includes tools to annotate and edit the resulting segmentations. Our pure JavaScript implementation includes optimized helper functions for conforming volumes and filtering connected components with minimal dependencies. Brainchop provides a simple mechanism for distributing models for additional image processing tasks, including registration and identification of abnormal tissue, including tumors, lesions and hyperintensities. We discuss considerations for other AI model developers to leverage this open-source resource.
Neuroimaging involves the acquisition of extensive 3D images and 4D time series data to gain insights into brain structure and function. The analysis of such data necessitates both spatial and temporal processing. In this context, "fslmaths" has established itself as a foundational software tool within our field, facilitating domain-specific image processing. Here, we introduce "niimath," a clone of fslmaths. While the term "clone" often carries negative connotations, we illustrate the merits of replicating widely-used tools, touching on aspects of licensing, performance optimization, and portability. For instance, our work enables the popular functions of fslmaths to be disseminated in various forms, such as a high-performance compiled R package known as "imbibe", a Windows executable, and a WebAssembly plugin compatible with JavaScript. This versatility is demonstrated through our NiiVue live demo web page. This application allows 'edge computing' where image processing can be done with a zero-footprint tool that runs on any web device without requiring private data to be shared to the cloud. Furthermore, our efforts have contributed back to FSL, which has integrated the optimizations that we've developed. This synergy has enhanced the overall transparency, utility and efficiency of tools widely relied upon in the neuroimaging community.
Visually guided grasping is a fundamental building block of animal behavior, the specific neural mechanisms of which remain poorly documented in the human brain. We have mapped the causal contribution of different brain parts to grasping behavior by studying the kinematic parameters of 33 patients with brain tumors, engaged in actions directed toward objects of different sizes. Using motion capture techniques, we analyzed the dynamics of grip aperture and wrist transport. Voxel-based lesion-symptom mapping analysis was applied to correlate lesion volumes with specific behavioral deficits. Results showed that lesions in the anterior and lateral bank of the intraparietal sulcus produced impaired finger scaling related to object size. Conversely, impaired velocity of finger aperture was associated with lesions in the dorsal premotor cortex (PMd). Grip aperture deficits following dominant hemisphere lesions were bilateral and were unilateral when following nondominant hemisphere lesions. Impaired wrist transport during reaching was associated with lesions in the first segment of the superior longitudinal fasciculus. Our work highlights an architecture of the grasping network in humans, with unique species-specific features. We hypothesize a model of human neural architecture in which object geometry for hand preshaping is first coded in the left anterior intraparietal cortex and then shared with the right hemisphere. Execution of the motor program of hand preshaping is then performed by the PMd on the corresponding side.
Interactions between corneal nerves and immune cells are essential for corneal homeostasis and inflammation regulation. Although simultaneous imaging has been demonstrated, existing in vivo techniques often provide limited contrast for resolving fine cellular morphology. This study evaluates a label-free, high-resolution phase contrast microscopy approach for simultaneous visualization of corneal nerves and immune cells in mouse model. A high-resolution differential phase contrast (DPC) microscopy system was developed using highly angled oblique illumination and a high numerical aperture objective. The system was applied to mouse corneas (n = 5) before and 6 h after partial circular corneal nerve cut (CNC). Three-dimensional and time-lapse imaging were performed and compared with in vivo confocal microscopy (IVCM). Immunofluorescence (IF) imaging of ex vivo corneas provided structural validation. Immune cell density in the central cornea was quantified before and after injury. DPC microscopy enabled clear visualization of the sub-basal nerve plexus (SBNP) and cellular structures in naïve corneas. Compared with IVCM, DPC provided more continuous visualization of nerve fibers and revealed fine immune cell structures based on refractive index variation. Following CNC, reduced visibility of SBNP fibers and an increase in cell density were observed, from 50 ± 18 to 226 ± 59 cells/mm2. Time-lapse DPC imaging enabled distinction of cells with intracellular activity. Structural features observed with DPC imaging were corroborated by IF imaging. High-resolution DPC microscopy enables label-free visualization of corneal nerves and immune cells with improved structural continuity compared with conventional IVCM. This approach provides a versatile platform for studying corneal neuro-immune interactions, with further development, may support translational research and clinical diagnostics.
Anorexia nervosa is a severe psychiatric disorder with a heterogeneous course with one of the highest rates of morbidity and mortality of all psychiatric disorders. Little is known about factors that predict both course and treatment outcomes of this disorder.The BRAVE Study is a longitudinal first-onset anorexia nervosa cohort study focusing on four topics of interest in girls only: (1) behavior, (2) neurobiology, (3) cognitive functions, and (4) physical health. The goal of this paper is to introduce the BRAVE Study. The primary aim of the BRAVE Study is to identify predictors of treatment response in a large sample of 12-to-22-year-old females with first-onset typical or atypical anorexia nervosa. The second aim is to longitudinally investigate the association between clinically significant changes in eating disorder symptoms with the underlying behavioral, neurobiological, cognitive and physical health changes. The results of this study will allow us to develop more precise treatment strategies in order to provide more optimal treatment. The BRAVE Study implements a longitudinal case-control design. Study recruitment was designed within a collaborative network of 16 Dutch mental health organizations, each with expertise in the diagnosis and treatment of patients with anorexia nervosa. After obtaining informed consent, assessments were performed at baseline and one-year follow-up. Patients with anorexia nervosa received treatment as usual. The primary outcome measures at one year are restoration of weight and a reduction of eating disorder symptomatology. Predictive measures include neurobiological, cognitive, behavioral and physical health measures. In the BRAVE Study 79 girls with anorexia nervosa and 75 typically developing girls were included between May 2017 and October 2021. This period of time partially overlapped with the COVID-19 pandemic. 72% of the girls with anorexia nervosa and 88% of the typically developing girls also completed measurements at follow-up. The mean time between data collections points was 13 months. The groups were comparable in education level of their mothers, neurodevelopmental disorders, and ethnical background. The girls with anorexia nervosa were slightly younger than the typically developing girls. The BRAVE Study aligns with one of the most important study priorities in the field of anorexia nervosa by examining (i) predictors of treatment response and (ii) investigating how symptoms with eating disorder symptoms track with changes in neurobiological, cognitive, behavorial and physical health functioning. Moreover, the study is innovative by its longitunal case control design, relatively large study sample and broad selection of measures.
The present study delineates the large-scale, organic responses of growth in the dorsal pallium to targeted genetic ablations of the principal PP (preplate) neurons of the neocortex. Ganciclovir treatment during prenatal development [from E11 (embryonic age 11) to E13] of mice selectively killed cells with shared S-phase vulnerability and targeted expression of a GPT [golli promoter transgene; GPT linked to HSV-TK (herpes simplex virus-thymidine kinase), τ-eGFP and lacZ reporters] localized in PP neurons and their intermediate progenitor neuroblasts. The volume, area and thickness of the pallium were measured in an E12-P4 (postnatal age 4) longitudinal study with comparisons between ablated (HSV-TK(+/0)) and control (HSV-TK(0/0)) littermates. The extent of ablations was also systematically varied, and the effect on physical growth was assessed in an E18 cross-sectional study. The morphological evidence obtained in the present study supports the conclusion that genetically targeted ablations delay the settlement of the principal PP neurons of the dorsal pallium. This leads to progressive and substantial reductions of growth, despite compensatory responses that rapidly replace the ablated cells. These growth defects originate from inductive cellular interactions in the proliferative matrix of the ventricular zone of the pallium, but are amplified by subsequent morphogenic and trophic cellular interactions. The defects persist during the course of prenatal and postnatal development to demonstrate a constrained dose-response relationship with the extent of specific killing of GPT neurons. The defects propagate simultaneously in both the horizontal and vertical cytoarchitectural dimensions of the developing pallium, an outcome that produces a localized shortfall of volume in the telencephalic vesicles.
Neuroimaging relies on separate statistical inferences at tens of thousands of spatial locations. Such massively univariate analysis typically requires an adjustment for multiple testing in an attempt to maintain the family-wise error rate at a nominal level of 5%. First, we examine three sources of substantial information loss that are associated with the common practice under the massively univariate framework: (a) the hierarchical data structures (spatial units and trials) are not well maintained in the modeling process; (b) the adjustment for multiple testing leads to an artificial step of strict thresholding; (c) information is excessively reduced during both modeling and result reporting. These sources of information loss have far-reaching impacts on result interpretability as well as reproducibility in neuroimaging. Second, to improve inference efficiency, predictive accuracy, and generalizability, we propose a Bayesian multilevel modeling framework that closely characterizes the data hierarchies across spatial units and experimental trials. Rather than analyzing the data in a way that first creates multiplicity and then resorts to a post hoc solution to address them, we suggest directly incorporating the cross-space information into one single model under the Bayesian framework (so there is no multiplicity issue). Third, regardless of the modeling framework one adopts, we make four actionable suggestions to alleviate information waste and to improve reproducibility: 1) model data hierarchies, 2) quantify effects, 3) abandon strict dichotomization, and 4) report full results. We provide examples for all of these points using both demo and real studies, including the recent Neuroimaging Analysis Replication and Prediction Study (NARPS).
The manifold mandibular movements of oral aperture can be modelled by movements of couples in neuromuscular gear systems. These systems consist of the dimeric link chain of the neuromuscular hinge axis (rocking arm) and a neuromuscularly enforced cyclic trajectory of a well-defined point of the mandible. The neuromuscular hinge axis is the common constant of all gear systems whereas the position of the cyclic trajectory at the fixed plane (maxilla) is closely related to the specific path of the entire rigid body mandible. The presented theory is inferred by measurements of the mandible's movement that take all six degrees of freedom into account.
For 100 years three ideas dominated efforts to understand the apposition compound eye. In Müller's theory, the eye viewed the panorama through an array of little windows without overlaps and without gaps, with no details within windows. Spatial resolution then depended on the interommatidial angle (Deltaphi) and the number of ommatidia. In the second proposal, the insect detected the temporal modulation of the light, which was limited by the aperture of the lens and the wavelength, assuming good focus. Modulation is the change of intensity in the receptor, usually caused by motion of a spatial contrast in the stimulus. Thirdly, motion was detected from the successive temporal modulations at adjacent visual axes. Recently, two more principles arose. The light-sensitive elements, called rhabdomeres, project through the nodal point of the lens to the outside world, and the resolution was limited by their grain size, like the pixels in a digital camera. Finally, detection of contrast and colour was limited by the signal/noise ratio (SNR) which was improved by brighter light and more visual pigment. These five physical principles provide satisfying explanations of eye function but they all originated from theory. Actual measurements of resolution depend on the operation of the test. The visual system of the honeybee recognizes a limited variety of simple cues, but there is no evidence that the pattern of ommatidial stimulation is re-assembled, or even seen. The known cues are: the temporal modulation of groups of receptors, the direction and angular velocity of motion, some measure of the spatial disruption of the pattern or the length of edge (related to spatial frequency and contrast), colour, the intensity, the position of the centre and the size of large well-separated areas of black or colour, the angle of orientation of a bar or grating, radial or tangential edges, and bilateral symmetry. Neurons connected to more than two adjacent ommatidia collaborate in the detection of cues, and the resolution depends on the neuro-sensory feature detectors at work at the time. Although some behavioural and electrophysiological measurements give a spatial resolution similar to the interommatidial angle, different spatial properties of neuro-sensory detectors predominate at different light intensities and with a diurnal rhythm. During the long history of this topic, the belief that the resolution ought to be Deltaphi has frequently been overturned by experimental measurement.
The free movements of mandibular, oral apertures can be related to the couples' movements of neuromuscular throttle cranks which reveal a common specific property: a double dead position of the mandible (couple). As the neuromuscular system uses the same cyclic path of a well-defined mandibular point for the opening and the closing process of a specific mandibular movement, the mandible can follow the same or two different trajectories although the positive drive works on. The different movements of oral aperture are related to the geometrical positions of the cranks at the fixed plane. Geometrical properties and measures of the gear systems of eleven class-I-patients are reported and discussed.
Deep Brain Stimulation (DBS) is a neurosurgical procedure that involves implanting electrodes into specific brain regions to treat brain disorders. Accurate reconstruction of electrode placement is crucial for treatment optimization. Several systems, such as Lead-DBS, have been developed to reconstruct DBS electrodes, and typically require expert user input. However, open DBS datasets with localized electrodes are not available, posing a challenge to train research personnel on accurate use of these methods. In this paper, we introduce Lead-Tutor, an open-access educational resource that combines an imaging dataset of anonymized DBS cases with a software tool for self-teaching. This resource includes a dataset of pre- and post-operative magnetic resonance imaging (MRI) and computed tomography (CT) scans from ten patients with DBS implants. Along with this dataset, we provide a means for users to practice and enhance their electrode localization skills through the Lead-DBS pipeline. Aimed at new scientists in the DBS field, Lead-Tutor is a comprehensive resource available within Lead-DBS that promotes open science and education for enhanced reproducibility and potential clinical applications.
Quality control (QC) is an important part of all scientific analyses, including neuroscience. With manual curation considered the gold standard, there remains a lack of available tools that make manual neuroimaging QC accessible, fast, and easy. In this article we present Qrater, a containerized web-based Python application that enables viewing and rating of any type of image for QC purposes. Qrater functionalities allow collaboration between various raters on the same dataset which can facilitate completing large QC tasks. Qrater was used to evaluate QC rater performance on three different magnetic resonance (MR) image QC tasks by a group of raters having different amounts of experience. The tasks included QC of raw MR images (10,196 images), QC of linear registration to a standard template (10,196 images), and QC of skull segmentation (6,968 images). We measured the proportion of failed images, average rating time per image, intra- and inter-rater agreement, as well as the comparison against QC using a conventional method. The median time spent rating per image differed significantly between raters (depending on rater experience) in each of the three QC tasks. Evaluating raw MR images was slightly faster using Qrater than an image viewer (expert: 99 vs. 90 images in 63 min; trainee 99 vs 79 images in 98 min). Reviewing the linear registration using Qrater was twice faster for the expert (99 vs. 43 images in 36 min) and three times faster for the trainee (99 vs. 30 images in 37 min). The greatest difference in rating speed resulted from the skull segmentation task where the expert took a full minute to inspect the volume on a slice-by-slice basis compared to just 3 s using Qrater. Rating agreement also depended on the experience of the raters and the task at hand: trained raters' inter-rater agreements with the expert's gold standard were moderate for both raw images (Fleiss' Kappa = 0.44) and linear registration (Fleiss' Kappa = 0.56); the experts' inter-rater agreement of the skull segmentation task was excellent (Cohen's Kappa = 0.83). These results demonstrate that Qrater is a useful asset for QC tasks that rely on manual evaluation of QC images.
Effect size estimation is crucial for power analyses and experimental design, but poses unique challenges in fMRI research due to the complexity of the data and analysis techniques. Here, we introduce an interactive web application for exploring fMRI effect maps (neuroprismlab.shinyapps.io/BrainEffeX). We utilized large fMRI datasets to obtain precise voxel-wise and multivariate effect size estimates from "typical" fMRI study designs: brain-behavior correlation, task vs. rest, and between-group analyses of functional connectivity and task-based activation maps. The app is intentionally designed as a growing resource, and we welcome contributions of large (n > 500) datasets.
Cognitive and physical function are interrelated in aging. Co-occurring impairments in both domains can be debilitating and lead to increased risk of developing dementia. Amyloid beta (Aβ) deposition in the brain is linked to cognitive decline and is also associated with poorer physical function in older adults. However, significant inter-individual variability exists with respect to the influence of increased brain Aβ concentrations on cognitive and physical outcomes. Identifying factors that explain inter-individual variability in associations between Aβ and clinical outcomes could inform interventions designed to delay declines in both cognitive and physical function. Cognitive reserve (CR) is considered a buffer that allows for cognitive performance that is better than expected for a given level of brain injury or pathology. Although the neural mechanisms underlying CR remain unknown, there is growing evidence that resting-state brain networks may serve as a neural surrogate for CR. The current study utilized a statistical interaction model to evaluate if functional brain networks moderated associations between brain Aβ and cognitive and physical function in community-dwelling older adults from the Brain Networks and Mobility (B-NET) study. Significant moderations were found between Aβ levels and both the central executive and subcortical networks with cognitive and physical function. The findings suggest that brain networks serve as a buffer against the influence of Aβ accumulation on cognitive and physical function indicating that the network integrity could one of the neural mechanisms supporting CR.