Changes In Coherence Research Articles

Pan-cortical coordination underlying mental effort

ObjectiveIt is well known that activity in, or coordination among, brain regions, can underlie movement, sensation, language, and cognition but there are observations that tasks unrelated to specific brain regions can nonetheless alter activity in those regions. These tasks might invoke activity in multiregional networks, but it also is possible that they are associated with changes beyond these networks. We therefore evaluated the possibility that more widespread, or even whole-cortical, mechanisms might complement or alter focal or multifocal cortical activity. MethodsWe assessed the extent of electroencephalographic changes occurring outside areas with epileptiform activity, but that were associated with termination of the epileptiform activity. To do this, we measured the distribution of wavelet cross-coherence changes based on electrocorticography from 15 patients who showed regional afterdischarges in response to electrical brain stimulation prior to epilepsy surgery and in whom cognitive tasks were used in attempts to end the afterdischarges. There were 1276 electrodes implanted in these patients, and we analyzed a total of 55,494 electrode combinations. We compared recordings when cognitive effort was versus when it was not successful in ending afterdischarges. ResultsWe found that when afterdischarges were suppressed there were changes in electrocorticographic coherence that were similar throughout cortex, regardless of the distance between sites. ConclusionsThe similarity implies coordination of the changes, and the similarity regardless of distance or location implies a pan-cortical effect. SignificanceOur results provide physical support for hypotheses that pan-cortical processes complement the well-known regional and multiregional networks. These processes may participate in, be recruited by, modify, or underlie the conative experiences of waking life.

Different modulation of oscillatory common neural drives to ankle muscles during abrupt and gradual gait adaptations.

Different neural contributions to motor learning might be involved when different error sizes of perturbation are introduced. Although the corticospinal drive contributes to abrupt gait adaptation processes, no studies have investigated whether cortical involvement during gait differs between perturbations applied abruptly and gradually. This study aimed to investigate the differences in oscillatory common neural drives to ankle muscles during gait between abrupt and gradual adaptations, using coherence analyses of paired surface electromyographic (EMG) recordings. Sixteen healthy young adults performed the treadmill gait with perturbation resisting forward movement of the swing leg for 10min under two conditions: abrupt (a large perturbation from the beginning of the adaptation period) and gradual (a series of small perturbations that gradually increased). Swing phase duration and step length showed significantly greater asymmetry in the abrupt condition than in the gradual condition in the early adaptation period (p < 0.01), despite no significant differences in gait symmetries between the two conditions in the early post-adaptation period. EMG-EMG coherence calculated from the tibialis anterior muscle in the beta band (15-35Hz) on the perturbed side was significantly higher in the early adaptation period in the abrupt condition (p < 0.05), but not in the gradual condition. There were significant relationships between changes in temporal gait symmetry and EMG-EMG coherence during the different adaptation periods between the two conditions (p < 0.05). The abrupt large perturbation seems to require a cortical involvement, whereas a gradual adaptation with small gait asymmetry requires no modulation of cortical involvement.

A Weighted Coherence Estimator for SAR Coherent Change Detection

Synthetic aperture radar (SAR) coherent change detection (CCD) predominantly uses the degree of coherence or similar change metrics as a measurement of the changes that have occurred between two data collections. Many existing coherence estimators have shown some performances for change detection, but are still relatively limited because the change areas do not stand out well from all decorrelation areas due to low clutter-to-noise ratio (CNR) and volume scattering. Besides, many estimators require the equal-variance assumption between two SAR images of the same scene. However, the assumption is less likely to be met in areas with significant intensity differences, especially in change regions. In this paper, a novel weighted coherence estimator is proposed to address these problems. The estimator is derived based on the statistical characteristics of SAR images by using the maximum-likelihood (ML) principle. The introduction of weight parameters not only makes the estimator no longer need to satisfy the equal-variance assumption but also combines the advantages of coherent and noncoherent algorithms to a certain extent because the weights are closely related to the ratio change statistic. Experiments on simulated and real SAR image pairs demonstrate the effectiveness of the proposed estimator in highlighting change areas and the boundaries between change and other areas in theory and practice.

Multitemporal SAR and Polarimetric SAR Optimization and Classification: Reinterpreting Temporal Coherence

In multitemporal SAR and Polarimetric SAR (Pol-SAR) coherence is a capital parameter to exploit common information between temporal acquisitions. Yet, its use is limited to high coherences. This article proposes the analysis of low coherence scenarios by introducing a reinterpretation of coherence. It is demonstrated that coherence results from the product of two terms accounting for coherent and radiometric changes, respectively. For low coherences, the first term presents low values, preventing its exploitation for information retrieval. The information provided by the second term can be used in these circumstances to exploit common information. This second term is proposed, as an alternative to coherence, for information retrieval for low coherences. Besides, it is shown that polarimetry allows the temporal optimization of its values. To prove the benefits of this approach, multitemporal SAR and PolSAR data classification is considered as a tool, showing that improvements of the classification overall accuracy may range between 20% and 50%, compared to classification based on coherence.

Controlling High Blood Pressure

Recently published national data demonstrate inadequate and worsening control of high blood pressure (HBP) in the United States, outcomes that likely have been made even worse by the coronavirus disease 2019 (COVID-19) pandemic. This major public health crisis exposes shortcomings of the US health care delivery system and creates an urgent opportunity to reduce mortality, major cardiovascular events, and costs for 115 million Americans. Ending this crisis will require a more coherent and systemic change to traditional patterns of care. The authors present an evidence-based Blueprint for Change for comprehensive health delivery system redesign based on current national clinical practice guidelines and quality measures. This innovative model includes a systems-based approach to ensuring proper BP measurement, assessment of cardiovascular risk, effective patient-centered team-based care, addressing social determinants of health, and shared decision-making. The authors also propose building on current national quality improvement initiatives designed to better control HBP.

Vehicle Trace Detection in Two-Pass SAR Coherent Change Detection Images With Spatial Feature Enhanced Unet and Adaptive Augmentation

As a typical application of remote sensing technology, change detection can find the ground information changes by acquiring images of the same region at different times. The change detection using the synthetic aperture radar (SAR) with the advantages of all day and all-weather usually monitors the significant surface change, like flood disasters and earthquake deformation. However, when it comes to detecting subtle changes like vehicle traces, the traditional methods ignoring the phase coherence between image pairs cannot intensify these faint changes in the difference image. The SAR coherent change detection (CCD) based on repeat-pass repeat-geometry complex images utilizing both the intensity and phase fraction could exhibit the subtle vehicle trace in the difference image. However, the complicated background and decorrelation factors significantly affect the quality of difference images, further causing great trouble for automatic trace detection. This paper proposes the spatial feature enhanced Unet and adaptive data augmentation to realize vehicle trace detection. More specifically, the pseudo-color image is first synthesized based on a two-stage coherence estimation method. Then considering the long-continuity and parallel distribution of vehicle trace samples, the enhanced Unet is constructed by fusing spatial convolutional neural network and spatial attention mechanism. After that, the adaptation data augmentation strategy is presented by introducing manual registration errors and multiple estimation windows. Finally, the experimental results on the Sandia CCD data and our measured data demonstrate the effectiveness of the proposed method.

Change Captioning: A New Paradigm for Multitemporal Remote Sensing Image Analysis

Change detection (CD) is among the most important applications in remote sensing that allows identifying the changes that occurred in a given geographical area across different times. Even though CD systems have seen a lot of progress in RS, their output is either a binary map highlighting the changing area or a semantic change map that indicates the type of change for each pixel. The change maps are often difficult to interpret by end-users and they omit important information such are relationships and attributes of the changed areas. Motivated by the recent advancement of image captioning in the RS community, in this article we propose to describe the changes over bi-temporal images through change sentence descriptions. The aim of this article is to provide a user-friendly interpretation of the occurred changes. To this end, we propose two change captioning (CC) systems that take as input bi-temporal images and generate coherent sentence descriptions of the occurred changes. Convolutional neural networks (CNNs) are used to extract discriminative features from the bi-temporal images and recurrent neural networks (RNNs) or support vector machines (SVMs) are exploited to generate coherent change descriptions. Furthermore, in absence of a CC dataset to test our systems, we propose two new datasets. One is based on very high-resolution RGB images and the other one is based on multispectral RS images. The obtained experimental results show promising capabilities of the proposed systems to generate coherent change descriptions from the bi-temporal images. The datasets are available at the following link: https://disi.unitn.it/&#x007E;melgani/datasets.html.

Coherent and Incoherent Change Detection for Soil Moisture Retrieval From Sentinel-1 Data

This study proposes a hybrid incoherent–coherent change detection (CD) approach to retrieve surface soil moisture (SSM) from Sentinel-1 data. It combines time-series observations of synthetic aperture radar (SAR) backscatter and interferometric closure phase to deliver a method that does not require external calibration. A proof-of-concept assessment based on synthetic and experimental data is presented. Sentinel-1 and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> data over a study site in Southern Italy during the Winter–Spring season 2017 that covered both bare and vegetated soil conditions have been acquired and analyzed. For bare soils, results indicate good performance, that is, Pearson correlation ≈0.8 and root mean square error (RMSE) ≈0.05 m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> /m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> . Conversely, over vegetated surfaces, poor results are found.

An Adaptive and Adjustable Maximum-Likelihood Estimator for SAR Change Detection

Synthetic aperture radar (SAR) change detection can be broadly classified into two categories: noncoherent intensity change detection and coherent change detection (CCD). The former methods, belonging to the field of image processing, are theoretically suitable for all SAR images since only utilize the information of SAR magnitude, however, the detection precision cannot be guaranteed. The latter methods can show effective performances for most SAR image pairs using identical collection geometrics because of the basis of the probability and statistics theory. In this paper, we propose a novel change estimator to combine the advantages of the two kinds of algorithms in a theoretical derivation way. An intensity-based estimator, inspired by the derivation of the coherence estimator in CCD, is first proposed. It is a new maximum-likelihood (ML) change estimator maximizing the probability distribution function (pdf) of the ratio change statistic instead of SAR complex data. In addition, the simple linear iterative cluster (SLIC) algorithm is introduced to make the new estimator adjustable because changes at different degrees can be extracted with varying settings of the superpixels number, which is further demonstrated in real SAR images. Finally, experiments in SAR image pairs of different statistical characteristics show that the proposed estimator can yield higher-contrast SAR change detection images than the other five common change statistics and obtain better change detection maps than the other four classic thresholding methods.

Cortical Stimulation Paired With Volitional Unimanual Movement Affects Interhemispheric Communication.

Cortical stimulation (CS) of the motor cortex can cause excitability changes in both hemispheres, showing potential to be a technique for clinical rehabilitation of motor function. However, previous studies that have investigated the effects of delivering CS during movement typically focus on a single hemisphere. On the other hand, studies exploring interhemispheric interactions typically deliver CS at rest. We sought to bridge these two approaches by documenting the consequences of delivering CS to a single motor cortex during different phases of contralateral and ipsilateral limb movement, and simultaneously assessing changes in interactions within and between the hemispheres via local field potential (LFP) recordings. Three macaques were trained in a unimanual reaction time (RT) task and implanted with epidural or intracortical electrodes over bilateral motor cortices. During a given session CS was delivered to one hemisphere with respect to movements of either the contralateral or ipsilateral limb. Stimulation delivered before contralateral limb movement onset shortened the contralateral limb RT. In contrast, stimulation delivered after the end of contralateral movement increased contralateral RT but decreased ipsilateral RT. Stimulation delivered before ipsilateral limb movement decreased ipsilateral RT. All other stimulus conditions as well as random stimulation and periodic stimulation did not have consistently significant effects on either limb. Simultaneous LFP recordings from one animal revealed correlations between changes in interhemispheric alpha band coherence and changes in RT, suggesting that alpha activity may be indicative of interhemispheric communication. These results show that changes caused by CS to the functional coupling within and between precentral cortices is contingent on the timing of CS relative to movement.

Proteomics Investigations of Potential Protein Biomarkers in Sera of Rabbits Infected With Schistosoma japonicum.

Schistosomiasis is a chronic parasitic disease that continues to be a pressing public health problem in many developing countries. The primary pathological damage from the disease is granuloma and fibrosis caused by egg aggregation, and early treatment can effectively prevent the occurrence of liver fibrosis. Therefore, it is very important to identify biomarkers that can be used for early diagnosis of Schistosoma japonicum infection. In this study, a label-free proteomics method was performed to observe the alteration of proteins before infection, 1 and 6 weeks after infection, and 5 and 7 weeks after treatment. A total of 10 proteins derived from S. japonicum and 242 host-derived proteins were identified and quantified as significantly changed. Temporal analysis was carried out to further analyze potential biomarkers with coherent changes during infection and treatment. The results revealed biological process changes in serum proteins compared to infection and treatment groups, which implicated receptor-mediated endocytosis, inflammatory response, and acute-phase response such as mannan-binding lectin serine peptidase 1, immunoglobulin, and collagen. These findings offer guidance for the in-depth analysis of potential biomarkers of schistosomiasis, host protein, and early diagnosis of S. japonicum and its pathogenesis. Data are available via ProteomeXchange with identifier PXD029635.

Enhancing Coherence Images for Coherent Change Detection: An Example on Vehicle Tracks in Airborne SAR Images

In Synthetic Aperture Radar (SAR) interferometry, one of the most widely used measures for the quality of the interferometric phase is coherence. However, in favorable conditions coherence can also be used to detect subtle changes on the ground, which are not visible in the amplitude images. For such applications, i.e., coherent change detection, it is important to have a good contrast between the unchanged (high-coherence) parts of the scene and the changed (low-coherence) parts. In this paper, an algorithm is introduced that aims at enhancing this contrast. The enhancement is achieved by a combination of careful filtering of the amplitude images and the interferometric phase image. The algorithm is applied to an airborne interferometric SAR image pair recorded by the SmartRadar experimental sensor of Hensoldt Sensors GmbH. The data were recorded during a measurement campaign over the Bann B installations of POLYGONE Range in southern Rhineland-Palatinate (Germany), with a time gap of approximately four hours between the overflights. In-between the overflights, several vehicles were moved on the site and the goal of this work is to enhance the coherence image such that the tracks of these vehicles can be detected as completely as possible in an automated way. Several coherence estimation schemes found in the literature are explored for the enhancement, as well as several commonly used speckle filters. The results of these filtering steps are evaluated visually and quantitatively, showing that the mean gray-level difference between the low-coherence tracks and their high-coherence surroundings could be enhanced by at least 28%. Line extraction is then applied to the best enhancement. The results show that the tracks can be detected much more completely using the coherence contrast enhancement scheme proposed in this paper.

Detecting spatio-temporal urban surface changes using identified temporary coherent scatterers

Synthetic aperture radar (SAR) is able to detect surface changes in urban areas with a short revisit time, showing its capability in disaster assessment and urbanization monitoring. Most presented change detection methods are conducted using couples of SAR amplitude images. However, a prior date of surface change is required to select a feasible image pair. We propose an automatic spatio-temporal change detection method by identifying the temporary coherent scatterers. Based on amplitude time series, x <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> -test and iterative single pixel change detection are proposed to identify all step-times: the moments of the surface change. Then the parameters, e.g., deformation velocity and relative height, are estimated and corresponding coherent periods are identified by using interferometric phase time series. With identified temporary coherent scatterers, different types of temporal surface changes can be classified using the location of the coherent periods and spatial significant changes are identified combining point density and F values. The main advantage of our method is automatically detecting spatio-temporal surface changes without prior information. Experimental results by the proposed method show that both appearing and disappearing buildings with their step-times are successfully identified and results by ascending and descending SAR images show a good agreement.

Revealing potential areas of water resources using integrated remote-sensing data and GIS-based analytical hierarchy process

In this article, a part of Wadi Al-Sahba, Saudi Arabia, is tested for revealing and modelling potential area of groundwater using integrated data derived from remote-sensing, geology and hydrology through GIS-based analytical hierarchy process method. Nine thematic maps e.g. geology, stream-networks, topography, slope, lineaments, depressions, radar intensity, rainfall and land use/cover that control the occurrence of groundwater were weighted and combined to quantify the potential area of groundwater resources. The output prospection map revealed five predicting zones of groundwater (GPZs) are very low (11.55%), low (28.18%), moderate (29.14%), high (22.41%) and very high (8.73%). The most predicted areas are covering wide part of Al Kharj and downstream of Wadi Al-Sahba. Information derived from well data (# 59), thermal sensor and interferometric SAR coherence change detection data are validated the prospective map. Overall, integration of remote sensing data has the capability for revealing and predicting potential areas of groundwater resources.

Understanding the Basin Asymmetry in Surface Response to Sudden Stratospheric Warmings from an Ocean–Atmosphere Coupled Perspective

AbstractThe canonical tropospheric response to a weakening of the stratospheric vortex—an equatorward shift of the eddy-driven jet—is mostly limited to the North Atlantic following sudden stratospheric warmings (SSWs). A coherent change in the Pacific eddy-driven jet is notably absent. Why is this so? Using daily reanalysis data, we show that air–sea interactions over the North Pacific are responsible for the basin-asymmetric response to SSWs. Prior to the onset of some SSWs, their tropospheric precursors produce a dipolar SST pattern in the North Pacific, which then persists as the stratospheric polar vortex breaks down following the onset of the SSW. By reinforcing the lower-tropospheric baroclinicity, the dipolar SST pattern helps sustain the generation of baroclinic eddies, strengthening the near-surface Pacific eddy-driven jet and maintaining its near-climatological-mean state. This prevents the jet from being perturbed by the downward influence of the stratospheric anomalies. As a result, these SSWs exhibit a highly basin-asymmetric surface response with only the Atlantic eddy-driven jet shifted equatorward. For SSWs occurring without the atmospheric precursors in the North Pacific troposphere, the dipolar SST pattern is absent due to the lack of the atmospheric forcing. In the absence of the dipolar SST pattern and the resultant eddy–mean flow feedbacks, these SSWs exhibit a basin-symmetric surface response with both the Atlantic and the Pacific eddy-driven jets shifted equatorward. Our results provide an ocean–atmosphere coupled perspective on stratosphere–troposphere interaction following SSW events and have potential for improving subseasonal to seasonal forecasts for surface weather and climate.

Managers’ experience-based understanding of capacity to work in workers with common mental disorders

Abstract Background The capacity to work among workers with common mental disorders (CMD) is important to understand but scarcely explored from a manager perspective, even though their views could add essential knowledge. The aim of this study was to explore and describe managers' experience-based understanding of capacity to work in individuals with CMD. Methods This qualitative focus group study used inductive manifest content analysis as analytic technique. First-line managers with experiences of employees with CMDs were recruited via organizations and networks. Eight focus group interviews with altogether 31 participants were performed. Results The analysis resulted in five categories of managers' experience-based understanding of occupational functioning in workers with CMDs: (1) The capacity to mentally focus on work tasks decreases or disappears, with negative consequences for work output. (2) The capacity to commit to continuous and coherent tasks changes, making tasks that span over longer periods of time difficult. (3) The capacity to independently adapt to the needs of the situation decreases, causing the worker to need more guidance and instructions than usual. (4) The capacity to keep up professional appearances is reduced, meaning that the worker struggle with the professional role. Finally, (5) the ability to interact socially and professionally decreases, which potentially causes conflicts at the workplace. Conclusions This study shows managers' experience-based understanding of CMDs in workers as severe changes and reductions of employees' capacities needed for occupational functioning. These findings add to the understanding of the construction of the capacity at the workplace. A deeper understanding of reduced work capacity is also needed to adapt workplaces and our findings can facilitate work accommodations for employees with CMDs. Key messages This study adds a manager perspective to the increasing knowledge about how capacity to work is influenced by CMD. This study shows that managers experience that CMD in workers severely change and reduce employees’ capacities needed for occupational functioning.

Interpersonal Emotion Dynamics in Couples With Somatic Symptom Disorder: Dyadic Coherence in Facial Temperature During Emotional Interactions.

Disturbances in emotional processes are commonly reported in patients with a somatic symptom disorder (SSD). Although emotions usually occur in social interactions, little is known about interpersonal emotion dynamics of SSD patients during their actual emotional encounters. This study examined physiological coherence (linkage) between SSD patients and their partners, and in healthy couples during their emotional interactions. Secondarily, we explored group-level relationships between participants' and their partners' subjective affect. Twenty-nine romantic couples (16 healthy and 13 SSD patient-couples) underwent a dyadic conversation task with neutral and anger-eliciting topics followed by a guided relaxation. Partners' cutaneous facial temperature was recorded simultaneously by functional infrared thermal imaging. Immediately after each condition, participants reported on their pain intensity, self-affect, and perceived partner-affect. Emotional conditions and having a partner with an SSD significantly affected coherence amplitude on the forehead (F(2,54) = 4.95, p = .011) and nose tip temperature (F(2,54) = 3.75, p = .030). From baseline to anger condition, coherence amplitude significantly increased in the patient-couples, whereas it decreased in the healthy couples. Correlation changes between partners' subjective affect comparably accompanied the changes in physiological coherence in healthy and patient-couples. Inability to reduce emotional interdependence in sympathetic activity and subjective affect during a mutual conflict observed in SSD patient-couples seems to capture emotion co-dysregulation. Interventions should frame patients' emotional experiences as embodied and social. Functional infrared thermal imaging confirms to be an ecological and reliable method for examining autonomic changes in interpersonal contexts.Registration Page: https://osf.io/8eyjr.

Forest frontiers out of control: The long-term effects of discourses, policies, and markets on conservation and development of the Brazilian Amazon

With the Brazilian military governments of the 1960s, systematic economic development of the Amazon began. Social and environmental concerns have entered Amazonian discourses and policies only since the 1990s. Since then, reports of threats to forests and indigenous people have alternated with reports of socio-economic progress and environmental achievements. These contradictions often arise from limited thematic, sectoral, temporal, or spatial perspectives, and lead to misinterpretation. Our paper offers a comprehensive picture of discourses, policies, and socio-environmental dynamics for the entire region over the last five decades. We distinguish eight historical policy phases, each of which had little effect on near-linear dynamics of demographic growth and land-use expansion, although some policies showed the potential to change the course of development. To prevent local, national, and international actors from continuing to assert harmful interests in the region, a coherent long-term commitment and change in the collective mindset are needed.

High temperature phase stability of the compositionally complex alloy AlMo0.5NbTa0.5TiZr

Recently, a class of refractory high-entropy alloys has been developed with a refined microstructure consisting of an ordered B2 matrix with cuboidal BCC precipitates resembling an “inverted superalloy-like” microstructure. In this paper, we have studied the evolution of the duplex microstructure of AlMo0.5NbTa0.5TiZr during aging at elevated temperatures, particularly with regard to the nature of the B2 and BCC phases. Samples were aged at 1000 °C for 6 h, followed by a water quench. It was found that while the relative volume fractions of the B2 and BCC phases remained nearly constant after ageing, compositional changes of both the B2 and BCC phases were determined. In the aged condition, there is evidence from high-resolution STEM HAADF imaging that suggests that the B2 phase in the aged condition may undergo a spinodal reaction, with the sub-lattice occupancies differing within the ordered precipitates. A change in size and shape of the BCC precipitates was also noted, and this was accompanied by a difference in the nature of the B2/BCC interfaces. Thus, a step-like B2/BCC interface is evidenced in the aged condition, in contrast with the planar {100} interfaces in the “superalloy-like” microstructure, likely adopted to accommodate a change in coherency resulting from an increase in misfit between the two phases from compositional changes occurring during the coarsening of the BCC precipitates.

A mechanism for inter-areal coherence through communication based on connectivity and oscillatory power

SummaryInter-areal coherence between field potentials is a widespread phenomenon in cortex. Coherence has been hypothesized to reflect phase-synchronization between oscillators and flexibly gate communication according to behavioral and cognitive demands. We reveal an alternative mechanism where coherence is not the cause but the consequence of communication and naturally emerges because spiking activity in a sending area causes post-synaptic potentials both in the same and in other areas. Consequently, coherence depends in a lawful manner on power and phase-locking in the sender and connectivity. Changes in oscillatory power explained prominent changes in fronto-parietal and LGN-V1 coherence across behavioral conditions. Optogenetic experiments and excitatory-inhibitory network simulations identified afferent synaptic inputs rather than spiking entrainment as the principal determinant of coherence. These findings suggest that unique spectral profiles of different brain areas automatically give rise to large-scale coherence patterns that follow anatomical connectivity and continuously reconfigure as a function of behavior and cognition.