org). Use of digital reconstructions in morphologically and biophysically realistic simulations and network models allows direct investigation of the neuronal structure-activity-function relation.

The following is an overview of currently available modeling software, all of which are free and typically open source. The first four programs are for morphological modeling (marked with “∗∗∗” in Table 1). The remaining are for biophysical simulations of neuronal this website electrophysiology. 1. L-Neuron is a computational tool to generate anatomically accurate virtual neurons of various morphological classes. L-Neuron resamples statistical distributions extracted from experimental data to generate virtual neurons according to algorithms that implement established anatomical rules. The

3D morphological models can be visualized with the companion L-Viewer program and exported into classic graphic formats (bitmap, VRML, DXF, POV, and Blob) or standard SWC format for morphometric analysis and electrophysiological simulations. Online documentation and e-mail user support are available. Actively maintained but no longer developed, L-Neuron is written in C/C++ and runs on Windows and Linux. The source code is available upon request bundled within L-Measure. The above list does not include the numerous published computational models of neuronal morphology (e.g., Samsonovich and Dasatinib concentration Ascoli, 2005; López-Cruz et al., 2011), as this compilation focuses on research tools available to the scientific community as opposed to individual custom solutions restricted GBA3 to the domain of a single laboratory. The software programs listed for computational modeling of neuron electrophysiology include resources for circuit simulation but always with the ability of representing

dendritic and axonal morphology. Various other neural network simulators largely or exclusively consider point neurons as the elementary unit of computation, sacrificing neuron-level realism for larger-scale modeling. For example, PCSIM (Parallel neural Circuit SIMulator; http://www.lsm.tugraz.at/pcsim) allows parallel simulation of large-scale heterogeneous spiking and analog neural networks with up to millions of different point neurons and billions of synapses. Emergent (http://grey.colorado.edu/emergent) models neural dynamics at the level of activity rates. Topographica (http://topographica.org) focuses on modeling activity in cortical maps. CNS (Cortical Network Simulator; http://cbcl.mit.edu/jmutch/cns) is designed specifically for graphical processing units (GPUs). Other neural network simulators include CNRun (http://johnhommer.com/academic/code/cnrun), LENS (http://tedlab.mit.edu/∼dr/Lens), Nodus (http://www.tnb.ua.ac.be/software/nodus/nodus_info.shtml), Simbrain (http://simbrain.net), and NEST (Neural Simulation Technology; http://nest-initiative.org). PyNN (http://neuralensemble.

Significance was set at p < 0.05. No differences were observed on any of the measured variables between those who provided accelerometer data and those who did not with the exception of enjoyment of PA, which was higher

in those without 4 valid days of accelerometer data compared to those with less than 4 days of data (4.28 vs. 4.16, p < 0.05). While the mean age was similar for both boys (12.5 ± 1.1) and girls (12.1 ± 1.0), respectively, girls had a slightly higher mean BMI (22.8 ± 6.0) compared to boys (21.8 ± 4.7), but this difference was not statistically significant. Accelerometry data showed that, on average, boys participated in more daily minutes of MVPA than girls did (40.1 ± 19.1 vs. 22.9 ± 12.8, p < 0.01). This was consistent with the self-reported MVPA data, as boys reported being Selleck Abiraterone more physically active than girls (3.0 ± 0.6 vs. 2.8 ± 0.6, p < 0.01). Perceived sport competence was slightly higher in boys (3.0 ± 0.6) than in girls (2.7 ± 0.6). This same trend was found for appearance (boys (2.9 ± 0.7); girls (2.8 ± 0.7)) and PA enjoyment (boys (4.3 ± 0.5); girls (4.1 ± 0.5)). PA self-efficacy was the only self-perception

variable that was slightly higher in girls (3.5 ± 0.8) than in boys (3.4 ± 0.8). These differences were only statistically significant for PD0332991 nmr perceived sport competence (p < 0.01). The associations between self-perception variables and objective MVPA, objective total PA, and subjective MVPA are shown in Table 2. When looking at subjective

MVPA, PA enjoyment (boys (r = 0.361); girls (r = 0.438)) and PA self-efficacy (boys (r = 0.317); girls (r = 0.490)) were both independently and significantly correlated with the self-reported amount of MVPA in both boys and girls (all p < 0.01). Subjective MVPA was also positively and significantly correlated with appearance (r = 0.182, p < 0.05) and sport competence (r = 0.285, p < 0.01) in girls, although the magnitude of association was smaller. These relationships were only slightly attenuated when adjusting for BMI Z-score. For both objectively measured MVPA and total PA, only the association between PA enjoyment (r = 0.19 for each, p < 0.05) was significant in girls. This relationship was slightly attenuated Oxygenase when adjusting for BMI Z-score, but remained significant. Hierarchical regression models predicting objective and subjective MVPA are shown in Table 3. The first model contained only the descriptive variables as predictors explained 25%, 5%, and 3% of the variance in objective MVPA (p < 0.01), objective total PA (p < 0.05), and subjective MVPA (p = 0.113), respectively. The second model contained the descriptive and perception variables as predictors explained 27%, 7%, and 27% of the variance in objective MVPA (p < 0.01), objective total PA (p < 0.05), and subjective MVPA (p < 0.01), respectively.

, 2012; Zylka et al., 2005). To determine whether peptidergic endings were missing in DTX-treated CGRPα-DTR+/− mice, we immunostained hindpaw sections with antibodies to CGRP and the pannerve fiber marker PGP9.5. We found that DTX treatment eliminated CGRP-IR terminals from the glabrous skin and hairy skin (epidermis and dermis) and from guard hairs (Figures 3A–3F, Figure S2). In contrast, DTX treatment did not eliminate CGRP-IR−, PGP9.5+ terminals, including terminals in the epidermis, hair follicles, and sweat glands (Figures 3A–3F, Figure S2, data not shown). Since ∼50% of all TRPV1+ DRG neurons were ablated in DTX-treated CGRPα-DTR+/− mice

(Figure 1H), we hypothesized that peripheral nerve responses to noxious heat might be impaired. To test this hypothesis, we utilized a skin-nerve preparation to quantify hot, cold, and mechanical responses of isolated C-fibers in the hindpaw of saline- and DTX-treated Vorinostat cell line CGRPα-DTR+/− mice (Koltzenburg et al., 1997; Pribisko and Perl,

2011). We also mapped the distribution of noxious heat- and cold-receptive fields in this preparation by recording from the entire sural nerve (Figures 3G–3K). A near-infrared diode laser was used to control the intensity and location of heat stimulation (Pribisko and Perl, 2011). In saline-treated mice, laser heat stimulation (using an intensity that is in excess Selleck PD-1/PD-L1 inhibitor 2 of the threshold of most C-fibers) activated multiple units in all of the spots (Figures 3G, 3I, and 3K). However, in DTX-treated mice, activity was detected in only 38.1% ± 2.4% of the spots (Figures 3G, 3I, and 3K). This is a profound reduction, particularly given that a response was scored as positive if as few as one action potential was detected when recording from the entire sural nerve. When averaged over all 40 spots, significantly fewer heat-evoked action potentials were

generated over the 2 s stimulation period in DTX-treated mice (Figure 3K). Furthermore, Cediranib (AZD2171) the laser heat threshold to activate isolated C-fibers was ∼2-fold higher in DTX-treated mice (Figure 3K). In contrast, there was no statistically significant change in the number of cold-responsive spots when recording from the entire sural nerve and no change in the cold threshold of activation in isolated C-fibers between groups (Figures 3H, 3J, and 3K). There was also no change in the mechanical thresholds of isolated C-fibers between saline- and DTX-treated CGRPα-DTR+/− mice (Figure 3K). Taken together, these data demonstrate that ablation of CGRPα+ afferents causes a profound loss of noxious heat sensitivity in skin with no change in cold or mechanical sensitivity. To determine whether this profound physiological loss of heat sensitivity also affected behavioral responses to heat, we tested saline- and DTX-treated CGRPα-DTR+/− mice using multiple heat-related behavioral assays (Table 1). For all of these experiments, we studied mice pre- and postsaline/DTX treatment and separately tested males and females.

, 2005, Bretscher et al., 2008, Hallem and Sternberg, 2008 and Zimmer et al., 2009). Even animals that live in enclosed spaces may monitor ambient concentrations. When CO2 levels

in the hive increase by ∼1%–2%, honeybees exhibit fanning behavior to ventilate the nest in order to maintain a low CO2 environment ( Seeley, 1974). CO2 emitted during respiration may also serve as a secreted chemical signal that other animals detect. In this way, CO2 may act as a chemosensory signal that alerts animals to potential food, predators, or danger. Blood-feeding insects such as mosquitoes, black flies, and tsetse flies are attracted to CO2 and use this signal to hone in on their human hosts (Gibson and Torr, 1999). The hawkmoth, Manduca Sexta, prefers flowers that emit a high level of CO2, suggesting that CO2 acts as a proximal signal learn more for nectar ( Guerenstein et al., 2004 and Thom et al., 2004). CO2 increases can also signal avoidance, as CO2 emitted by Drosophila upon stress acts as a signal for other Drosophila to flee ( Suh et al., 2004). How do animals detect and respond to varying concentrations of O2 and CO2 in their environment? check details Recent studies of the model

organisms C. elegans, Drosophila melanogaster and mice have begun to elucidate the neural and molecular bases of detection. In all cases, detection occurs in specialized sensory cells; in Drosophila and mice, subsets of olfactory and gustatory neurons respond specifically to CO2. In most cases, these neurons respond to discrete features in their environment, such as increases or decreases in O2 or short-range or long-range cues. Detection can lead to attraction or avoidance behavior, and these behaviors are plastic. Plasticity may be especially important to allow animals to interpret the rather nonspecific signals of O2 and CO2 in the context of their complex sensory world. The molecular underpinnings almost of detection are beginning to be elucidated, highlighting similarities across organisms and commonalities with ancient cellular mechanisms of detection. The nematode C. elegans lives in the soil. O2 levels in this environment vary from 1%–21%, depending on depth from

the surface as well as soil properties such as compaction, aeration, and drainage ( Anderson and Ultsch, 1987). C. elegans show a behavioral preference for 5%–10% O2 levels and avoid higher and lower concentrations ( Gray et al., 2004). This preferred O2 setpoint may reflect a compromise between the metabolic needs of the animal (favoring high O2) and oxidative stress (favoring low O2) ( Lee and Atkinson, 1977). The study of C. elegans O2 sensation has provided a framework for understanding how animals monitor gas levels to select a preferred environment. Recent progress has been made elucidating the neural and molecular bases for hyperoxia avoidance. Two pairs of neurons, URX and BAG, play critical roles in sensing O2 (Zimmer et al., 2009) (Figure 1).

In all, we recorded Screening Library from over 4,000 neurons, with populations ranging from hundreds to thousands of neurons from each of seven visual areas (V1,

LM, LI, AL, RL, AM, PM; Table 1). Two-photon calcium imaging permits recording of neural activity with single cell resolution simultaneously from populations of hundreds of neurons in a given field of view (Figure 3A, left panel). Importantly, tuning curves generated from Oregon Green Bapta-1 AM fluorescence are comparable to those recorded with traditional electrophysiological techniques in mouse visual cortex (Kerlin et al., 2010 and Nauhaus et al., 2011). We repeated the retinotopy stimulus to measure the eccentricity represented by each neuron in the 40× field of view and restricted analyses to neurons representing eccentricities within 50° of the center of space so as to match eccentricities across areas. Next, we presented drifting grating stimuli that varied across five spatial Hydroxychloroquine cost frequencies, ranging from 0.01–0.16 cycles per degree (cpd), and eight directions (SF experiment), or five temporal frequencies, ranging from 0.05 to 8 Hz, and eight directions (TF experiment). Responses were measured as the average change in the fluorescence of the calcium dye during

the stimulus period across multiple trials, relative to the baseline fluorescence during the prestimulus period (Figure 3A and Figure S3; Experimental Procedures). Mean response magnitude was similar across areas (11%–13% ΔF/F, ANOVA n.s.). Two-photon calcium imaging provides the unique advantage

of being able to quantify the fraction of neurons in a cortical region that reliably respond under a given stimulus condition. Across the entire population of cells from all visual areas, 39% (n = 1,811/4,609) of neurons in the SF experiments, and 27% (n = 1,195/4,449) of neurons in the TF experiments were reliably found responsive to at least one stimulus condition (Table 1; Experimental Procedures). Areas differed in the proportion of neurons that responded robustly and reliably to at least one stimulus condition (see Table 1). Intriguingly, in areas with lower proportions of responsive cells (such as AM), responsive neurons were generally extremely robust and selective (Figure 3B and Figure S3F). This demonstrates that neurons in extrastriate visual areas are highly selective for the appropriate stimulus, and suggests that the neurons that did not respond likely require stimuli or other conditions not explored in this study. That a higher fraction of neurons responded during the SF experiment suggests that neurons may be more selective to the appropriate SF than they are to TF within the ranges we tested. Indeed, SF bandwidth tuning was generally sharper than TF bandwidth tuning over the four octaves we sampled in each domain (Figures S4 and S5).

The process by which the RPE cells acquire a retinal progenitor phenotype appears to be a critical one, since the process after this point resembles that of normal development. This phenomenon has been variously termed metaplasia, transdifferentiation (Okada, 1980), or dedifferentiation (since the RPE cells are reverting to a developmentally earlier state). This phenomenon involves shifting the pattern of gene expression in a highly regulated way and might be called “regulated reprogramming” to distinguish it from the NVP-BGJ398 datasheet “direct

transdifferentiation” process that occurs in support cells in mechanosensory receptor regeneration in the inner ear or lateral line. Pigmented epithelial cells reprogram to a progenitor state in birds as well; however, this phenomenon is restricted to the earliest stages of

eye development, a few days after the lineages of the retinal progenitors and the RPE progenitors have diverged (Coulombre and Coulombre, 1970). Fish also have considerable ability to regenerate sensory receptor Linsitinib solubility dmso cells and other retinal neurons from sources within the retina. When the fish retina is damaged (via surgical, neurotoxic, or genetic lesions or excessive light), there is a burst of proliferation. As noted above, the fish retina contains a precursor cell that continues to generate new rod photoreceptors throughout the lifetime of the animal. For many years it was believed that

the primary source of new retinal neurons was the rod precursor (Raymond et al., 1988). More recently, it became clear that the Müller glia were another source, if not the major source and of proliferating cells after retinal damage in the fish (Fausett and Goldman, 2006 and Wu et al., 2001), although rod precursors contribute as well, particularly when only rods are damaged. After retinal damage, the Müller glia in the fish retina undergo a dedifferentiation process (Bernardos et al., 2007, Fausett and Goldman, 2006, Qin et al., 2009, Ramachandran et al., 2010, Raymond et al., 2006 and Thummel et al., 2008), somewhat like that described for the RPE in the amphibian; they re-express many, if not all, of the genes normally expressed in retinal progenitors. Thus, in both fish and amphibians, damage in the central retina causes nonneuronal cells to change their phenotype into retinal progenitors: in amphibians, the progenitors are derived from the RPE cells, while in fish these progenitors are derived from Müller glia. However, damage to cells in the peripheral retina can be repaired by a very different mechanism in these species. In both fish and amphibians, the retina contains a specialized zone of progenitor cells at the periphery, called the ciliary marginal zone (or CMZ), which adds new neurons of all types throughout the lifetime of the animal (for review, see Lamba et al., 2008).

The majority of cingulate SB appeared widely synchronized, whereas the relative low occurrence of NG precluded a consistent analysis of their coupling over the Cg. In the PL, most of SB (720 out

of 1200) were also widely synchronized, while the majority of prelimbic NG (768 out of 1472) synchronized the upper layers and the cortical plate (CP) (Figure 3D). The distinct spatial organization, current generators, and synchronization patterns of SB and Z-VAD-FMK clinical trial NG argue for different oscillatory entrainment of cingulate and prelimbic networks during neonatal development. This distinction persisted also at prejuvenile age, since the amplitude and main frequency of continuous theta-gamma rhythms in P10–14 rats (n = 19) differed significantly between the Cg and PL. Moreover, the power of superimposed gamma episodes was significantly (p < 0.001) higher in the PL (2737 ± 109 μV2/Hz, n = 19 pups) than in the Cg (2646 ± 110 μV2/Hz). The distinct properties of discontinuous versus continuous prefrontal oscillations suggest that the networks entrained for their generation are subject of intense

refinement and reorganization during postnatal development. In the light of the recently demonstrated function of hippocampal theta to temporally coordinate the prefrontal activity at adulthood (Siapas et al., 2005 and Sirota et al., 2008) the question arises, when during development the hippocampal control Selleck Vorinostat over the PFC emerges. The premise for addressing this question was to characterize in neonatal and prejuvenile rats (n = 33) the activity of the CA1 area of the intermediate Hipp, which at adulthood is known to densely project to the PFC (Hoover and Vertes, Ketanserin 2007). Already at birth prominent sharp-waves (SPWs) (Table S3; Figure S3A), which reversed across the pyramidal layer (Str pyr) and were accompanied by strong MUA discharge (13.07 ± 3.51 Hz, n = 10 pups), were present in the CA1 area. From P1

on, discontinuous oscillations with main frequency in theta band (7.03 ± 0.15 Hz, n = 398 events from 15 pups) were additionally present (Table S3; Figure S3B). They represent the dominant pattern of slow oscillatory activity in the neonatal Hipp. Since their mechanisms of generation are still unknown and might differ from those of the adult theta rhythms, we defined these events as hippocampal theta bursts. About one-third of the theta bursts (136 out of 398 events) were accompanied by SPWs. Their duration and maximal amplitude were significantly (p < 0.001) higher than of the theta bursts without superimposed SPWs (Table S3). As previously reported (Palva et al., 2000 and Lahtinen et al., 2002), gamma oscillations and ripples developed toward the end of the first postnatal week and appeared superimposed on theta bursts and SPWs, respectively.

First, there is slice physiology, which, when correlated with in vivo calcium imaging, can be used to examine the probability that neurons of a given functional type, GSK-3 inhibitor for instance, with the same preferred orientation, are synaptically connected (Ko et al., 2011). Second, there is transsynaptic tracing with replication-incompetent (G-deleted) rabies, which in one variant can label only neurons that are presynaptic

to a single target neuron (Marshel et al., 2010). When combined with in vivo calcium imaging, this technique holds the promise to fulfill the dream of Hubel and Wiesel to “examine one by one the receptive fields of all the afferents projecting upon that cell” (Hubel and Wiesel, 1962). Despite the conceptual simplicity of the technique, it has proven difficult so far to apply routinely, principally because it requires the delivery of multiple genes to a single target neuron in vivo. Slice physiology is an ideal technique to study the interconnections between neurons, but it is currently

limited to tens of connections in a given experiment. The single-cell version of G-deleted rabies may allow hundreds of connections to be examined but all from the vantage point of one postsynaptic cell. In the long run, serial-section electron microscopy has the potential to examine the thousands of connections between neurons that may be necessary to understand the functional logic of a cortical others circuit (Figure 1F). Serial-section EM has long been a powerful method for analyzing the dense neuropil of the central nervous system. But except for Alectinib supplier the simplest nervous systems (White et al., 1986), it has been poorly suited for studying extended circuits, with a few notable exceptions (for instance Sterling, 1983; Hamos et al., 1987). The major drawback in the method is one of scale. Although serial-section microscopy

was well developed in the 1960s and began to be computerized as early as the 1970s (Ware and LoPresti, 1975), computers were too slow and storage was too expensive for very large-scale reconstructions. In order to collect three-dimensional nanoscale data from a circuit that spans hundreds of micrometers, terabytes of data are required, a scale that has only become tractable in recent years (Anderson et al., 2011; Bock et al., 2011; Briggman et al., 2011). Because of the technical hurdles needed to collect and annotate EM data sets of this size, it has taken some time for the first research studies since the original demonstration of ultrastructural reconstructions at the circuit scale (Denk and Horstmann, 2004; Bock et al., 2011; Briggman et al., 2011; Anderson et al., 2011). At present, however, large-scale EM data collection is now being performed in a number of laboratories. The greatest challenge in the coming years for EM circuit reconstruction will not be data collection but image segmentation (Jain et al., 2010).

Only a small percentage of exposed adult humans or animals develop clinical signs of toxoplasmosis. Several factors can be related to the severity of toxoplasmosis in immunocompetent hosts, including parasite strain, host variability and genetic variability of the parasite. Most T. gondii isolates from humans and animals in Europe and North America have been classified into one of the three clonal lineages named Types I, II and III ( Dardé et al., 1992, Howe and Sibley, 1995 and Ajzenberg et al., 2002). However, recent studies have reported that the parasite isolates in Brazil are biologically and genetically

different ( Dubey et al., 2002, Dubey et al., 2007a, Dubey et al., 2007b and Lehmann et al., 2006). Pena selleck chemical et al. (2008) identified 48 RFLP (Restriction Fragment Length Polymorphism) genotypes in 125 isolates from chickens, dogs and cats; four of these isolates are considered to be common clonal lineages

in Brazil, designated as Types BrI, BrII, BrIII and BrIV. Little is known about the genotypes of T. gondii circulating in wild animals in Brazil. Brazil is considered to be the country with the greatest biodiversity on the planet, accounting for the highest numbers of both terrestrial vertebrates and invertebrates in the world ( Lambertini, 2000). Recently, Yai et al. (2009) have identified 16 genotypes among 36 T. gondii isolates from capybaras (Hydrochaeris hydrochaeris) in Brazil, corroborating the previous finding that this parasite population is highly diverse in this region. In the present study, we described the genetic Selleckchem PD0332991 and biological characteristics of T. gondii isolates from a red-handed howler monkey (Alouatta belzebul), a jaguarundi (Puma yagouaroundi), and a black-eared opossum (Didelphis aurita) from two Brazilian regions. A young male red-handed howler monkey (A. belzebul) had inhabited the Zoo of Parque Phosphatidylinositol diacylglycerol-lyase Estadual Dois Irmãos, in the municipality of Recife, Pernambuco State, Northeastern Brazil, since January 2008. It was fed on fruits and leaves and died 5 days after showing prostration, diarrhoea and hyperthermia

in July 2009, suspected with toxoplasmosis. The heart, brain and diaphragm were collected soon after the death of the monkey. An adult male jaguarundi (P. yagouaroundi) had inhabited the same Zoo since 2001. It was fed on pre-frozen beef, chicken and viscera. This felid died of trauma in July 2009. Its heart, brain and muscles were collected for the study. A wild adult female black-eared opossum (D. aurita) was captured alive in Sorocaba municipality, São Paulo State, Southeastern Brazil. A serologic examination using the modified agglutination test (MAT) ( Dubey and Desmonts, 1987) was performed soon after the capture; the result showed that this female black-eared opossum carried antibodies to T. gondii (MAT titre 1:100). This animal was euthanised, and its tissues (brain, heart and diaphragm) were collected for bioassay analysis.

Two novel and two standard methods of graph definition were examined within a large cohort of healthy young adults (and in a matched replication cohort; see Table S1 available online). To reiterate, graphs are composed of a set of nodes and a set of ties between nodes. Graphs were formed using the nodes described below, BLZ945 and ties were defined using Pearson correlation coefficients between node rs-fcMRI timecourses. The cross correlation matrix of a set of nodes thus defines a graph. Because most graph theoretic techniques are developed (and are most meaningful) in sparse graphs (Newman, 2010), thresholds were

applied to the graphs to eliminate weak ties (such that correlations under the threshold were ignored). Because there is no “correct” threshold, all analyses were performed over a range of thresholds, typically beginning around 10% tie density (retaining the strongest 10% of correlations) and rising until the networks became severely fragmented (see Supplemental Experimental Procedures). The first novel graph (referred to as the areal graph) was defined in accord with

neurobiological principles. The brain is a complex network with a hierarchical spatial and functional organization (in the cortex) at the level of neurons, local circuits, columns, functional areas, and functional systems. Standard rs-fcMRI analyses use cubic voxels that are Y-27632 a few millimeters on each side, and thus can potentially resolve brain relationships at the level of areas. Centers of putative areas were identified using two independent methods operating on data sets that were not used in graph analyses (see Experimental Procedures). The first method was meta-analytic in nature (as in Dosenbach et al., 2006), and explored a large fMRI data set to identify voxels that were reliably and significantly modulated

when certain behaviors were demanded secondly (e.g., button-pressing) or certain signal types were found (e.g., error-related activity). The second method extended a recently developed technique of mapping cortical areas using rs-fcMRI to entire cortical sheets (fc-Mapping) (Barnes et al., 2011, Cohen et al., 2008 and Nelson et al., 2010a). The combination of these methods yielded 264 putative areas spanning the cerebral cortex, subcortical structures, and the cerebellum (see Experimental Procedures, Figure S1, and Table S1 for analysis details, and Table S2 for coordinates). Regions of interest (ROIs) were modeled as 10 mm diameter spheres. Graphs were formed using ROIs as nodes (n = 264) and ties terminating within 20 mm of a source node center were set to zero to avoid possible shared signal between nearby nodes. This procedure yielded graphs of putative functional areas in which each node represented, to the best of our capabilities, an element of brain organization.