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In summary, FBC offers a novel way to unify static and dynamic connectivity analyses and can provide additional information about the frequency profile of connectivity patterns.Data-driven parcellations are widely used for exploring the functional organization of the brain, and also for reducing the high dimensionality of fMRI data. Despite the flurry of methods proposed in the literature, functional brain parcellations are not highly reproducible at the level of individual subjects, even with very long acquisitions. Some brain areas are also more difficult to parcellate than others, with association heteromodal cortices being the most challenging. An important limitation of classical parcellations is that they are static, that is, they neglect dynamic reconfigurations of brain networks. In this paper, we proposed a new method to identify dynamic states of parcellations, which we hypothesized would improve reproducibility over static parcellation approaches. For a series of seed voxels in the brain, we applied a cluster analysis to regroup short (3 min) time windows into “states” with highly similar seed parcels. We split individual time series of the Midnight scan club sample into two independent sets of 2.5 hr (test and retest). We found that average within-state parcellations, called stability maps, were highly reproducible (over 0.9 test-retest spatial correlation in many instances) and subject specific (fingerprinting accuracy over 70% on average) between test and retest. Consistent with our hypothesis, seeds in heteromodal cortices (posterior and anterior cingulate) showed a richer repertoire of states than unimodal (visual) cortex. Taken together, our results indicate that static functional parcellations are incorrectly averaging well-defined and distinct dynamic states of brain parcellations. This work calls to revisit previous methods based on static parcellations, which includes the majority of published network analyses of fMRI data. Our method may, thus, impact how researchers model the rich interactions between brain networks in health and disease.Dimension reduction is widely used and often necessary to make network analyses and their interpretation tractable by reducing high-dimensional data to a small number of underlying variables. Techniques such as exploratory factor analysis (EFA) are used by neuroscientists to reduce measurements from a large number of brain regions to a tractable number of factors. However, dimension reduction often ignores relevant a priori knowledge about the structure of the data. For example, it is well established that the brain is highly symmetric. In this paper, we (a) show the adverse consequences of ignoring a priori structure in factor analysis, (b) propose a technique to accommodate structure in EFA by using structured residuals (EFAST), and (c) apply this technique to three large and varied brain-imaging network datasets, demonstrating the superior fit and interpretability of our approach. We provide an R software package to enable researchers to apply EFAST to other suitable datasets.

As yet, there is limited research that can identify factors that differentiate between painful and nonpainful neuropathies after traumatic nerve injury. The aim of this study was to compare subjects with pain and without pain, all after operative nerve repair in the upper extremities.

Subjects in both groups (pain, n = 69; painless, n = 62) underwent clinical assessment of sensory nerve function and psychophysical tests quantitative sensory testing and conditioned pain modulation (CPM). Conditioned pain modulation was assessed by pain ratings to 120 seconds pressure stimuli administered before and after a 60 seconds noxious 4°C cold conditioning stimulus (CS). Time of recovery (time off) of pain intensity from peak VAS

after CS was recorded. Questionnaires about the quality of life (RAND-36) and disability of the extremity (QuickDash) were completed.

There were no significant differences between groups for CPM (

= 0.19). Time off was 42 seconds in subjects with pain in comparison with 28 seconds in those without pain (

< 0.0001). Compared with individuals reporting no pain, participants with neuropathic pain after nerve injuries had 1.8 times the odds of recovering later after CS, gain of function findings at sensory examination (

< 0.0001), lower scores of the physical component of RAND-36 (

< 0.0001), and increase arm disability (

< 0.0001). Hyperesthesia to cold pain stimulation (

= 0.03) and lowered pain pressure threshold (

= 0.01) were found in the pain group.

Recovery after the pain induced by cold CS indicates changes in central processing of pain and provides a potential measurement of endogenous pain modulation in individuals with chronic neuropathic pain.

Recovery after the pain induced by cold CS indicates changes in central processing of pain and provides a potential measurement of endogenous pain modulation in individuals with chronic neuropathic pain.

A single injection of nerve growth factor (NGF) into a low back muscle induces a latent sensitization of rat dorsal horn neurons (DHNs) that primes for a manifest sensitization by a subsequent second NGF injection. Repeated restraint stress also causes a latent DHN sensitization.

In this study, we investigated whether repeated restraint stress followed by a single NGF injection causes a manifest sensitization of DHNs.

Rats were stressed repeatedly in a narrow plastic restrainer (1 hour on 12 consecutive days). Control animals were handled but not restrained. Raptinal Two days after stress paradigm, behavioral tests and electrophysiological in vivo recordings from single DHNs were performed. Mild nociceptive low back input was induced by a single NGF injection into the lumbar multifidus muscle just before the recording started.

Restraint stress slightly lowered the low back pressure pain threshold (Cohen

= 0.83). Subsequent NGF injection increased the proportion of neurons responsive to deep low back input (control + NGF 14%, stress + NGF 39%;

= 0.041), mostly for neurons with input from outside the low back (7% vs 26%;

= 0.081). There was an increased proportion of neurons with resting activity (28% vs 55%;

= 0.039), especially in neurons having deep input (0% vs 26%;

= 0.004).

The results indicate that stress followed by a short-lasting nociceptive input causes manifest sensitization of DHNs to deep input, mainly from tissue outside the low back associated with an increased resting activity. These findings on neuronal mechanisms in our rodent model suggest how stress might predispose to radiating pain in patients.

The results indicate that stress followed by a short-lasting nociceptive input causes manifest sensitization of DHNs to deep input, mainly from tissue outside the low back associated with an increased resting activity. These findings on neuronal mechanisms in our rodent model suggest how stress might predispose to radiating pain in patients.