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Spontaneous brain activity, measured with resting state fMRI (R-fMRI), is correlated among regions that are co-activated by behavioral tasks. It is unclear, however, whether spatial patterns of spontaneous activity within a cortical region correspond to spatial patterns of activity evoked by specific stimuli, actions, or mental states. The current study investigated the hypothesis that spontaneous activity in motor cortex represents motor patterns commonly occurring in daily life. To test this hypothesis 15 healthy participants were scanned while performing four different hand movements. Three movements (Grip, Extend, Pinch) were ecological involving grip and grasp hand movements; one control movement involving the rotation of the wrist was not ecological and infrequent (Shake). They were also scanned at rest before and after the execution of the motor tasks (resting-state scans). Using the task data, we identified movement-specific patterns in the primary motor cortex. These task-defined patterns were compared to resting-state patterns in the same motor region. We also performed a control analysis within the primary visual cortex. We found that spontaneous activity patterns in the primary motor cortex were more like task patterns for ecological than control movements. In contrast, there was no difference between ecological and control hand movements in the primary visual area. These findings provide evidence that spontaneous activity in human motor cortex forms fine-scale, patterned representations associated with behaviors that frequently occur in daily life., (© 2022. The Author(s).)

The function of spontaneous brain activity is an important issue in neuroscience. Here we test the hypothesis that patterns of spontaneous activity code representational patterns evoked by stimuli. We compared in human visual cortex multivertex patterns of spontaneous activity to patterns evoked by ecological visual stimuli (faces, bodies, scenes) and low-level visual features (e.g., phase-scrambled faces). Specifically, we identified regions that preferred particular stimulus categories during localizer scans (e.g., extrastriate body area for bodies), measured multivertex patterns for each category during event-related task scans, and then correlated over vertices these stimulus-evoked patterns to the pattern measured on each frame of resting-state scans. The mean correlation coefficient was essentially zero for all regions/stimulus categories, indicating that resting multivertex patterns were not biased toward particular stimulus-evoked patterns. However, the spread of correlation coefficients between stimulus-evoked and resting patterns, positive and negative, was significantly greater for the preferred stimulus category of an ROI. The relationship between spontaneous and stimulus-evoked multivertex patterns also governed the temporal correlation or functional connectivity of patterns of spontaneous activity between individual regions (pattern-based functional connectivity). Resting multivertex patterns related to an object category fluctuated preferentially between ROIs preferring the same category, and fluctuations of the pattern for a category (e.g., body) within its preferred ROIs were largely uncorrelated with fluctuations of the pattern for a disparate category (e.g., scene) within its preferred ROIs. These results support the proposal that spontaneous multivertex activity patterns are linked to stimulus-evoked patterns, consistent with a representational function for spontaneous activity. NEW & NOTEWORTHY Spontaneous brain activity was once thought to reflect only noise, but evidence of strong spatiotemporal regularities has motivated a search for functional explanations. Here we show that the spatial pattern of spontaneous activity in human high-level and early visual cortex is related to the spatial patterns evoked by stimuli. Moreover, these patterns partly govern spontaneous spatiotemporal interactions between regions, so-called functional connectivity. These results support the hypothesis that spontaneous activity serves a representational function.

Insulin and insulin-like growth factor-1 (IGF1), acting respectively via the insulin (INSR) and IGF1 (IGF1R) receptors, play key developmental and metabolic roles throughout life. In addition, both signaling pathways fulfill important roles in cancer initiation and progression. The present study was aimed at identifying mechanistic differences between INSR and IGF1R using a recently developed bioinformatics tool, the Biological Network Simulator (BioNSi). This application allows to import and merge multiple pathways and interaction information from the KEGG database into a single network representation. The BioNsi network simulation tool allowed us to exploit the availability of gene expression data derived from breast cancer cell lines with specific disruptions of the INSR or IGF1R genes in order to investigate potential differences in protein expression that might be linked to biological attributes of the specific receptor networks. Modeling-generated information was corroborated by experimental and biological assays. BioNSi analyses revealed that the expression of 75 and 71 genes changed during simulation of IGF1R-KD and INSR-KD, compared to control cells, respectively. Out of 16 proteins that BioNSi analysis was based on, validated by Western blotting, nine were shown to be involved in DNA repair, eight in cell cycle checkpoints, six in proliferation, eight in apoptosis, seven in oxidative stress, six in cell migration, two in energy homeostasis, and three in senescence. Taken together, analyses identified a number of commonalities and, most importantly, dissimilarities between the IGF1R and INSR pathways that might help explain the basis for the biological differences between these networks., (Copyright © 2020 Sarfstein, Yeheskel, Sinai-Livne, Pasmanik-Chor and Werner.)

Clinical, epidemiological and experimental data identified the insulin-like growth factor-1 receptor (IGF1R) as a candidate therapeutic target in oncology. While this paradigm is based on well-established biological facts, including the potent anti-apoptotic and cell survival capabilities of the receptor, most Phase III clinical trials designed to target the IGF1R led to disappointing results. The present study was aimed at evaluating the hypothesis that combined treatment composed of selective IGF1R inhibitor along with classical chemotherapy might be more effective than individual monotherapies in breast cancer treatment. Analyses included comprehensive measurements of the synergism achieved by various combination regimens using the CompuSyn software. In addition, proteomic analyses were conducted to identify the proteins involved in the synergistic killing effect at a global level. Data presented here demonstrates that co-treatment of IGF1R inhibitor along with chemotherapeutic drugs markedly improves the therapeutic efficiency in breast cancer cells. Of clinical relevance, our analyses indicate that high IGF1R baseline expression may serve as a predictive biomarker for IGF1R targeted therapy. In addition, we identified a ten-genes signature with potential predictive value. In conclusion, the use of a series of bioinformatics tools shed light on some of the biological pathways that might be responsible for synergysm in cancer therapy., Competing Interests: CONFLICTS OF INTEREST The authors declare that they have no conflicts of interest., (Copyright: © 2020 Sinai-Livne et al.)

Cognitive models of social anxiety disorder (SAD) emphasize the role of explicit and implicit self-evaluations (SEs) in the etiology and maintenance of this condition. Whereas individuals with SAD consistently report lower explicit SEs as compared with nonanxious individuals, findings concerning implicit SEs are mixed. To gain a more nuanced understanding of the nature of SEs in SAD, we examined explicit and implicit SEs in two significant interpersonal domains: social rank and affiliation. Consistent with cognitive theorizing, we predicted that, compared to nonclinical controls (NCCs), individuals with SAD would exhibit lower explicit and implicit SEs in both domains. Guided by evolutionary theories we also predicted that the differences in SEs between the groups would be greater in the social rank, as compared to the affiliation, domain. Individuals diagnosed with SAD (n = 38) and NCCs) n = 40) performed two variants of the Self Implicit Association Test: one concerning social rank, and the other concerning affiliation. They also rated themselves on social-rank and affiliation traits. We found that, as compared to NCCs, individuals with SAD exhibited lower social-rank and affiliation SEs. Moreover, differences between the groups in social-rank SEs were greater than in affiliation SEs. Importantly, this pattern was evident in implicit SEs, as much as in explicit SEs. Our findings dovetail with evolutionary accounts highlighting the centrality of the social-rank system in SAD, and refine central tenets of cognitive theories of SAD. A multidomain, multimethod approach to the understanding of the self may broaden our conceptualization of SAD and related disorders. (PsycINFO Database Record, ((c) 2017 APA, all rights reserved).)

Public health nurses (PHNs) working in Well Baby Clinic in Israel's Haifa district were voicing great distress to inspectors-the impossibility of meeting their workload, feeling overwhelmed, poor physical, and technological conditions. They were feeling tired and frustrated and burn-out was rising. The district's nursing management took the decision, together with Tel Aviv University's nursing research unit, to conduct a quality improvement project based on issues that arose from meetings with focus groups on the nurses' difficulties. This paper is a case study of a quality improvement project targeting nurses daily working life. One of its chief contributions is as a study of meeting PHNs' frustration by integrating focus groups and round-table brainstorming (involving nurses, clinic managers and nursing inspectors) in order to identify targets for practical intervention. This strategy has been very successful. It has provided the district's nursing management a battery of forcefully argued and realistically grounded proposals for making the work of Well Baby clinics more relevant to their communities and giving nurses (a) the conditions to meet their assignments and (b) greater professional self-respect., (© 2016 Wiley Periodicals, Inc.)

Recognizing objects in the environment and understanding our surroundings often depends on context: the presence of other objects and knowledge about their relations with each other. Such contextual information activates a set of medial lobe brain regions, the parahippocampal cortex and the retrosplenial complex. Both regions are more activated by single objects with a unique contextual association than by objects not associated with any specific context. Similarly they are more activated by spatially coherent arrangements of objects when those are consistent with their known spatial relations. The current study tested how context in multiple-object displays is represented in these regions in the absence of relevant spatial information. Using an fMRI slow-event-related design, we show that the precuneus (a subpart of the retrosplenial complex) is more activated by simultaneously presented contextually related objects than by unrelated objects. This suggests that the representation of context in this region is cumulative, representing integrated information across objects in the display. We discuss these findings in relation to processing of visual information and relate them to previous findings of contextual effects in perception.

The visual system can integrate discrete units of information to construct a coherent description of the input it receives. Little is known about the processes of grouping and their implementation in the visual system. Previously we described a configural effect in which the global arrangement (degree of co-circularity) of Gabor flankers affected the degree of crowding with a Gabor target that they surrounded. Here we tested possible mechanisms by which the configural effect might operate in crowding. We ruled out simple explanations based on the effect of basic units constructing these configurations (pairs of opposing Gabors). Our results support an explanation for crowding that is based on grouping processes between flankers. They also suggest that not all flankers necessarily directly affect the target. Flankers might group together and interact with the target as a single element. Finally, using a computational model of crowding based on compulsory grouping (following Gestalt principles) and segmentation, we define the relative contribution of different pair relations of grouped elements to crowding.

The influence of configuration on visual crowding was tested. Eight Gabor patches surrounding a central one were arranged in a way that created several global configurations differing by their internal arrangements (smooth contour vs. random), while still preserving pairwise relationships between the target and flankers. Orientation discrimination and contrast detection of the central Gabor were measured. These measurements revealed differences in the magnitude of crowding produced by the different configurations, especially on the discrimination task. The crowding effect was stronger when random configurations were used and was reduced considerably when a smooth one was used. These results showed the typical dependence of crowding on eccentricity and target-flanker separation, which was independent of the configural effect. Controlling flankers' local orientation allowed addressing the nature of the effect. It was found to be sensitive to spatial relations and did not represent a simple averaging of local orientation estimates. Our results show that crowding operates at a level where configuration information has already been extracted. We relate all this to the object-based nature of perception.