A Multi-Stage Model for Fundamental Functional Properties in Primary Visual Cortex

Many neurons in mammalian primary visual cortex have properties such as sharp tuning for contour orientation, strong selectivity for motion direction, and insensitivity to stimulus polarity, that are not shared with their sub-cortical counterparts. Successful models have been developed for a number of these properties but in one case, direction selectivity, there is no consensus about underlying mechanisms. We here define a model that accounts for many of the empirical observations concerning direction selectivity. The model describes a single column of cat primary visual cortex and comprises a series of processing stages. Each neuron in the first cortical stage receives input from a small number of on-centre and off-centre relay cells in the lateral geniculate nucleus. Consistent with recent physiological evidence, the off-centre inputs to cortex precede the on-centre inputs by a small (∼4 ms) interval, and it is this difference that confers direction selectivity on model neurons. We show that the resulting model successfully matches the following empirical data: the proportion of cells that are direction selective; tilted spatiotemporal receptive fields; phase advance in the response to a stationary contrast-reversing grating stepped across the receptive field. The model also accounts for several other fundamental properties. Receptive fields have elongated subregions, orientation selectivity is strong, and the distribution of orientation tuning bandwidth across neurons is similar to that seen in the laboratory. Finally, neurons in the first stage have properties corresponding to simple cells, and more complex-like cells emerge in later stages. The results therefore show that a simple feed-forward model can account for a number of the fundamental properties of primary visual cortex

Shock compression experiments using the DiPOLE 100-X laser on the high energy density instrument at the European x-ray free electron laser: quantitative structural analysis of liquid Sn

X-ray free electron laser (XFEL) sources coupled to high-power laser systems offer an avenue to study the structural dynamics of materials at extreme pressures and temperatures. The recent commissioning of the DiPOLE 100-X laser on the high energy density (HED) instrument at the European XFEL represents the state-of-the-art in combining x-ray diffraction with laser compression, allowing for compressed materials to be probed in unprecedented detail. Here, we report quantitative structural measurements of molten Sn compressed to 85(5) GPa and ∼ 3500 K. The capabilities of the HED instrument enable liquid density measurements with an uncertainty of ∼ 1 % at conditions which are extremely challenging to reach via static compression methods. We discuss best practices for conducting liquid diffraction dynamic compression experiments and the necessary intensity corrections which allow for accurate quantitative analysis. We also provide a polyimide ablation pressure vs input laser energy for the DiPOLE 100-X drive laser which will serve future users of the HED instrument

Incidental pulmonary embolism in oncologic patients—a systematic review and meta-analysis

Purpose!#!Incidental pulmonary embolism (IPE) is a common finding on computed tomography (CT). IPE is frequent in oncologic patients undergoing staging CT. The aim of this analysis was to provide the pooled frequency of IPE and frequencies of IPE in different primary tumors.!##!Methods!#!MEDLINE, SCOPUS, and EMBASE databases were screened for studies investigating frequency of IPE in oncologic staging CT up to February 2020. Overall, 12 studies met the inclusion criteria and were included into the present study.!##!Results!#!The pooled analysis yielded a total of 28,626 patients. IPE was identified in 963 patients (3.36%, 95% CI = 3.15; 3.57). The highest frequency was found in prostate cancer (8.59%, 95%CI = 3.74; 13.44), followed by hepatobiliary carcinoma (6.07%, 95%CI = 3.09; 9.05) and pancreatic cancer (5.65%, 95%CI = 3.54; 7.76). The lowest frequencies were identified in tumors of male reproductive organs (0.79%, 95%CI = 0.21; 1.37) and hematological diseases (1.11% 95%CI = 0.74; 1.48).!##!Conclusion!#!The overall frequency of IPE in oncologic patients was 3.36%. There are considerable differences in regard to primary tumors with the highest frequency in prostate cancer and pancreatic and hepatobiliary carcinomas

Optimality and modularity in human movement: from optimal control to muscle synergies

International audienceIn this chapter, we review recent work related to the optimal and modular control hypotheses for human movement. Optimal control theory is often thought to imply that the brain continuously computes global optima for each motor task it faces. Modular control theory typically assumes that the brain explicitly stores genuine synergies in specific neural circuits whose combined recruitment yields task-effective motor inputs to muscles. Put this way, these two influential motor control theories are pushed to extreme positions. A more nuanced view, framed within Marr’s tri-level taxonomy of a computational theory of movement neuroscience, is discussed here. We argue that optimal control is best viewed as helping to understand “why” certain movements are preferred over others but does not say much about how the brain would practically trigger optimal strategies. We also argue that dimensionality reduction found in muscle activities may be a by-product of optimality and cannot be attributed to neurally hardwired synergies stricto sensu, in particular when the synergies are extracted from simple factorization algorithms applied to electromyographic data; their putative nature is indeed strongly dictated by the methodology itself. Hence, more modeling work is required to critically test the modularity hypothesis and assess its potential neural origins. We propose that an adequate mathematical formulation of hierarchical motor control could help to bridge the gap between optimality and modularity, thereby accounting for the most appealing aspects of the human motor controller that robotic controllers would like to mimic: rapidity, efficiency, and robustness