The slime mould Physarum polycephalum displays adaptive transport dynamics and network formation that have inspired its use as a model of biological computation. We develop a Lagrangian formulation of Physarum's adaptive dynamics on predefined graphs, showing that steady states arise as extrema of a least-action functional balancing metabolic dissipation and transport efficiency. The organism's apparent ability to find optimal paths between nutrient sources and sinks emerges from minimizing global energy dissipation under predefined boundary conditions that specify the problem to be solved. Applied to ring, tree, and lattice geometries, the framework accurately reproduces the optimal conductance and flux configurations observed experimentally. These results show that Physarum's problem-solving on constrained topologies follows a physics-based variational principle, revealing least-action dynamics as the foundation of its adaptive organization.
Thea Parsberg Støle, Marianne Lunde, Katja Gehmlich
et al.
The transmembrane proteoglycan syndecan-4 is known to be involved in the hypertrophic response to pressure overload. Although multiple downstream signaling pathways have been found to be involved in this response in a syndecan-4-dependent manner, there are likely more signaling components involved. As part of a larger syndecan-4 interactome screening, we have previously identified MLP as a binding partner to the cytoplasmic tail of syndecan-4. Interestingly, many human MLP mutations have been found in patients with hypertrophic (HCM) and dilated cardiomyopathy (DCM). To gain deeper insight into the role of the syndecan-4–MLP interaction and its potential involvement in MLP-associated cardiomyopathy, we have here investigated the syndecan-4–MLP interaction in primary adult rat cardiomyocytes and the H9c2 cell line. The binding of syndecan-4 and MLP was analyzed in total lysates and subcellular fractions of primary adult rat cardiomyocytes, and baseline and differentiated H9c2 cells by immunoprecipitation. MLP and syndecan-4 localization were determined by confocal microscopy, and MLP oligomerization was determined by immunoblotting under native conditions. Syndecan-4–MLP binding, as well as MLP self-association, were also analyzed by ELISA and peptide arrays. Our results showed that MLP-WT and syndecan-4 co-localized in many subcellular compartments; however, their binding was only detected in nuclear-enriched fractions of isolated adult cardiomyocytes. In vitro, syndecan-4 bound to MLP at three sites, and this binding was reduced in some HCM-associated MLP mutations. While MLP and syndecan-4 also co-localized in many subcellular fractions of H9c2 cells, these proteins did not bind at baseline or after differentiation into cardiomyocyte-resembling cells. Independently of syndecan-4, mutated MLP proteins had an altered subcellular localization in H9c2 cells, compared to MLP-WT. The DCM- and HCM-associated MLP mutations, W4R, L44P, C58G, R64C, Y66C, K69R, G72R, and Q91L, affected the oligomerization of MLP with an increase in monomeric at the expense of trimeric and tetrameric recombinant MLP protein. Lastly, two crucial sites for MLP self-association were identified, which were reduced in most MLP mutations. Our data indicate that the syndecan-4–MLP interaction was present in nuclear-enriched fractions of isolated adult cardiomyocytes and that this interaction was disrupted by some HCM-associated MLP mutations. MLP mutations were also linked to changes in MLP oligomerization and self-association, which may be essential for its interaction with syndecan-4 and a critical molecular mechanism of MLP-associated cardiomyopathy.
Iron accumulates in the neural tissue during peripheral nerve degeneration. Some studies have already been suggested that iron facilitates Wallerian degeneration (WD) events such as Schwann cell de-differentiation. On the other hand, intracellular iron levels remain elevated during nerve regeneration and gradually decrease. Iron enhances Schwann cell differentiation and axonal outgrowth. Therefore, there seems to be a paradox in the role of iron during nerve degeneration and regeneration. We explain this contradiction by suggesting that the increase in intracellular iron concentration during peripheral nerve degeneration is likely to prepare neural cells for the initiation of regeneration. Changes in iron levels are the result of changes in the expression of iron homeostasis proteins. In this review, we will first discuss the changes in the iron/iron homeostasis protein levels during peripheral nerve degeneration and regeneration and then explain how iron is related to nerve regeneration. This data may help better understand the mechanisms of peripheral nerve repair and find a solution to prevent or slow the progression of peripheral neuropathies.
This paper presents quantitative information on the effectiveness of seismic retrofit solutions using bilinear oil dampers for seismically deficient existing tall steel buildings. For this purpose, a benchmark 40-story steel space moment-resisting frame building is studied that represents 1970s design practice in North America. Rigorous seismic performance assessment based on ASCE 41 recommendations reveals a high collapse risk for the existing building. The local engineering demand parameters are comprehensively assessed to quantify the impact of seismic retrofit on steel columns and column splices, which are particularly vulnerable due to the time of construction. Multiple retrofit schemes are explored with numerous damping levels and vertical damping distribution methods. The dampers are designed via a recently developed multi-degree-of-freedom performance curves method. A new balanced vertical damping method is proposed to account for the effects of frame inelasticity. This strongly depends on the supplemental damping level, and it determines the effectiveness of the employed vertical damping distribution method. The results indicate that the proposed retrofit strategies can minimize the collapse risk of the tall building. It is shown that the balanced vertical damping distribution method provides the most uniform drift distribution along the building height. Despite the reduction in story drift ratios, the axial force demand in exterior columns remains relatively high in the bottom stories regardless of the seismic retrofit solution. On the other hand, bilinear oil dampers produce relative constant forces despite exhibiting higher velocity demands than expected.
Parvin Zarei Eskikand, David B Grayden, Tatiana Kameneva
et al.
Computational modeling helps neuroscientists to integrate and explain experimental data obtained through neurophysiological and anatomical studies, thus providing a mechanism by which we can better understand and predict the principles of neural computation. Computational modeling of the neuronal pathways of the visual cortex has been successful in developing theories of biological motion processing. This review describes a range of computational models that have been inspired by neurophysiological experiments. Theories of local motion integration and pattern motion processing are presented, together with suggested neurophysiological experiments designed to test those hypotheses.
This work presents a bunched of promising technologies to treat blind people: the bionic eyes. The strategy is to combine a retina implant with software capable to interpret the information received. Along this line of thinking, projects such as Retinal Prosthetic Strategy with the Capacity to Restore Normal Vision from Weill Medical College of Cornell University Project, Update on Retinal Prosthetic Research from The Boston Retinal Implant Project, and Restoration of Vision Using Wireless Cortical Implants from Monash Vision Group Project, have shown in a different context the use of technologies that commits to bring the vision through its use.
Mechanical alloying is among the few cost effective techniques for synthesizing nanocrystalline alloy powders. This article reviews mechanical alloying or ball-milling of (NC) powders of Fe-Cr alloys of different compositions, and the remarkable oxidation resistance of the NC alloy. The article also reviews challenges in thermal processing of the mechanically alloyed powders (such as compaction into monolithic mass) and means to overcome the challenges.
Jesse D. Marshall, Tianqing Li, Joshua H. Wu
et al.
Animals move in three dimensions (3D). Thus, 3D measurement is necessary to report the true kinematics of animal movement. Existing 3D measurement techniques draw on specialized hardware, such as motion capture or depth cameras, as well as deep multi-view and monocular computer vision. Continued advances at the intersection of deep learning and computer vision will facilitate 3D tracking across more anatomical features, with less training data, in additional species, and within more natural, occlusive environments. 3D behavioral measurement enables unique applications in phenotyping, investigating the neural basis of behavior, and designing artificial agents capable of imitating animal behavior.
We introduce the TUH EEG Seizure Corpus (TUSZ), which is the largest open source corpus of its type, and represents an accurate characterization of clinical conditions. In this paper, we describe the techniques used to develop TUSZ, evaluate their effectiveness, and present some descriptive statistics on the resulting corpus.
The ultrastructure fluctuations and complex dynamics of the multi-layered membrane structure of myelin are fundamental for understanding and control its formation process and its degeneration and repair in neurological diseases such as multiple sclerosis (MS). Myelin is considered a liquid-crystal but information are confined to its average structure due to limitations of the available standard techniques. To overcome this limitation in this work we have used Scanning micro X-ray Diffraction (SμXRD) which is a unique non-invasive probe of both k-space and real space allowing to visualize disorder in myelin with high spatial resolution in real space. We have used this method to examine the myelin sheath in the sciatic nerve of Xenopus laevis. Our results open could open new venues for understanding formation and degradation of myelin.
Electroencephalography (EEG) signals' interpretation is based on waveform analysis, where meaningful information should emerge from a plethora of data. Nonetheless, the continuous increase in computational power and the development of new data processing algorithms in the recent years have put into reach the possibility of analysing raw EEG signals. Bearing that motivation, the authors propose a new approach using raw data EEG signals and deep learning neural networks, for the classification of motor activities (executed and imagery). The hypothesis to be presented here is: each instantaneous measurement of the raw signal of all EEG channels (superchord) is unique per motor activity regardless the moment of measurement. This study has confirmed the hypothesis (results with accuracy over 80%, mean for 109 subjects), reinforcing the need of further research for the understanding of mental processes.
It has been suggested that the origins of cognitive modernity in the Middle/Upper Paleolithic following the appearance of anatomically modern humans was due to the onset of dual processing or contextual focus (CF), the ability to shift between different modes of thought: an explicit mode conducive to logical problem solving, and an implicit mode conducive to free-association and breaking out of a rut. Mathematical and computational models of CF supported this hypothesis, showing that CF is conducive to making creative connections by placing concepts in new contexts. This paper proposes that CF was made possible by mutation of the FOXP2 gene in the Paleolithic. FOXP2, once thought to be the 'language gene', turned out not to be uniquely associated with language. In its modern form FOXP2 enabled fine-tuning of the neurological mechanisms underlying the capacity to shift between processing modes by varying the size of the activated region of memory.
Several neurological disorders are associated with the aggregation of aberrant proteins, often localized in intracellular organelles such as the endoplasmic reticulum. Here we study protein aggregation kinetics by mean-field reactions and three dimensional Monte carlo simulations of diffusion-limited aggregation of linear polymers in a confined space, representing the endoplasmic reticulum. By tuning the rates of protein production and degradation, we show that the system undergoes a non-equilibrium phase transition from a physiological phase with little or no polymer accumulation to a pathological phase characterized by persistent polymerization. A combination of external factors accumulating during the lifetime of a patient can thus slightly modify the phase transition control parameters, tipping the balance from a long symptomless lag phase to an accelerated pathological development. The model can be successfully used to interpret experimental data on amyloid-\b{eta} clearance from the central nervous system.
We review quantitative methods and software developed to analyze genome-scale, brain-wide spatially-mapped gene-expression data. We expose new methods based on the underlying high-dimensional geometry of voxel space and gene space, and on simulations of the distribution of co-expression networks of a given size. We apply them to the Allen Atlas of the adult mouse brain, and to the co-expression network of a set of genes related to nicotine addiction retrieved from the NicSNP database. The computational methods are implemented in {\ttfamily{BrainGeneExpressionAnalysis}}, a Matlab toolbox available for download.
Calcium dynamics is the highly responsible for intracellular electrical (action potential) and chemical (neurotransmitter) signaling in neuron cell. The Mathematical modeling of calcium dynamics in neurons lead to the reaction diffusion equation which involves the parameters like diffusion coefficient, free calcium, bound calcium, buffers and bound buffer. Here the parameters like receptors, serca and leak are also incorporated in the model. Appropriate boundary conditions have been framed based on biophysical conditions of the problem. The finite volume method has been employed to obtain the solution. The computer program has been developed using MATLAB 7.11 for the entire problem to compute Ca2+ profiles and study the relationships among various parameters.
In this paper we present a biologically detailed mathematical model of tripartite synapses, where astrocytes modulate short-term synaptic plasticity. The model consists of a pre-synaptic bouton, a post-synaptic dendritic spine-head, a synaptic cleft and a peri-synaptic astrocyte controlling Ca2+ dynamics inside the synaptic bouton. This in turn controls glutamate release dynamics in the cleft. As a consequence of this, glutamate concentration in the cleft has been modeled, in which glutamate reuptake by astrocytes has also been incorporated. Finally, dendritic spine-head dynamics has been modeled. As an application, this model clearly shows synaptic potentiation in the hippocampal region, i.e., astrocyte Ca2+ mediates synaptic plasticity, which is in conformity with the majority of the recent findings (Perea & Araque, 2007; Henneberger et al., 2010; Navarrete et al., 2012).