Recent studies have suggested that some neural computational mechanisms are based on the fine temporal structure of spiking activity. However, less effort has been devoted to investigating the ...evolutionary aspects of such mechanisms. In this paper we explore the issue of temporal neural computation from an evolutionary point of view, using a genetic simulation of the evolutionary development of neural systems. We evolve neural systems in an environment with selective pressure based on mate finding, and examine the temporal aspects of the evolved systems. In repeating evolutionary sessions, there was a significant increase during evolution in the mutual information between the evolved agent's temporal neural representation and the external environment. In ten different simulated evolutionary sessions, there was an increased effect of time-related neural ablations on the agents' fitness. These results suggest that in some fitness landscapes the emergence of temporal elements in neural computation is almost inevitable. Future research using similar evolutionary simulations may shed new light on various biological mechanisms.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
We show that times of spikes can be very precise. In the cerebral cortex, where each nerve cell is affected by thousands of others, it is the common belief that the exact time of a spike is random up ...to an averaged firing rate over tens of milliseconds. In a brain slice, precise time relations of several neurons have been observed. It remained unclear whether this phenomenon can also be observed in brains of behaving animals. Here we show, in behaving monkeys, that time intervals between spikes, measured in correspondence to a specific behavior, may be controlled to within the milliseconds range. data mining motor cortex neural codes precise timing single units
Thinking development processes among high-school students is an important and significant issue that has been widely investigated (Leviathan, 2012; Ball, 1996; De Risi, 2015). A few studies discuss ...the development of mathematical thinking as this field contains additional difficulties to the traditional factors, teachers, students, and parents, and is one of the most important areas taught in school, according to De Risi (2015). Due to the importance of this subject, the challenge facing researchers, mathematicians, and educators is how to improve students' abilities and achievements in mathematics. In recent years, researchers have found that in order to improve students' achievements and abilities in mathematics, one can use self-direction. Self-direction is a strategy by which the learner acquires the ability to cope with learning from several aspects and contributes to inking development. In this study, we showed that self-directed learning with an emphasis on metacognition would improve students' understanding of the subject in question. Using the metacognitive guidance model, the students acquire and develop learning skills that contribute to developing their geometric thinking. In this study, there is the added value of using a learning model based on metacognitive guidance and its significant contribution to combining multiple subjects into one problem.
"We learn by doing and by thinking about what we are doing." (John Dewey)
In this article, we shall present findings that describe the degree to which metacognitive orientation contributes to the ...study of the geometry the plan in boys compared to girls in 9th grade of middle school. The geometry study process does not only involve knowledge but also high thinking abilities. Beyond the knowledge of definitions and sentences, the students are required to write a full, precise, and logically constructed proof, as well as to show the validity and its correctness. In this article, we shall present a model of metacognitive orientation aiming to develop higher-order thinking skills in geometry. We built and applied the model to 9th-grade students. Since students experience difficulties in the study of geometry, the development of a structured study process is required. Numerous studies clearly show that the study process involving metacognitive orientation improves their study ability and deepens their understanding of the topic in question. The question that we addressed was to what extent the metacognitive orientation in geometry impacted boys in comparison to girls?
In this study, we shall present data according to which metacognitive learning explicitly benefits girls more than boys. Nevertheless, as a modular model, it allowed every student of both sexes to strengthen the weak aspect and to overcome blockades inhibiting the learning process.
In this paper, we examine the importance of building instructional units that incorporate metacognition intent processes that contribute to the development of geometric thinking. We show that the ...implementation of metacognition processes in the initial stages of constructing tailored instructional units will improve students' geometric ability. The study was performed on middle school mathematics teachers of the ninth grade. The experiment we conducted shows that building instructional units that incorporate metacognition intent benefit learning processes on two levels: First, in the subject matter. Second, they contribute to a deeper understanding that improves student's ability to connect related subjects to mathematical geometry. moreover, we will present a practical model that incorporates different aspects that could operate a guideline for middle school mathematics teachers.
Background
Deep‐learning is widely used for lesion classification. However, in the clinic patient data often has missing images.
Purpose
To evaluate the use of generated, duplicate and empty(black) ...images for replacing missing MRI data in AI brain tumor classification tasks.
Study Type
Retrospective.
Population
224 patients (local‐dataset; low‐grade‐glioma (LGG) = 37, high‐grade‐glioma (HGG) = 187) and 335 patients (public‐dataset (BraTS); LGG = 76, HGG = 259). The local‐dataset was divided into training (64), validation (16), and internal‐test‐data (20), while the public‐dataset was an independent test‐set.
Field Strength/Sequence
T1WI, T1WI+C, T2WI, and FLAIR images (1.5T/3.0T‐MR), obtained from different suppliers.
Assessment
Three image‐to‐image translation generative‐adversarial‐network (Pix2Pix‐GAN) models were trained on the local‐dataset, to generate T1WI, T2WI, and FLAIR images. The rating‐and‐preference‐judgment assessment was performed by three human‐readers (radiologist (MD) and two MRI‐technicians). Resnet152 was used for classification, and inference was performed on both datasets, with baseline input, and with missing data replaced by 1) generated images; 2) duplication of existing images; and 3) black images.
Statistical Tests
The similarity between the generated and the original images was evaluated using the peak‐signal‐to‐noise‐ratio (PSNR) and the structural‐similarity‐index‐measure (SSIM). Classification results were evaluated using accuracy, F1‐score and the Kolmogorov–Smirnov test and distance.
Results
For baseline‐state, the classification model reached to accuracy = 0.93,0.82 on the local and public‐datasets. For the missing‐data methods, high similarity was obtained between the generated and the original images with mean PSNR = 35.65,32.94 and SSIM = 0.87,0.91 on the local and public‐datasets; 39% of the generated‐images were labeled as real images by the human‐readers. The classification model using generated‐images to replace missing images produced the highest results with mean accuracy = 0.91,0.82 compared to 0.85,0.79 for duplicated and 0.77,0.68 for use of black images;
Data Conclusion
The feasibility for inference classification model on an MRI dataset with missing images using the Pix2pix‐GAN generated images, was shown. The stability and generalization ability of the model was demonstrated by producing consistent results on two independent datasets.
Level of Evidence
3
Technical Efficacy
Stage 5
We list all the possible fundamental groups of the complements of real conic-line arrangements with two conics which are tangent to each other at two points, with up to two additional lines. For the ...computations we use the topological local braid monodromies and the techniques of Moishezon–Teicher and van-Kampen. We also include some conjectures concerning the connection between the presentation of the fundamental group of the complements and the geometry of an interesting family of conic-line arrangements.
We give an algorithmic computation for the height of Kauffman's clock lattice obtained from a knot diagram with two adjacent regions starred and without crossing information specified. We show that ...this lattice is more familiarly the graph of perfect matchings of a bipartite graph obtained from the knot diagram by overlaying the two dual Tait graphs of the knot diagram. Furthermore we prove structural properties of the bipartite graph in general. This setting also makes evident applications to Chebyshev or harmonic knots, whose related bipartite graph is the popular grid graph, and to discrete Morse functions.
Deep brain stimulation (DBS) significantly alleviates symptoms in various neurological disorders. Current research focuses on developing programmed stimulation protocols for customization to ...individual symptoms. However, the therapeutic mechanism of action of programmed DBS (pDBS) is poorly understood. We previously demonstrated that pDBS in the ventral tegmental area (VTA) normalizes molecular and behavioral abnormalities in the Flinders Sensitive Line (FSL) rat model for depression. Herein, we examined the effect of a short-duration, low-frequency DBS template on local field potential (LFP) synchronization patterns along the anterior–posterior axis of the VTA of FSL rats, and correlation of this effect with depressive-like behavior, as compared with non-programmed, continuous low-frequency DBS (npDBS). We used the wavelet phase coherence (WPC) measure for effective representation of time and frequency of LFP patterns, and the forced swim test to measure immobility (despair). Baseline WPC values were lower in FSLs as compared with SD controls, at the low and high gamma frequency range (above 30 Hz). Baseline immobility scores for FSL rats were higher than those of SD rats, while pDBS, and not npDBS, significantly reduced FSL immobility scores to control SD levels, up to day 14. pDBS also significantly increased the change (between baseline and day 14) in WPC values, in beta, low gamma and high gamma frequency ranges. The change in high gamma (60–100 Hz) WPC values correlated with improvement in depressive-like behavior. Our results suggest that programmed DBS of the VTA increases interaction among local neuronal populations, an effect that may underlie the normalization of depressive-like behavior.
•We examined local field potential (LFP) in a genetic rat model for depression.•We found impaired ventral tegmental LFP synchronization in the gamma frequency range.•Programmed deep brain stimulation increased LFP synchronization.•Increases at high gamma band correlated with normalized depressive-like behavior.
Covers of D-Type Artin Groups Amram, Meirav; Shwartz, Robert; Teicher, Mina
The Electronic journal of combinatorics,
10/2017, Letnik:
24, Številka:
4
Journal Article
Recenzirano
Odprti dostop
We study certain quotients of generalized Artin groups which have a natural map onto D-type Artin groups, where the generalized Artin group $A(T)$ is defined by a signed graph $T$. Then we find a ...certain quotient $G(T)$ according to the graph $T$, which also have a natural map onto $A(D_n)$. We prove that $G(T)$ is isomorphic to a semidirect product of a group $K^{(m,n)}$, with the Artin group $A(D_n)$, where $K^{(m,n)}$ depends only on the number $m$ of cycles and on the number $n$ of vertices of the graph $T$.
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