Neural representations for multi-context visuomotor adaptation and the impact of common representation on multi-task performance: a multivariate decoding approach

The human brain's remarkable motor adaptability stems from the formation of context representations and the use of a common context representation (e.g., an invariant task structure across task contexts) derived from structural learning. However, direct evaluation of context representations and structural learning in sensorimotor tasks remains limited. This study aimed to rigorously distinguish neural representations of visual, movement, and context levels crucial for multi-context visuomotor adaptation and investigate the association between representation commonality across task contexts and adaptation performance using multivariate decoding analysis with fMRI data. Here, we focused on three distinct task contexts, two of which share a rotation structure (i.e., visuomotor rotation contexts with −90° and +90° rotations, in which the mouse cursor's movement was rotated 90 degrees counterclockwise and clockwise relative to the hand-movement direction, respectively) and the remaining one does not (i.e., mirror-reversal context where the horizontal movement of the computer mouse was inverted). This study found that visual representations (i.e., visual direction) were decoded in the occipital area, while movement representations (i.e., hand-movement direction) were decoded across various visuomotor-related regions. These findings are consistent with prior research and the widely recognized roles of those areas. Task-context representations (i.e., either −90° rotation, +90° rotation, or mirror-reversal) were also distinguishable in various brain regions. Notably, these regions largely overlapped with those encoding visual and movement representations. This overlap suggests a potential intricate dependency of encoding visual and movement directions on the context information. Moreover, we discovered that higher task performance is associated with task-context representation commonality, as evidenced by negative correlations between task performance and task-context-decoding accuracy in various brain regions, potentially supporting structural learning. Importantly, despite limited similarities between tasks (e.g., rotation and mirror-reversal contexts), such association was still observed, suggesting an efficient mechanism in the brain that extracts commonalities from different task contexts (such as visuomotor rotations or mirror-reversal) at multiple structural levels, from high-level abstractions to lower-level details. In summary, while illuminating the intricate interplay between visuomotor processing and context information, our study highlights the efficiency of learning mechanisms, thereby paving the way for future exploration of the brain's versatile motor ability

An Evaluation of the Weibull and the Logistic Models for Cox's Proportional Hazards Model

Cox's proportional hazards model has been widely used in medical researches to evaluate the relationship between prognostic factors of a disease and the occurrence of outcome event. On a theoretical basis, regression coefficient estimated from Cox's proportional hazards model could be approximated by using the Weibull and the logistic model. Breast cancer cases (n=86) diagnosed at the Seoul National University Hospital were selected to evaluate the possibility of some accelerated models as an approximate model to Cox's proportional hazards model. Age at operation, tumor size and lymph node metastasis were the variables concerned in this study. Parameter estimates of two variables from the Weibull model, which seemed not to violate the proportionality assumption of Cox's model, showed almost identical values to those from Cox's proportional hazards model. However, there was a substantial degree of discrepancy in the parameter estimate of another variable, which showed an apparent unproportionality. This study confirmed that both the Weibull and the logistic models could be used as approximate methods to the estimates from Cox's proportional hazards model. Particularly noteworthy was the fact that the PC-SAS system could be successfully applied to survival analysis when the parameters were going to be estimated using Cox's model

Synthesis and Characterization of ZnO Nanowire–CdO Composite Nanostructures

ZnO nanowire–CdO composite nanostructures were fabricated by a simple two-step process involving ammonia solution method and thermal evaporation. First, ZnO nanowires (NWs) were grown on Si substrate by aqueous ammonia solution method and then CdO was deposited on these ZnO NWs by thermal evaporation of cadmium chloride powder. The surface morphology and structure of the synthesized composite structures were analyzed by scanning electron microscopy, X-ray diffraction and transmission electron microscopy. The optical absorbance spectrum showed that ZnO NW–CdO composites can absorb light up to 550 nm. The photoluminescence spectrum of the composite structure does not show any CdO-related emission peak and also there was no band gap modification of ZnO due to CdO. The photocurrent measurements showed that ZnO NW–CdO composite structures have better photocurrent when compared with the bare ZnO NWs

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

Effect of Carbon Addition on Direct Reduction Behavior of Low Quality Magnetite Ore by Reducing Gas Atmosphere

Recently, direct reduced iron (DRI) has been highlighted as a promising iron source for electric arc furnace (EAF)-based steelmaking. The two typical production methods for DRI are gas-based reduction and reduction using carbon composite pellets. While the gas-based reduction is strongly dependent on the reliable supply of hydrocarbon fuel, reduction using ore-coal composite pellets has relatively low productivity due to solid–solid reactions. To overcome the limitations of the above two processes, and to achieve a more efficient direct reduction process of iron ore, the possibility of combining these two methods was investigated. The experiments focused on performing an initial direct reduction using ore-coal composite pellets followed by a second stage gas reduction. It was assumed that the initial reduction of the carbon composite pellets would enhance the efficiency of the subsequent reduction by gas and the total reduction efficiency. The porosity, as well as the carbon efficiency for direct reduction, were measured to determine the optimal conditions for the initial reduction, such as the size ratio of ore and coal particles. Thereafter, further reduction by the reducing gas was carried out to verify the effect of the preliminary reduction. The reduction kinetics of the reducing gas was also discussed

Enhanced magnetic moment with cobalt dopant in SnS2semiconductor

© 2021 Author(s).We report the strong ferromagnetic order in van der Waals (vdW) layered SnS2 induced by cobalt substitution. The single-crystal Co-doped SnS2 grown by a self-flux method reveals a relatively high Curie temperature (TC) of ∼131 K with an in-plane magnetic easy axis and a large saturation magnetization of ∼0.65 emu g-1 for the 2 at. % Co concentration, which is two orders of magnitude larger than the previously reported value for transition-metal-doped SnS2. The average magnetic moment per Co atom, as high as 1.08 μB, is consistent with the calculated value based on density functional theory, i.e., 1 μB, indicating a negligible antiferromagnetic coupling between Co atoms. Magnetoresistance shows a change in sign from positive to negative, which further confirms the ferromagnetic order in Co-doped SnS2. Our s-p hybridized vdW layered SnS2 serves as a host semiconductor material to search for a suitable magnetic dopant with a high magnetic moment and room temperature TC for next-generation spintronics.11Nsciescopu

Multiple Magnetic Phases in Van Der Waals Mn-doped SnS2 Semiconductor

© 2021 Wiley-VCH GmbH2D van der Waals magnetic semiconductors have emerged along with the possibilities of achieving an efficient gate tunability and a proximity effect with a high magnetic anisotropy compared with 3D counterparts. Little explored are multiple magnetic phases with a single crystallographic phase. Herein, the multiple magnetic phases in a Mn-doped SnS2 single crystal with different doping concentrations using a one-step self-flux method are reported. Two ferromagnetic phases with a canted spin direction exist regardless of the Mn-doping concentration at up to 5 at%. Antiferromagnetism coexists with the ferromagnetic order and strengthens at high Mn-doping concentrations. A magnetoresistance measurement conducted on a 2 at% Mn-SnS2 flake exhibits a positive-to-negative crossover with a value of as high as 50% and clear anisotropy, confirming the presence of ferromagnetic order in the material. By revealing multiple magnetic phases in Mn-doped SnS2, the study broadens the scope of state-of-the-art research on layered magnetic semiconductors.11Nsciescopu