Acurracy comparison of CCA and FBCCA algorithms. by Hossein Hamidi Shishavan (19688384)

Parameters to configure the multi-staged vascularization using the PDCCO algorithm. by Eduardo G. Zilves (22209247)

Geometric interpretation and data visualisation equivalent describing the DI algorithmic pipeline. by Borjan Milinkovic (21349908)

Data Sheet 1_Simplified two-compartment neuron with calcium dynamics capturing brain-state specific apical-amplification, -isolation and -drive.pdf by Elena Pastorelli (7024235)

“…This work provides the computational community with a two-compartment spiking neuron model that supports the proposed forms of brain-state-specific activity. A machine learning evolutionary algorithm, guided by a set of fitness functions, selected parameters defining neurons that express the desired apical dendritic mechanisms. …”

Longitudinal trajectories of functional network development across the birth transition. by Lanxin Ji (20290942)

“…Stronger RSFC within networks affirms validity of the network clustering algorithm. (B) Functional parcels and networks. (C) Age effect on the ROI-to-ROI functional connectivity. …”

Flawless analysis framework overview, with application to EEG power spectral densities as functional data observed over time. by Owen Forbes (4530652)

<b>Functional excitation-inhibition ratio indicates near-critical oscillations across frequencies</b> by Marina Diachenko (19739092)

“…Mansvelder, Hilgo Bruining, Eco de Geus, Arthur-Ervin Avramiea^$, Klaus Linkenkaer-Hansen^$,*</p><p dir="ltr">*Correspondence: Klaus Linkenkaer-Hansen (klaus.linkenkaer@cncr.vu.nl)</p><p dir="ltr">^$Shared authorship</p><p><br></p><p><br></p><p dir="ltr"><b>Abstract</b></p><p dir="ltr">The concept of excitation/inhibition (E/I) balance plays an important role in understanding brain function in health and disease. We recently introduced an algorithm to determine a functional E/I ratio based on the critical brain dynamics that emerge in neuronal networks balancing between order and disorder. …”

Summary of recent and state-of-the-art optimization algorithms. by Mahmood A. Jumaah (22272371)

Performance comparisons of OMWOA with state-of-the-art competitors on the IEEE CEC 2022 benchmark functions. by Kankan Tang (21474968)

Ant colony algorithm function and parameter explanation. by Yang Yu (4292)

Performance comparisons of MGFOA with state-of-the-art competitors on the IEEE CEC 2022 benchmark functions. by Yang Gao (18005)

Comparative validation of overflow state feedback indicator in reward functions. by Yulin Tian (1457986)

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Box plots of different algorithms on CEC2017 test function. by Tengfei Ma (597633)

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Analysis of ABIDE dataset: Conventional regression frameworks for optimized algorithmic value. by Alexandria M. Jensen (6494957)

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PATH has state-of-the-art performance versus previous binding affinity prediction algorithms. by Yuxi Long (11024307)

“…^<b>b</b>ROC curves of scoring functions benchmarked on the DUD-E dataset show PATH⁻ has state-of-the-art performance in discriminating decoys in the DUD-E dataset. …”

Table 1_Static and temporal dynamic changes in brain activity in patients with post-stroke balance dysfunction: a pilot resting state fMRI.docx by Zhiqing Tang (12895406)

“…</p>Methods<p>In the current study, twenty-six patients with post-stroke balance dysfunction and twenty-four HCs were examined by resting-state functional magnetic resonance imaging (rs-fMRI). …”

Results from different ML algorithms. by Caroline L. Alves (14271413)

ROC curve for each ML algorithm. by Caroline L. Alves (14271413)

Distribution of cross correlations in functional connectivity in ABIDE sample. by Alexandria M. Jensen (6494957)

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CEC2017 test function images and iteration curves of different algorithms. by Tengfei Ma (597633)

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