Reverse engineering information flow using stimulus-encoding and stimulus-transfer estimation algorithms. by Gabriel Matías Lorenz (21094672)

Data_Sheet_1_Decoding emotional resilience in aging: unveiling the interplay between daily functioning and emotional health.PDF by Minhua Guo (18392646)

Confusion matrices depict the performance of various ML algorithms. by Caroline L. Alves (14271413)

Definitions of global parameters used for constructing random ecosystems. by Robert Marsland (8616483)

Average quality scores of the models of the analysis set as a function of the <i>w</i>_<i>SP</i> with which the DOPE potential has been included in the objective function... by Giacomo Janson (8138517)

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

Table_1_A comparison of the composition and functions of the oral and gut microbiotas in Alzheimer’s patients.docx by Lili Chen (66681)

“…Thus, we compared alterations in the composition and gene functions of the oral and gut microbiota between different phases of AD.…”

Reward function related parameters. by Honglei Pang (22693724)

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Dataset of networks used in assessing the Troika algorithm for clique partitioning and community detection by Samin Aref (4683934)

“…Each network is provided in .gml format or .pkl format which can be read into a networkX graph object using standard functions from the networkX library in Python. For accessing other networks used in the study, please refer to the article for references to the primary sources of those network data.…”

Examples of four simulated networks and adjacency matrices. by Alexandria M. Jensen (6494957)

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PyNoetic’s online mode in action. Data is streamed from an Emotiv EPOC headset. by Gursimran Singh (575288)

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Examples of between- and within-community Beta distributions. by Alexandria M. Jensen (6494957)

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Data from: Structural and Functional Analysis of Multi-interface Domains by ZHAO Liang (8657694)

“…This work applies graph theory and algorithms to discover fingerprints for the multiple interfaces of a domain and to establish associations between the interfaces and functions, based on a huge set of multi-interface proteins from PDB. …”

Image_2_Distinct Brain Dynamic Functional Connectivity Patterns in Schizophrenia Patients With and Without Auditory Verbal Hallucinations.JPEG by Yao Zhang (134381)

“…In this study, 25 Schizophrenia patients with AVHs (AVHs group, 23.2 ± 5.35 years), 52 Schizophrenia patients without AVHs (non-AVHs group, 25.79 ± 5.63 years) and 28 healthy subjects (NC group, 26.14 ± 5.45 years) were enrolled. Dynamic functional connectivity was studied with a sliding-window method and functional connectivity states were then obtained with the k-means clustering algorithm in the three groups. …”

Image_3_Distinct Brain Dynamic Functional Connectivity Patterns in Schizophrenia Patients With and Without Auditory Verbal Hallucinations.JPEG by Yao Zhang (134381)

“…In this study, 25 Schizophrenia patients with AVHs (AVHs group, 23.2 ± 5.35 years), 52 Schizophrenia patients without AVHs (non-AVHs group, 25.79 ± 5.63 years) and 28 healthy subjects (NC group, 26.14 ± 5.45 years) were enrolled. Dynamic functional connectivity was studied with a sliding-window method and functional connectivity states were then obtained with the k-means clustering algorithm in the three groups. …”

Image_1_Distinct Brain Dynamic Functional Connectivity Patterns in Schizophrenia Patients With and Without Auditory Verbal Hallucinations.JPEG by Yao Zhang (134381)

“…In this study, 25 Schizophrenia patients with AVHs (AVHs group, 23.2 ± 5.35 years), 52 Schizophrenia patients without AVHs (non-AVHs group, 25.79 ± 5.63 years) and 28 healthy subjects (NC group, 26.14 ± 5.45 years) were enrolled. Dynamic functional connectivity was studied with a sliding-window method and functional connectivity states were then obtained with the k-means clustering algorithm in the three groups. …”

Resting state functional MRI brain signatures of fast disease progression in amyotrophic lateral sclerosis: a retrospective study by Francesca Trojsi (707124)

“…We aim to investigate brain functional and structural magnetic resonance imaging (MRI) changes in a cohort of ALS patients, examined at diagnosis and clinically monitored over 18 months, in order to early discriminate fast progressors (FPs) from slow progressors (SPs). …”

IEM reconstruction of EEG recorded while subjects performed the 2-back task (<i>N</i> = 42, combining data from the pilot study and the preregistered experiment from Wan et al. [13... by Quan Wan (1329666)

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Plots of the SDNR versus each algorithm from the in-focus plane. by Tsutomu Gomi (7382183)

The PS-VAE enables a detailed brain region-to-behavior mapping in the two-view mouse dataset. by Matthew R. Whiteway (11467528)

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