Help for package NeuroDataSets

Type:

Package

Title:

A Comprehensive Collection of Neuroscience and Brain-Related Datasets

Version:

0.2.0

Maintainer:

Renzo Caceres Rossi <arenzocaceresrossi@gmail.com>

Description:

Offers a rich and diverse collection of datasets focused on the brain, nervous system, and related disorders. The package includes clinical, experimental, neuroimaging, behavioral, cognitive, and simulated data on conditions such as Parkinson's disease, Alzheimer's, epilepsy, schizophrenia, gliomas, and mental health. Datasets cover structural and functional brain data, neurotransmission, gene expression, cognitive performance, and treatment outcomes. Designed for researchers, neuroscientists, clinicians, psychologists, data scientists, and students, this package facilitates exploratory data analysis, statistical modeling, and hypothesis testing in neuroscience and neuroepidemiology.

License:

GPL-3

Language:

URL:

https://github.com/lightbluetitan/neurodatasets, https://lightbluetitan.github.io/neurodatasets/

BugReports:

https://github.com/lightbluetitan/neurodatasets/issues

Encoding:

UTF-8

LazyData:

true

Suggests:

ggplot2, testthat (≥ 3.0.0), dplyr, knitr, rmarkdown

Depends:

R (≥ 4.1.0)

Imports:

utils

RoxygenNote:

7.3.2

Config/testthat/edition:

VignetteBuilder:

knitr

NeedsCompilation:

Packaged:

2025-09-06 07:28:43 UTC; Renzo

Author:

Renzo Caceres Rossi

[aut, cre]

Repository:

CRAN

Date/Publication:

2025-09-07 22:20:02 UTC

NeuroDataSets: A Comprehensive Collection of Neuroscience and Brain-Related Datasets

Description

This package provides a wide variety of datasets focused on the brain, nervous system, and related disorders including Parkinson's disease, Alzheimer's, epilepsy, schizophrenia, gliomas, and mental health.

Details

NeuroDataSets: A Comprehensive Collection of Neuroscience and Brain-Related Datasets

A Comprehensive Collection of Neuroscience and Brain-Related Datasets.

Author(s)

Maintainer: Renzo Caceres Rossi arenzocaceresrossi@gmail.com

Allen Brain Atlas Phenotype Data

Description

This dataset, aba_phenotype_data_df, is a data frame containing brain tissue phenotype measurements from the Allen Brain Atlas Aging, Dementia, and TBI study. The data includes immunohistochemistry markers for microglia and astrocytes across 377 brain samples, intended for correlation analyses with expression data.

Usage

data(aba_phenotype_data_df)

Format

A data frame with 377 observations and 4 variables:

structure_acronym.x: Character: Brain structure acronym
ihc_iba1_ffpe: Numeric: IBA1 immunohistochemistry measurement (microglia marker)
ihc_gfap_ffpe: Numeric: GFAP immunohistochemistry measurement (astrocyte marker)
id: Character: Sample identification code

Details

The dataset name has been kept as 'aba_phenotype_data_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified.

Source

Data taken from the BRETIGEA package version 1.0.3. Original data from: Allen Brain Atlas Aging, Dementia, and TBI study.

Ability and Intelligence Tests

Description

This dataset, ability_intelligence_list, is a list containing psychometric data from six cognitive tests administered to 112 individuals. The list includes a covariance matrix, variable means, and observation count for tests measuring various intellectual abilities.

Usage

data(ability_intelligence_list)

Format

A list with 3 components:

cov: Numeric matrix [6×6]: Test score covariance matrix
center: Numeric vector [6]: Variable means
n.obs: Numeric: Number of observations (112)

Details

The dataset name has been kept as 'ability_intelligence_list' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package. The suffix 'list' indicates that the dataset is a list object. The original content has not been modified.

Source

Data taken from the educationR package version 0.10

Adolescent Mental Health Study

Description

This dataset, adolescent_mental_health_df, is a data frame containing mental health assessments from the National Longitudinal Study of Adolescent Health. The data includes depression and anxiety measures for 4,344 students in grades 7-12 from a cross-sectional sample analyzed by Warne (2014).

Usage

data(adolescent_mental_health_df)

Format

A data frame with 4,344 observations and 3 variables:

grade: Ordered factor with 6 levels: School grade (7-12)
depression: Integer: Depression symptom score
anxiety: Integer: Anxiety symptom score

Details

The dataset name has been kept as 'adolescent_mental_health_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified.

Source

Data taken from the heplots package version 1.7.4. Original analysis: Warne, R.T. (2014) A primer on Multivariate Analysis of Variance (MANOVA) for Behavioral Scientists. Practical Assessment, Research & Evaluation, 19(1).

Smoking and Alzheimer's Disease

Description

This dataset, alzheimer_smoking_df, is a data frame containing case-control data from a study examining the association between smoking and Alzheimer's disease. The study included 538 participants with information on smoking status, disease classification, and gender.

Usage

data(alzheimer_smoking_df)

Format

A data frame with 538 observations and 3 variables:

smoking: Factor: Smoking status of participants (4 levels)
disease: Factor: Disease classification including Alzheimer's diagnosis (3 levels)
gender: Factor: Participant's gender (2 levels)

Details

The dataset name has been kept as 'alzheimer_smoking_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified.

Source

Data taken from the coin package version 1.4-3. Original study: Salib, E. and Hillier, V. (1997). A case-control study of smoking and Alzheimer's disease. International Journal of Geriatric Psychiatry 12: 295-300.

Alzheimer's Disease Biomarkers Study

Description

This dataset, alzheimers_biomarkers_tbl_df, is a tibble containing clinical data from 333 patients in a study of Alzheimer's disease biomarkers. The study included patients with mild cognitive impairment and healthy controls, with measurements of demographic characteristics, apolipoprotein E genotype, protein biomarkers (including Abeta, Tau, and pTau), and clinical dementia scores.

Usage

data(alzheimers_biomarkers_tbl_df)

Format

A tibble with 333 observations and 131 variables:

age: Numeric: Patient age
male: Numeric: Indicator for male gender (1 = male, 0 = female)
Genotype: Factor: Apolipoprotein E genotype
Class: Factor: Clinical classification (e.g., healthy, impaired)
Ab_42: Numeric: Amyloid-beta 42 protein measurement
tau: Numeric: Tau protein measurement
p_tau: Numeric: Phosphorylated Tau protein measurement
[131 additional biomarker variables]: Numeric measurements of various proteins and biomarkers

Details

The dataset name has been kept as 'alzheimers_biomarkers_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified.

Source

Data taken from the modeldata package version 1.4.0. Original study: Craig-Schapiro R, Kuhn M, Xiong C, et al. (2011) Multiplexed Immunoassay Panel Identifies Novel CSF Biomarkers for Alzheimer's Disease Diagnosis and Prognosis. PLoS ONE 6(4): e18850.

Brain Structure in Bilingual Humans

Description

This dataset, bilingual_brains_df, is a data frame containing measurements of second language proficiency scores and gray matter density in the left inferior parietal region from 22 observations.

Usage

data(bilingual_brains_df)

Format

A data frame with 22 observations and 2 variables:

proficiency: Numeric vector representing second language proficiency scores (summary of reading, writing, and speech)
greymatter: Numeric vector representing density of gray matter in the left inferior parietal region

Details

The dataset name has been kept as 'bilingual_brains_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the abd package version 0.2-8

Blood-Brain Barrier

Description

This dataset, blood_brain_barrier_df, is a data frame containing experimental measurements from a rat study investigating sugar-infusion methods for temporary blood-brain barrier disruption. The barrier's protective function was assessed through multiple biological markers.

Usage

data(blood_brain_barrier_df)

Format

A data frame with 34 observations and 9 variables:

Brain: Integer: Brain tissue measurement (units?)
Liver: Integer: Liver tissue measurement (units?)
Time: Numeric: Experimental time measurement (hours)
Treatment: Factor with 2 levels: Experimental treatment groups
Days: Integer: Observation period (days)
Sex: Factor with 2 levels: Animal sex (Male/Female)
Weight: Integer: Subject weight (grams)
Loss: Numeric: Physiological loss measurement
Tumor: Integer: Tumor presence indicator (0/1)

Details

The dataset name has been kept as 'blood_brain_barrier_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified.

Source

Data taken from the Sleuth3 package version 1.0-6. Original reference: Ramsey, F.L. and Schafer, D.W. (2013) The Statistical Sleuth: A Course in Methods of Data Analysis (3rd ed), Cengage Learning.

Mammal Brain Size and Litter Size Relationship

Description

This dataset, brain_litter_mammals_df, is a data frame comparing relative brain weights between 96 mammalian species divided by reproductive strategy: 51 species with small litters (< 2 offspring) and 45 species with large litters (\geq 2 offspring).

Usage

data(brain_litter_mammals_df)

Format

A data frame with 96 observations and 2 variables:

BrainSize: Numeric: Relative brain weight measurement (encephalization quotient or similar metric)
LitterSize: Factor with 2 levels: Reproductive strategy ("Small" (< 2) and "Large" (\geq 2) litter sizes)

Details

The dataset name has been kept as brain_litter_mammals_df to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package. The suffix df indicates that the dataset is a data frame. The original content has not been modified.

Source

Data taken from the Sleuth3 package version 1.0-6. Original reference: Ramsey, F.L. and Schafer, D.W. (2002) The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

Brain Size and IQ Study Data

Description

This dataset, brain_size_iq_df, is a data frame containing neurocognitive measurements from a study examining relationships between brain size, gender, and intelligence. The data include 40 right-handed psychology students with no neurological history, selected based on extreme Scholastic Aptitude Test scores.

Usage

data(brain_size_iq_df)

Format

A data frame with 40 observations and 7 variables:

ID: Numeric: Participant identification number
GENDER: Factor with 2 levels: Participant's gender (Male/Female)
FSIQ: Numeric: Full Scale IQ score
VIQ: Numeric: Verbal IQ score
PIQ: Numeric: Performance IQ score
MRI: Numeric: Brain size measurement from MRI (in cubic cm)
IQDI: Factor with 2 levels: IQ group classification (High/Low)

Details

The dataset name has been kept as 'brain_size_iq_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified.

Source

Data taken from the sur package version 1.0.4. Original study: Willerman, L., Schultz, R., Rutledge, J.N. and Bigler, E.D. (1991) In Vivo Brain Size and Intelligence. Intelligence, 15, 223-228.

Brain Activity in String Players

Description

This dataset, brain_string_players_df, is a data frame containing neurophysiological measurements from a study of 15 violin and other string instrument players. The data examines the relationship between years of musical practice and measured brain activity levels in relevant cortical regions.

Usage

data(brain_string_players_df)

Format

A data frame with 15 observations and 2 variables:

Years: Integer: Years of musical practice
Activity: Numeric: Brain activity measurement (likely fMRI or similar neuroimaging units)

Details

The dataset name has been kept as 'brain_string_players_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified.

Source

Data taken from the Sleuth3 package version 1.0-6. Original reference: Ramsey, F.L. and Schafer, D.W. (2013) The Statistical Sleuth: A Course in Methods of Data Analysis (3rd ed), Cengage Learning.

BRAiNS Cohort Cognitive States Matrix

Description

This dataset, brains_cognitive_matrix, is a matrix containing the states and covariates of 649 participants enrolled in the BRAiNS cohort at the University of Kentucky's Alzheimer's Disease Research Center. The data includes longitudinal cognitive assessments and various health covariates across multiple visits.

Usage

data(brains_cognitive_matrix)

Format

A matrix with 6240 observations and 13 variables:

ID: Integer: Participant identification number
visitno: Integer: Visit number
prstate: Integer: Previous cognitive state
custate: Integer: Current cognitive state
bagec: Integer: Baseline age centered
famhx: Integer: Family history of dementia (0 = No, 1 = Yes)
HBP: Integer: History of high blood pressure (0 = No, 1 = Yes)
apoe4: Integer: APOE \varepsilon_4 allele carrier status (0 = Non-carrier, 1 = Carrier)
smk1: Integer: Smoking status indicator 1
smk2: Integer: Smoking status indicator 2
smk3: Integer: Smoking status indicator 3
lowed: Integer: Low education indicator (0 = No, 1 = Yes)
headinj: Integer: History of head injury (0 = No, 1 = Yes)

Details

The dataset name has been kept as brains_cognitive_matrix to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package. The suffix matrix indicates that the dataset is a matrix. The original content has not been modified.

Source

Data taken from the RRMLRfMC package version 0.4.0. Original study: University of Kentucky's Alzheimer's Disease Research Center BRAiNS cohort.

Effects of Cocaine on Dopamine Receptors

Description

This dataset, cocaine_dopamine_df, is a data frame containing measurements of dopamine receptor blockade and perceived high levels from 34 human subjects as determined by PET scans.

Usage

data(cocaine_dopamine_df)

Format

A data frame with 34 observations and 2 variables:

percent.blocked: Integer vector representing percent of dopamine receptors blocked
high: Integer vector representing perceived level of high from PET scans

Details

The dataset name has been kept as 'cocaine_dopamine_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the abd package version 0.2-8

Dopamine `\beta`-Hydroxylase Activity in Schizophrenia

Description

This dataset, 'dopamine_schizophrenia_tbl_df', is a tibble containing measurements of dopamine \beta-hydroxylase (DBH) activity in 25 schizophrenic patients treated with antipsychotic medication. The data compares DBH levels between patient groups.

Usage

data(dopamine_schizophrenia_tbl_df)

Format

A tibble with 25 observations and 2 variables:

dbh: Integer: Dopamine \beta-hydroxylase activity level (nmol/(mL\cdothr))
group: Character: Treatment/patient group classification

Details

The dataset name has been kept as dopamine_schizophrenia_tbl_df to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package. The suffix tbl_df indicates that the dataset is a tibble. The original content has not been modified.

Source

Data taken from the BSDA package version 1.2.2

Epilepsy Treatment Randomized Controlled Trial

Description

This dataset, epilepsy_RCT_tbl_df, is a tibble containing data from a randomized controlled trial of progabide for epilepsy treatment. The trial recorded seizure counts for 59 patients at baseline and four follow-up visits.

Usage

data(epilepsy_RCT_tbl_df)

Format

A tibble with 59 observations and 8 variables:

id: Integer: Patient identification number
treat: Factor with 2 levels: Treatment group (progabide/control)
base: Integer: Baseline seizure count
age: Integer: Patient age in years
y1: Integer: Seizure count at first follow-up
y2: Integer: Seizure count at second follow-up
y3: Integer: Seizure count at third follow-up
y4: Integer: Seizure count at fourth follow-up

Details

The dataset name has been kept as 'epilepsy_RCT_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified.

Source

Data taken from the pubh package version 2.0.0

SANAD Epilepsy Drug Treatment Quality of Life Study

Description

This dataset, epilepsy_drug_qol_df, is a data frame containing quality of life measurements from the SANAD randomized controlled trial comparing carbamazepine and lamotrigine in 544 epilepsy patients. QoL assessments were collected at baseline, 3 months, 1 year and 2 years using validated instruments.

Usage

data(epilepsy_drug_qol_df)

Format

A data frame with 1,852 observations and 9 variables:

id: Integer: Patient identification number
with.time: Numeric: Time to withdrawal/discontinuation (days)
trt: Factor with 2 levels: Treatment group (carbamazepine/lamotrigine)
with.status: Integer: Withdrawal status indicator
time: Numeric: Assessment time point (days since baseline)
anxiety: Numeric: Anxiety score (from QoL measure)
depress: Numeric: Depression score (from QoL measure)
aep: Numeric: Adverse effects profile score
with.status2: Numeric: Alternative withdrawal coding

Details

The dataset name has been kept as 'epilepsy_drug_qol_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified.

Source

Data taken from the joineRML package version 0.4.7. Original study: Marson, A.G., et al. (2007) The SANAD study of effectiveness of carbamazepine, gabapentin, lamotrigine, oxcarbazepine, or topiramate for treatment of partial epilepsy: an unblinded randomised controlled trial. The Lancet, 369(9566), 1000-1015.

Epileptic Seizures Clinical Drug Trial

Description

This dataset, epilepsy_drug_trial_df, is a data frame containing seizure counts from a clinical trial of anti-epileptic medication. The data includes seizure frequency measurements along with treatment indicators and patient covariates for 295 observations.

Usage

data(epilepsy_drug_trial_df)

Format

A data frame with 295 observations and 6 variables:

seizures: Numeric: Count of epileptic seizures
id: Integer: Patient identification number
treat: Numeric: Treatment indicator
expind: Numeric: Exposure period indicator
timeadj: Numeric: Adjusted time period
age: Numeric: Patient age in years

Details

The dataset name has been kept as 'epilepsy_drug_trial_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified.

Source

Data taken from the faraway package version 1.0.9

Patterns of Gray Matter in Schizophrenia

Description

This dataset, gm_expected_patterns_tbl_df, is a tibble containing expected patterns of gray matter in schizophrenia derived from large-scale meta-analyses by the ENIGMA consortium. It includes data from multiple neurological and psychiatric conditions for comparison.

Usage

data(gm_expected_patterns_tbl_df)

Format

A tibble with 33 observations and 16 variables:

GM: Character vector indicating gray matter regions
SSD: Numeric vector of expected patterns for schizophrenia spectrum disorder
MDD: Numeric vector of expected patterns for major depressive disorder
AD_ADNI: Numeric vector of expected patterns for Alzheimer's disease (ADNI cohort)
AD_ADNIOSYRIX: Numeric vector of expected patterns for Alzheimer's disease (ADNI+OSYRIX cohort)
BD: Numeric vector of expected patterns for bipolar disorder
PD: Numeric vector of expected patterns for Parkinson's disease
Diabetes: Numeric vector of expected patterns for diabetes
HighBP: Numeric vector of expected patterns for high blood pressure
HighLipids: Numeric vector of expected patterns for high lipids
MET: Numeric vector of expected patterns for metabolic syndrome
DS_22q: Numeric vector of expected patterns for 22q11.2 deletion syndrome
Suicide: Numeric vector of expected patterns for suicide
OCD_pediatric: Numeric vector of expected patterns for pediatric OCD
OCD_adult: Numeric vector of expected patterns for adult OCD
AN: Numeric vector of expected patterns for anorexia nervosa

Details

The dataset name has been kept as 'gm_expected_patterns_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.

Source

Data taken from the RVIpkg package version 0.3.2.

Neurotransmission in Guinea Pig Brains

Description

This dataset, guineapig_neurotransmission_df, is a data frame containing measurements of spontaneous current amplitudes recorded from individual brain cells in adult guinea pigs. The study investigated whether synaptic transmission occurs in quantal units, which would manifest as multimodal amplitude distributions with regularly spaced peaks.

Usage

data(guineapig_neurotransmission_df)

Format

A data frame with 346 observations and 1 variable:

y: Numeric: Peak amplitude of spontaneous synaptic currents (pA or similar units)

Details

The dataset name has been kept as 'guineapig_neurotransmission_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified.

Source

Data taken from the boot package version 1.3-31. Original study: Paulsen, O. and Heggelund, P. (1994) The quantal size at retinogeniculate synapses determined from spontaneous and evoked EPSCs in guinea-pig thalamic slices. Journal of Physiology, 480, 505–511.

Memory and the Hippocampus

Description

This dataset, hippocampus_lesions_df, is a data frame containing measurements of spatial memory scores and percent lesion of the hippocampus from 57 observations.

Usage

data(hippocampus_lesions_df)

Format

A data frame with 57 observations and 2 variables:

lesion: Numeric vector representing percent lesion of the hippocampus
memory: Numeric vector representing spatial memory scores

Details

The dataset name has been kept as 'hippocampus_lesions_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the abd package version 0.2-8

Mammal Brain and Body Size

Description

This dataset, mammals_brain_body_df, is a data frame containing comparative neuroanatomical and life history data for 96 mammalian species. The data examine the relationship between brain size, body size, and reproductive characteristics across different mammal species.

Usage

data(mammals_brain_body_df)

Format

A data frame with 96 observations and 5 variables:

Species: Factor with 96 levels: Mammalian species names
Brain: Numeric: Brain weight (grams)
Body: Numeric: Body weight (kilograms)
Gestation: Integer: Gestation period (days)
Litter: Numeric: Average litter size

Details

The dataset name has been kept as 'mammals_brain_body_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified.

Source

Data taken from the Sleuth3 package version 1.0-6. Original study: Allison, T. and Cicchetti, D.V. (1976) Sleep in Mammals: Ecological and Constitutional Correlates. Science, 194, 732-734.

Cross-Species Brain Cell Marker Genes

Description

This dataset, markers_brain_df, is a data frame containing the top 1,000 marker genes for each of six major brain cell types (astrocytes, endothelial cells, microglia, neurons, oligodendrocytes, and OPCs) identified through meta-analysis of both human and mouse brain gene expression data.

Usage

data(markers_brain_df)

Format

A data frame with 6,000 observations and 2 variables:

markers: Character: Gene symbol for cell-type specific marker (human/mouse orthologs)
cell: Character: Cell type classification (astrocytes/endothelial/microglia/neurons/oligodendrocytes/OPCs)

Details

The dataset name has been kept as 'markers_brain_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified.

Source

Data taken from the BRETIGEA package version 1.0.3. Derived from: Meta-analysis of human and mouse brain cell-type specific gene expression datasets.

Human Brain Cell Marker Genes

Description

This dataset, markers_human_brain_df, is a data frame containing the top 1,000 marker genes for each of six major brain cell types (astrocytes, endothelial cells, microglia, neurons, oligodendrocytes, and OPCs) identified through meta-analysis of human brain gene expression data.

Usage

data(markers_human_brain_df)

Format

A data frame with 5,500 observations and 2 variables:

markers: Character: Gene symbol for cell-type specific marker
cell: Character: Cell type classification (astrocytes/endothelial/microglia/neurons/oligodendrocytes/OPCs)

Details

The dataset name has been kept as 'markers_human_brain_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified.

Source

Data taken from the BRETIGEA package version 1.0.3.

Mouse Brain Cell Marker Genes

Description

This dataset, markers_mouse_brain_df, is a data frame containing the top 1,000 marker genes for each of six major brain cell types (astrocytes, endothelial cells, microglia, neurons, oligodendrocytes, and OPCs) identified through meta-analysis of mouse brain gene expression data.

Usage

data(markers_mouse_brain_df)

Format

A data frame with 5,430 observations and 2 variables:

markers: Character: Gene symbol for cell-type specific marker
cell: Character: Cell type classification (astrocytes/endothelial/microglia/neurons/oligodendrocytes/OPCs)

Details

The dataset name has been kept as 'markers_mouse_brain_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified.

Source

Data taken from the BRETIGEA package version 1.0.3. Original study: Mckenzie AT, Wang M, Hauberg ME, et al. (2018) Brain Cell Type Specific Gene Expression and Co-expression Network Architectures. Scientific Reports, 8(1), 8868.

Migraine Headache Treatment

Description

This dataset, migraine_treatment_df, is a data frame containing clinical data on 4,152 migraine treatment cases collected by Tammy Kostecki-Dillon. The data includes treatment details, headache characteristics, and patient demographics.

Usage

data(migraine_treatment_df)

Format

A data frame with 4,152 observations and 9 variables:

id: Integer: Patient identification number
time: Integer: Time measurement (likely days or hours)
dos: Integer: Treatment dosage
hatype: Factor with 3 levels: Headache type classification
age: Integer: Patient age in years
airq: Numeric: Air quality index measurement
medication: Factor with 3 levels: Medication type
headache: Factor with 2 levels: Headache presence/severity
sex: Factor with 2 levels: Patient sex

Details

The dataset name has been kept as 'migraine_treatment_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified.

Source

Data taken from the carData package version 3.0-5. Original collection: Kostecki-Dillon, T. (Year not specified) Migraine Treatment Study.

Cranial Capacity in Neanderthals and Modern Humans

Description

This dataset, neanderthal_brains_df, is a data frame containing measurements of brain size (lnbrain) and body mass (lnmass) from 39 specimens of Neanderthals and early modern humans, identified by species.

Usage

data(neanderthal_brains_df)

Format

A data frame with 39 observations and 3 variables:

ln.mass: Numeric vector representing natural logarithm of body mass
ln.brain: Numeric vector representing natural logarithm of brain size
species: Factor indicating species with 2 levels (Neanderthals and early modern humans)

Details

The dataset name has been kept as 'neanderthal_brains_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the abd package version 0.2-8

Neurophysiological Point Process Data

Description

This dataset, neuro_pointprocess_matrix, is a matrix containing times of observed neuronal firing in windows of 250ms surrounding stimulus application in human subjects. Each row represents an experimental replication (469 total replicates), with values indicating spike times relative to stimulus onset.

Usage

data(neuro_pointprocess_matrix)

Format

A numeric matrix with 469 observations (rows) and 6 variables (columns):

[,1:6]: Numeric: Spike times (milliseconds) relative to stimulus onset, with NA representing no spike in that trial window

Details

The dataset name has been kept as 'neuro_pointprocess_matrix' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package. The suffix 'matrix' indicates that the dataset is a matrix. The original content has not been modified.

Source

Data taken from the boot package version 1.3-31. Original collection: Dr. S.J. Boniface, Neurophysiology Unit, Radcliffe Infirmary, Oxford.

Neurocognitive Performance in Psychosis

Description

This dataset, neurocognitive_psychiatric_df, is a data frame containing comprehensive neurocognitive assessments from a study comparing performance patterns in schizophrenia, schizoaffective disorder, and controls. The data includes 242 observations across multiple cognitive domains using a psychosis-specific neurocognitive battery.

Usage

data(neurocognitive_psychiatric_df)

Format

A data frame with 242 observations and 10 variables:

Dx: Factor with 3 levels: Diagnostic group (Schizophrenia/Schizoaffective/Control)
Speed: Integer: Processing speed score
Attention: Integer: Attention/vigilance score
Memory: Integer: Working memory score
Verbal: Integer: Verbal learning score
Visual: Integer: Visual learning score
ProbSolv: Integer: Problem solving score
SocialCog: Integer: Social cognition score
Age: Integer: Participant age in years
Sex: Factor with 2 levels: Participant sex

Details

The dataset name has been kept as 'neurocognitive_psychiatric_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified.

Source

Data taken from the heplots package version 1.7.4. Original research: Hartman, L.I. (2016) Schizophrenia and Schizoaffective Disorder: One Condition or Two? Unpublished PhD dissertation, York University.

OASIS Aging-Dementia Longitudinal MRI

Description

This dataset, oasis_dementia_mri_df, is a data frame containing longitudinal neuroimaging and clinical data from 150 older adults (60-96 years) with repeated MRI scans over multiple visits. The study includes both nondemented and demented individuals, with 373 total imaging sessions featuring 3-4 T1-weighted scans per session.

Usage

data(oasis_dementia_mri_df)

Format

A data frame with 373 observations and 15 variables:

Subject.ID: Character: Unique subject identifier
MRI.ID: Character: Unique MRI session identifier
Group: Factor with 3 levels: Diagnostic group classification
Visit: Integer: Visit number
MR.Delay: Integer: Days since first visit
Gender: Character: Subject gender
Hand: Character: Handedness
Age: Integer: Subject age in years
EDUC: Integer: Years of education
SES: Integer: Socioeconomic status
MMSE: Integer: Mini-Mental State Examination score (0-30)
CDR: Numeric: Clinical Dementia Rating (0-3)
eTIV: Integer: Estimated total intracranial volume (mm³)
nWBV: Numeric: Normalized whole brain volume
ASF: Numeric: Atlas scaling factor

Details

The dataset name has been kept as 'oasis_dementia_mri_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified.

Source

Data taken from the jointest package version 1.0. Original study: Marcus, D.S. et al. (2007) Open Access Series of Imaging Studies (OASIS): Cross-sectional MRI Data in Young, Middle Aged, Nondemented and Demented Older Adults. Journal of Cognitive Neuroscience, 19(9), 1498-1507.

Dopamine Agonists as Adjunct Therapy in Parkinson’s

Description

This dataset, parkinsons_dopamine_list, is a list containing information from 7 studies investigating the mean lost work-time reduction in patients given 4 dopamine agonists and placebo as adjunct therapy for Parkinson's disease. There is placebo and four active drugs coded 2 to 5.

Usage

data(parkinsons_dopamine_list)

Format

A list with 5 components:

Outcomes: Numeric vector containing the outcomes (mean lost work-time reduction)
SE: Numeric vector containing standard errors for the outcomes
Treat: Character vector indicating the treatment (placebo or drug codes 2-5)
Study: Numeric vector indicating the study number (1-7)
Treat.order: Character vector showing the treatment order (placebo and drugs 2-5)

Details

The dataset name has been kept as 'parkinsons_dopamine_list' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package and assists users in identifying its specific characteristics. The suffix 'list' indicates that the dataset is a list. The original content has not been modified in any way.

Source

Data taken from the bnma package version 1.6.0.

Pediatric High-Grade Glioma Clinical Dataset

Description

This dataset, pediatric_glioma_tbl_df, is a tibble containing comprehensive clinical and tumor characteristics for 57 pediatric patients with high-grade glioma. The data includes 22 variables covering demographic, symptomatic, pathological, treatment, and outcome measures.

Usage

data(pediatric_glioma_tbl_df)

Format

A tibble with 57 observations and 22 variables:

Age: Numeric: Patient age in years
Gender: Character: Patient gender
Headache: Character: Headache presence/characteristics
Epilepsy: Character: Epilepsy status
Hemparesis: Character: Hemiparesis presence
increaseICT: Character: Increased intracranial pressure indicators
Pathology: Character: Tumor pathology classification
Pathology_Grade: Numeric: WHO tumor grade (III-IV)
Thalamic_extension: Character: Thalamic involvement
Bil_extension: Character: Bilateral extension
Post_extension: Character: Posterior fossa extension
BrainStem_extension: Character: Brainstem involvement
MultiFocality: Character: Multifocal tumor presence
Midlineshift: Character: Midline shift presence
Edema: Character: Peritumoral edema characteristics
Approx_Tumor_Vol: Numeric: Estimated tumor volume (cm³)
ExtentofSurgicalresection: Character: Surgical resection extent
Shunt: Character: Ventricular shunt presence
ResidualsizeonMRI: Character: Post-surgical residual tumor
Neurostate: Character: Neurological status
PSBeforeRT: Numeric: Performance status pre-radiotherapy
Died: Character: Mortality outcome

Details

The dataset name has been kept as 'pediatric_glioma_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified.

Source

Kaggle dataset: Pediatric High-Grade Glioma Dataset. URL: https://www.kaggle.com/datasets/amraam/pediatric-high-grade-glioma-dataset

Sleep and Learning Performance

Description

This dataset, sleep_performance_df, is a data frame containing measurements of the increase in slow-wave sleep and corresponding improvements in spatial learning tasks from 10 human subjects.

Usage

data(sleep_performance_df)

Format

A data frame with 10 observations and 2 variables:

sleep: Integer vector representing increase in slow-wave sleep (units)
improvement: Integer vector representing improvement in spatial learning tasks (units)

Details

The dataset name has been kept as 'sleep_performance_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package and assists users in identifying its specific characteristics. The suffix 'df' indicates that the dataset is a data frame. The original content has not been modified in any way.

Source

Data taken from the abd package version 0.2-8

Patterns of Subcortical Structures

Description

This dataset, subcortical_patterns_tbl_df, is a tibble containing expected patterns of subcortical structures in schizophrenia derived from large-scale meta-analyses by the ENIGMA consortium. It includes data from multiple neurological and psychiatric conditions for comparison.

Usage

data(subcortical_patterns_tbl_df)

Format

A tibble with 8 observations and 16 variables:

Subcortical: Character vector indicating subcortical regions
SSD: Numeric vector of expected patterns for schizophrenia spectrum disorder
MDD: Numeric vector of expected patterns for major depressive disorder
AD_ADNI: Numeric vector of expected patterns for Alzheimer's disease (ADNI cohort)
AD_ADNIOSYRIX: Numeric vector of expected patterns for Alzheimer's disease (ADNI+OSYRIX cohort)
BD: Numeric vector of expected patterns for bipolar disorder
PD: Numeric vector of expected patterns for Parkinson's disease
Diabetes: Numeric vector of expected patterns for diabetes
HighBP: Numeric vector of expected patterns for high blood pressure
HighLipids: Numeric vector of expected patterns for high lipids
MET: Numeric vector of expected patterns for metabolic syndrome
DS_22q: Numeric vector of expected patterns for 22q11.2 deletion syndrome
Suicide: Numeric vector of expected patterns for suicide
OCD_pediatric: Numeric vector of expected patterns for pediatric OCD
OCD_adult: Numeric vector of expected patterns for adult OCD
AN: Numeric vector of expected patterns for anorexia nervosa

Details

The dataset name has been kept as 'subcortical_patterns_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.

Source

Data taken from the RVIpkg package version 0.3.2

View Available Datasets in NeuroDataSets

Description

This function lists all datasets available in the 'NeuroDataSets' package. If the 'NeuroDataSets' package is not loaded, it stops and shows an error message. If no datasets are available, it returns a message and an empty vector.

Usage

view_datasets_NeuroDataSets()

Value

A character vector with the names of the available datasets. If no datasets are found, it returns an empty character vector.

Examples

if (requireNamespace("NeuroDataSets", quietly = TRUE)) {
  library(NeuroDataSets)
  view_datasets_NeuroDataSets()
}

Expected Patterns of White Matter

Description

This dataset, white_matter_patterns_tbl_df, is a tibble containing expected patterns of white matter in schizophrenia derived from large-scale meta-analyses by the ENIGMA consortium. It includes data from multiple neurological and psychiatric conditions for comparison.

Usage

data(white_matter_patterns_tbl_df)

Format

A tibble with 24 observations and 15 variables:

WM: Character vector indicating white matter regions
SSD: Numeric vector of expected patterns for schizophrenia spectrum disorder
MDD: Numeric vector of expected patterns for major depressive disorder
AD_ADNI: Numeric vector of expected patterns for Alzheimer's disease (ADNI cohort)
AD_ADNIOSYRIX: Numeric vector of expected patterns for Alzheimer's disease (ADNI+OSYRIX cohort)
BD: Numeric vector of expected patterns for bipolar disorder
Diabetes: Numeric vector of expected patterns for diabetes
HighBP: Numeric vector of expected patterns for high blood pressure
HighLipids: Numeric vector of expected patterns for high lipids
MET: Numeric vector of expected patterns for metabolic syndrome
DS_22q: Numeric vector of expected patterns for 22q11.2 deletion syndrome
PTSD: Numeric vector of expected patterns for post-traumatic stress disorder
TBI: Numeric vector of expected patterns for traumatic brain injury
OCD_pediatric: Numeric vector of expected patterns for pediatric OCD
OCD_adult: Numeric vector of expected patterns for adult OCD

Details

The dataset name has been kept as 'white_matter_patterns_tbl_df' to avoid confusion with other datasets in the R ecosystem. This naming convention helps distinguish this dataset as part of the NeuroDataSets package and assists users in identifying its specific characteristics. The suffix 'tbl_df' indicates that the dataset is a tibble. The original content has not been modified in any way.

Source

Data taken from the RVIpkg package version 0.3.2

NeuroDataSets: A Comprehensive Collection of Neuroscience and Brain-Related Datasets

Description

Details

Author(s)

See Also

Allen Brain Atlas Phenotype Data

Description

Usage

Format

Details

Source

Ability and Intelligence Tests

Description

Usage

Format

Details

Source

Adolescent Mental Health Study

Description

Usage

Format

Details

Source

Smoking and Alzheimer's Disease

Description

Usage

Format

Details

Source

Alzheimer's Disease Biomarkers Study

Description

Usage

Format

Details

Source

Brain Structure in Bilingual Humans

Description

Usage

Format

Details

Source

Blood-Brain Barrier

Description

Usage

Format

Details

Source

Mammal Brain Size and Litter Size Relationship

Description

Usage

Format

Details

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Brain Size and IQ Study Data

Description

Usage

Format

Details

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Brain Activity in String Players

Description

Usage

Format

Details

Source

BRAiNS Cohort Cognitive States Matrix

Description

Usage

Format

Details

Source

Effects of Cocaine on Dopamine Receptors

Description

Usage

Format

Details

Source

Dopamine \beta-Hydroxylase Activity in Schizophrenia

Description

Usage

Dopamine `\beta`-Hydroxylase Activity in Schizophrenia