Training of neural networks using backpropagation,
    resilient backpropagation with (Riedmiller, 1994) or without
    weight backtracking (Riedmiller and Braun, 1993) or the
    modified globally convergent version by Anastasiadis et al.
    (2005). The package allows flexible settings through
    custom-choice of error and activation function. Furthermore,
    the calculation of generalized weights (Intrator O & Intrator
    N, 1993) is implemented.

Visualization and analysis tools to aid in the interpretation of
    neural network models.  Functions are available for plotting,
    quantifying variable importance, conducting a sensitivity analysis, and
    obtaining a simple list of model weights.

Analysis functions to quantify inputs importance in neural network models.
  Functions are available for calculating and plotting the inputs importance and obtaining
  the activation function of each neuron layer and its derivatives. The importance of a given
  input is defined as the distribution of the derivatives of the output with respect to that
  input in each training data point <doi:10.18637/jss.v102.i07>.

Base package for 'Neuroconductor', which includes many helper 
    functions that interact with objects of class 'nifti', implemented by
    package 'oro.nifti', for reading/writing and also other manipulation 
    functions.

Annotated neuroblastoma copy number profiles,
 a benchmark data set for change-point detection algorithms,
 as described by Hocking et al. <doi:10.1186/1471-2105-14-164>.

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 disease, dementia, epilepsy, schizophrenia, autism spectrum disorder, attention deficit, hyperactivity disorder, 
    Tourette's syndrome, traumatic brain injury, gliomas, migraines, headaches, sleep disorders, concussions, encephalitis, 
    subarachnoid hemorrhage, and mental health conditions. Datasets cover structural and functional brain data, cross-sectional and longitudinal 
    MRI imaging studies, neurotransmission, gene expression, cognitive performance, intelligence metrics, sleep deprivation effects, treatment outcomes, 
    brain-body relationships across species, neurological injury patterns, and acupuncture interventions. Data sources include peer-reviewed studies, 
    clinical trials, military health records, sports injury databases, and international comparative studies.
    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.