Analyses grouped by
disease classification.
Fifteen clinical categories, each mapped to the Neuron Lab modules that best model, quantify, or diagnose the phenotype. Every module listed here is runnable in the platform.
Progressive loss of neurons over time.
Disorders affecting blood vessels supplying the brain.
Damage to the myelin sheath surrounding nerve fibers.
Characterized by recurrent seizures.
Affect voluntary movement.
Affect peripheral nerves, muscles, or neuromuscular junction.
Begin during brain development.
Caused primarily by inherited genetic mutations.
Caused by infections of the nervous system.
Immune system attacks nervous tissue.
Result from injury.
Benign or malignant tumors of the nervous system.
Disorders where pain is the primary symptom.
Disorders affecting sleep regulation.
Disorders involving brain function, cognition, and behavior.
Neurodegenerative Diseases
Progressive loss of neurons over time.
Attractor recall, altered excitability, polygenic risk, rare-variant burden, differential expression, and epigenetic aging capture the network, cellular, and molecular signatures of neurodegeneration.
Discrete Hopfield network with Hebbian weights. Recalls a stored ±1 pattern from a noisy probe and reports energy descent and per-pattern overlaps.
Brette–Gerstner adaptive exponential integrate-and-fire neuron with subthreshold and spike-triggered adaptation. Returns V(t), w(t), spike raster and firing rate.
N phase oscillators with all-to-all coupling. Tracks the Kuramoto order parameter r(t) and detects synchronization vs incoherence.
Additive PRS across risk variants under HWE; distribution, summary stats and top-effect variants.
Collapse rare variants per individual; test carrier enrichment in cases vs. controls with Fisher's exact.
Compare expression between two groups of cells/samples; volcano + table.
Weighted linear methylation-age predictor with per-sample chronological vs. predicted age, MAE, RMSE and Pearson r.
Region-level expression browsing across a brain atlas.
Survival curves per group with log-rank hypothesis test.
Cerebrovascular Diseases
Disorders affecting blood vessels supplying the brain.
Resting-state fluctuations (ALFF), seed connectivity, spectral disruption, and survival modeling quantify vascular-driven functional loss and outcomes.
Amplitude of low-frequency fluctuations and fractional ALFF from BOLD time series.
Correlation map from a seed region to all others in a BOLD time-series matrix.
Power spectral density and band power from a continuous signal.
Kendall's W concordance across each region and its neighbours in a BOLD time × region matrix.
Univariate survival regression with hazard ratio, Wald test, partial likelihood, and concordance.
Survival curves per group with log-rank hypothesis test.
Demyelinating Diseases
Damage to the myelin sheath surrounding nerve fibers.
Conduction disruption manifests as altered functional connectivity, spatial component structure, and graph topology across brain networks.
Region-by-region correlation matrix and graph summary from BOLD time series.
FastICA on multichannel signals (e.g. BOLD, EEG) with logcosh nonlinearity.
Kendall's W concordance across each region and its neighbours in a BOLD time × region matrix.
Density, degree distribution, clustering and hubs from a connectivity matrix.
Correlation map from a seed region to all others in a BOLD time-series matrix.
Epileptic Disorders
Characterized by recurrent seizures.
Wilson–Cowan captures ictal bifurcations; Hodgkin–Huxley models hyperexcitable dynamics; spectral and time-frequency tools localize onset in EEG/LFP.
Two-population excitatory–inhibitory rate model with sigmoid activation. Simulates E(t), I(t), reports fixed-point vs limit-cycle behaviour and the dominant oscillation frequency.
Simulate a single HH neuron under step-current injection and measure spiking.
Power spectral density and band power from a continuous signal.
Short-time Fourier transform with band power over time for EEG/LFP.
Pairwise coincident-spike histogram between two spike trains.
Conductance-based Ca²⁺/K⁺ model of a barnacle muscle fiber. Produces V(t), gating variable n(t), spike times and firing rate under step current.
Movement Disorders
Affect voluntary movement.
Kuramoto captures pathological β-band synchrony; Izhikevich and Hindmarsh–Rose reproduce tremor-like bursting; ring attractors model motor drift.
N phase oscillators with all-to-all coupling. Tracks the Kuramoto order parameter r(t) and detects synchronization vs incoherence.
Izhikevich 2-variable model with canonical cortical regimes — regular spiking (RS), intrinsically bursting (IB), chattering (CH), fast spiking (FS), and low-threshold spiking (LTS). Returns V(t), rate, spike raster.
3-variable model producing spikes, bursts and chaotic dynamics. Reports spikes per burst, burst count and (x, z) phase-plane trajectory.
Brette–Gerstner adaptive exponential integrate-and-fire neuron with subthreshold and spike-triggered adaptation. Returns V(t), w(t), spike raster and firing rate.
1-D ring of rate neurons with Mexican-hat coupling. Forms a persistent activity bump that encodes a stimulus angle after the input is removed.
Neuromuscular Diseases
Affect peripheral nerves, muscles, or neuromuscular junction.
AdEx and LIF quantify rheobase and firing collapse; Morris–Lecar models NMJ excitability; spike statistics assess motor unit output.
Brette–Gerstner adaptive exponential integrate-and-fire neuron with subthreshold and spike-triggered adaptation. Returns V(t), w(t), spike raster and firing rate.
Leaky integrate-and-fire neuron f-I curve and voltage trace.
Conductance-based Ca²⁺/K⁺ model of a barnacle muscle fiber. Produces V(t), gating variable n(t), spike times and firing rate under step current.
ISI distribution, firing rate, CV and Fano factor from a spike train.
Event-triggered firing rate around triggers.
Neurodevelopmental Disorders
Begin during brain development.
E/I balance (Wilson–Cowan), plasticity (STDP), spiking network dynamics, and connectome topology probe cortical circuit development.
Two-population excitatory–inhibitory rate model with sigmoid activation. Simulates E(t), I(t), reports fixed-point vs limit-cycle behaviour and the dominant oscillation frequency.
Recurrent excitatory/inhibitory LIF network; population dynamics and raster.
Classical exponential STDP learning window — Δw = A+·exp(−Δt/τ+) for pre→post and Δw = −A−·exp(Δt/τ−) for post→pre. Returns full Δw(Δt) curve, LTP/LTD peaks and areas.
Density, degree distribution, clustering and hubs from a connectivity matrix.
Region-by-region correlation matrix and graph summary from BOLD time series.
Neurogenetic Disorders
Caused primarily by inherited genetic mutations.
Polygenic risk, rare-variant burden, eQTL scans, heritability regression, GWAS QC, and ancestry PCA are the core molecular readouts.
Additive PRS across risk variants under HWE; distribution, summary stats and top-effect variants.
Collapse rare variants per individual; test carrier enrichment in cases vs. controls with Fisher's exact.
Single-variant case/control association with a Manhattan plot and top hits.
QQ plot of observed vs expected -log10 p-values with genomic inflation factor.
Per-SNP linear regression of expression on genotype dosage with BH-FDR; reports top SNP and significant hits.
Regress χ² on LD score to estimate SNP-heritability ĥ² and intercept, following the LDSC framework.
Top PCs on a standardised genotype matrix to reveal population structure.
Neuroinfectious Diseases
Caused by infections of the nervous system.
Pathogen sequence QC, variant statistics, k-mer profiles, ORF discovery, and phylogeny characterize infectious agents in CSF/tissue samples.
Read counts, GC%, N50, length distribution, mean quality from FASTA/FASTQ.
Ts/Tv, het/hom, SNP vs indel counts, and allele-frequency spectrum from VCF.
Distinct/total k-mers, top-k table, and occurrence histogram from sequences.
Six-frame ORF discovery on a DNA sequence with codon-usage table.
Neighbor-joining tree from a square distance matrix; returns Newick string.
k-mer counts in foreground vs background sequences with binomial p and BH-FDR.
Global pairwise sequence alignment with configurable match/mismatch/gap scores.
Neuroimmune Disorders
Immune system attacks nervous tissue.
Differential expression, gene-set enrichment, and supervised classifiers separate autoimmune signatures from controls in transcriptomic data.
Compare expression between two groups of cells/samples; volcano + table.
Over-representation of pathways via hypergeometric test + BH-FDR.
Binary logistic regression via Newton-Raphson; coefficients, z, p, AUC.
Bagged decision-tree ensemble with √d random feature subset per split; returns training and out-of-bag accuracy plus per-class metrics. Input: numeric matrix, label = last column.
Gradient boosting with regression stumps (squared-error loss) and learning-rate shrinkage; returns MSE, RMSE, R² and sample predictions. Input: numeric matrix, target = last column.
Traumatic Nervous System Disorders
Result from injury.
ERPs, spectrograms, spectral changes, and graph-theoretic disruption quantify functional impact of trauma across acute and chronic phases.
Trial-averaged waveform around event markers with bootstrap 95% CI.
Short-time Fourier transform with band power over time for EEG/LFP.
Power spectral density and band power from a continuous signal.
Density, degree distribution, clustering and hubs from a connectivity matrix.
Correlation map from a seed region to all others in a BOLD time-series matrix.
Brain Tumors (Neuro-oncology)
Benign or malignant tumors of the nervous system.
Tumor scRNA-seq QC, differential expression, dimensionality reduction, unsupervised clustering, and survival modeling map heterogeneity and outcomes.
Per-cell QC metrics and MAD-based outlier filtering for single-cell/single-nucleus RNA-seq.
Compare expression between two groups of cells/samples; volcano + table.
Non-linear dimensionality reduction to a 2D map (exact O(N²) t-SNE).
k-means++ initialization + Lloyd's algorithm; labels, centroids, inertia.
Agglomerative clustering with average/single/complete linkage; flat cut at k.
Survival curves per group with log-rank hypothesis test.
Univariate survival regression with hazard ratio, Wald test, partial likelihood, and concordance.
Gradient boosting with regression stumps (squared-error loss) and learning-rate shrinkage; returns MSE, RMSE, R² and sample predictions. Input: numeric matrix, target = last column.
Headache and Pain Disorders
Disorders where pain is the primary symptom.
EEG spectral power, ERPs, PSTHs of nociceptive responses, and non-parametric group tests characterize pain-related neural activity.
Power spectral density and band power from a continuous signal.
Trial-averaged waveform around event markers with bootstrap 95% CI.
Event-triggered firing rate around triggers.
Non-parametric two-sample test with tie-corrected normal approximation.
Non-parametric paired-sample test with tie correction.
Sleep Disorders
Disorders affecting sleep regulation.
Sleep staging via HMM decoding, spectrograms, band-limited spectral power, and oscillator coupling probe circadian and ultradian dynamics.
Scaled forward-backward posteriors plus Viterbi state decoding for discrete observations.
Short-time Fourier transform with band power over time for EEG/LFP.
Power spectral density and band power from a continuous signal.
N phase oscillators with all-to-all coupling. Tracks the Kuramoto order parameter r(t) and detects synchronization vs incoherence.
Biased autocorrelation estimator with Bartlett 95% white-noise confidence band for signal analysis.
Psychiatric and Behavioral Disorders
Disorders involving brain function, cognition, and behavior.
Reduced γ-band synchrony (Kuramoto), altered functional connectivity, ICA components, Granger causality, attractor recall, and polygenic risk together capture psychiatric endophenotypes.
N phase oscillators with all-to-all coupling. Tracks the Kuramoto order parameter r(t) and detects synchronization vs incoherence.
Region-by-region correlation matrix and graph summary from BOLD time series.
Correlation map from a seed region to all others in a BOLD time-series matrix.
FastICA on multichannel signals (e.g. BOLD, EEG) with logcosh nonlinearity.
Tests whether x's past improves prediction of y beyond y's past (VAR + F-test).
Discrete Hopfield network with Hebbian weights. Recalls a stored ±1 pattern from a noisy probe and reports energy descent and per-pattern overlaps.
Additive PRS across risk variants under HWE; distribution, summary stats and top-effect variants.
Run a disease-relevant analysis.
Launch any module with your own data or platform simulations — every result is typed, versioned, and reproducible.