Notes

Short observations, references, and questions across data, AI, science, and philosophy.

A closer look at a concept, a useful source, or a question worth returning to. Read on their own or alongside a longer piece, these notes leave room for connections to develop over time.

Choosing the rank of a dynamical model AI

How predictive dimension, estimation stability and held-out performance inform model rank.

topics dynamical-systems,model-selection,spectral-learning
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Clustering regions and detecting graph communities AI

Why grouping similar profiles and partitioning graph connections can produce different network organizations.

topics neuroimaging,clustering,community-detection
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Comparing subjects in a shared latent basis AI

Why common ROI locations do not guarantee comparable latent dimensions, and what a shared basis makes comparable.

topics neuroimaging,dimensionality-reduction,individual-differences
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Continuous dynamics and discrete states AI

Why signed predictive relationships between continuous components are different from probabilities of switching states.

topics neuroimaging,dynamical-systems,hidden-markov-models
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Contribution magnitude and variance explained AI

Why the size of a component contribution is not an additive percentage of the recorded signal.

topics neuroimaging,matrix-decomposition,interpretation
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From fMRI signals to network graphs AI

How measurement units, edge definitions and graph summaries shape the meaning of a brain network.

topics neuroimaging,graph-theory,functional-networks
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Hume on Causation

A short note on Hume’s treatment of causal necessity and constant conjunction.

topics philosophy,causation,empiricism
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Kant on Causation

A compact note on causality as a category required for objective temporal succession.

topics philosophy,causation,transcendental-idealism
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Parcels and functional systems describe different scales AI

How regional measurement units, distributed reference systems and learned network patterns relate.

topics neuroimaging,parcellation,functional-networks
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Registration, resampling, and anatomical coverage AI

Three distinct questions behind an ROI time series: anatomical alignment, image sampling, and available tissue.

topics neuroimaging,spatial-processing,quality-control
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Second moments, covariance, and connectivity AI

Why a matrix of signal products can retain mean structure that is absent from covariance and correlation.

topics neuroimaging,statistics,connectivity
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Spatial resemblance and concentration measure different things AI

Why a strong spatial correlation need not mean that most of a pattern lies inside a reference system.

topics neuroimaging,spatial-statistics,network-matching
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Spectral learning of predictive dynamics AI

How past–future relationships become a compact dynamical representation and spatial network patterns.

topics neuroimaging,dynamical-systems,spectral-learning
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Visual systems beyond a single visual network AI

How retinotopic maps, processing streams and category-selective regions relate to broad visual reference labels.

topics neuroimaging,visual-cortex,functional-anatomy
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What block and resting state designs reveal about dynamics AI

How an experimental clock changes the interpretation of network dynamics, including the limits of fixation baselines.

topics neuroimaging,experimental-design,bold-timing
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What different connectivity measures ask AI

A practical distinction between correlation, conditional association, frequency-specific coupling and directed models.

topics neuroimaging,connectivity,statistics
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What might resting state activity be doing AI

Evidence and complementary interpretations of intrinsic organization, self-generated thought and postexperience processing.

topics neuroimaging,resting-state,default-mode-network
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