{"id":683,"date":"2026-02-26T17:54:35","date_gmt":"2026-02-26T17:54:35","guid":{"rendered":"https:\/\/globalsolidarity.live\/maitreyamusic\/?p=683"},"modified":"2026-02-26T17:54:39","modified_gmt":"2026-02-26T17:54:39","slug":"neuroyoga-and-predictive-processing","status":"publish","type":"post","link":"https:\/\/globalsolidarity.live\/maitreyamusic\/neuroyoga\/neuroyoga-and-predictive-processing\/","title":{"rendered":"NeuroYoga and Predictive Processing"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\">Intentional Modulation of Generative Models and Precision Weighting in the Human Brain<\/h2>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h1 class=\"wp-block-heading\">Abstract<\/h1>\n\n\n\n<p>Predictive Processing (PP) describes the brain as a hierarchical generative model that continuously minimizes prediction error through active inference. This paper proposes that structured contemplative training (NeuroYoga 3.0) can be interpreted as an intentional modulation of generative priors, precision weighting, and hierarchical error propagation.<\/p>\n\n\n\n<p>We argue that:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Meditation alters precision assignment.<\/li>\n\n\n\n<li>Semantic structuring reshapes generative priors.<\/li>\n\n\n\n<li>Coherence training modulates hierarchical integration.<\/li>\n\n\n\n<li>Stable contemplative states reduce maladaptive overfitting of prediction models.<\/li>\n<\/ul>\n\n\n\n<p>This integration provides a mechanistic account of contemplative cognition within the Free Energy Principle framework.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h1 class=\"wp-block-heading\">1\ufe0f\u20e3 Predictive Processing: Core Model<\/h1>\n\n\n\n<p>Under PP, the brain:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Generates top-down predictions.<\/li>\n\n\n\n<li>Receives bottom-up sensory input.<\/li>\n\n\n\n<li>Computes prediction error:<\/li>\n<\/ul>\n\n\n\n<p><math xmlns=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"block\"><semantics><mrow><mi>\u03f5<\/mi><mo>=<\/mo><mi>s<\/mi><mi>e<\/mi><mi>n<\/mi><mi>s<\/mi><mi>o<\/mi><mi>r<\/mi><mi>y<\/mi><mtext>&nbsp;<\/mtext><mi>i<\/mi><mi>n<\/mi><mi>p<\/mi><mi>u<\/mi><mi>t<\/mi><mo>\u2212<\/mo><mi>p<\/mi><mi>r<\/mi><mi>e<\/mi><mi>d<\/mi><mi>i<\/mi><mi>c<\/mi><mi>t<\/mi><mi>e<\/mi><mi>d<\/mi><mtext>&nbsp;<\/mtext><mi>i<\/mi><mi>n<\/mi><mi>p<\/mi><mi>u<\/mi><mi>t<\/mi><\/mrow><annotation encoding=\"application\/x-tex\">\\epsilon = sensory\\ input &#8211; predicted\\ input<\/annotation><\/semantics><\/math>\u03f5=sensory&nbsp;input\u2212predicted&nbsp;input<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Updates its internal model to minimize free energy:<\/li>\n<\/ul>\n\n\n\n<p><math xmlns=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"block\"><semantics><mrow><mi>F<\/mi><mo>\u2248<\/mo><mi>P<\/mi><mi>r<\/mi><mi>e<\/mi><mi>d<\/mi><mi>i<\/mi><mi>c<\/mi><mi>t<\/mi><mi>i<\/mi><mi>o<\/mi><mi>n<\/mi><mtext>&nbsp;<\/mtext><mi>E<\/mi><mi>r<\/mi><mi>r<\/mi><mi>o<\/mi><mi>r<\/mi><mo>+<\/mo><mi>C<\/mi><mi>o<\/mi><mi>m<\/mi><mi>p<\/mi><mi>l<\/mi><mi>e<\/mi><mi>x<\/mi><mi>i<\/mi><mi>t<\/mi><mi>y<\/mi><mtext>&nbsp;<\/mtext><mi>C<\/mi><mi>o<\/mi><mi>s<\/mi><mi>t<\/mi><\/mrow><annotation encoding=\"application\/x-tex\">F \\approx Prediction\\ Error + Complexity\\ Cost<\/annotation><\/semantics><\/math>F\u2248Prediction&nbsp;Error+Complexity&nbsp;Cost<\/p>\n\n\n\n<p>Thus, perception is inference.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h1 class=\"wp-block-heading\">2\ufe0f\u20e3 The Free Energy Principle (FEP)<\/h1>\n\n\n\n<p>Friston\u2019s formulation:<math xmlns=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"block\"><semantics><mrow><mi>F<\/mi><mo>=<\/mo><msub><mi>E<\/mi><mi>q<\/mi><\/msub><mo stretchy=\"false\">[<\/mo><mi>ln<\/mi><mo>\u2061<\/mo><mi>q<\/mi><mo stretchy=\"false\">(<\/mo><mi>s<\/mi><mo stretchy=\"false\">)<\/mo><mo>\u2212<\/mo><mi>ln<\/mi><mo>\u2061<\/mo><mi>p<\/mi><mo stretchy=\"false\">(<\/mo><mi>s<\/mi><mo separator=\"true\">,<\/mo><mi>o<\/mi><mo stretchy=\"false\">)<\/mo><mo stretchy=\"false\">]<\/mo><\/mrow><annotation encoding=\"application\/x-tex\">F = E_q[\\ln q(s) &#8211; \\ln p(s,o)]<\/annotation><\/semantics><\/math>F=Eq\u200b[lnq(s)\u2212lnp(s,o)]<\/p>\n\n\n\n<p>Where:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><math xmlns=\"http:\/\/www.w3.org\/1998\/Math\/MathML\"><semantics><mrow><mi>q<\/mi><mo stretchy=\"false\">(<\/mo><mi>s<\/mi><mo stretchy=\"false\">)<\/mo><\/mrow><annotation encoding=\"application\/x-tex\">q(s)<\/annotation><\/semantics><\/math>q(s) = internal model<\/li>\n\n\n\n<li><math xmlns=\"http:\/\/www.w3.org\/1998\/Math\/MathML\"><semantics><mrow><mi>p<\/mi><mo stretchy=\"false\">(<\/mo><mi>s<\/mi><mo separator=\"true\">,<\/mo><mi>o<\/mi><mo stretchy=\"false\">)<\/mo><\/mrow><annotation encoding=\"application\/x-tex\">p(s,o)<\/annotation><\/semantics><\/math>p(s,o) = generative probability of states and observations<\/li>\n<\/ul>\n\n\n\n<p>Minimizing F means reducing surprise.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h1 class=\"wp-block-heading\">3\ufe0f\u20e3 Where NeuroYoga Enters<\/h1>\n\n\n\n<p>NeuroYoga 3.0 can be framed as:<\/p>\n\n\n\n<p><strong>Voluntary restructuring of the generative model.<\/strong><\/p>\n\n\n\n<p>Three axes of intervention:<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\">A. Precision Weighting Modulation<\/h2>\n\n\n\n<p>In predictive processing:<\/p>\n\n\n\n<p>Precision <math xmlns=\"http:\/\/www.w3.org\/1998\/Math\/MathML\"><semantics><mrow><mi mathvariant=\"normal\">\u03a0<\/mi><\/mrow><annotation encoding=\"application\/x-tex\">\\Pi<\/annotation><\/semantics><\/math>\u03a0 determines how strongly prediction errors update the model.<\/p>\n\n\n\n<p>Anxiety example:<math xmlns=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"block\"><semantics><mrow><msub><mi mathvariant=\"normal\">\u03a0<\/mi><mrow><mi>e<\/mi><mi>r<\/mi><mi>r<\/mi><mi>o<\/mi><mi>r<\/mi><\/mrow><\/msub><mo>\u2191<\/mo><\/mrow><annotation encoding=\"application\/x-tex\">\\Pi_{error} \\uparrow<\/annotation><\/semantics><\/math>\u03a0error\u200b\u2191<\/p>\n\n\n\n<p>\u2192 hyper-reactivity<\/p>\n\n\n\n<p>Meditative training reduces maladaptive precision:<math xmlns=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"block\"><semantics><mrow><msub><mi mathvariant=\"normal\">\u03a0<\/mi><mrow><mi>m<\/mi><mi>a<\/mi><mi>l<\/mi><mi>a<\/mi><mi>d<\/mi><mi>a<\/mi><mi>p<\/mi><mi>t<\/mi><mi>i<\/mi><mi>v<\/mi><mi>e<\/mi><\/mrow><\/msub><mo>\u2193<\/mo><\/mrow><annotation encoding=\"application\/x-tex\">\\Pi_{maladaptive} \\downarrow<\/annotation><\/semantics><\/math>\u03a0maladaptive\u200b\u2193<\/p>\n\n\n\n<p>\u2192 reduced reactivity<\/p>\n\n\n\n<p>Thus meditation acts on:<math xmlns=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"block\"><semantics><mrow><mi>F<\/mi><mo>=<\/mo><mi mathvariant=\"normal\">\u03a0<\/mi><msup><mi>\u03f5<\/mi><mn>2<\/mn><\/msup><\/mrow><annotation encoding=\"application\/x-tex\">F = \\Pi \\epsilon^2<\/annotation><\/semantics><\/math>F=\u03a0\u03f52<\/p>\n\n\n\n<p>Reducing <math xmlns=\"http:\/\/www.w3.org\/1998\/Math\/MathML\"><semantics><mrow><mi mathvariant=\"normal\">\u03a0<\/mi><\/mrow><annotation encoding=\"application\/x-tex\">\\Pi<\/annotation><\/semantics><\/math>\u03a0 lowers error amplification.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\">B. Prior Restructuring<\/h2>\n\n\n\n<p>Generative priors shape perception.<\/p>\n\n\n\n<p>Rigid priors \u2192 cognitive bias.<\/p>\n\n\n\n<p>Neurosemantic training introduces hierarchical restructuring:<math xmlns=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"block\"><semantics><mrow><mi>p<\/mi><mo stretchy=\"false\">(<\/mo><mi>s<\/mi><mo stretchy=\"false\">)<\/mo><mo>\u2192<\/mo><msup><mi>p<\/mi><mo mathvariant=\"normal\" lspace=\"0em\" rspace=\"0em\">\u2032<\/mo><\/msup><mo stretchy=\"false\">(<\/mo><mi>s<\/mi><mo stretchy=\"false\">)<\/mo><\/mrow><annotation encoding=\"application\/x-tex\">p(s) \\rightarrow p'(s)<\/annotation><\/semantics><\/math>p(s)\u2192p\u2032(s)<\/p>\n\n\n\n<p>Where priors become:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Broader<\/li>\n\n\n\n<li>More flexible<\/li>\n\n\n\n<li>Less overconfident<\/li>\n<\/ul>\n\n\n\n<p>This reduces model rigidity.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\">C. Hierarchical Integration<\/h2>\n\n\n\n<p>Predictive models are hierarchical:<\/p>\n\n\n\n<p>Low-level \u2192 sensory<br>Mid-level \u2192 conceptual<br>High-level \u2192 narrative self<\/p>\n\n\n\n<p>NeuroYoga practices reduce dominance of high-level narrative priors (Default Mode Network suppression).<\/p>\n\n\n\n<p>Effect:<\/p>\n\n\n\n<p>Top-down priors weaken.<\/p>\n\n\n\n<p>Bottom-up signal integration increases.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h1 class=\"wp-block-heading\">4\ufe0f\u20e3 Samadhi as Precision Collapse<\/h1>\n\n\n\n<p>In deep meditative absorption:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Narrative priors quiet.<\/li>\n\n\n\n<li>Precision of self-model reduces.<\/li>\n\n\n\n<li>Hierarchical depth temporarily flattens.<\/li>\n<\/ul>\n\n\n\n<p>Mathematically:<math xmlns=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"block\"><semantics><mrow><msub><mi mathvariant=\"normal\">\u03a0<\/mi><mrow><mi>s<\/mi><mi>e<\/mi><mi>l<\/mi><mi>f<\/mi><\/mrow><\/msub><mo>\u2192<\/mo><mn>0<\/mn><\/mrow><annotation encoding=\"application\/x-tex\">\\Pi_{self} \\rightarrow 0<\/annotation><\/semantics><\/math>\u03a0self\u200b\u21920<\/p>\n\n\n\n<p>Prediction error minimized not by updating world model,<br>but by suspending interpretive overfitting.<\/p>\n\n\n\n<p>This produces:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Reduced cognitive entropy.<\/li>\n\n\n\n<li>Increased coherence.<\/li>\n\n\n\n<li>Subjective unity experience.<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h1 class=\"wp-block-heading\">5\ufe0f\u20e3 Active Inference and Behavior<\/h1>\n\n\n\n<p>Active inference states:<\/p>\n\n\n\n<p>The brain acts to minimize prediction error.<\/p>\n\n\n\n<p>Two options:<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>Update model.<\/li>\n\n\n\n<li>Change environment.<\/li>\n<\/ol>\n\n\n\n<p>NeuroYoga introduces third vector:<\/p>\n\n\n\n<ol start=\"3\" class=\"wp-block-list\">\n<li>Modulate internal precision weighting without behavioral reaction.<\/li>\n<\/ol>\n\n\n\n<p>Thus reducing compulsive action loops.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h1 class=\"wp-block-heading\">6\ufe0f\u20e3 Stability and Overfitting<\/h1>\n\n\n\n<p>Maladaptive cognition can be seen as overfitted generative models.<\/p>\n\n\n\n<p>Examples:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Trauma \u2192 hyper-precise threat priors.<\/li>\n\n\n\n<li>Depression \u2192 negative prediction bias.<\/li>\n<\/ul>\n\n\n\n<p>NeuroYoga 3.0 trains:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Model flexibility.<\/li>\n\n\n\n<li>Reduced overconfidence in priors.<\/li>\n\n\n\n<li>Increased meta-model awareness.<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h1 class=\"wp-block-heading\">7\ufe0f\u20e3 Coherence as Error Alignment<\/h1>\n\n\n\n<p>Gamma coherence may represent:<\/p>\n\n\n\n<p>Synchronous updating across hierarchical layers.<\/p>\n\n\n\n<p>Let prediction error at level i:<math xmlns=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"block\"><semantics><mrow><msub><mi>\u03f5<\/mi><mi>i<\/mi><\/msub><\/mrow><annotation encoding=\"application\/x-tex\">\\epsilon_i<\/annotation><\/semantics><\/math>\u03f5i\u200b<\/p>\n\n\n\n<p>Coherence increases cross-level alignment:<math xmlns=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"block\"><semantics><mrow><mi>C<\/mi><mi>o<\/mi><mi>r<\/mi><mi>r<\/mi><mo stretchy=\"false\">(<\/mo><msub><mi>\u03f5<\/mi><mi>i<\/mi><\/msub><mo separator=\"true\">,<\/mo><msub><mi>\u03f5<\/mi><mrow><mi>i<\/mi><mo>+<\/mo><mn>1<\/mn><\/mrow><\/msub><mo stretchy=\"false\">)<\/mo><mo>\u2191<\/mo><\/mrow><annotation encoding=\"application\/x-tex\">Corr(\\epsilon_i, \\epsilon_{i+1}) \\uparrow<\/annotation><\/semantics><\/math>Corr(\u03f5i\u200b,\u03f5i+1\u200b)\u2191<\/p>\n\n\n\n<p>Thus hierarchical mismatch reduces.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h1 class=\"wp-block-heading\">8\ufe0f\u20e3 Bounded Optimization<\/h1>\n\n\n\n<p>Predictive processing warns:<\/p>\n\n\n\n<p>Too little precision \u2192 apathy<br>Too much precision \u2192 anxiety<\/p>\n\n\n\n<p>NeuroYoga 3.0 seeks optimal precision:<math xmlns=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"block\"><semantics><mrow><msub><mi mathvariant=\"normal\">\u03a0<\/mi><mrow><mi>o<\/mi><mi>p<\/mi><mi>t<\/mi><mi>i<\/mi><mi>m<\/mi><mi>a<\/mi><mi>l<\/mi><\/mrow><\/msub><\/mrow><annotation encoding=\"application\/x-tex\">\\Pi_{optimal}<\/annotation><\/semantics><\/math>\u03a0optimal\u200b<\/p>\n\n\n\n<p>Such that:<math xmlns=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"block\"><semantics><mrow><mfrac><mrow><mi>d<\/mi><mi>F<\/mi><\/mrow><mrow><mi>d<\/mi><mi mathvariant=\"normal\">\u03a0<\/mi><\/mrow><\/mfrac><mo>=<\/mo><mn>0<\/mn><\/mrow><annotation encoding=\"application\/x-tex\">\\frac{dF}{d\\Pi} = 0<\/annotation><\/semantics><\/math>d\u03a0dF\u200b=0<\/p>\n\n\n\n<p>Balanced reactivity.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h1 class=\"wp-block-heading\">9\ufe0f\u20e3 Cognitive Longevity Interpretation<\/h1>\n\n\n\n<p>Chronic stress = persistent prediction error amplification.<\/p>\n\n\n\n<p>NeuroYoga reduces:<math xmlns=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"block\"><semantics><mrow><msub><mi>\u03f5<\/mi><mrow><mi>c<\/mi><mi>h<\/mi><mi>r<\/mi><mi>o<\/mi><mi>n<\/mi><mi>i<\/mi><mi>c<\/mi><\/mrow><\/msub><\/mrow><annotation encoding=\"application\/x-tex\">\\epsilon_{chronic}<\/annotation><\/semantics><\/math>\u03f5chronic\u200b<\/p>\n\n\n\n<p>Lower free energy accumulation \u2192 reduced systemic stress \u2192 reduced inflammation.<\/p>\n\n\n\n<p>Indirect epigenetic impact.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h1 class=\"wp-block-heading\">\ud83d\udd1f Theoretical Contribution<\/h1>\n\n\n\n<p>This integration proposes:<\/p>\n\n\n\n<p>NeuroYoga 3.0 is a <strong>precision-training protocol for generative models<\/strong>.<\/p>\n\n\n\n<p>It does not add mystical content.<br>It modifies inference dynamics.<\/p>\n\n\n\n<p>It is:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Model regularization.<\/li>\n\n\n\n<li>Precision recalibration.<\/li>\n\n\n\n<li>Hierarchical synchronization training.<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h1 class=\"wp-block-heading\">11\ufe0f\u20e3 Critical Caveats<\/h1>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Not all meditative states reduce error adaptively.<\/li>\n\n\n\n<li>Excess prior weakening may induce dissociation.<\/li>\n\n\n\n<li>Over-suppression of precision can reduce motivation.<\/li>\n\n\n\n<li>Stability boundaries must be respected.<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h1 class=\"wp-block-heading\">12\ufe0f\u20e3 Unified Statement<\/h1>\n\n\n\n<p>Predictive Processing describes how the brain models reality.<\/p>\n\n\n\n<p>NeuroYoga 3.0 proposes how to consciously regulate that modeling process.<\/p>\n\n\n\n<p>The bridge is not metaphysical.<\/p>\n\n\n\n<p>It is computational.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Intentional Modulation of Generative Models and Precision Weighting in the Human Brain Abstract Predictive Processing (PP) describes the<\/p>\n","protected":false},"author":1,"featured_media":204,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[22,10],"tags":[],"class_list":["post-683","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-neuroscience","category-neuroyoga"],"jetpack_featured_media_url":"https:\/\/globalsolidarity.live\/maitreyamusic\/wp-content\/uploads\/2026\/02\/neuromeditation.png","_links":{"self":[{"href":"https:\/\/globalsolidarity.live\/maitreyamusic\/wp-json\/wp\/v2\/posts\/683","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/globalsolidarity.live\/maitreyamusic\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/globalsolidarity.live\/maitreyamusic\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/globalsolidarity.live\/maitreyamusic\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/globalsolidarity.live\/maitreyamusic\/wp-json\/wp\/v2\/comments?post=683"}],"version-history":[{"count":1,"href":"https:\/\/globalsolidarity.live\/maitreyamusic\/wp-json\/wp\/v2\/posts\/683\/revisions"}],"predecessor-version":[{"id":684,"href":"https:\/\/globalsolidarity.live\/maitreyamusic\/wp-json\/wp\/v2\/posts\/683\/revisions\/684"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/globalsolidarity.live\/maitreyamusic\/wp-json\/wp\/v2\/media\/204"}],"wp:attachment":[{"href":"https:\/\/globalsolidarity.live\/maitreyamusic\/wp-json\/wp\/v2\/media?parent=683"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/globalsolidarity.live\/maitreyamusic\/wp-json\/wp\/v2\/categories?post=683"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/globalsolidarity.live\/maitreyamusic\/wp-json\/wp\/v2\/tags?post=683"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}