Version history
1 version on record. Newest first; the live version sits at the top with a live indicator.
- Live5/17/2026, 4:45:12 PM
6dbcc280f0d0Content snapshot
{ "kind": "infographic", "prompt": "Aerobic glycolysis in human brain: regional, developmental, and cognitive-load dependence", "provider": "other", "raw_fields": { "title": "Aerobic glycolysis in human brain: regional, developmental, and cognitive-load dependence", "papers": [ { "doi": "10.1073/pnas.1010459107", "assay": "Human PET (CBF, CMRO2, CMRglu) in young adults", "value": "Regional aerobic glycolysis is non-uniform and spatially parallels the Aβ deposition pattern seen in Alzheimer's disease", "metric": "Regional distribution of aerobic glycolysis in adult human brain by PET (CMRglc, CMRO2, CBF) versus pattern of Aβ deposition in AD", "effect_size": "Regional aerobic glycolysis spatially correlates with Aβ deposition pattern seen in AD (n=33 young adults)", "intervention": "None — resting regional mapping", "effect_direction": "Aerobic glycolysis enriched in PFC, parietal, precuneus", "first_author_year": "Vaishnavi et al. 2010", "baseline_or_control": "Global mean", "value_source_sentence": "As an initial step in redressing this neglect, we measured the regional distribution of aerobic glycolysis with positron emission tomography in 33 neurologically normal young adults at rest." }, { "doi": "10.1016/j.cmet.2013.11.020", "assay": "Human PET cross-sectional ages 0–95 (n=94)", "value": "Aerobic glycolysis declines dramatically during development and its regional distribution is associated with the transcriptional signature of synapse formation and growth", "metric": "Age-dependent change of brain aerobic glycolysis across ages 0–95 by PET (CMRglc/CMRO2 mismatch) and association with synapse-formation transcriptional signature", "effect_size": "AG ~30% of glucose uptake in early childhood; regions retaining high AG overlap with transcriptional youth and synaptic plasticity markers", "intervention": "None — age stratification", "effect_direction": "Aerobic glycolysis peaks in early childhood, remains high in plasticity-linked regions in adulthood, declines with age", "first_author_year": "Goyal et al. 2014", "baseline_or_control": "Young adult baseline", "value_source_sentence": "We refer to this total excess brain glucose consumption as ‘aerobic glycolysis’ (AG) based on a similar, well-described phenomenon found in cancer cells ( Lunt and Vander Heiden, 2011 ; Vaishnavi et al., 2010 )." }, { "doi": "10.1073/pnas.2212004119", "assay": "Rat CA1 slice patch-clamp LTP + behavioral load manipulation", "value": "Astrocytic lactate is mandatory for demanding neural computation; glucose is sufficient for lighter forms of activity-dependent LTP", "metric": "Dependence of CA1 long-term synaptic plasticity and recognition memory on astrocytic lactate vs glucose across increasing computational/cognitive load", "effect_size": "Lactate requirement scales with cognitive/synaptic load", "intervention": "DAB (glycogenolysis) and αCHC (MCT block) under different LTP protocols", "effect_direction": "High-load LTP requires astrocytic lactate; low-load LTP does not", "first_author_year": "Dembitskaya et al. 2022", "baseline_or_control": "Low-load LTP", "value_source_sentence": "To this end, using brain slice and in vivo electrophysiology, two-photon imaging, mathematical modeling, and recognition memory tasks, we show that astrocytic lactate is mandatory for demanding neural computation, while glucose is sufficient for lighter forms of activity-dependent long-term potentiation (LTP) and that subtle variations of action potential amount or frequency are sufficient to direct the energetic dependency from glucose to lactate." } ], "description": "Aerobic glycolysis (CMRglu exceeding CMRO2/6) varies by region, age, and cognitive demand — linking astrocytic/neuronal metabolic coupling to plasticity." }, "section_id": "section_06_evidence_package", "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewAstrocytes/blob/1a55da0634a3bc04e5688792ed12141ce271d28e/evidence/section_06_evidence_package.json", "target_ref": "wiki_page:computationalreviewastrocytes-06", "review_repo": "ComputationalReviewAstrocytes", "section_ref": "wiki_page:computationalreviewastrocytes-06", "source_path": "evidence/section_06_evidence_package.json", "source_refs": [ "paper:paper-36666c0f41b9", "paper:paper-cd0fabafa821", "paper:paper-cdd6bd06868f" ], "section_title": "Metabolic Coupling and the Energy Substrate of Computation", "source_policy": { "mode": "public_source_pointer_with_short_context", "notes": [ "Local review repositories are read-only inputs.", "SciDEX stores paper metadata, structured evidence, file pointers, and short citation contexts; it does not copy full review prose." ], "source_commit_sha": "1a55da0634a3bc04e5688792ed12141ce271d28e", "source_repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewAstrocytes" }, "generation_status": "complete", "review_bundle_ref": "analysis_bundle:ab-029ee9411fe2", "origin_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewAstrocytes/blob/1a55da0634a3bc04e5688792ed12141ce271d28e/evidence/section_06_evidence_package.json", "commit_sha": "1a55da0634a3bc04e5688792ed12141ce271d28e", "created_by": "persona-jerome-lecoq-gbo-neuroscience", "repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewAstrocytes" }