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The Energy balance between Glycolysis and OxPhos in Neurons

I think it is useful to try to identify:
a) The most heavily energy using neurons
b) The balance in those cells between OxPhos (which produces Reactive Oxygen Species - ROS) and Glycolysis

I will be using various LLMs to search for information relating to this and will be spending time checking the responses for hallucinations, but I may not at the time of you reading this page finished validating everything. I will also be concentrating on validating the analysis for dopaminergic and motor neurons because those are the neurons which cause PD and ALS/MND.

In principle the rank is not really valid. Although this table is produced using a ranking that is not going to be reliable, it is still useful. What I am trying to get from this is to identify the cells which would be vulnerable to rapid deterioration through ROS. The first step is those with a high energy usage. This, however, I would expect to vary from time to time and any actual accurate calculation for one human being would be likely to vary. Hence I am not really bothered about the sequence merely trying to select some particular neurons (high energy requirements) for further review.

Obviously this also highlights neurons that may be the cause of other neurodegenerative diseases caused by mitochondrial dysfunction as well as ALS/MND and PD.

This table looks for the 10 heaviest ATP using Neurons (original search source chatGPT)

Neuron type (circuit) Key reason for high ATP burn Research link(s) Notes
1 Cone photoreceptor (retina) Continuous dark/light “leak” currents keep Na+/K+‑ATPase & Ca2+ pumps running at full tilt Beyond Genetics: The Role of Metabolism in Photoreceptor Survival, Development and Repair Per‑cell ATP usage is the highest measured in the nervous system.
2 Fast‑spiking parvalbumin interneuron (cortex/hippocampus) 200–600 Hz firing and enormous axonal arbor → dense mitochondrial load Native-state proteomics of Parvalbumin interneurons identifies unique molecular signatures and vulnerabilities to early Alzheimer’s pathology Cytochrome‑c oxidase enrichment marks extreme OxPhos reliance.
3 Cerebellar Purkinje cell Intrinsic 30–100 Hz spiking plus energy‑intense complex spikes; huge dendritic tree Updated Energy Budgets for Neural Computation in the Neocortex and Cerebellum Estimated to consume 62 × the energy of a granule cell.
4 Dopaminergic neuron (SNc) Autonomous Ca2+‑dependent pacemaking & 1 M+ striatal synapses Increased vulnerability of nigral dopamine neurons after expansion of their axonal arborization size through D2 dopamine receptor conditional knockout High OxPhos rate explains selective mitochondrial vulnerability in PD.
5 Betz cell (layer V corticospinal) Giant soma and meter‑long axon → vast surface‑area pump burden Betz cells of the primary motor cortex Transcriptome enriched for oxidative‑phosphorylation genes.
6 Spinal α‑motor neuron Thick, fast‑conducting axons projecting to distal muscle; constant synaptic drive Motor neuron mitochondrial dysfunction in spinal muscular atrophy Energy stress is an early factor in ALS pathophysiology.
7 Rod photoreceptor (retina) Dark‑current Na+/Ca2+ leak keeps pumps active even without light Aerobic Glycolysis Is Essential for Normal Rod Function and Controls Secondary Cone Death in Retinitis Pigmentosa Uses aerobic glycolysis but still relies heavily on OxPhos.
8 Subthalamic‑nucleus projection neuron Autonomous 25–45 Hz tonic spiking plus burst modes; long unmyelinated branches High cytochrome‑oxidase expression correlates with firing rate.
9 Medium spiny neuron (striatum) ~10 000 cortical inputs & dense spine upkeep drive high Na+/K+ pump load The Striatum Is Highly Susceptible to Mitochondrial Oxidative Phosphorylation Dysfunctions Mitochondrial dysfunction central to Huntington’s vulnerability.
10 CA3 pyramidal neuron (hippocampus) Recurrent collateral bursts & sharp‑wave ripple generation elevate O2 use Oxygen consumption rates during three different neuronal activity states in the hippocampal CA3 network Oxygen‑consumption study shows 2–5 × rise during gamma oscillations.

Where does this get to

If we combine the first table with the following two tables it is clear that some high energy cells are very dependent on OxPhos (eg Motor Neurons and Dopaminergic cells) others such as the retinal cells (cones and Rods) use a lot of energy, but not all from glycolysis. Hence there is a useful conclusion as to the types of cells that are vulnerable to rapid deterioration from oxidative stress in the mitochondria damaging mitochondrial DNA.

These two tables use the previous list and tries to identify the balance of usage of energy between OxPhos and Glycolysis

Approximate contribution of oxidative phosphorylation (OXPHOS) and glycolysis to ATP production in selected neuron classes
# Neuron type
(species / preparation)
% ATP from
OXPHOS
% ATP from
glycolysis
Key method Primary research link
1 Cortical pyramidal neurons (mouse primary culture) ≈ 85 % ≈ 15 % Seahorse XF “Real‑Time ATP‑Rate” assay ± veratridine Desousa et al., 2023
2 Parvalbumin‑positive fast‑spiking interneurons (rodent cortex/slice) ≥ 90 % ≤ 10 % Cytochrome‑c‑oxidase histochemistry & ultrastructure Kann et al., 2016
3 Substantia nigra pars compacta dopaminergic neurons (mouse) ≈ 80 % ≈ 20 % High OCR / complex‑I sensitivity in vivo & culture González‑Rodríguez et al., 2021
4 Cerebellar Purkinje cells (adult mouse, in vivo) ≈ 40 % ≈ 60 % FDG‑PET, metabolomics & Seahorse (ATG5 cKO) Tutas et al., 2025
5 Rod photoreceptors (mouse retinal explant) ≈ 75 % ≈ 25 % ¹H‑NMR metabolomics ± ETC uncoupler Chen et al., 2024
6 Cone photoreceptors (same study) ≈ 30 % ≈ 70 % Survival under FCCP, GLUT1‑dependence Chen et al., 2024
Neuron type (circuit) OxPhos (%) Aerobic glycolysis (%) Key source(s)
1 Cone photoreceptor (retina) 10–20 80–90 Retinal metabolism displays evidence for uncoupling of glycolysis and oxidative phosphorylation via Cori-, Cahill-, and mini-Krebs-cycle
Beyond Genetics: The Role of Metabolism in Photoreceptor Survival, Development and Repair
2 Rod photoreceptor (retina) 70–80 20–30 Retinal metabolism displays evidence for uncoupling of glycolysis and oxidative phosphorylation via Cori-, Cahill-, and mini-Krebs-cycle
3 Fast‑spiking parvalbumin interneuron (cortex/hippocampus) 90–95 5–10 Native-state proteomics of Parvalbumin interneurons identifies unique molecular signatures and vulnerabilities to early Alzheimer’s pathology
4 Cerebellar Purkinje cell 85–90 10–15 Cytochrome oxidase activity is increased in +/Lc Purkinje cells destined to die
5 SNc dopaminergic neuron 90–95 5–10 Increased vulnerability of nigral dopamine neurons after expansion of their axonal arborization size through D2 dopamine receptor conditional knockout
6 Betz (giant corticospinal) cell ~90 ~10 Betz cells of the primary motor cortex
7 Spinal α‑motor neuron ≈ 88 ≈ 12 Energy metabolism in ALS: an underappreciated opportunity?
8 Subthalamic‑nucleus projection neuron ≈ 85 ≈ 15 Subthalamic nucleus deep brain stimulation alleviates oxidative stress via mitophagy in Parkinson’s disease
9 Medium spiny neuron (striatum) ≈ 85 ≈ 15 The Striatum Is Highly Susceptible to Mitochondrial Oxidative Phosphorylation Dysfunctions
10 CA3 pyramidal neuron (hippocampus) ≈ 85 ≈ 15 NADH in the pyramidal cell layer of hippocampal regions CA1 and CA3 upon selective inhibition and uncoupling of oxidative phosphorylation

Grok's response on high energy:

Top Ten Types of Neurons by Energy Usage

There isn’t enough specific data available to rank the top ten types of neurons by their energy usage with precision, as direct measurements of energy consumption across all neuron types are limited and vary by context (e.g., species, brain region, or activity state). However, below is a list of neuron types likely to rank among the highest in energy usage based on their structural and functional characteristics, such as size, firing rate, synaptic activity, and ion channel density, which are known to influence energy demands.

Factors Influencing Neuronal Energy Usage

Energy usage in neurons is primarily driven by:

  • Action potentials: Generating and propagating action potentials requires ATP to restore ion gradients via the Na+/K+ ATPase pump. Neurons with high firing rates consume more energy.
  • Synaptic activity: Synaptic transmission, especially at presynaptic terminals and postsynaptic spines, is a major energy sink due to vesicle recycling, neurotransmitter release, and postsynaptic ion flux.
  • Morphology: Larger neurons with extensive dendritic trees or long axons require more energy for signal propagation and maintenance of membrane potentials.
  • Ion channel density: Neurons with high density of voltage-gated or leak channels (e.g., in MSO neurons) have higher energy costs due to constant ion pumping.
  • Myelination: Myelinated axons are more energy-efficient for long-distance signaling, while unmyelinated axons consume more energy per action potential.

List of Neuron Types Likely to Have High Energy Usage

The following list includes neuron types with characteristics like high firing rates, large size, extensive synaptic connections, or specialized functions that suggest elevated energy demands. Since exact energy measurements are unavailable for most, this is an informed ranking based on available evidence and logical inference.

  1. Purkinje Cells (Cerebellum)

    Why High Energy? Purkinje cells have large, fan-shaped dendritic trees with over 1,000 dendritic branches, receiving tens of thousands of synaptic inputs. Their high synaptic density and rapid firing rates (up to 50–100 Hz in some contexts) make them energy-intensive, as synaptic transmission accounts for a significant portion of brain energy use (up to 47% for action potentials and 34% for postsynaptic currents in some estimates).

    Location/Function: Located in the cerebellar cortex, they modulate motor output via sparse distributed coding, which is energy-demanding due to the high number of inputs processed.

  2. Medial Superior Olive (MSO) Neurons (Auditory Brainstem)

    Why High Energy? MSO neurons are specialized for detecting interaural time differences (ITDs) for sound localization, requiring very fast membrane time constants (<1 ms) and high input rates (hundreds of spikes/s). Their leaky membranes and high-density potassium channels (e.g., IKLT) increase energy costs, as evidenced by high glucose utilization in auditory brainstem regions.

    Location/Function: Found in the brainstem, they process precise auditory timing cues, demanding significant energy for rapid signal integration.

  3. Pyramidal Neurons (Cerebral Cortex, Layers III and V)

    Why High Energy? Pyramidal neurons, especially giant pyramidal cells (Betz cells) in the motor cortex, have large cell bodies, long axons (e.g., in the corticospinal tract), and extensive dendritic trees. Their high synaptic connectivity and role in voluntary movement control suggest substantial energy use, particularly for maintaining resting potentials and propagating signals over long distances.

    Location/Function: Found in the cerebral cortex and subcortical structures like the hippocampus, they are key for cognitive and motor functions.

  4. Motor Neurons (Spinal Cord, Lower Motor Neurons)

    Why High Energy? Lower motor neurons have long, often myelinated axons that connect the spinal cord to muscles. Their frequent firing to control muscle activity (e.g., during walking) and the need to maintain large axonal lengths increase energy demands, despite myelination improving efficiency.

    Location/Function: Connect the CNS to skeletal and smooth muscles for movement control.

  5. Sensory Neurons (Pseudounipolar, Peripheral Nervous System)

    Why High Energy? Pseudounipolar sensory neurons, especially those innervating distant regions (e.g., the foot), have long axons that can be unmyelinated or lightly myelinated, increasing energy costs for signal propagation. Their role in transmitting sensory inputs (e.g., pain, touch) involves frequent activity, further driving energy use.

    Location/Function: Carry sensory information from the periphery to the CNS.

  6. Interneurons (Relay, Long-Axon)

    Why High Energy? Relay interneurons have long axons connecting different brain regions, requiring energy to propagate signals over distance. Their role in coordinating complex networks, especially in the cortex, involves high synaptic activity, which is energy-intensive.

    Location/Function: Found throughout the brain, they connect sensory and motor neurons or different brain regions.

  7. Granule Cells (Cerebellum)

    Why High Energy? Granule cells are small but numerous, contributing to sparse distributed coding in the cerebellum. Their high numbers and role in processing sensorimotor inputs via many synaptic connections suggest significant collective energy use, even if individual cells are less demanding.

    Location/Function: Located in the cerebellar granular layer, they process afferent sensorimotor data.

  8. Stellate Cells (Cerebral Cortex, Layer IV)

    Why High Energy? Stellate cells are multipolar neurons with short, radiating dendrites that receive high-fidelity thalamic inputs. Their role in rapidly relaying sensory information to other cortical areas involves frequent synaptic activity, increasing energy demands.

    Location/Function: Found in the cerebral and cerebellar cortex, they process sensory inputs from the thalamus.

  9. Magnocellular Neurons (Supraoptic Nucleus)

    Why High Energy? These neurons have fewer dendrites (one or two) but receive thousands of synaptic inputs each, driving high energy use for synaptic processing. Their role in neuroendocrine functions, like hormone release, involves sustained activity.

    Location/Function: Located in the hypothalamus, they regulate physiological processes like water balance.

  10. Basket Cells (Cerebral Cortex, Inhibitory Interneurons)

    Why High Energy? Basket cells are GABAergic interneurons that target the cell bodies of other neurons, requiring rapid firing to modulate cortical activity. Their high firing rates and synaptic output contribute to significant energy consumption, particularly in active cortical circuits.

    Location/Function: Found in the cortex, they provide inhibitory control over pyramidal neurons.

Notes and Limitations

  • Lack of Direct Data: Exact energy usage (e.g., ATP consumption per second) isn’t well-documented for most neuron types due to the complexity of measuring energy at the cellular level in vivo. Estimates often rely on computational models or indirect measures like glucose utilization.
  • Context-Dependent Usage: Energy consumption varies with activity state (resting vs. active). For example, synaptic vesicles consume significant energy even at rest due to proton leakage, which may disproportionately affect neurons with high synaptic density (e.g., Purkinje cells).
  • Ranking Approximation: This list prioritizes neurons with high synaptic activity, large size, or fast firing rates, as these are known to drive energy use. However, without precise measurements, the order is speculative and based on relative comparisons.
  • Myelination Impact: Myelinated neurons (e.g., motor neurons) are more energy-efficient than unmyelinated ones for long-distance signaling, which may lower their relative energy use compared to unmyelinated sensory neurons.

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