You already sat through the slide with dendrites, soma, axon, and terminal buttons. This reading isn't going to redraw that diagram for you. What it will do is connect the dots your slides leave implicit: why the wiring is built the way it is, where students usually get confused, and what it means when a headline says a brain scan "found" the seat of love, addiction, or free will.
One neuron, one decision
Picture the neuron the way your slide laid it out: dendrites gather input, the soma (cell body) integrates it, the axon carries the outgoing signal, and the terminal buttons pass it along. What the slide's static image can't show you is that this is a live decision process happening constantly, all over your nervous system, in parallel, thousands of times a second.
Here's the part worth sitting with. The action potential — the electrical signal that travels down the axon — is all-or-none. A neuron doesn't fire "a little bit" in response to a weak stimulus and "a lot" in response to a strong one. Either the input reaching the soma crosses threshold and the neuron fires a full-strength spike, or it doesn't fire at all. There's no dial, only a switch. What varies with stimulus intensity isn't the size of any single spike — it's the rate of firing and how many neurons join in. A bright light doesn't give you a bigger action potential than a dim one; it gives you more of them, faster, across more cells.
Myelin — the fatty sheath wrapped around many axons — is what makes this fast enough to be useful. It insulates the axon and lets the signal jump between the gaps (nodes of Ranvier) instead of crawling down every inch of membrane. This is also not fixed at birth: myelination is experience-dependent, meaning the sheathing around circuits you actually use gets reinforced over time. Skill practice, in a very literal sense, is partly an insulation project.
Electrical within, chemical between
This is the distinction students blur most on exams, so it's worth making explicit and keeping separate in your head.
Within a neuron
Signaling is electrical. The action potential is a wave of voltage change that travels down the axon, from soma to terminal buttons. One neuron, one continuous electrical event.
Between neurons
Signaling is chemical. When the electrical signal reaches the terminal buttons, it triggers the release of neurotransmitters into the synapse — the tiny gap between neurons. Those chemicals cross the gap, bind to receptors on the next neuron, and either excite or inhibit it. Afterward, leftover neurotransmitter is cleared out largely through reuptake, where the sending neuron reabsorbs it for reuse.
Why it matters: this chemical step — release, binding, reuptake — is exactly where psychoactive drugs do their work. An agonist mimics or boosts a neurotransmitter's effect at the receptor; an antagonist blocks it. A drug that slows reuptake leaves more neurotransmitter sitting in the synapse longer, amplifying its effect. None of this touches the electrical action potential directly — it all happens at the chemical handoff between cells. That's also why so much of pharmacology, and so much of clinical psychology's biological toolkit, is really synapse-level engineering.
The major neurotransmitters, briefly
Your slide likely listed these. Here's what each one is mainly doing, in a sentence apiece, so the names stop being interchangeable jargon:
Dopamine — reward, motivation, and movement. Serotonin — mood, sleep, and appetite regulation. GABA — the brain's main inhibitory neurotransmitter, calming activity down. Glutamate — the main excitatory neurotransmitter, the accelerator to GABA's brake. Acetylcholine — muscle movement and memory formation. Norepinephrine — arousal and alertness. Endorphins — the body's own pain relief and pleasure signaling.
◆ Update: the "chemical imbalance" story is oversimplified
You've probably heard depression explained as "a chemical imbalance — too little serotonin." That framing is a slogan, not a settled finding. A large umbrella review of the evidence found that the data do not support the simple claim that low serotonin causes depression (Moncrieff et al., 2023). Neurotransmitters clearly matter to mood — that's not in dispute — but the tidy, single-cause story oversells a mechanism science hasn't actually nailed down. This is a good example of how a metaphor that's easy to put on a pamphlet can outrun the evidence behind it.
Zooming out: how the brain is organized
Your slides walked bottom-to-top through brain structure, and that ordering isn't arbitrary — it roughly tracks evolutionary age and how automatic versus deliberate the functions are.
At the base, the brainstem and hindbrain handle the functions you don't have to think about and can't easily override: heartbeat, breathing, arousal, basic survival. Above that sits the limbic system, where the amygdala handles threat detection and emotional reactivity and the hippocampus handles forming new memories. On top of all of it is the cerebral cortex, wrapped in its four lobes: the frontal lobe for control, planning, and decision-making; the parietal lobe for touch and spatial processing; the temporal lobe for hearing and language; and the occipital lobe for vision.
This layered structure isn't fixed hardware, either. The brain shows neuroplasticity — it rewires itself with use, strengthening the connections you exercise and pruning the ones you don't. Myelination getting reinforced with practice, mentioned earlier, is one expression of this same broader principle: the brain you have today is shaped by what you've actually been doing with it.
The myth
We only use 10% of our brain — the rest is untapped potential just waiting to be unlocked.
What's actually true
Virtually all of the brain is active over the course of a day. Brain imaging doesn't show 90% of the brain sitting dark. What's true is that not every region is maximally active at the exact same moment — different tasks recruit different networks. "Not all at once" got flattened into "only 10% at all," and the flattened version stuck around because it's a great movie premise.
Watching the brain work: methods and their tradeoffs
Your slides likely named several imaging and manipulation techniques. Each one buys you something and costs you something else — mainly a tradeoff between when something happened and where.
Step 1 · EEG
Electrodes on the scalp track electrical activity in real time. Excellent temporal resolution — it can catch changes millisecond to millisecond — but poor spatial resolution. It tells you something happened right now; it's much vaguer about exactly where.
Step 2 · CT and MRI
These image brain structure — the physical anatomy — rather than ongoing activity. Useful for spotting damage, tumors, or structural differences, but they're a snapshot of the hardware, not a recording of the brain in action.
Step 3 · PET and fMRI
These aim to capture brain activity. fMRI in particular offers good spatial resolution — it can localize activity fairly precisely — but poor temporal resolution, and, critically, it's indirect. fMRI doesn't measure neurons firing. It measures blood oxygenation — the BOLD signal — as a proxy for neural activity, on the assumption that busier neurons draw more oxygenated blood. That's a reasonable assumption, but it's an inference, not a direct readout of the brain thinking (Logothetis, 2008).
Step 4 · TMS
Transcranial magnetic stimulation nudges neural activity in a targeted region up or down. Because it manipulates rather than just observes, it's one of the few tools that lets researchers move toward causal claims — if disrupting a region disrupts a function, that's stronger evidence than just watching the region light up during that function.
◆ The caveat that matters most
Most neuroimaging is correlational, not causal. A region "lighting up" on a scan during a task tells you that region was more active during that task — it does not make that region "the center for" love, honesty, or anything else, however catchy that headline sounds. Poldrack (2018) makes the case at length: neuroimaging can tell us a great deal, but reverse-inferring a specific mental state from a pattern of activation is far shakier than popular coverage implies.
The point gets made vividly — and a little absurdly — by the famous dead-salmon study. Researchers ran a dead Atlantic salmon through an fMRI task and, without correcting for the huge number of statistical comparisons involved in whole-brain imaging, found "significant" activation. The salmon was dead. The result was noise, not neural life (Bennett et al., 2010). It's a demonstration of why multiple-comparisons correction isn't optional bookkeeping — skip it, and you can find a "significant" brain response in a fish that isn't thinking about anything.
Bodhi says
When you read "a study found brain region X controls Y," pause and ask two questions: was this correlational (a scan during a task) or causal (a lesion, TMS, or intervention study)? And was it corrected for multiple comparisons? Those two questions alone will make you a more careful consumer of neuroscience headlines than most people writing them.
The one thing to carry out of this unit
Signaling within a neuron is electrical and all-or-none; signaling between neurons is chemical, and that chemical handoff is where drugs, disorders, and treatments mostly do their work. Zoom out and the brain's organization — brainstem, limbic system, cortex — tracks a rough gradient from automatic to deliberate. But however precise a scan looks, remember what it's actually measuring: mostly an indirect, correlational snapshot of activity, not a direct window into meaning. A lit-up region is a clue, not a verdict.
References
Bear, M. F., Connors, B. W., & Paradiso, M. A. (2020). Neuroscience: Exploring the brain (4th ed.). Jones & Bartlett.
Bennett, C. M., Baird, A. A., Miller, M. B., & Wolford, G. L. (2010). Neural correlates of interspecies perspective taking in the post-mortem Atlantic salmon: An argument for proper multiple comparisons correction. Journal of Serendipitous and Unexpected Results, 1(1), 1–5.
Logothetis, N. K. (2008). What we can do and what we cannot do with fMRI. Nature, 453(7197), 869–878.
Moncrieff, J., Cooper, R. E., Stockmann, T., Amendola, S., Hengartner, M. P., & Horowitz, M. A. (2023). The serotonin theory of depression: A systematic umbrella review of the evidence. Molecular Psychiatry, 28(8), 3243–3256.
Poldrack, R. A. (2018). The new mind readers: What neuroimaging can and cannot reveal about our thoughts. Princeton University Press.