The A-Z of The Spike

A reading guide

I founded The Spike in 2016 to bring the triumphs and challenges of modern systems neuroscience to a broad audience. Our readers represent a diverse swathe of the scientifically-curious public. We also draw our readers from many fields with an interest in the deep secrets of the brain, from clinicians and neurologists, scientists of all stripes, and researchers in data science, machine learning, and artificial intelligence.

Reflecting that diverse audience, our essays have covered everything from a primer on dopamine, to the limits of what we can learn from neuroscience experiments. There are rich pickings here for anyone curious about the brain: students looking to understand the cutting edge of neuroscience, to those looking for inspiration for the next generation of AI, to researchers at the forefront of neuroscience looking to see how their work fits into a wider context.

To help you find your way, here is an A to Z guide to the topics, themes, and subjects we’ve published on in The Spike. (We’ll update this page with every new piece, so check back here!) If nothing else, in compiling this list I learnt a few lessons: how little I write about stuff I work on directly in my day-to-day; that we’ve covered a lot about some things (e.g. cortex) and strangely little of others (e.g. learning); and that Frozen was playing so often in our house at one point that it seeped into everything (see entry: Frozen (Disney)).

(And if you like this, then you’ll like my new book, “The Spike: An Epic Journey Through the Brain in 2.1 Seconds” published by Princeton University Press. Available now in paperback, hardback, ebook, and audiobook — listen to a sample).

All pieces are authored by Mark Humphries, unless explicitly noted

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(Reviews of the year in neuroscience)

• 2023: A Review of the Year in Neuroscience
• 2022: A Review of the Year in Neuroscience
• 2021: the review of the year in neuroscience
• 2020: A Moderately Bemused Review of the Year in Neuroscience
• 2019: a lightly bamboozled review of the year in neuroscience
• 2018: a mildly muddled review of the year in neuroscience
• 2017: a moderately baffled review of the year in neuroscience
• 2016, a slightly perplexed review of neuroscience

A

Academia

• Why Scientists Feel Dumb
• Chasing the research dragon
• Who will use the open data?
• How not to choose which science is worth funding
• How to be a more productive scientist
• What real academics do in their unreal world
• The research funding singularity
• How a happy moment for neuroscience is a sad moment for science

Active inference

• Empirical Enactivism: How our brains simulate the world in order to experiment on the future (by Jeremy Gordon)

Alexander von Humboldt

• The three most powerful words in science

Algorithms

• How To Find Out If Your Brain Is a Computer

Alzheimer’s disease

• 2016, a slightly perplexed review of neuroscience (section “1: We could treat Alzheimer’s by looking at a broken television?”)

Analog computers

• Brains as Analog Computers (by Corey J Maley)

Aplysia

• Unraveling the hidden systems of the brain

Artificial intelligence

• Handing Science Over to the Machines
• AI Psychosis
• Your Cortex Contains 17 Billion Computers

Attractors

• Unraveling the hidden systems of the brain
• Heading in the right direction: the brain’s internal compass

Axons

• Mindlessly mapping the brain

B

Basal ganglia

• The unreasonable effectiveness of deep brain stimulation

Bayesian brains

• Empirical Enactivism: How our brains simulate the world in order to experiment on the future (by Jeremy Gordon)
• Why does the brain have a reward prediction error?

Behaviour (brain and)

• When To Flee
• Is neuroscience doomed to go round in circles?
• Hail Hydra! Doing neuroscience without a brain

Ben Barres

• Ben Barres tells his story in his own words (by Ashley Juavinett)

Bird song

• Your brain is smarter than you: how it tells you when you made a mistake

Blue Brain Project

• Blueprint for a billion euros: the “Brain-on-a-Chip” Project
• How to spend a billion euros on the brain

C

C Elegans

• Maps of a Growing Brain Show That Genes Do Less Than We Thought
• 2019: a lightly bamboozled review of the year in neuroscience
• Mindlessly mapping the brain
• 2017: a moderately baffled review of the year in neuroscience (section “Sleep little worm, don’t you cry”
• Neurons: pretending to be important since 1888

Calcium imaging

• Now We Can Record One Million Neurons At The Same Time
• What Should Systems Neuroscience Do Next? Voltage Imaging

Causality

• When Cortex Stops Making Sense
• Some limits on interpreting causality in neuroscience experiments
• Watching a paradigm shift unfold: how the brain makes decisions
• When the chips are down, should I ask a neuroscientist?

Coding (computers)

• There is no such thing as a computational person (by Ashley Juavinett)

Cognitive disorders

• AI Psychosis
• 2017: a moderately baffled review of the year in neuroscience (section “Would you like to hear voices?”)

Complexity

• Occam’s dice (by Kelly Clancy)

Computers (brains as)
(Listed in order of publication)

1. How To Find Out If Your Brain Is a Computer
2. Yes, the brain is a computer… (by Blake Richards)
3. Brains as Analog Computers (by Corey J Maley)

Computational neuroscience

• The Core Computational Principles of a Neuron (by Viacheslav Osaulenko)
• Why Model The Brain? (An actual scientific case for brain simulation)

Connectomics

• Maps of a Growing Brain Show That Genes Do Less Than We Thought
• 2019: a lightly bamboozled review of the year in neuroscience
• What Should Systems Neuroscience Do Next? Voltage Imaging
• Mindlessly mapping the brain

Cortex

• When Cortex Stops Making Sense
• Your Cortex Contains 17 Billion Computers
• Evolution doesn’t give a damn what you think a brain region is called
• Watching a paradigm shift unfold: how the brain makes decisions
• Neurons: pretending to be important since 1888
• How to spend a billion euros on the brain

D

Dark neurons

• The dark neuron problem

Data science

• A neural data science: how and why
• Who will use the open data?
• Brain data needs data brains

David Marr

• David Marr: neuroscience’s Einstein

Decision making

• We Don’t Know How You Make a Decision
• The pitfalls of persistence (by Raeesa Gupta)
• Watching a paradigm shift unfold: how the brain makes decisions

Deep brain stimulation

• The unreasonable effectiveness of deep brain stimulation

Dendrites

• Your Cortex Contains 17 Billion Computers
• Mindlessly mapping the brain

Depression

• A New Prime Suspect For Depression

Dimension reduction

• Warning! Unsupervised Neuroscience Ahead
• Unraveling the hidden systems of the brain
• Some limits on interpreting causality in neuroscience experiments

Dopamine

• 2023: A Review of the Year in Neuroscience (section “ErrorErrorError”)
• The crimes against dopamine
• Your brain is smarter than you: how it tells you when you made a mistake
• A solution to the paradox of Parkinson’s disease
• How hard should I work? Ask dopamine

Drosophila

• 2023: A Review of the Year in Neuroscience (section “Unexpected papers in the bagging area”)
• Mindlessly mapping the brain
• Heading in the right direction: the brain’s internal compass

E

Enactivism

• Empirical Enactivism: How our brains simulate the world in order to experiment on the future (by Jeremy Gordon)

Ensembles (neural)

• Neurons: pretending to be important since 1888

Epilepsy

• Thoughts on a medical mystery (by Kelly Clancy)

Evolution

• Occam’s dice (by Kelly Clancy)
• Evolution doesn’t give a damn what you think a brain region is called
• 2017: a moderately baffled review of the year in neuroscience (section “Turning one nervous system into another”)

F

False memory

• The fallacy of memory (by Raeesa Gupta)

Fear

• When To Flee

fMRI

• 2021: the review of the year in neuroscience
• Why I Wrote a Book About Spikes
• Now We Can Record One Million Neurons At The Same Time
• Seventy Teams of Scientists Analysed the Same Brain Data, and It Went Badly

Frozen (Disney)

• Your brain is smarter than you: how it tells you when you made a mistake
• How to be a more productive scientist

G

Glia

• A New Prime Suspect For Depression
• Ben Barres tells his story in his own words (by Ashley Juavinett)

Graduate school (in neuroscience) — see “PhD Advice”

H

Head direction

• Heading in the right direction: the brain’s internal compass

Hearing

• The sound of memory

Hierarchical processing

• An illustrated overview of how our brains (might) think — the fascinating intuition of the generative predictive model (by Jeremy Gordon)

Hippocampus

• The sound of memory
• Wired for memory: how your brain remembers by completing patterns
• Neurons: pretending to be important since 1888

Human Brain Project

• Blueprint for a billion euros: the “Brain-on-a-Chip” Project
• How to spend a billion euros on the brain

Humour (attempts at)

• Now We Can Record One Millions Neurons at the Same Time
• The Neuroscientist, A Field Guide
• A not entirely serious future history of neuroscience
• How to be a more productive scientist
• Most research I publish will be wrong. And I’m OK with that

Hydra

• Hail Hydra! Doing neuroscience without a brain

I

Imposter Syndrome

• Why Scientists Feel Dumb

Intel processors

• When the chips are down, should I ask a neuroscientist?

Intelligence

• 2019: a lightly bamboozled review of the year in neuroscience

J

Journals

• Selective Journals Are The A&R of Science
• 2016, a slightly perplexed review of neuroscience (section “2: The slow, agonising collapse of Frontiers’ reputation”)

K

Ketamine

• A New Prime Suspect For Depression

L

Lateral habenula

• A New Prime Suspect For Depression

Learning

• When Cortex Stops Making Sense
• 2018: a mildly muddled review of the year in neuroscience (section “2/ Who watches the watch-people?”)

Lifespan (human maximum)

• 2016, a slightly perplexed review of neuroscience (section “4: Nature reaches a nadir”

M

Machine learning

• Warning! Unsupervised Neuroscience Ahead
• A neural data science: how and why
• Why does the brain have a reward prediction error?

Memory

• 2018: a mildly muddled review of the year in neuroscience (section “Misplaced Childhood” on recovering lost memories)
• The fallacy of memory (by Raeesa Gupta)
• The sound of memory
• Wired for memory: how your brain remembers by completing patterns

N

Navigation

• Heading in the right direction: the brain’s internal compass

Network theory

• Friends, Brains and Crickets: a (Scientific) Love Story
• Wired for memory: how your brain remembers by completing patterns

Neural coding

• A neural data science: how and why
• The Loneliest Neuron
• Unraveling the hidden systems of the brain
• Neurons: pretending to be important since 1888

Neural networks

• Your Cortex Contains 17 Billion Computers

Neuromorphic chips

• Blueprint for a billion euros: the “Brain-on-a-Chip” Project

Neuroplasticity (brain adaptations to injury & disorders)

• Thoughts on a medical mystery (by Kelly Clancy)

O

Occam’s razor

• Occam’s dice (by Kelly Clancy)

Open science

• Selective Journals Are The A&R of Science
• Who will use the open data?
• How a happy moment for neuroscience is a sad moment for science
• Brain data needs data brains

Optogenetics

• When Cortex Stops Making Sense
• When To Flee
• Some limits on interpreting causality in neuroscience experiments

P

Pattern completion

• Wired for memory: how your brain remembers by completing patterns

Parkinson’s disease

• The unreasonable effectiveness of deep brain stimulation
• A solution to the paradox of Parkinson’s disease

Periaqueductal gray

• When To Flee

PhD advice

• Choosing a neuroscience graduate program (by Ashely Juavinett)
• There is no such thing as a computational person (by Ashley Juavinett)
• Preparing for a neuroscience PhD (by Ashley Juavinett)
• Why you should (or shouldn’t) get a PhD in Neuroscience (by Ashley Juavinett)

Prediction error

• Why does the brain have a reward prediction error?
• The crimes against dopamine
• Your brain is smarter than you: how it tells you when you made a mistake

Predictive processing

• An illustrated overview of how our brains (might) think — the fascinating intuition of the generative predictive model (by Jeremy Gordon)

Publishing (scientific)

• Selective Journals Are The A&R of Science
• Handing Science Over to the Machines

Q

R

Reproducibility crisis (aka replication crisis)

• Seventy Teams of Scientists Analysed the Same Brain Data, and It Went Badly
• Handing Science Over to the Machines
• Most research I publish will be wrong. And I’m OK with that

RNA transmission

• 2018: a mildly muddled review of the year in neuroscience (section Neurons “transmit” RNA)

S

Science controversies

• On “The Lie” of Basic Science
• How not to choose which science is worth funding
• The three most powerful words in science
• Blueprint for a billion euros: the “Brain-on-a-Chip” Project

Simulation (in the mind)

• Empirical Enactivism: How our brains simulate the world in order to experiment on the future (by Jeremy Gordon)

Sleep

• 2017: a moderately baffled review of the year in neuroscience (section “Sleep little worm, don’t you cry”)

Small world

• Friends, Brains and Crickets: a (Scientific) Love Story

Spikes

• The Spike: An Epic Journey Through the Brain in 2.1 Seconds
• A neural data science: how and why
• Some limits on interpreting causality in neuroscience experiments
• An illustrated overview of how our brains (might) think — the fascinating intuition of the generative predictive model (by Jeremy Gordon)
• The dark neuron problem

Superior colliculus

• When To Flee

Synaptic failure

• When To Flee

Systems neuroscience

• Now We Can Record One Million Neurons At The Same Time
• The Spike: An Epic Journey Through the Brain in 2.1 Seconds
• What Should Systems Neuroscience Do Next? Voltage Imaging
• A neural data science: how and why
• A not entirely serious future history of neuroscience
• The Loneliest Neuron
• Some limits on interpreting causality in neuroscience experiments
• Is neuroscience doomed to go round in circles?
• The dark neuron problem
• When the chips are down, should I ask a neuroscientist?

T

Theory of Mind

• 2018: a mildly muddled review of the year in neuroscience (section “Who watches the watch people?”)

Theories (in neuroscience)

• Why Model The Brain? (An actual scientific case for brain simulation)
• Why does the brain have a reward prediction error?
• Heading in the right direction: the brain’s internal compass
• Is neuroscience doomed to go round in circles?
• Hail Hydra! Doing neuroscience without a brain
• The crimes against dopamine
• Watching a paradigm shift unfold: how the brain makes decisions
• David Marr: neuroscience’s Einstein
• Most research I publish will be wrong. And I’m OK with that

U

Unsupervised learning

• Warning! Unsupervised Neuroscience Ahead

V

Voltage imaging

• What Should Systems Neuroscience Do Next? Voltage Imaging
• Mindlessly mapping the brain
• Unraveling the hidden systems of the brain

W

Whiskers

• When Cortex Stops Making Sense

Work

• How hard should I work? Ask dopamine

Writing

• It’s A Good Thing When I Don’t Know What I’m Writing About
• Four Books That Profoundly Influenced Me, Despite Not Having Read Them

X

Y

Ynigwie Malmsteen

• The dark neuron problem

Z

Want more? Follow us at The Spike

Twitter: @markdhumphries