Sleeping on the Wing

There is an old Monty Python skit where John Cleese and Graham Chapman play airplane pilots. Presumably on a long, tedious flight, they are clearly bored and keen on amusing themselves at the expense of their passengers.

They find entertainment through relaying worrisome, nonsensical messages. Cleese begins their prank with the truism, “Hello, this is your captain speaking. There is absolutely no cause for alarm.” And after some internal discussion about what there should be no cause for alarm about, they add: “The wings are not on fire.” The messages get more ridiculous, and hilarity (at least for the pilots) ensues.

Activity Recall in a Visual Cortical Ensemble

Associational memory, as its name implies, is a type of memory that allows one to fuse multiple events in memory. If your boss constantly yells at you in his office, you might begin to form some bad memories of being in that office. While the phenomenon of associative memory is a familiar experience, the neural basis for it isn’t well understood. A prominent theory, which was formed in the mid-20th century but only tested recently is that neurons encode associations by wiring together. In the boss’s office example, the sight of the boss’s office might activate one subset of neurons, and those neurons would then “fill in” activation of neurons that code for fear or memories of yelling (obviously this is a gross oversimplification - I’m only using it to demonstrate the principle).

Coordination Between Motor and Sensory Systems

One interesting problem in systems neuroscience is how the nervous system’s motor output interacts with its sensory systems. Sensory inputs that result from motor commands must be either filtered out or used to guide future motor actions. In other words, the organism must distinguish between sensory inputs that are self-generated and those from the outside world. In the juvenile songbird, for example, motor commands for song generation must be sent to some internal critic (likely basal ganglia) so the bird can compare the actual song output to some internal tutor model and improve subsequent renditions.

How does sensory experience change cortex?

The neocortex is an evolutionarily new part of the brain unique to mammals and is responsible for high level sensation, movement and cognition. It wouldn't be fair to summarize in a sentence or two what cortex "does," but it is clear that it is an important part of the brain. Korbinian Brodmann famously divided the human cortex into about 50 areas based on histology of the six cortical layers in different parts of the brain; Brodmann's areas are still used today because their functions follow their histological structure. While cortical areas have largely stereotyped wiring patterns, some connectivity “motifs” are thought to be area-specific, varying based on the type of input the area receives. It is unknown whether the type of input (i.e. statistics of incoming activity that vary with types of sensory stimuli) to a given cortical area determines the types of connectivity motifs present in that region. And while classical cortical “rewiring”experiments from Mriganka Sur’s lab have shown that primary sensory cortices are somewhat tolerant to process foreign inputs, it is not clear to what extent those circuits constitute basic computational units or if foreign inputs cause reorganization of connections within the circuit.

Connectomic Reconstruction of Direction-Selective Circuit in the Retina

Connectomics is the area of neuroscience that aims to collect and curate the entirety of the connections made by all neurons in a brain (the product being called a “connectome”). For the human brain, that would be a data set of 100 billion neurons, each of which is estimated to make 1000-10000 synapses with other neurons (on the order of 1017 connections). The roll-up-your-sleeves-this-will-get-really-messy way of collecting that kind of data is to slice the brain into nanometers-thick sections and to image each slice with an electron-microscope, which has resolution below the nanometer range, and can reveal the structure of cells on a fine scale. In the image from Kristen Harris's lab below you can see a part of a neuron’s dendrite making a synapse with an axon filled with neurotransmitter vesicles; EM images however cannot show individual proteins or molecules).

Not Another Rodent

Slate magazine had a slideshow by Daniel Engber a little more than a week ago on unusual laboratory animals and why they're important. The slideshow was prompted by Engber's observation that mice and rats make up an enormous proportion of all lab animals, perhaps limiting what we can conclude from experimental results and narrowing our perspective on what questions to ask. In short, scientists need to start thinking outside the box when it comes to model organisms. Engber lists fourteen animals, some of which have already given important clues to specific questions. I will mention some of those here. 1. The squid: the squid peaked in importance in the 1950's, when Hodgkin and Huxley got the idea to use its giant axon (up to 1mm diameter) to study properties of the action potential. The large diameter made it possible for them to insert micro-electrodes directly into the intracellular space of the axon, thereby measuring the flow of ions across the membrane during various stages of the action potential or under different extracellular ionic concentrations. This work resulted in Hodgkin and Huxley's mathematical model of AP generation, which earned them the 1963 Nobel Prize. 

The squid giant axon (not "giant squid axon") was used primarily because its large diameter made it possible for researchers to stick electrodes into the lumen. These days, better equipment and techniques allow scientists to record electrical activity of neurons with intracellular electrodes placed into cell bodies with widths in the range tens of microns in slice preparations or even awake behaving animals!

2. Xenopus laevis frogs are used for the eggs females produce, oocytes, which can be around 1mm in diameter. As with the squid giant axon, these cells were first used because their large size makes them easy to handle. 

Xenopus oocytes contain machinery for protein production, which scientists can hijack by injecting DNA or RNA coding a desired protein. Once injected with DNA or RNA, the oocyte starts making protein. Oocytes are typically used in electrophysiological experiments on the function of particular neurotransmitter- or voltage-gated ion channels, like the GABA-A receptor.

3. The zebra finch and other songbirds are great models for motor learning/planning and language acquisition. Adult male Zebra finches sing the same song - a highly structured, complex sequence of sounds that requires equally sophisticated motor control - throughout their lives (hundreds of times per day); how the brain codes for such learned sequences and maintains them for years is a question of great interest, and arguably more amenable to scientific study than motor control in primates (the typical model for such questions), whose movement repertoire is much more diverse and variable. 

Other birds don't sing the same tune every time, but instead combine syllables or motifs into songs that differ in composition each time. Canaries have a rich repertoire that may provide clues into sequence and even syntax learning. Their songs contain non-random sequences of syllables, each of which determines what syllable comes next. So any given syllable transition point  in a Canary song depends on what syllable came before. Even cooler, Bengalese finches were recently shown to be able to spontaneously discriminate among songs of variable syntactic structure, indicating that birds have not only the ability to produce songs with hierarchical syllable structure, but to perceive such structure too.

Other model organisms Engber mentions are the zebrafish, traditionally used in genetics experiments, has recently been added to the list of species with an optogenetics toolkit (others include flies, mice and primates); the sea slug Aplysia - used famously by Eric Kandel to demonstrate the concept of long term potentiation, LTP, and the molecular principles behind it; the prairie vole - first demonstration of molecular principles behind "monogamous" relationships; the fruit fly, used for everything genetic because its generations are so short, actually accounts for a small fraction of all papers published since the 1950's, according to Engber's analysis.

We do need out of the box thinking in asking the right questions in science. Choosing appropriate (or simply different) model organisms could be one way to start. The animals listed above are good examples of the results that were achieved by doing so. Archaebacteria also come to mind, since they were the first organisms to contribute to the booming field of optogenetics. But using the same organism to study a given scientific problem is still a necessary way to standardize all the research coming out every day. Tons of data would be uninterpretable if every team used a different organism to perform different experiments. What will the next animal of choice be for neuroscience? Something with decent intelligence, complex neurophysiology, yet not so complex that it becomes criminal to keep it in a cage. Perhaps corvids, with their amazing cognition despite the lack of a six-layer neocortex?