New learning mechanism for individual nerve cells

“This means a dramatic increase in the brain’s learning capacity. The cells we have studied control the blink reflex, but there are many cells of the same type that control entirely different processes. It is therefore likely that the timing mechanism we have discovered also exists in other parts of the brain”, said Professor of neurophysiology Germund Hesslow.

Professor Hesslow and colleagues Fredrik Johansson and Dan-Anders Jirenhed have used ‘conditioned reflexes’ for the research. The principle comes from the Russian researcher Ivan Pavlov, who, around the turn of the last century, taught dogs to associate a certain sound with food so that they began to drool on hearing the sound.

In the present experiment, the researchers studied animals that learnt to associate a sound with a puff of air in the eye that caused them to blink. If the time between the sound and the puff of air was quarter of a second, the animals blinked after quarter of a second even if the puff of air was removed. If the time was changed to half a second, the animals blinked after half a second, and so on.

The prevalent theories in brain research state that this learnt timing mechanism is a result of strengthening or weakening of the contacts – or synapses – throughout a network of nerve cells. However, using super-thin electrodes, the Lund group have now shown that no networks are needed: one single cell can learn when it is time to react.

The cells which the researchers have studied are called Purkinje cells and are located in the cerebellum. The cerebellum is the part of the brain responsible for posture, balance and movement, and the researchers focused on those cells that control blinking.

This work is basic research, but possible future applications could include rehabilitation following a stroke, which often affects a patient’s movements. The findings could also have a bearing on conditions such as autism, ADHD and language problems, in which the cerebellum is believed to play a part.

“Intelligible speech is dependent on correct timing, so that the pauses between the sounds are right”, explained Germund Hesslow.

The new findings have already attracted attention in the research community: the internationally renowned memory researcher Charles Gallistel came all the way from Rutgers University in the spring to study the group’s work. Work is now continuing to study what transmitter substance and what receptor on the surface of the cell are responsible for the newly discovered timing mechanism.

Research Shows How Brain Can Tell Magnitude of Errors

University of Pennsylvania researchers have made another advance in understanding how the brain detects errors caused by unexpected sensory events. This type of error detection is what allows the brain to learn from its mistakes, which is critical for improving fine motor control.  

Their previous work explained how the brain can distinguish true error signals from noise; their new findings show how it can tell the difference between errors of different magnitudes. Fine-tuning a tennis serve, for example, requires that the brain distinguish whether it needs to make a minor correction if the ball barely misses the target or a much bigger correction if it is way off.

The study was led by Javier Medina, an assistant professor in the Department of Psychology in Penn’s School of Arts & Sciences, and Farzaneh Najafi, then a graduate student in the Department of Biology. They collaborated with postdoctoral fellow Andrea Giovannucci and associate professor Samuel S. H. Wang of Princeton University.

It was published in the journal eLife.

Our movements are controlled by neurons known as Purkinje cells. Each muscle receives instructions from a dedicated set of hundreds of these brain cells. The instructions sent by each set of Purkinje cells are constantly fine tuned by climbing fibers, a specialized group of neurons that alert Purkinje cells whenever an unexpected stimulus occurs.

“An unexpected stimulus is often a sign that something has gone wrong,” Medina said, “When this happens, climbing fibers send signals to their related Purkinje cells that an error has occurred. These Purkinje cells can then make changes to avoid the error in the future.”

These error signals are mixed in with random firings of the climbing fibers, however, and researchers were long mystified about how the brain tells the difference between this noise and the useful, error-related information it needs to improve motor control.

Medina and his team showed the mechanism behind this differentiation in a study published earlier this year. By using a non-invasive microscopy technique that could monitor the Purkinje cells of awake and active mice, the researchers could measure the level of calcium within these cells when they received signals from climbing fibers.

The unexpected stimuli in this experiment were random puffs of air to the face, which caused the mice to blink. The researchers located Purkinje cells that control the mice’s eyelids and saw that calcium levels necessary for neuroplasticity, i.e., the brain’s ability to learn, were greater when the mice got an error signal triggered by a puff of air than they were after a random signal.

While being able to make such a distinction is critical to the brain’s ability to improve motor control, more information is needed to fine-tune it.  

“We wanted to see if the Purkinje cells could tell the difference not just between random firings and true errors signals but between smaller and bigger errors,” Medina said.

In their new study, the researchers used the same experimental set-up, with one key difference. They used air puffs of different durations: 15 milliseconds and 30 milliseconds.

What they found was that the eyelid-associated Purkinje cells filled with different amounts of calcium depending on the length of the puff; the longer ones produced larger spikes in calcium levels.        

In addition, the researchers saw that different percentages of eyelid-related Purkinje cells respond depending on the length of the puff.  

“Though there is a large population of climbing fibers that can give error-related information to the relevant Purkinje cells when they encounter something unexpected, not all of them fire each time,” Medina said. “We saw that there is information coded in the number of climbing fibers that fire. The longer puffs corresponded to more climbing fibers sending signals to their Purkinje cells.”

Their study could help explain how practice makes perfect, even when errors are imperceptibly small.

“If you felt a short puff and a long puff, you might not be able to say which one was which, but Purkinje cells can tell the difference,” Medina said. “The difference between a ‘very good’ and an ‘awesome’ tennis serve rests on being able to distinguish errors even as tiny as that.” 

How does the cerebellum work?

Nothing says “don’t mess with me” like a deeply-fissured cortex. Even the sharpest jaws and claws in the animal kingdom are worthless without some serious thought muscle under the hood. But beneath the highly convoluted membrane covering the brains of the evolutionary upper crust hides the original crumpled processor—the cerebellum. How this organ might actually work is the subject of a review published in Frontiers of Systems Neuroscience by researchers at the University of Minnesota.

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Muscle-controlling Neurons Know When They Mess Up

Whether it is playing a piano sonata or acing a tennis serve, the brain needs to orchestrate precise, coordinated control over the body’s many muscles. Moreover, there needs to be some kind of feedback from the senses should any of those movements go wrong. Neurons that coordinate those movements, known as Purkinje cells, and ones that provide feedback when there is an error or unexpected sensation, known as climbing fibers, work in close concert to fine-tune motor control.   

A team of researchers from the University of Pennsylvania and Princeton University has now begun to unravel the decades-spanning paradox concerning how this feedback system works.

At the heart of this puzzle is the fact that while climbing fibers send signals to Purkinje cells when there is an error to report, they also fire spontaneously, about once a second. There did not seem to be any mechanism by which individual Purkinje cells could detect a legitimate error signal from within this deafening noise of random firing. 

Using a microscopy technique that allowed the researchers to directly visualize the chemical signaling occurring between the climbing fibers and Purkinje cells of live, active mice, the Penn team has for the first time shown that there is a measurable difference between “true” and “false” signals.

This knowledge will be fundamental to future studies of fine motor control, particularly with regards to how movements can be improved with practice. 

The research was conducted by Javier Medina, assistant professor in the Department of Psychology in Penn’s School of Arts and Sciences, and Farzaneh Najafi, a graduate student in the Department of Biology. They collaborated with postdoctoral fellow Andrea Giovannucci and associate professor Samuel S. H. Wang of Princeton University.

It was published in the journal Cell Reports.

The cerebellum is one of the brain’s motor control centers. It contains thousands of Purkinje cells, each of which collects information from elsewhere in the brain and funnels it down to the muscle-triggering motor neurons. Each Purkinje cell receives messages from a climbing fiber, a type of neuron that extends from the brain stem and sends feedback about the associated muscles. 

“Climbing fibers are not just sensory neurons, however,” Medina said. “What makes climbing fibers interesting is that they don’t just say, ‘Something touched my face’; They say, ‘Something touched my face when I wasn’t expecting it.’ This is something that our brains do all the time, which explains why you can’t tickle yourself. There’s part of your brain that’s already expecting the sensation that will come from moving your fingers. But if someone else does it, the brain can’t predict it in the same way and it is that unexpectedness that leads to the tickling sensation.”

Not only does the climbing fiber feedback system for unexpected sensations serve as an alert to potential danger — unstable footing, an unseen predator brushing by — it helps the brain improve when an intended action doesn’t go as planned.    

“The sensation of muscles that don’t move in the way the Purkinje cells direct them to also counts as unexpected, which is why some people call climbing fibers ‘error cells,’” Medina said. “When you mess up your tennis swing, they’re saying to the Purkinje cells, ‘Stop! Change! What you’re doing is not right!’ That’s where they help you learn how to correct your movements.

“When the Purkinje cells get these signals from climbing fibers, they change by adding or tweaking the strength of the connections coming in from the rest of the brain to their dendrites. And because the Purkinje cells are so closely connected to the motor neurons, the changes to those synapses are going to result in changes to the movements that Purkinje cell controls.”

This is a phenomenon known as neuroplasticity, and it is fundamental for learning new behaviors or improving on them. That new neural pathways form in response to error signals from the climbing fibers allows the cerebellum to send better instructions to motor neurons the next time the same action is attempted.

The paradox that faced neuroscientists was that these climbing fibers, like many other neurons, are spontaneously activated. About once every second, they send a signal to their corresponding Purkinje cell, whether or not there were any unexpected stimuli or errors to report.

“So if you’re the Purkinje cell,” Medina said, “how are you ever going to tell the difference between signals that are spontaneous, meaning you don’t need to change anything, and ones that really need to be paid attention to?”

Medina and his colleagues devised an experiment to test whether there was a measurable difference between legitimate and spontaneous signals from the climbing fibers. In their study, the researchers had mice walk on treadmills while their heads were kept stationary. This allowed the researchers to blow random puffs of air at their faces, causing them to blink, and to use a non-invasive microscopy technique to look at how the relevant Purkinje cells respond.

The technique, two-photon microscopy, uses an infrared laser and a reflective dye to look deep into living tissue, providing information on both structure and chemical composition. Neural signals are transmitted within neurons by changing calcium concentrations, so the researchers used this technique to measure the amount of calcium contained within the Purkinje cells in real time.

Because the random puffs of air were unexpected stimuli for the mice, the researchers could directly compare the differences between legitimate and spontaneous signals in the eyelid-related Purkinje cells that made the mice blink.

“What we have found is that the Purkinje cell fills with more calcium when its corresponding climbing fiber sends a signal associated with that kind of sensory input, rather than a spontaneous one,” Medina said. “This was a bit of a surprise for us because climbing fibers had been thought of as ‘all or nothing’ for more than 50 years now.”

The mechanism that allows individual Purkinje cells to differentiate between the two kinds of climbing fiber signals is an open question. These signals come in bursts, so the number and spacing of the electrical impulses from climbing fiber to Purkinje cell might be significant. Medina and his colleagues also suspect that another mechanism is at play: Purkinje cells might respond differently when a signal from a climbing fiber is synchronized with signals coming elsewhere from the brain.   

Whether either or both of these explanations are confirmed, the fact that individual Purkinje cells are able to distinguish when their corresponding muscle neurons encounter an error must be taken into account in future studies of fine motor control. This understanding could lead to new research into the fundamentals of neuroplasticity and learning.    

“Something that would be very useful for the brain is to have information not just about whether there was an error but how big the error was — whether the Purkinje cell needs to make a minor or major adjustment,” Medina said. “That sort of information would seem to be necessary for us to get very good at any kind of activity that requires precise control. Perhaps climbing fiber signals are not as ‘all-or-nothing’ as we all thought and can provide that sort of graded information”

Purkinje neurons (yellow) generated from embryonic stem cells integrate into the cerebellum (red) when transplanted into the fetal mouse brain.

© 2010 K. Muguruma et al.

Elucidating the neural pathways that underlie brain function is one of the greatest challenges in neuroscience. Light sheet based microscopy is a cutting edge method to map cerebral circuitry through optical sectioning of cleared mouse brains. However, the image contrast provided by this method is not sufficient to resolve and reconstruct the entire neuronal network. Here we combined the advantages of light sheet illumination and confocal slit detection to increase the image contrast in real time, with a frame rate of 10 Hz. In fact, in confocal light sheet microscopy (CLSM), the out-of-focus and scattered light is filtered out before detection, without multiple acquisitions or any post-processing of the acquired data. The background rejection capabilities of CLSM were validated in cleared mouse brains by comparison with a structured illumination approach. We show that CLSM allows reconstructing macroscopic brain volumes with sub-cellular resolution. We obtained a comprehensive map of Purkinje cells in the cerebellum of L7-GFP transgenic mice. Further, we were able to trace neuronal projections across brain of thy1-GFP-M transgenic mice. The whole-brain high-resolution fluorescence imaging assured by CLSM may represent a powerful tool to navigate the brain through neuronal pathways. Although this work is focused on brain imaging, the macro-scale high-resolution tomographies affordable with CLSM are ideally suited to explore, at micron-scale resolution, the anatomy of different specimens like murine organs, embryos or flies.

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Neuronal network in the cerebellum

Fluorescence microscopy image showing the cerebellar network of Purkinje neurons from a mouse. The neurons are visualised by labelling the cells with green fluorescent protein (GFP). Purkinje cells are specialised neurons found in layers within the cerebellum (at the back of the brain). In humans they are one of the longest types of neurons in the brain and are involved in transmitting motor output from the cerebellum. 

Credit: Prof. M Hausser/UCL, Wellcome Images