How Brain Injuries Affect Sleep-Related Neurons Differently in Male and Female Mice

Rebecca Somach was the lead author on this study in the Cohen lab. Rebecca is currently doing her postdoctoral fellowship at Swarthmore College. Her current research uses planarians as a model system to understand how pesticides affect developmental neurotoxicity. She's interested in helping students understand neurobiology and helping them achieve their research goals. 

or technically,

Mild Traumatic Brain Injury Affects Orexin/Hypocretin Physiology Differently in Male and Female Mice

[See Original Abstract on Pubmed]

Authors of the study: Rebecca T Somach, Ian D Jean, Anthony M Farrugia, Akiva S Cohen

A traumatic brain injury (TBI) occurs when an external source, such as a strong hit to the head, damages the brain. TBIs can be mild or severe, with mild TBIs (mTBI) being especially common and accounting for a large portion of TBI cases. Both TBI and mTBI can negatively impact brain physiology and lead to problems like sleep issues. Surprisingly, despite a large portion of TBI patients experiencing disordered sleep, there is very little research focusing on how these injuries may affect neural circuits that regulate sleep. Understanding the link between TBI and disrupted sleep is an important step in improving treatments for TBI patients.

Orexin/hypocretin neurons are specialized brain cells found in a brain region called the Lateral Hypothalamus. These neurons play a critical role in sleep and wake regulation. When they are not working properly or if they die off, it can lead to sleep-related issues, such as narcolepsy (a disorder where people fall asleep unexpectedly) or excessive sleepiness during the day. Some research suggests that TBIs can disrupt orexin, which could explain why many TBI patients have sleep troubles. 

However, the Cohen lab found that sleep problems after mTBI can happen even when the number of orexin neurons does not decrease due to the injury. This raised an interesting and important question: is it the activity of these neurons after injury, rather than how many there are overall, that is important? To tackle this question, the Cohen lab looked at how active orexin neurons were after mTBI by labeling them for cFOS, a protein that is produced when neurons are active. They found that instead of orexin neurons dying off, the activity of the overall population was actually reduced (less cFOS in the population), suggesting that the number of neurons alone is not the only factor to consider after TBI. These findings were important, as only two other studies have looked at how orexin neuron activity changes after brain injury. 

Rebecca Somach, an NGG graduate from the Cohen lab, decided to further expand on this work by incorporating other fascinating neuroscience techniques. These included electrophysiological recordings, which measure electrical activity in the brain, and a mouse that has orexin neurons tagged with a glowing protein, making it easier to study and see these neurons in the brain. Rebecca also wanted to examine the effects of brain injury might be different in male and female mice, since sleep can vary between sexes. This is particularly important because of the little research on the effects of TBI, specifically mTBI, on orexin in female animals.

Rebecca specifically examined whether mTBI changes how orexin neurons might respond to electrical signals or how often they fire in male and female mice. To do this, they used current clamp recording, a neuroscience technique used to see how neurons react when they are injected with electrical current. In female mice, they found that orexin neurons became more negatively charged after mTBI, which is a process called hyperpolarization. In contrast, they found that in male mice, orexin neurons had a reduction in action potential threshold after mTBI, making it easier for them to fire. These seemingly small changes in how neurons behave after mTBI can have a big impact on how they communicate to other areas of the brain.

While orexin neurons are found in the Lateral Hypothalamus and talk to neurons adjacent to them, they are also connected to many different parts of the brain. Because of this, Rebecca wanted to examine whether mTBI could affect the connections these neurons receive from other brain regions. Orexin neurons receive both excitatory and inhibitory signals. To only focus on excitatory signals, Rebecca recorded neurons while applying a chemical called bicuculline, that blocks inhibitory signals. This allowed them to study how only excitatory signals may have changed after brain injury in male and female mice. They looked at two types of excitatory post-synaptic currents - spontaneous (sEPSC) and miniature (mEPSC), which can be thought of as the orexin neurons’ responses to excitatory inputs from other neurons. In short, the stronger the EPSCs, the more likely the neurons are to become active. After injury, they saw that these signals were less frequent and weaker in both male and female mice, meaning that the orexin neurons were getting less excitatory activity. 

Next, Rebecca did the reverse experiment and isolated only the inhibitory signals to examine if there were mTBI-induced changes. She did this by recording orexin neurons with AP5 and CNQX, which are chemicals that remove excitatory currents. Rather than looking at sEPSCs and mESPSCs, she then focused on recording spontaneous and miniature inhibitory currents (sIPSC, mIPSC) in male and female mice. After injury, she saw reduced time between sIPSCs, meaning they occurred more often. Interestingly, she only saw stronger sIPSCs and mIPSCs in female mice, which could help explain why sleep disturbances after TBI can vary depending on sex.

Overall, while previous research has shown an effect of mTBIs on orexin neurons, not many studies looked at how brain injury impacts the activity of these neurons. Rebecca addressed this gap by exploring how the activity and connections of orexin neurons are altered after brain injury in both males and females. She shows that mTBI significantly alters how orexin neurons respond to inputs from other neurons and that although these changes appear similar between male and female mice, the underlying mechanisms are not the same. Ultimately, her work provides insight into how brain injury may disrupt sleep-related circuits and informs us why TBI patients may experience disordered sleep.

About the brief writer: Diana Pham

Diana is a Neuroscience Ph.D. student in Dr. Brett Foster’s lab. She is broadly interested in how memories are encoded and consolidated in the brain.

Want to learn more about the effects of brain injury on sleep-related neurons? You can find Rebecca’s full paper here!

Can a single neuron in the brain really solve complicated problems all by itself?

Ilenna Jones was the lead author on these studies. She is a Neuroscience Ph.D. candidate in Dr. Konrad Kording’s lab at Penn.

or technically,

Might a single neuron solve interesting machine learning problems through successive computations on its dendritic tree? & Do biological constraints impair dendritic computation?

See Original Abstracts on Pubmed: Paper 1 Paper 2

Authors of the studies: Ilenna Simone Jones & Konrad Kording

Figure 1: A Purkinje neuron found exclusively in the cerebellum. Illustration by Ramon y Cajal.

In the late 1800s, a scientist named Ramon y Cajal turned his microscope to the brain and discovered neurons, the cells of the brain. At the time, cameras had not yet been invented, so instead he drew what he saw. He compiled a collection of beautiful illustrations of the many different shapes and variations of neurons, which are still cited and referenced to this day (see Figure 1). In doing so he gave birth to the field of modern neuroscience.

Cajal’s drawings demonstrated the anatomical complexity and variety of neurons throughout the brain. He observed that neurons are composed of several parts, including branched fibers called dendrites that converge onto a cell body, and a single thin fiber that departs the cell body called an axon. Since Cajal’s time, neuroscientists have learned that neurons receive electrical activity from other neurons through their dendrites and send electrical activity through their axons. These electrical signals form the basis of brain activity and allow us to sense, interpret, and respond to cues in our environment.  

Much of neuroscience research has focused on the activity of populations and networks of neurons, but how much can a single neuron do? Does a neuron’s extensive tree of dendrites allow it to perform complex calculations and send new information to other neurons? Or does a neuron simply act like a relay station that transfers the signals it receives without analyzing it? These are the questions that Neuroscience Graduate Group student Ilenna Jones wanted to answer. 

In her first paper, Ilenna used a computerized version of a neuron and asked it to perform various complex tasks. By modifying the number and organization of dendrites on her “virtual neuron,” she found that neurons with complex branching patterns performed tasks better than neurons with simpler branching patterns. This finding suggests that the shape of a neuron actually influences how much it can do! Neurons with densely layered, tree-like dendritic structures can perform sophisticated calculations, as opposed to neurons with more simple dendritic structures which cannot. 

In her second paper, Ilenna next wondered whether making her “virtual neuron” more realistic would change how they performed the same tasks. To do this she included even more of the biological properties found in real neurons, including how dendrites receive and respond to electrical signals from other neurons. She expected that by ‘humanizing’ her virtual neuron it would impair its ability to perform complex calculations, leading to worse task performance. This is a reasonable prediction because in many cases adding more rules for a computer model to follow can push it farther from the ‘idealized case' where it performs very well. But to her surprise, adding these new, realistic characteristics to her neuron actually improved performance in many cases! 

Thanks to Ilenna, we now know that dendritic complexity can allow individual neurons to act as mini-computers that receive information, perform calculations on it, and send new information to many other neurons. Moreover, because neurons come in many shapes and sizes across the brain, it’s likely that different types of neurons can perform completely different calculations depending on their shape. Her findings are significant because it opens up a whole new perspective as to how neurons process information. Understanding what individual neurons are capable of will help neuroscientists study the brain more closely and ultimately help us understand how the brain works!

Want to learn more about the details of Ilenna’s computational modeling of neurons? You can check out the full papers here and here!

About the brief writer: Joe Stucynski

Joe is a graduate student in Dr. Franz Weber’s and Dr. Shinjae Chung’s labs at Penn. He is broadly interested in what makes us sleep how the brain transitions between states.

Citations:

1. Purkinje Neuron Picture: https://upload.wikimedia.org/wikipedia/commons/b/bb/PurkinjeCellCajal.gif