Module 1 : The Cells of the Nervous System

Lab Introduction

Do you think of your mental experiences as being composed of pieces….probably not. However, your experiences depend on the activity of a huge number of separate but interconnected cells. Researchers are far from fully understanding how they achieve all that they do, but the place to begin is by trying to understand how cells of the nervous system function.

• 1.1 Neurons and Glia o 1.1a The Structure of a Neuron o 1.1b Variations among Neurons o 1.1c Glia

1.1a The Structure of a Neuron

The most distinctive feature of neurons is their shape, which varies enormously from one neuron to another. These physical features define the morphology of a neuron. Unlike most other body cells, neurons have long branching extensions. The larger neurons have dendrites (from the Greek word dendron, for tree), a soma (cell body), an axon, and presynaptic terminals. Contrast the motor neuron in Figure 1A and the sensory neuron in Figure 1B. A motor neuron that receives excitation from other neurons and conducts impulses to a muscle, with its soma in the spinal cord, receives excitation through its dendrites and conducts impulses along its axon to a muscle. A sensory neuron that is highly sensitive to a specific type of stimulation is specialized at one end to be highly sensitive to a particular type of stimulation, such as light, sound, or touch. The sensory neuron shown in Figure 1B transmits light information from the retina to the brain.

Figure 1. Example of motor and sensory neuron morphologies. A, motor neuron from a 10 day old mouse (neuromorpho.org ID: NMO_00909), this neuron resides in the spinal cord and controls muscle contractions. B, ganglion neuron from the 60 day old mouse retina (NMO_10769), this neuron sends axons from the retina to the brain. White, Soma; Green, dendrites; gray, axon.

1.1b Variations among Neurons

Of the ~190 billion cells in the human brain , about half of them neurons while the other half is comprised of glia, ependymal, and endothelial cells (Azevedo et al., 2009). Neurons vary enormously in size, shape, and function. The shape of a neuron determines its connections with other cells and thereby determines its function. For example, the widely branching dendrites of the Purkinje cell in the cerebellum (see Figure 2) enable it to receive input from up to 200,000 other neurons. By contrast, bipolar neurons in the retina have only short branches, and some receive input from as few as two other cells.

Figure 2. Purkinje cell from the Guinea-pig cerebellum, (NMO_00610). Notice the highly arborized dendrites (green), A. The Purkinje dendritic tree forms a nearly flat 2-D layer when rotated on its axis, B. This can be viewed by searching the neurmorpho ID on Neuromorpho.org and viewing the animation, which rotates the cell in 3-D. Alternatively, the cell can be viewed using the 3D neuron viewer, and rotated manually by holding right click and dragging the mouse to rotate. The purkinje cell axons, not shown here, are inhibitory, and provide the entire output of the cerebellar cortex.

Excitatory neurons

Neurons in the same brain region may also have very different morphologies reflecting their unique function in the brain. In the cerebral cortex, >80% of neurons use excitatory neurotransmitters (they elicit more activity in other neurons) and serve to encode and relay information necessary for sensations, perceptions, motor functioning and all mental processes. Most of these excitatory neurons use the amino acid glutamate as their excitatory neurotransmitter. Given this overwhelming majority, it wouldn't be an overstatement to say that glutamatergic (glutamate secreting) excitatory neurons are the foundation for the brain. Many of these neurons have pyramid shaped cell bodies and thus are called pyramidal cells (Figure 3A). The apex of the pyramid has one long dendrite that protrudes towards the surface of the brain (Apical dendrite) and branches extensively to increase the amount of information that can be received and coded for by the cell. Pyramidal cells also have multiple branching dendrites protruding from their base (Basilar dendrites).

Excitatory neurons have axons that can vary greatly in length and width. Some pyramidal neurons in the primary motor cortex can project their axons all the way to the lumbar segment of the spinal cord (long range projection neurons). This distance, roughly from the top of your head to your lower back, can be over a meter in length! Some axons are relatively short (about <100-2000 micrometers) and are considered locally projecting cells, or interneurons (Figure 3B). An example of these type of cells are the neurons in layer 4 of the primary visual cortex, which are the "first responders" to visual stimuli within the cerebral cortex (As a side note, the time it takes for light information to go from your retina to your visual cortex in the occipital lobe in the back of your head is ~60 millisecond). These excitatory interneurons are called spiny stellate cells (Figure 3B), because of their star like appearance and the tiny rose thorn like membrane protuberances coming off their dendrites called dendritic spines. These spines are characteristic of excitatory cells in general, and are the primary location of excitatory synapses onto

excitatory cells. Many in the field believe that spines are smaller information processing units within the processing unit of the neuron and may even serve to store pieces of memories!

Figure 3. Two types of neocortical excitatory neurons from the rat somatosensory cortex. A, Pyramidal cell (NMO_09379). Note the distinct prominent apical dendrite (purple) facing towards the surface of the brain compared with the basilar dendrites (green) protrudes from the base of the soma of the pyramidal neuron and the axon (gray) protrudes from the bottom of the soma. Although only a single axon protrudes from the soma, it typically bifurcates (splits into two) multiple times resulting in many axon outputs from one neuron. B, This spiny stellate cell (NMO_00982) exists in the somatosensory representation of the rat whisker pad. Notice how its dendrites (green) are generally all oriented in one direction to receive synapses from the whisker follicles via the thalamus, axons not shown.

Inhibitory interneurons

Only about 10% of neurons use inhibitory neurotransmitters, but they serve a critical role in regulating the development, plasticity, and healthy functioning of the brain. Inhibitory cells have a key feature that makes them unique, most of them using gamma-aminobutryic acid (GABA) and are interneurons with locally projecting axons. Inhibitory interneurons are an extremely diverse population of cells (Fishell & Rudy, 2011). In contrast to the excitatory spiny stellate interneuron, most inhibitory interneurons are sparsely spiny or aspiny, meaning they have little to no dendritic spines. In these cells, excitatory synapses are made on the relatively smooth surface of the neuronal membrane. In the cerebral cortex, inhibitory interneurons are comprised of at least 10 different highly specialized subtypes. In the somatosensory cortex, inhibitory interneuron populations have been well studied and the subtypes are identified based on two criteria, specific protein expression and the morphology of their axons.

Around 40% of inhibitory interneurons express the calcium binding protein Parvalbumin (PV+). These cells have a morphology of either basket cells or chandelier cells. Basket interneurons form axosomatic synapses around the somas of excitatory neurons. Basket cell axons look like a basket surrounding the soma of excitatory neurons. Chandelier cells form axoaxonic synapses around the axon

initial segment of excitatory neurons. These axons loop around the axon initial segments of excitatory neurons and give them the appearance of old chandeliers. Together, PV+ interneurons are critical for maintaining the high resolution of sensory signals coming into the brain and are involved in the high frequency oscillations (gamma band) in the brain associated with attentional states. The other large class of inhibitory interneurons express the somatostatin protein (SST+) and are called Martinotti cells. These cells generally have axons that target the dendrites of pyramidal cells that are close to the surface of the cerebral cortex. These neurons have special roles in providing inhibition to these pyramidal cells and are, counter intuitively quiet during sensory input into the somatosensory cortex while active when there isn't sensory input (Gentet et al., 2012).

The role of inhibitory interneurons are still quite mysterious, however we know that they are critical for normal brain function. Inhibitory neurons mature later than excitatory neurons in development. As they mature, plasticity in the brain decreases. Neuroscientists have been studying the development of inhibitory interneurons in the rodent brain in great detail and have discovered that the maturation of inhibition closes a critical period of development (Fagiolini & Hensch, 2000). During the critical period, the brain is highly malleable and is capable of rewiring itself very easily. After the critical period, the brain begins to "crystallize" and is far less malleable then during that period. An example of a critical period is that for language development. The theory is that it is easier to acquire fluency in a language before the age of ~10 years old, but this becomes more difficult as you get older. You wouldn't think that a small population of inhibitory interneurons in your brain could be responsible for your ability to properly communicate with your friends, family and loved ones, but this does seem to be the case.

Figure 4. Inhibitory interneurons in the rat somatosensory cortex. The most distinctive morphological features of inhibitory interneurons are the type of synapses they make. Basket cells (NMO_00243) make axosomatic synapses (A), chandelier cells (NMO_00291) make axoaxonic synapses (B), and martinotti cells (NMO_02730) make axodendritic synapses (C).

Neuromodulators

A third class of neurons in the CNS secrete neuromodulators, such as acetylcholine (ACh), dopamine (DA), serotonin (5HT) norepinephrine (NE). These neurotransmitters modulate the activity of the cells that they synapse on by causing excitation, inhibition or a complex combination of responses depending on the type of receptor on the post-synaptic cell (after the synapse, a.k.a the neuron receiving

the synaptic input). In fact, excitatory neurotransmitters can also elicit a complex set of responses in the post-synaptic cell depending on the receptor (but this is a lesson for a different day). Additionally, neuromodulators also modulate a wide variety of brain and body functions.

ACh cells are involved in muscle contractions, learning, memory, arousal and reward. Mysteriously, ACh neurons die in mass during Alzheimers disease, the principal neurodegenerative disorder affecting ~45% of adults over 85, and underlie some of the early debilitating memory impairments that occur in the disease. DA neurons are involved in motor function, cognition, and reward. DA neurons are highly active during the presence of rewarding stimuli such as drugs or delicious foods. Interestingly, these neurons also become active when stimuli associated with the rewarding stimuli are present. This property of DA neurons explains the cravings that heroin addicts feel when they see needles, or the rush that coffee drinkers experience when they smell a brew. In Parkinson's disease, the second most prevalent neurodegenerative disease, ~50% of DA neurons in the substantia nigra region of the brain degenerate. When these neurons degenerate, the source of DA that usually goes from the substantia nigra to the striatum, a region involved in motor regulation, is lost. This loss of DA is manifested in the profound loss of motor initiation and control in Parksinsons patients, resulting in multiple symptoms including a resting tremor, rigidity, and a profound slowing of movements. Additionally, patients experience a loss of automatic movements, like that which occurs during walking, resulting in a slow, hunched over shuffle, or magnetic gait. 5HT is involved in sleepiness, mood, body temperature and satiety. During the intake of drugs like methylphenedioxymethamphetamine or MDMA (street names "extacy", "molly"), 5HT is released in large quantities from the presynaptic terminal of 5HT neurons. This explains many of the psychotropic affects of MDMA such as elevated mood, satiety, and changes in temperature regulation. Unfortunately, MDMA over stimulates the release of 5HT, resulting in a depressive state once the effect of the drug wears off. NE neurons play a role in arousal, reward, cognition, and regulates the fight or flight response. For example, NE directly increases heart rate which is a sympathetic nervous system response to stress or danger.

For all the roles that the neuromodulators play, they have a surprisingly small footprint, only <1% of neurons in the brain secrete these chemicals as their primary neurotransmitter. The reason for their significant impact on psychology and behavior is partly due to their morphologies. Dendrites of neuromodulators vary in size and shape, but a distinctive characteristics of these types of neurons are their long range "diffuse" projecting axons that synapse into multiple areas of the brain. This way, a relatively small population of specialized neuromodulators can have a large and global impact on brain function.

Figure 5. Dopamine neuron in the substantia nigra of the midbrain (NMO_05747), a region involved in motor function. These types of neurons are selectively afflicted by Parkinson's disease.

1.1c Glia

Other components of the nervous system called glia, perform many functions. The brain has several types of glia, that generally are smaller but more numerous than neurons. One, the star-shaped

astrocytes that synchronize the activity of the axons wrap around the presynaptic terminals of a group of functionally related axons, as shown in Figure 1.7a. Others, such as the oligodendrocytes, produce myelin sheaths that insulate certain vertebrate axons in the central nervous system (CNS) and schwann cells have a similar function in the periphery (see Figure 1.7b-c). Last, we have microglia that proliferate in areas of brain damage and remove toxic materials and radial glia that guide the migration of neurons during embryological development (see Figure 1.7d-e). It’s important to note that glia have other functions as well. Glial cells come in many morphological forms that are beyond the scope of the materials here.

1.2a Methods for visualizing neurons

Special terms

1. Golgi stain 2. Neuron doctrine 3. Nissl stain 4. Single cell fill 5. Immunohistochemistry 6. Green fluorescent protein 7. Connectomics

Without any staining, the appearance of brain tissue is a pinkish white blob and even with powerful microscopes, it is nearly impossible to distinguish neurons from each other let alone determine the shape or connections of the neurons. It wasn't until the 19th century that a technique was developed by an Italian scientist Camillo Golgi to allow the visualization of the full morphology of neurons in the nervous system. This stain uses a reaction that fills neurons with silver chromate, a dark precipitate that fills the entire neuron including the axon, dendrites, and soma. A Spanish scientist named Ramon Y. Cajal, then famously used the 'Golgi stain' (Figure 6A) to map out the diverse neuronal populations in the retina, cerebellum, spinal cord and cerebral cortex providing humanity with its first look into the microstructure of the brain. Mysteriously, only about ~5% of neurons are stained using the Golgi method, but was enough to provide evidence for the hypothesis that neurons are individual units with spaces in between them (neuron doctrine) rather than interconnected in a continuous reticulum (net).

Around the same time, a German neuropathologist Franz Nissl developed the eponymous Nissl stain (Figure 6B). Nissl uses basic dyes to stain acidic structures like RNA and DNA in cell bodies. The Nissl stain labels ALL cell bodies except for the ones that don’t have nuclei (red blood cells). The advantage of this technique is that unlike the Golgi stain, an entire population of cells can be visualized to reveal the patterns of anatomical structure, albeit without any of the fine details dendrites or axons.

A more recent approach targets individual neurons for labeling using miniscule pipettes with tips ~5 micrometer. These pipettes can directly attach onto then fill individual neurons with compounds that result in a dark precipitate within the neuron following fixation and processing of the tissue. Fluorescent compounds can also be used to immediately view the morphology of the neurons using lasers and cameras. This single cell fill technique (Figure 6C) usually follows an electrophysiological experiment where the pipette is recording the electrical activity of a single neuron while simultaneously filling the neuron with the visualizing compounds.

Another technique exploits the powerful specificity of the immune system to target specific proteins expressed in biological tissues. This technique, called immunohistochemistry (Figure 6D), takes a protein of interest, exposes antibody producing immune cells (B cells) to that protein, and then isolates the resultant antibodies for that protein from those immune cells. The antibodies are then linked to compounds that produce dark precipitation under special conditions, or fluorescent compounds. This method can be very powerful in identifying specific proteins within a cell and is sometimes used to resolve cellular morphology. One key advantage of using fluorescence in general is the ability to use fluorophores (fluorescent molecules) of different colors to visualize many different objects simultaneously.

A very modern technique to visualize neurons involve using fluorescence, either manually filling neurons with fluorescent dyes or using genetically encoded fluorescent proteins. The genetic approaches often use, Green Fluorescent Protein (GFP, Figure 6D), which is a fluorescent protein originally derived from the jelly fish Aequorea Victoria that allows it to glow green in its natural habitat of the Pacific Ocean. The benefit of GFP and its derivatives, is that research animals can now be genetically modified so as to express the GFP protein like Aequorea Victoria! Using different colors of fluorescece in the brain, many different types of neurons can be illuminated simultaneously so that their interrelationships can be deciphered.

Although structure often implies function within neurons, recent years have shown that it can be exceedingly difficult to classify cells based entirely off morphology (DeFelipe et al., 2013). Sometimes neurons are classified by their morphologies, sometimes they are classified based on physiological responses or neurotransmitter type, and other times they are classified based on the types of proteins or genetic material they express. Just to give you one clean example, basket cells and chandelier cells (morphological distinction) express the calcium binding protein Parvalbumin (protein distinction), thus contain Parvalbumin RNA (genetic material), secrete GABA (the primary inhibitory neurotransmitter) and fire high frequency action potentials (physiological distinction).

Mapping out all the connections between all the neurons in the brain has only become possible with modern techniques and has recently been given the name of connectomics. Like genomics, which seeks to discover the structure and function of the entire genome, connectomics seeks to determine the structure and function of all the connections in the brain. This is a monumental task, since the brain is estimated to have about 7 x 1014 synapses, >10 different types of neurotransmitters, and hundreds of neurotransmitter receptor subtypes. This diversity is one of the reasons the brain is such an astonishing biological computer and one of the most complex objects in the universe.

The exercises below are intended to allow you to integrate the knowledge you have learned so far about neurons and the brain. The ultimate goal, is to be scientifically literate and capable of presenting a research article to your peers! Presentations are one of the best ways to improve your scientific literacy and the more you practice, the more confident you will become!

Figure 6. Different methods for visualizing neurons. The Golgi method only stains about 5% of neurons, but provides a detailed picture of the neurons morphology (micrograph generously provided by Adesh Bajnath), A. Pan-cellular Nissl stain labels all cells excluding red blood cells. Blue spots are cell bodies in the neocortex. Note the dark and light bands indicating denser and sparser regions of cell distribution, B. A single cell filled pyramidal neuron imaged using a high magnification lens and stitched following electrophysiological recording experiments (Yang et al., 2014), C. Using immunohistochemistry to label extracellular matrix molecules (blue) and GFP to identify the 5HT3a serotonin receptor expressing inhibitory interneurons (green) simultaneously demonstrates non-overlapping populations of cells showcasing the advantage to fluorescence, D.

Exercise 1. Qualitative comparisons.

In order to fully appreciate the complexity of neuronal morphology and how that relates to function, you first need to gets hands on! One benefit of digital databases is the free and easy access to anyone with a device and internet access. Neuromorpho.org is currently the largest database for neuronal morphology from real scientific laboratories around the world (Gardner et al., 2008; Halavi et al., 2012; Parekh & Ascoli, 2013). In fact, many of the neuron examples shown above are from neuromorpho.org! At this point you should refer to the PowerPoint slides provided by your instructor for instructions on navigating the website.

Once you are familiar with the navigation, go to the browse--> neuron atlas then download the zip file for your appropriate operating system. Follow the instructions to load the Neuron_atlas.exe file, you should then see this window pop up.

The image on the left is a 3-D digital reconstruction of a real rat brain, the atlas menu on the top left can change the visibility of different anatomical structures, as all as add digital sections in the coronal, sagittal, or horizontal plane. The menu on the right allows you to select the visibility of different anatomical regions as well as neuron types within those regions. Right clicking on the little balls embedded in the digital brain will load a browser window with the cell of your choice, left clicking on the balls will load the 3-D neuron viewer with the cell you chose. Checking or unchecking the menu boxes will help you narrow down selections. Take a minute to familiarize yourself with the options here.

1. Search the regions listed below for different pyramidal cell types (orange balls), 2. On a piece of paper, sketch their neuronal morphologies as best you can, then compare and contrast their qualitative physical features (no need to look at the detailed quantitative measurements for this!). 3. Write down your comparisons and discuss how the neurons your picked facilitate the function of the brain region (you should do some reading for this!). Cerebral cortex Medulla

olfactory bulb Cerebellum hippocampal formation Thalamus striatum Midbrain Some terms to help you describe morphology:

1. Arbor: the branching structure of a neuronal process e.g. the dendritic arbor was complex. Synonymous with ramification. e.g. the extensive axonal ramification.

2. Dendritic trunk: the thickest and main protrusion of the dendrite coming out of the soma. Synonymous with Dendritic stem.

3. Dendritic branch: a thinner portion of dendrite protruding off of a trunk or stem. 4. Dendritic tree: a term that encompasses all the dendrites and branches. E.g. the Dendritic tree had

2 trunks with 5 branches per trunk. 5. Bifurcation: division of something into two parts, split in two. E.g. the dendrite of this neuron

bifurcated many times, increasing its surface area of coverage. Things to attend to when analyzing neurons:

1. Geometry of the Dendritic arbor e.g. purkinje cells have very flat Dendritic arbors. 2. How ‘twisty’ are the dendrites? E.g. the motor neuron in Figure 1 is twistier than the ganglion

cell. 3. How long are the dendrites? The scales on the x and y axis are in the 3-D visualization window

are in microns. No precise measurements needed her, just estimate.

Exercise 2. Quantitative digital experiment.

In order to truly understand how neuronal morphology contributes to brain function, we need to first make a hypothesis, then test it using quantitative measurements. One hypothesis about brain function is that neurons are the individual computational units that collectively manifest the emergent properties of sensory experiences, learning, memories and cognitive processing. If we use computers as an analogy for the brain, then we know that having more transistors makes a computer faster and able to store more information. Compared to modern computers, the circuits of the brain are arguably more powerful and flexible, since the individual transistors (neurons) are three dimensional and have high structural complexity. For example, neurons have dendrites with dozens of branches and thousands of dendritic spines, each serving as a miniature processing unit on the cell. Therefore, a reasonable hypothesis could be that dendritically more complex neurons should exist in functionally more complex brain regions. Jacobs and colleagues (2001) examined the post-mortem human brain and found differences in pyramidal cell basilar dendrite complexity across different brain regions. Here we will analyze a portion of their data to test whether the data support the hypothesis.

Special terms

Brodmann areas: A numerical system used to define specific anatomical regions in primates, including humans. Developed by the German anatomist Korbinian Brodmann by analyzing the morphology of cells stained with Nissl, there are 52 Brodmann areas in the non-human primate and roughly the same for humans.

Finding the article

1. Go to the search dropdown menu, then select keyword. Type in NMO_03471 as the search criteria, show summary, and select the only cell that appears.

2. Scroll down to the reference article, and click the PubMed/Abstract Link.

3. From the next page you will be able to access the Free Final Text for the article.

4. First things first, read the abstract to get a summary of what the article is all about!

5. Now download the article (or if you dont have access, you can use a search engine to find the article based on its name, the PDFs are sometimes available for free).

Introduction questions (look for the answers to these questions in the introduction section)

1. What is the reasoning of the authors for conducting this work?

2. What were the author’s hypotheses?

Methods questions (look for the answers to these questions in the methods section)

1. In order to appreciate the results, we need to understand the methods. What method did Jacobs et al. (2001) use to stain neurons in the human brain?

2. How did the authors operationally define dendritic complexity? What do you think about their definition?

3. How did the authors define how complex the different brain regions were? Fill in table 1. with the function and relative complexity of the brain regions found in Jacobs et al. (2001).

Results exercises

1. Go to neuromorpho.org, here you can find the raw data from the many of the cells that were analyzed in the study. Since we aren't trying to replicate the entire study, let's just select four brain regions, two that are "low integrative" and two that are "high integrative". This is shown in Table 2 and Table 3.

Now, we can start collecting our data. Click search-->metadata. For the animal, select "Human". For the archive, select "Jacobs". For brain regions, select "neocortex". Now we want to narrow down the brain regions more specifically. Remember the anatomical and Brodmann area names in table 1? We can now use those terms to specify our search. After you specified the search to "neocortex", another list popped up below, there you can specify which anatomical region you want to search, this is where you can refer to table 1's anatomical names. After you select the anatomical name, you can then select the Brodmanns area in the list that pops up below! An example is shown in Figure 1. After your neurons criteria are set, scroll down and click "hits from current criteria" to show how many neurons fit the parameters you specified, then click "show summary" to view the list of neurons.

2. Normally, we would make our best attempt to randomly select the neurons for our sample. In this case, the neurons were already analyzed so the sample is limited. However, we can still make our best attempt to randomly pick out of the cells that are available in the summary list. Scroll down the list and choose 3 neurons as randomly as you can.

3. Click on the name of the cell (can be numerical designation).

4. Note the computer assisted drawing of the neuron. Purple is the apical dendrite, green is the basilar dendrite and white is the soma. Note that the apical dendrite was not fully reconstructed nor analyzed.

5. Scroll down to the Measurements section. Note the various quantitative measures that are available. Find the data for the total length and number of branches.

6. Log your data into table 2 and table 3.

Results/discussion questions (look for the answers to these questions in the results/discussion section)

1. Does the complexity of dendrites vary as a function of brain region?

2. Do the authors’ results support or refute the hypothesis?

3. Do YOUR results support or refute the hypothesis?

4. Scientific laws only become accepted after hypotheses are rigorously testing. If we were to further test the hypothesis that complex dendrites underlie complex brain processing, but this time comparing the prefrontal cortex of mice, elephants, and humans, what results would support the hypothesis and what results would refute it?

Table 1. Function and relative complexity of brain regions in Jacobs et al. (2001).

Anatomical designation: Brodmann's Area (BA)

Gross anatomical name (specific anatomical or functional name)

Function Relative degree of integration (high or low)

1,2,3 Post-central gyrus (primary somatosensory cortex)

22 Temporal lobe (Primary auditory cortex, including Wernickes area)

4 Precentral gyrus (primary motor cortex)

44 Prefrontal cortex (Inferior frontal gyrus, part of Brocas area)

11 Prefrontal cortex (Orbitofrontal prefrontal cortex)

39 Parietal cortex (Angular gyrus) 6 Frontal lobe

(Premotor/supplementary motor cortex)

10 Frontopolar (Anterior prefrontal cortex)

Table 2. Total length

Table 3. Number of branches (segments)

Anatomical designation: Brodmann's Area (BA)

Neuron 1 Neuron 2 Neuron 3 Average

1,2,3 22 6

10

Anatomical designation: Brodmann's Area (BA)

Neuron 1 Neuron 2 Neuron 3 Average

1,2,3 22 6

10

Exercise 3. Quantitative digital experiment (with a focus on critical reading of Kole et al., 2002)

Imagine if a 6’5 basketball player tried to be a horse racing jockey. You would feel very sorry for that horse! Similarly, the physical structure of a neuron can correlate with its function. But how does the neuron function? Well, you are not an island… and neither are your brain cells! Neurons in the brain are connected in dense webs of synapses. If we want to learn about how brain cells operate we need to understand how their physical structures underlie their functional qualities.

The hippocampus is an area of the brain strongly associated with memory formation. In fact, if you were to remove the hippocampus you would not be able to form new memories, such is the tragedy that occurred to a man 27 year old man named Henri Gustav Molaison. Suffering from intractable epilepsy he underwent an experimental surgical procedure to remove his hippocampi in both hemispheres of the brain, leaving him with permanent anterograde amnesia. Unable to remember anything new for more than few minutes, he was effectively stuck with his memories of the past for the rest of his life. Although this is a dramatic example of the memory function of the hippocampus, microscopic alterations to neuronal morphology within the hippocampus are also correlated with impaired memory. In fact, that feeling that you experience before an exam… (stress!) is a major contributor to memory impairment and is associated with alterations to neuronal morphology in the hippocampus (Kim & Diamond, 2002).

Kole and colleagues (2002), exposed rats to either 21 days of repeated stress, or a brief 2 day stressor and examined the structure and functions of neurons in the hippocampus. Here, we will retrace their steps to determine how the morphology of neurons may impact their function. The authors of this work decided to analyze both the apical and basilar dendrites of CA3 neurons and then correlated their morphological data with physiological data collected from stimulating axons fibers and recording the activity induced in a post-synaptic neuron. Special terms

1. Hippocampus: specialized region of the brain involved in generating new memories. 2. Cornus ammonis 3(CA3): a part of the hippocampus involved in encoding memories in short term

memory. 3. Apical/basal cone: morphological descriptors for the apical and basilar dendrites of CA3

pyramidal neuronals (see figure 2 in Kole et al., (2002)). 4. Social defeat: a paradigm for inducing stress where a social stressor cannot be escaped. 5. Morphometric analysis: quantitative analysis of morphology 6. Post hoc: after the fact. In this case, electrophysiological experiments occurred first, then

morphometric analysis occurred post hoc. 7. Excitatory post-synaptic potentials (EPSPs): synaptic neurotransmitter induced excitation in a

cell being recorded from. EPSPs give an idea of the nature and strength of connections between neurons.

8. Long term potentiation (LTP): persistent strengthening of a synaptic connection resulting from specific patterns of synaptic activity. Can be induced by high frequency artificial stimulation (tetantic potentiation). EPSPs are faster and larger following LTP induction. Memories are thought to be the manifestation of LTP occurring between neurons.

Introduction questions

1. What was the rationale for conducting this research?

2. What are the author’s hypotheses?

Methods questions

1. What methods did the authors use to reconstruct neuronal morphology?

2. Why did they use this method versus a different method?

3. What do the authors state as the downfall of using this method?

4. How did the authors induce stress in this experiment? Does the method seem valid?

Results exercise 1. Go to neuromoro.org metadata. 2. Click experimental condition, and then click control from the dropdown list. 3. Now click archive, and then select Kole. 4. Click show summary 5. Pick 5 neurons at random (Scroll up and down with your eyes closed!). 6. Click on the neuron name (usually #’s) to open the file. 7. Unfortunately the neurmorpho.org does not separate apical and basilar dendrites like in the Kole

et al., (2002) article. However, by visualizing the neurons in 3-D, you can see that the widest part of the cell is due to the basilar dendrite and the longest length of the cell is roughly due to the length of the apical dendrite (not as clear as the basilar though). Copy down the total widths and total heights for the 5 control neurons in the table below.

8. Go back to the metadata window, keep the archive name the same (Kole), but now change the experimental condition to brief stress.

9. Fill in the same parameters for the brief stress animals. Table 1. Dendritic lengths Control Brief stress Control Brief stress Neuron # Total width Total width Total height Total height 1 2 3 4 5 6 Average Results/discussion questions

1. From the Kole et al., (2002) paper Table 1. Describe how basilar dendrites are qualitatively similar or different to apical dendrites.

2. Does brief stress influence the size of the dendritic tree?

3. Are your results consistent with what is reported in Kole et al., (2002)? If not, provide a brief analysis of what may be different (hint: parameters you analyzed versus what the authors analyzed).

4. Do your results support or refute the hypothesis?

5. How does dendritic morphology correlate with physiology? You may want to work together or ask your instructor for help with this question.

6. If you were to make a prediction about apical and basilar dendrites, what would you expect would be happening to the apical and basilar dendrites in your hippocampus CA3 the night before your final exam?

Exercise 4. Population distributions.

Neurons aren't isolated structures, they usually function together. Seeing specific patterns of neurons in the brain helps us understand what its functions are. Neurons can be identified morphologically, but also using molecular markers that label proteins and genetic material such as RNA (which translates DNA into proteins). Some molecular markers have been identified and are available on databases such as the Allen Brain Atlas (ABA). The benefit of using molecular markers is that you can visualize the pattern of expression of one entire population of neuron type throughout entire brain regions and even the entire brain to understand how they are distributed. Using a technique called In Situ Hybridization, all cells expressing a specific RNA can be visualized using fluorescent compounds. Two inhibitory interneuron subtypes (basket cells, chandelier cells) can be visualized using a single protein that they both express, the calcium binding protein parvalbumin. At this point, you should refer to the PowerPoint slides for detailed instructions on how to navigate the ABA. Brief instructions are below.

1. Go to www.brain-map.org, then click Data & Tools, and select Mouse Connectivity from the menus.

2. Select the REFERENCE DATA from the menu. Check the box for immunohistochemistry (Pvalb + SMI-32), then click View selections.

3. A new window should appear, from here you will launch the high resolution viewer.

4. At this point you are looking at the fluorescently labeled neurons in the olfactory bulb. On the top right corner, there is a menu. Clicking on the key in that menu will launch the reference brain atlas that will appear next to the brain image.

5. Use your scroll wheel to zoom in and out of the images.

6. Search for the six brain regions listed in the table below, describe the brain regions function, and indicate the relative presence of parvalbumin+ interneurons (green) in those regions.

7. How are Pvalb (abbreviation for parvalbumin) cells distributed in the brain?

Brain region Function Level of expression (rank highest (1) to lowest (6).

ABA expression levels

Olfactory bulb Neocortex Striatum Hippocampus Medulla Cerebellum

Although you can clearly see the individual green glowing cells across different brain regions. You may notice that although some regions have such high expression that they seem to meld together, this can be solved by zooming in with the scroll wheel of your mouse. The scientists at the ABA have also conducted analysis of the different proteins expressed by different cell types.

8. Go to www.brain-map.org and select the mouse brain from the data and tools drop down menu.

9. In the search bar, type in parvalbumin and click search. What appears are all the individual experiments done on different brains looking at the expression of Pvalb RNA.

10. click on the first experiment # on the left column of the list.

You should now see this window.

8. The brain here is shown from a sagittal plane. Change the pattern of expression to see a false colored heat map of expression with red coloring being the greatest expression.

9. Hover over the different bars in the bar graph to see the names of the anatomical regions (you may want to ask your instructor for details for some of the names). Notice how the expression level is also shown in raw and log2 format. Finish filling out the table above with the log values!

10. Do your qualitative observations of the expression distribution of Pvalb match up with the ABA analysis?

8. How might the presence of Pvalb be correlated with some property of different brain regions?

9. Imagine a with a scenario where the morphology of Pvalb neuron morphology might contribute to its functioning in these different brain regions to assist in brain functioning. Do some research on this!

Exercise 5. Neuronal morphology presentation. Excitatory neurons, inhibitory interneurons and neurmodulators are not only functionally, but also structurally different from each other. In fact, some of the structural (or morphological) features are what give these cells their astonishing diversity. Using neuromorpho.org, we can narrow down our search criteria to better understand the literature of neuronal morphology and how that contributes to brain processing. 1. In this exercise, you are free to choose any cell type, from any species and present the article where the neurons came from. 2. Use the search--> metadata options in neuromorpho.org to search for a specific cell type of interest (you can read the material above, refer to your textbook, or talk to your instructor for guidance on picking cells).

<-- From the metadata page, species, stage of development and brain region are some options that you can choose to specify! After you choose your search parameters, select a cell and then go to the Reference Article section. This is how the particular cell you chose contributed to science! You can click the PubMed/Abstract Link to access the article, some are freely available. If the article is not freely available, you can use www.pubmed.gov or www.scholar.google.com to find an article related to your specified selections! After you find an article, make a ~15 min PowerPoint presentation. As a general hint, do not fill any given slide with more than 2 paragraphs of text, use bullet points. 1. Introduction Discuss the reasoning and hypothesis of the authors for the current work. 2. Methods Briefly explain the general methods of the article, but know the details in case the class or professor asks you about them! 3. Results This section is very important; always include all of the graphs and figures. Not all tables need to be included because they are generally difficult to read, but if you do include them, make sure to highlight the important data. Often times, if you can't explain a complex graph, your instructor will be able to assist thus making it a learning experience! 4. Discussion

Last but not least, review the results in the context of the original hypothesis or reasoning. Articulate how these results contribute to the overall understanding of the topic and if there is any future research that is proposed.

References

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