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Dendrodendritic synapse through axodendritic synapse at same dendrite?

Dendrodendritic synapse through axodendritic synapse at same dendrite?



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Reading Wikipedia's article of dendrodendritic synapse, I find that:

Dendrodendritic synapses are activated in a similar fashion to axodendritic synapses in respects to using a chemical synapse. These chemical synapses receive a depolarizing signal from an incoming action potential which results in an influx of calcium ions that permit release of Neurotransmitters to propagate the signal the post synaptic cell. There is also evidence of bi-directionality in signaling at dendrodendritic synapses. Ordinarily, one of the dendrites will display inhibitory effects while the other will display excitatory effects.

Now I was wondering, does dendrodendritic synapse occur only when the neuron reaches the threshold action potential and "fires" or is it possible that dendrodendritic synapse occurs as a result of, for example, an axodendritic synapse at the same dendrite? (even though the neuron doesn't fire)

Edit

Clearly, we can see that the dendrite has multiple 'endings'. I was under the impression that a synapse can happen at any such 'ending'. Assuming that a synapse happens at one ending of the dendrite, is it viable that anything happens to a neighbouring neuron that is connected with a dendrodendritic synaptic connection to the other ending of the dendrite?


I'm not sure if you are asking if an axon that sends a signal to a dendrite would then be released from that dendrite to another dendrite?

I don't see how this is possible seeing as the dendrite is already paired with the axon and downstream of said dendrite there would be a neuron.

A dendrodenritic synapse is two dendrites of two different neurons in contact with each other. For there to be a signal an action potential must have been reached.

Synapse is a junction between two neurons where chemical signaling occurs, but it is not the definition of a signal occurring. If that makes sense.

It seems like you are confused on the location and anatomy of a synapse.

There wouldn't be an axodendritic synapse followed by a dendrodendritic synapse then the neuron. It would either be axodendritic or dendrodendritic. Now there can be multitudes of connections between neurons but I don't think that is what you were asking.

Edit: Seeing your edit makes your question much clearer.

If the signal from the axodendritic synapse excites the neuron enough to reach action potential then that signal would be sent out through its synapses, including the dendrodendritic ones. So I guess in this way it was a "consequence" of the axodendritic synapse.

Though I would rather you think about it in that the action potential of one neuron sent a signal through it's connections to the neighborhing neuron, thus causing that neuron to reach action potential and further send out the signal. It's not really a "consequence" of the synapse, the synapse is more a pathway for the signal to travel.

The stimulus for the action potential is what causes a signal to fire and travel through a synapse.

Hopefully that answers your question.


Sequential development of synapses in dendritic domains during adult neurogenesis

During the process of integration into brain circuits, new neurons develop both input and output synapses with their appropriate targets. The vast majority of neurons in the mammalian brain are generated before birth and integrate into immature circuits while these are being assembled. In contrast, adult-generated neurons face an additional challenge as they integrate into a mature, fully functional circuit. Here, we examined how synapses of a single neuronal type, the granule cell in the olfactory bulb, develop during their integration into the immature circuit of the newborn and the fully mature circuit of the adult rat. We used a genetic method to label pre and postsynaptic sites in granule neurons and observed a stereotypical development of synapses in specific dendritic domains. In adult-generated neurons, synapses appeared sequentially in different dendritic domains with glutamatergic input synapses that developed first at the proximal dendritic domain, followed several days later by the development of input-output synapses in the distal domain and additional input synapses in the basal domain. In contrast, for neurons generated in neonatal animals, input and input-output synapses appeared simultaneously in the proximal and distal domains, respectively, followed by the later appearance of input synapses to the basal domain. The sequential formation of synapses in adult-born neurons, with input synapses appearing before output synapses, may represent a cellular mechanism to minimize the disruption caused by the integration of new neurons into a mature circuit in the adult brain.

Integration of new neurons continues throughout life in the adult mammalian olfactory bulb (OB) (1, 2). During the process of integration into brain circuits, new neurons develop both input and output synapses with their appropriate targets. Whereas the majority of neurons in the olfactory bulb integrate into an immature circuit while it is being assembled, neurons generated in adulthood face an additional challenge as they integrate into a mature, fully functional circuit. In particular, the formation of synapses by a new neuron in a functioning circuit may interfere with circuit operation and, thus, it could result in maladaptive behaviors. Additionally, it is still not known whether new neurons integrating into the neonatal and adult olfactory system have the same or different functions in the circuit and, therefore, adult- and neonatal-generated neurons could employ different modes of integration. To compare how new neurons are added to neonatal and adult circuits, we examined the pattern of synapse development of a single neuronal type, the granule cell (GC) in the olfactory bulb, during its integration into the immature circuit of the newborn and the mature circuit of the adult rat.

The majority of neurons added to the OB of adult rats are GC neurons. GCs are axonless inhibitory interneurons that have both a basal dendrite and an apical dendrite (Fig. 1A). The apical dendrite can be divided into an unbranched segment emerging from the soma followed by a branched segment (distal domain). The basal dendrite (basal domain) and unbranched apical dendrite receive axo-dendritic glutamatergic input from axon collaterals of the OB's projection neurons and from the olfactory cortices (3–6). The distal domain of the apical dendrite has bidirectional dendro-dendritic synapses present in spines where input and output synapses are colocalized and functionally coupled. These bidirectional synapses receive glutamatergic input synapses from the lateral dendrites of the OB's projection neurons and release GABA back onto these projection neurons (7). These dendro-dendritic synapses in the distal domain are the exclusive output of GCs, and are responsible for local inhibition of the projection neurons in the olfactory bulb (7–9). Activation of axo-dendritic input sites in the basal domain and the unbranched apical dendrite is thought to globally excite the GCs, thus facilitating recurrent dendro-dendritic inhibition in the distal domain (8, 9).

To visualize the development and distribution of input and output synaptic sites in entire GCs, we labeled their progenitors with genetic markers localized specifically to synapses. To visualize glutamatergic input synapses, we expressed a PSD-95:GFP fusion protein. PSD-95 is a scaffolding protein that localizes to the postsynaptic density of glutamatergic synapses (10) and has been extensively used as a postsynaptic marker of glutamatergic synapses (11–14). PSD-95 is present in virtually all GC glutamatergic synapses, where it is restricted to clusters in the postsynaptic density (15), is already highly expressed at birth (16), and appears early during assembly of the postsynaptic density (15). To label presynaptic synapses (output synapses), we used a synaptophysin:GFP fusion protein. Synaptophysin:GFP was the first synaptic vesicle protein to be cloned and has been extensively used to study the distribution and density of presynaptic sites in neurons both in vitro and in vivo (17–22).

We labeled progenitors for GC neurons with these genetic markers to visualize their synapse development, and observed that in adult-generated neurons, PSD-95:GFP-positive clusters (PSD + C) developed initially at high density in the proximal 15% of the unbranched apical dendrite. We therefore defined the proximal 15% of the unbranched apical dendrite as the proximal domain. In contrast, PSD + Cs in the basal domain only developed later together with PSD + Cs in the distal domain. The late development of PSD + Cs in the distal domain was tightly coupled to the development of output synapses as labeled by synaptophysin:GFP + clusters (Syp + C) in the same domain. In contrast, neonatal-generated GCs developed PSD + Cs and Syp + Cs in the distal domain simultaneously to PSD + Cs in the proximal and before those in the basal domain. These observations revealed that new GCs in an adult brain environment follow a pattern of integration that differs from that during the initial circuit assembly when most GCs are generated. The sequential formation of synapses in adult-born neurons, with proximal input synapses appearing before output synapses, may represent a cellular adaptation to minimize the disruption caused by the integration of new neurons into a functioning circuit.


Components and Functions of the Synapse

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B. The connection between two neurons is called a synapse, a term derived from the Latin word that means “to grasp.” The synapse consists of many components that are essential to the flow of information from one neuron to another. Through an outline of these components, we can begin to understand how processes such as synaptic transmission are possible.

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In regards to our understanding of the synapse, it is important to note the accomplishments of Charles Scott Sherrington and his initial work that first outlined the basic properties of the synapse. One of the properties, reflexes, or automatic muscular responses to stimuli was demonstrated by pinching a dog’s leg in his experiments. Sherrington demonstrated that a short delay occurs before the dog flexes the pinched leg and extends the others. This finding is important because he discovered that transmission through the reflex arc is slower than transmission through an equivalent length of axon. This led him to conclude that the delay must occur where one neuron communicates with another, a concept he introduced as a synapse.

Sherrington’s work outlines other basic properties of the synapse such as temporal and spatial summation. Temporal summation is a concept where a single stimulus (a single pinch) is too weak to reach threshold to produce an action potential in the postsynaptic neuron. When stimuli occur in succession (i.e., pinching the dog’s foot several times), however, the combined effect can be enough to produce an action potential, thereby causing a reflex. With spatial summation, several stimuli occurring at different points on the body combine their effects on a neuron. By pinching multiple places on a dog’s body, for example, the combined effect can be enough to produce a reflex. Sherrington work also infers the property of inhibitory synapses. This is a concept where after a reflex (action potential) occurs, hyperpolarization causes the cell to become more negative, therefore making it difficult for another action potential to immediately occur.

As technology has improved, so has our understanding of the mechanisms of the synapse. Before we can understand the components and functioning of the synapse, however, it is important to first consider neurons. Neurons have the responsibility of producing all of our movements, thoughts, memories, and emotions. There are four major types of neurons: motor neurons, sensory, interneurons, and projection neurons. Each of these neurons shares a common structure and function. For example, the soma, or cell body, contains the cell’s nucleus, most of the cytoplasm, and structures that convert nutrients into energy and eliminate waste materials for each of these neurons. This quality is not unique, however, as this is also a component of any cell in the body. The quality that separates neurons from other cells are dendrites, extensions that branch out from the soma to receive information from other neurons, and axons, which extend like a tail from the cell body and carries information to other locations. Branches at the end of the axon culminate in swellings called bulbs or terminals. The terminals contain chemical neurotransmitters, which the neuron releases to communicate with a muscle or an organ or the next neuron in the chain.

As introduced earlier, the connection between two neurons is called a synapse, a site where most communication among neurons occurs. To clarify the function and purpose of the synapse, it is important to understand the sequence of major chemical events that occur at the synapse. At the site of the cell body, neurons synthesize chemicals that serve as neurotransmitters, specifically peptide neurotransmitters. The neuron then transports the peptide neurotransmitters to the axon terminals. Action potentials then travel down the axon where at the presynaptic terminal, the action potential enables calcium to enter the cell. The calcium then releases neurotransmitters from the terminals and into the synaptic cleft (the space between the presynaptic and postsynaptic neurons). Next, the neurotransmitter binds to the receptor, diffusing across the cleft and altering the activity of the postsynaptic neuron. This alteration also causes the neurotransmitter molecules to separate from their receptors. Finally, reuptake of the neurotransmitter occurs, recycling neurotransmitters back into the presynaptic neuron. All of these events lead a successful transmission at the point of the synapse.

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There are different types of synapses used in the flow of information from neuron to neuron. Axodendritic synapses, synapses of axon terminal buttons on dendrites, terminate on dendritic spines, small synaptic buds that cover the surfaces of many dendrites. Also common are axosomatic synapses, synapses of axon terminal buttons on somas. Although axodendritic and axosomatic synapses are the most common synaptic arrangements, there are several others. For example, there are dendrodendritic synapses, which are capable of transmission in either direction and there are axoaxonal synapses, which can mediate presynaptic inhibition. Also, there are directed synapses, synapses at which the site of neurotransmitter release and the site of neurotransmitter reception are in close proximity. This is a common arrangement, but, there are also many nondirected synapses in the nervous system. Nondirected synapses are synapses at which the site of release is at some distance from the site of reception. In this type of arrangement, neurotransmitter molecules are released from a series of varicosities along the axon and its branches and thus are widely dispersed to surrounding targets. Because of their appearance, these synapses are often referred to as string-of-beads synapses.

In conclusion, with the initial contributions of Sherrington and with what is known about neurotransmission today, we have been able to outline the basic components and functions of the synapse. The synapse, in turn, is an essential component for the transmission of neurons, which enables the human body to respond to events in the environment. By acting as a “bridge” between the neurons, the synapse is helping to control human movements, thoughts, memories, and emotions. The synapse is truly a necessary component in the human body.

B. The connection between two neurons is called a synapse, a term derived from the Latin word that means “to grasp.” The synapse consists of many components that are essential to the flow of information from one neuron to another. Through an outline of these components, we can begin to understand how processes such as synaptic transmission are possible.

In regards to our understanding of the synapse, it is important to note the accomplishments of Charles Scott Sherrington and his initial work that first outlined the basic properties of the synapse. One of the properties, reflexes, or automatic muscular responses to stimuli was demonstrated by pinching a dog’s leg in his experiments. Sherrington demonstrated that a short delay occurs before the dog flexes the pinched leg and extends the others. This finding is important because he discovered that transmission through the reflex arc is slower than transmission through an equivalent length of axon. This led him to conclude that the delay must occur where one neuron communicates with another, a concept he introduced as a synapse.

Sherrington’s work outlines other basic properties of the synapse such as temporal and spatial summation. Temporal summation is a concept where a single stimulus (a single pinch) is too weak to reach threshold to produce an action potential in the postsynaptic neuron. When stimuli occur in succession (i.e., pinching the dog’s foot several times), however, the combined effect can be enough to produce an action potential, thereby causing a reflex. With spatial summation, several stimuli occurring at different points on the body combine their effects on a neuron. By pinching multiple places on a dog’s body, for example, the combined effect can be enough to produce a reflex. Sherrington work also infers the property of inhibitory synapses. This is a concept where after a reflex (action potential) occurs, hyperpolarization causes the cell to become more negative, therefore making it difficult for another action potential to immediately occur.

As technology has improved, so has our understanding of the mechanisms of the synapse. Before we can understand the components and functioning of the synapse, however, it is important to first consider neurons. Neurons have the responsibility of producing all of our movements, thoughts, memories, and emotions. There are four major types of neurons: motor neurons, sensory, interneurons, and projection neurons. Each of these neurons shares a common structure and function. For example, the soma, or cell body, contains the cell’s nucleus, most of the cytoplasm, and structures that convert nutrients into energy and eliminate waste materials for each of these neurons. This quality is not unique, however, as this is also a component of any cell in the body. The quality that separates neurons from other cells are dendrites, extensions that branch out from the soma to receive information from other neurons, and axons, which extend like a tail from the cell body and carries information to other locations. Branches at the end of the axon culminate in swellings called bulbs or terminals. The terminals contain chemical neurotransmitters, which the neuron releases to communicate with a muscle or an organ or the next neuron in the chain.

As introduced earlier, the connection between two neurons is called a synapse, a site where most communication among neurons occurs. To clarify the function and purpose of the synapse, it is important to understand the sequence of major chemical events that occur at the synapse. At the site of the cell body, neurons synthesize chemicals that serve as neurotransmitters, specifically peptide neurotransmitters. The neuron then transports the peptide neurotransmitters to the axon terminals. Action potentials then travel down the axon where at the presynaptic terminal, the action potential enables calcium to enter the cell. The calcium then releases neurotransmitters from the terminals and into the synaptic cleft (the space between the presynaptic and postsynaptic neurons). Next, the neurotransmitter binds to the receptor, diffusing across the cleft and altering the activity of the postsynaptic neuron. This alteration also causes the neurotransmitter molecules to separate from their receptors. Finally, reuptake of the neurotransmitter occurs, recycling neurotransmitters back into the presynaptic neuron. All of these events lead a successful transmission at the point of the synapse.

There are different types of synapses used in the flow of information from neuron to neuron. Axodendritic synapses, synapses of axon terminal buttons on dendrites, terminate on dendritic spines, small synaptic buds that cover the surfaces of many dendrites. Also common are axosomatic synapses, synapses of axon terminal buttons on somas. Although axodendritic and axosomatic synapses are the most common synaptic arrangements, there are several others. For example, there are dendrodendritic synapses, which are capable of transmission in either direction and there are axoaxonal synapses, which can mediate presynaptic inhibition. Also, there are directed synapses, synapses at which the site of neurotransmitter release and the site of neurotransmitter reception are in close proximity. This is a common arrangement, but, there are also many nondirected synapses in the nervous system. Nondirected synapses are synapses at which the site of release is at some distance from the site of reception. In this type of arrangement, neurotransmitter molecules are released from a series of varicosities along the axon and its branches and thus are widely dispersed to surrounding targets. Because of their appearance, these synapses are often referred to as string-of-beads synapses.

In conclusion, with the initial contributions of Sherrington and with what is known about neurotransmission today, we have been able to outline the basic components and functions of the synapse. The synapse, in turn, is an essential component for the transmission of neurons, which enables the human body to respond to events in the environment. By acting as a “bridge” between the neurons, the synapse is helping to control human movements, thoughts, memories, and emotions. The synapse is truly a necessary component in the human body.

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Contents

Complex interconnections of neurons form neural networks, which are responsible for various types of computation in the brain. Neurons receive inputs mainly through dendrites, which play a role in spatio-temporal computation, leading to the firing of an action potential which subsequently travels to synaptic terminals passing through axons. [12] Based on their locations, synapses can be classified into various kinds, such as axo-dendritic synapse, axo-somatic synapse, and axo-axonal synapse. The prefix here indicates the part of the presynaptic neuron (i.e., ‘axo-’ for axons), and the suffix represents the location where the synapse is formed on the postsynaptic neuron (i.e., ‘-dendritic’ for dendrites, ‘-somatic’ for cell body and ‘-axonic’ for synapses on axons). [13] Synapse location will govern the role of that synapse in a network of neurons. In axo-dendritic synapses, the presynaptic activity will affect the spatio-temporal computation in postsynaptic neurons by altering electrical potential in the dendritic branch. Whereas the axo-somatic synapse will affect the probability of firing an action potential in the postsynaptic neuron by causing inhibitory or excitatory effects directly at the cell body. [14]

Whereas the other types of synapses modulate postsynaptic neural activity, the axo-axonic synapses show subtle effects on the network-level neural information transfer. In such synapses, the activity in presynaptic neurons will not change the membrane potential (i.e., depolarize or hyperpolarize) of the cell body of postsynaptic neurons because presynaptic neurons project directly on the axons of the postsynaptic neurons. Thus, the axo-axonic synapse will mainly affect the probability of neurotransmitter vesicle release in response to an action potential firing in the postsynaptic neuron. Unlike other kinds of synapses, the axo-axonic synapse manipulates the effects of a postsynaptic neuron’s firing on the neurons further downstream in the network. [2] Due to the mechanism of how axo-axonic synapses work, most of these synapses are inhibitory, [6] and yet a few show excitatory effects in postsynaptic neurons. [9]

The first direct evidence of the existence of axo-axonic synapses was provided by E. G. Gray in 1962. Gray produced electron microscopy photographs of axo-axonic synapses formed on the terminals of muscle afferents involved in the spinal somatic reflex arc in a cat’s spinal cord slices. [15] Later, Gray coined the term ‘axo-axonic’ after getting photographic confirmation from as many as twelve axo-axonic synapses. Within the next two years, scientists found axo-axonic synapses in various other places in the nervous system in different animals, such as in the retina of cats and pigeons, [16] in the lateral geniculate nucleus of monkeys, [17] in the olfactory bulb of mice, [18] and in various lobes in the octopus brain. [19] This further confirmed the existence of axo-axonic synapses in the brain across animal phyla.

Prior to the discovery of axo-axonic synapses, physiologists predicted the possibility of such mechanisms as early as in year 1935, following their observations of electrophysiological recordings and quantal analysis of brain segments. [20] They had observed inhibitory responses in postsynaptic motoneurons in the slice preparation of the monosynaptic reflex arc. During simultaneous recordings from presynaptic and postsynaptic neurons, the physiologists could not make sense of the infrequent inhibition observed in the postsynaptic neuron, with no membrane potential changes in the presynaptic neuron. At that time, this phenomenon was known as “presynaptic inhibitory action”, the term proposed by Karl Frank in 1959 [14] and later well summarized by John Eccles in his book. [10] After Gray’s finding of the axo-axonic synapse in 1962, scientists confirmed that this phenomenon was in fact due to the axo-axonic synapse present in the reflex arc. [10]

More recently, in 2006 researchers discovered the first evidence of excitatory effects caused by an axo-axonic synapse. They found that GABAergic neurons project onto the axons of pyramidal cells in the cerebral cortex to form axo-axonic synapse and elicit excitatory effects in cortical microcircuits. [9]

Below are the brain locations where axo-axonic synapses are found in different animals.

Cerebellar cortex Edit

The axo-axonic synapse in the cerebellar cortex originally appeared in one of the drawings of Santiago Ramón y Cajal in his book published in 1909. [21] Later using electron microscopy, it was confirmed that the basket cell axon projects on the axon hillock of Purkinje cells in the cerebellar cortex in cats and other mammals, forming axo-axonic synapses. [5] The first electrophysiological characterization of an axo-axonic synapse formed on Purkinje cells was done in 1963, where the presynaptic basket cell axons were found to inhibit the terminal output of postsynaptic Purkinje cells through the axo-axonic synapse. [22] Network-level study revealed that the granule cells (a.k.a. the parallel fibers) which activated Purkinje cells, also activated the basket cells which subsequently inhibited the effect of Purkinje cells on the downstream network. [23]

Cerebral cortex Edit

Axo-axonic synapses are found In the visual cortex (in V1 and V2) in mammals, and have been well studied in cats, rats and primates such as monkeys. [4] [24] [25] [26] [27] The synapse is formed on the initial segments of the axons of pyramidal cells in several layers in the visual cortex. The projecting neurons for these synapses come from various parts of the central nervous system and neocortex. Similarly, axo-axonic synapses are found in the motor cortex, in the subiculum and in the piriform cortex. [4] In the striate cortex, as the Golgi’s method and electron microscopy revealed, as many as five axo-axonic synapses are formed onto a single pyramidal cell. [4] In the cerebral cortex, inhibitory axo-axonic synapses may play a widespread role in network level activity by enabling synchronized firing of pyramidal cells, essentially by modulating the threshold for output of these cells. [27] [4] These synapses are also found on the initial segments of axons in pyramidal cells in the somatosensory cortex, and in the primary olfactory cortex which are found to be the inhibitory kind. [28] [29] Studying the locations of axo-axonic synapses in the primary olfactory cortex, researchers have suggested that axo-axonic synapses may play a critical role in synchronizing oscillations in the piriform cortex (in the olfactory cortex), which aids olfaction. [30] The axo-axonic synapses are also found in the hippocampus. These synapses are found to be formed mainly on principal cells in stratum oriens and stratum pyramidale and rarely on stratum radiatum they commonly receive projections from GABAergic local interneurons. [31] The horizontal interneurons show a laminar distribution of dendrites and are involved in axo-axonic synapses in the hippocampus, which get direct synaptic inputs from CA1 pyramidal cells. [3] Thus, in general, these studies indicate that axo-axonic synapses can provide a basic mechanism of information processing in the cerebral cortex. [32] [30] [31]

Basal ganglia Edit

Microscopy studies in the striatum previously suggested rare occurrence of axo-axonic synapses in individual sections. Extrapolations from the topological data suggest much higher counts of such synapses in the striatum where the therapeutic role of the axo-axonic synapses in treating schizophrenia has been postulated previously. [33] In this study, authors examined 4,811 synapses in rat striatum sections, and 15 of them were found to be the axo-axonic synapses. These axo-axonic synapses are formed by dopaminergic inhibitory interneurons (on the presynaptic side) projecting onto the axons of glutamatergic cortico-striatal fibers in the rat striatum. [33]

Brainstem Edit

Axo-axonic synapses are found in the spinal trigeminal nucleus in the brainstem. [34] Electron microscopy studies on the kitten brainstem quantified synaptogenesis of axo-axonic synapses in the spinal trigeminal nucleus at different development ages of the brain. Authors identified the synapses by counting vesicles released in the synaptic cleft, which can be observed in the micrographs. Axo-axonic contacts are shown to consistently increase throughout the development period, starting from the age of 3 hours to the age of 27 days in kittens. The highest rate of synaptogenesis is during the first 3 to 6 days, at the end of which, the kitten’s spinal trigeminal nucleus will have nearly half of the axo-axonic synapses present in adult cats. Later, between 16 to 27 days of age, there is another surge of axo-axonic synaptogenesis. [34] Axo-axonic synapses are also observed in the solitary nucleus (also known as nucleus of the solitary tract) uniquely in the commissural portion in the neuroanatomical studies, which used 5-hydroxydopamine to label axo-axonic synapses. Axo-axonic synapses are formed on baroreceptor terminals by the presynaptic adrenergic fibers, and are proposed to play a role in baroreflex. [35]

Spinal Cord Edit

Axo-axonic synapses are found in the mammalian spinal reflex arc [36] [37] [38] and in Substantia gelatinosa of Rolando (SGR). [39] In the spinal cord, axo-axonic synapses are formed on the terminals of sensory neurons with presynaptic inhibitory interneurons. These synapses are first studied using intracellular recordings from the spinal motoneurons in cats, and have been shown to cause presynaptic inhibition. [40] This seems to be a common mechanism in spinal cords, in which GABAergic interneurons inhibit presynaptic activity in sensory neurons and eventually control activity in motor neurons enabling selective control of muscles. [41] In efforts to quantify the occurrence of axo-axonic synapses in the SGR region in rats, 54 such synapses were found among the total 6,045 synapses examined. These 54 axo-axonic synapses were shown to have either agranular vesicles or large granular vesicles. [39]

Vestibular system Edit

Axo-axonic synapses are found in the lateral vestibular nucleus in rats. Axo-axonic synapses are formed from the small axons of interneurons onto the axon terminals of large axons, which are upstream to the main dendritic stem. [42] Interestingly, the authors claimed that axo-axonic synapses, which are abundant in rats, are absent in the lateral vestibular nucleus in cats. [42] They note that the types of axon terminals identified and described in cats are all found in rats, but the reverse is not true because the axons forming the axo-axonic synapses are missing in cats. These synapses are proposed to enable complex neural computation for the vestibular reflex in rats. [42]

Hindbrain Edit

Axo-axonic synapses are found in the mauthner cells in goldfish. [43] [44] The axon hillock and initial axon segments of mauthner cells receive terminals from extremely fine unmyelinated fibers, which cover the axon hillock with helical projections. These helical projections around mauthner cells are also known as the axon cap. The difference between the axo-axonic synapses and other synapses on mauthner cells is that synapses on dendrites and soma receive myelinated fibers, while axons receive unmyelinated fibers. [43] [44] Mauthner cells are big neurons which are involved in fast escape reflexes in fish. Thus, these axo-axonic synapses could selectively disable the escape network by controlling the effect of mauthner cells on the neural network further downstream. Studying the morphological variation of the axo-axonic synapses at the axon hillock in mauthner cells suggests that, evolutionarily, these synapses are more recent than the mauthner cells. Response to the startle can be mapped phylogenetically, which confirms that basal actinopterygian fish, with little to no axo-axonic synapses on mauthner cells, show worse escape response than fish with axo-axonic synapses. [45]

Neuromuscular junction Edit

Inhibitory axo-axonic synapses are found in the crustacean neuromuscular junctions and have been widely studied in Crayfish. [6] [7] [46] Axo-axonic synapses are formed on the excitatory axons as a postsynaptic neuron by the motor neurons from the presynaptic side. Motor neurons, which is the common inhibitor in crab limb closers and limb accessory flexors, form axo-axonic synapses in addition to the neuromuscular junction with the muscles in crayfish. [46] These synapses were first observed in 1967, [6] when they were found to cause presynaptic inhibition in leg muscles of crayfish and crabs. Subsequent studies found that axo-axonic synapses showed varying numbers of occurrence based on the location of the leg muscles from the nervous system. For instance, proximal regions have thrice as many axo-axonic synapses than the central regions. [7] These synapses are proposed to function by limiting neurotransmitter release for controlled leg movements. [7]

An example of the physiological role of axo-axonic synapses, which are formed by GABAergic inhibitory interneurons to the axons of granule cells, is in eliciting spontaneous seizures, which is a key symptom of Intractable Epilepsy. [47] The presynaptic inhibitory interneurons, which can be labeled by cholecystokinin and GAT-1, are found to modulate the granule cells’s spike output. The same cells subsequently project excitatory mossy fibers to pyramidal neurons in the hippocampal CA3 region.

One of the two leading theories for the pathoetiology of schizophrenia is the glutamate theory. Glutamate is a well studied neurotransmitter for its role in learning and memory, and also in the brain development during prenatal and childhood. Studies of rat striatum found inhibitory axo-axonic synapses formed on the glutamatergic cortico-striatal fibers. [33] They proposed that these axo-axonic synapses in the striatum could be responsible for inhibiting the glutamatergic neurons. Additionally, these dopaminergic synapses are also proposed to cause hyperdopaminergic activity and become neurotoxic for the postsynaptic glutamatergic neurons. [48] This mechanism is proposed to be a possible mechanism for glutamate dysfunction in observed schizophrenia.

A study on the spinal cord in mice suggests that the sensory Ig/Caspr4 complex is involved in the formation of axo-axonic synapses on proprioceptive afferents. These synapses are formed through projection of GABAergic interneurons on sensory neurons, which is upstream to the motor neurons. In the axo-axonic synapse, expressing NB2 (Contactin5)/Caspr4 coreceptor complex in postsynaptic neurons along with expressing NrCAM/CHL1 in presynaptic interneurons results in the increased numbers of such synapses forming in the spinal cord. [49] Also, knocking out NB2 from the sensory neurons reduced the number of axo-axonic synapses from GABAergic interneurons, which suggests the necessity and the role of NB2 in synaptogenesis of axo-axonic type of synapses. [49] [36]


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Results

Using an acute brain slice preparation, 42 GnRH neurons from adult GnRH-green fluorescent protein (GFP) mice (60–70 days old) were patched and filled with 0.5% biocytin. Only 1 GnRH neuron was filled per coronal brain slice and a total of 8 male and 6 female mice were used. Filled GnRH neurons (males, 23 females, 19) represented a random sample of neurons spread throughout the GnRH neuron distribution. The majority of filled neurons were located in the rostral preoptic area (rPOA) (n = 29, 69%), while 11 were in the medial septum (26%) and 2 in the lateral anterior hypothalamic area (5%).

Confocal imaging of sections dual-labeled for GFP and biocytin showed that 36 of the 42 (86%) filled GnRH neurons had dendrites that exhibited close appositions with multiple other GnRH neuron dendrites identified by their endogenous GFP expression (Fig. 1). Processes were identified as dendrites (rather than axons) by noting either a tapered shape extending from their soma of origin, or through the presence of spines along their length. Two distinct types of dendro-dendritic interaction were noted a vertical bundling pattern (83%) (Fig. 1) and a horizontal intersecting pattern (17%) (Fig. 2).

Biocytin-filled GnRH neurons exhibiting dendro-dendritic bundling with other GnRH neurons in the verticle orientation. (A) Montage of low power confocal images through a thick slice of the rPOA shows GnRH-GFP neurons (black) and a single GnRH neuron that was filled with biocytin and subsequently labeled with a fluorescent marker (traced in red). (B) High power projection of confocal images of the filled neuron in A, showing endogenous GFP expression in multiple GnRH soma and in a plexus of processes (green) and fluorescently labeled, biocytin-filled GnRH neuron (yellow/red). (C and D) Three-dimensional isosurface rendering of GFP (green) and biocytin-filled (yellow) dendrites (rectangle in A) that bundle together viewed from 2 angles 180° apart. Arrowhead indicates 2 bundled dendrites arrow shows the bundling of 3 dendrites. (E) Montage of high power confocal image stacks showing another filled GnRH neuron exhibiting dendritic contacts and bundling in the vertical orientation. (F) A schematic traced from confocal image data illustrates 15 apparent close associations between the filled dendrite (red) and other GnRH neuron dendrites (blue). Three-dimensional rendered images of the filled dendrite and apposing dendrites created from high power confocal images are shown for the highlighted regions. (G) Two juxtaposed GnRH neuron dendrites can be seen in the upper portion of the image (arrowheads), and 3 dendrites are found bundling together further down the length of the dendrite (arrow). (H) Points of contact are apparent between the filled dendrite and 2 dendrites that run in parallel with the filled dendrite (arrowheads). (Scale bars: B, 50 μm C, D, G, and H, 5 μm.)

Dendro-dendritic associations in the horizontal orientation. (A) Montage of low power confocal images through a thick brain slice through the rPOA shows GnRH-GFP neurons (black) and a single GnRH neuron that was filled with biocytin and subsequently labeled with a fluorescent marker (traced in red). GnRH-GFP neuron dendrites in apparent close apposition with the dendrite of the filled GnRH neuron are traced in blue. (B) High power confocal projection of the area highlighted in panel A showing a portion of the filled dendrite (yellow) and other endogenously fluorescent GnRH processes. Arrows indicate 4 dendrites (a–d) found in close apposition with the filled dendrite. (C) Isosurface rendering of the dendrites in close apposition show the perpendicular nature of these interactions. (D) Individual optical sections (0.32 μm thick) showing the close apposition of dendritic processes. (Scale bars: A, 50 μm B, 10 μm.)

Vertically-orientated GnRH Neuron Dendrite Bundling.

Fig. 1A shows a representative brain slice from the rPOA containing multiple, scattered GnRH neurons and their processes. As has been noted previously (7) the bipolar shape and processes of GnRH neurons usually exhibit an “inverted Y”-type orientation in the coronal plane medial septal GnRH neurons have a vertical or 90° orientation while rPOA GnRH neurons have an approximate 45° orientation (Fig. 1A). This topography becomes even more apparent when the full extension of the GnRH neuron dendrite is viewed after biocytin filling (Fig. 1 A and B). A typical bipolar biocytin-filled GnRH neuron is shown in red within the slice in which it was filled (Fig. 1A) and at higher power in a projection of confocal stacks taken through the slice (Fig. 1B). Confocal analysis revealed that GnRH neuron dendrites extending in a similar direction often appeared to be juxtaposed and bundle together. Panels C and D illustrate, by way of a 3-dimensional rendering from high-power confocal images, the bundling of 3 GnRH neuron dendrites (1 filled with biocytin and the other 2 visualized by GFP expression) shown from 2 different angles.

A further example of a GnRH neuron exhibiting vertical dendritic bundling is shown in Fig. 1 E–H. The dendrite of this GnRH neuron was found to extend 1,025 μm until it exited the brain slice, and had 15 close appositions with other GFP-expressing GnRH dendrites (Fig. 1 E and F). Isosurface rendered images of the filled dendrites and portions of the bundling dendrites are shown for 2 parts of the GnRH neuron dendrite. Panel G shows 1 fine dendrite running in parallel to the filled dendrite over 40 μm of dendritic length (arrowheads) with 2 additional GnRH neuron dendrites seen coming together with the filled dendrite in a bundle (arrow). Panel H shows 2 dendrites twisting around the filled GnRH neuron dendrite at different levels (arrowheads).

GnRH neuron dendrites exhibiting vertical bundling were found to have (mean ± SEM) 4.0 ± 0.6 contacts/filled dendrite (range 1–15, n = 30). This was not different between males (4.3 ± 0.6) and females (3.6 ± 1.0) or dependent upon location MS GnRH neurons (3.5 ± 0.7), rPOA GnRH neurons (4.3 ± 0.9).

Horizontal Interactions between GnRH Neuron Dendrites.

Fig. 2A shows a biocytin-filled GnRH neuron (red) with the less common (17%) pattern of a dendritic extension that runs in the horizontal plane intercepting vertically-orientated GnRH neuron dendrites. In this example, the horizontally extended dendrite was found to intercept 12 other GnRH neuron dendrites 4 such appositions are depicted at higher power and in individual optical slices (Fig. 2 B–D). GnRH neuron dendrites exhibiting horizontal interactions were found to have (mean ± SEM) 3.3 ± 0.7 contacts/filled dendrite (range 1–12, n = 6).

Electron Microscopy Confirms Direct Dendro-dendritic Appositions between GnRH Neurons.

Preembedded, silver-enhanced immunogold labeling for both GnRH and GFP was performed on brain tissue from 2 female GnRH-GFP transgenic mice. We have found that the combination of GnRH and GFP immunolabeling facilitates the analysis of GnRH neuron dendrites as GFP molecules diffuse beyond the distribution of GnRH peptide in GnRH neuron dendrites. Dendritic elements of GnRH neurons were identified in semi-thin sections at the light microscopic level by their light brown label. Identified regions with dendritic labeling were trimmed and cut into serial ultra-thin sections. Electron microscopy showed silver-enhanced gold particle labeling in dendritic compartments, defined by their diameter (larger than axons in the same field), and arrangement of microtubules (asterisks, Figs. 3 and 4). Silver-enhanced gold particles were found associated with dense core vesicles in GnRH neuron axon terminals but also unassociated with vesicles in the soma and dendrites of the cell due to co-labeling with GnRH and GFP. Labeled dendrites were found in close association with one another without any intervening elements in both animals (Fig. 3 A–D). Adjacent GnRH neuron dendrites were often found with plasmalaemma specializations between them, including punctae and zonula adherens, also known as attachment plates (Fig. 3 A–D, arrows). No evidence of gap junction specializations between GnRH neuron dendrites was found. GnRH neuron dendrites cut in the longitudinal plane were found in close association, without any intervening elements, for distances greater than 5 μm.

Ultrastructural evidence of bundling GnRH dendrites. (A) Two distinct silver-enhanced immunogold labeled GnRH neuron dendrites (D1 and D2, pseudocolored for clarity) in parallel with membranes juxtaposed. Silver-enhanced immunogold label appears as scattered black dots. Note that both GnRH and GFP were labeled and that the latter does not associate with dense core vesicles. (A) Asterisk indicates an area of loosely arranged microtubules running longitudinally through the labeled dendrites. Arrow indicates a zonula adherens junction between the 2 dendrites. (B and C) Higher power view in adjacent serial sections through the juxtaposed dendrites shown in A, showing additional zonula adherens membrane specializations. (D) Another example of adjacent GnRH neuron dendrites (D1 and D2, pseudocolored for clarity). Arrow indicates punctae adherens junction (arrows) linking the 2 membranes. (Scale bars: A, 1 μm B–D, 200 nm.

Double synapses are present on bundling GnRH dendrites. (A and B) Two examples from different animals of bundling GnRH neuron dendrites in cross section (D1 and D2) receiving shared afferent input (arrows) from single axon terminals (A). (B) Arrowhead indicates a single dense core vesicle amongst numerous clear vesicles in the terminal. Asterisks are positioned amongst typical microtubules, seen in cross section as small circles, in the labeled dendrites. (C–E) Serial ultra-thin images through the labeled, bundled GnRH dendrites shown in B were collected and a 3-dimensional model created (E). Postsynaptic densities (green) were present on the dendritic shaft (B) and on the neck of sessile spines (arrows, C and D). The 3-dimensional, reconstructed dendrites are pictured with and without the shared afferent terminal (yellow).

Bundled GnRH Neuron Dendrites Have Shared Synaptic Inputs.

Juxtaposed dendrites in cross section could be found across multiple serial ultra-thin sections. Examination of apposed dendrites in this plane revealed that single nerve terminals formed synapses with 2 adjacent dendrites (Fig. 4). These “shared synapses” on GnRH neuron dendrites were encountered in tissue from both animals. In 6 juxtaposed dendritic bundles examined, a total of 24 synapses were observed of which 4 were shared synapses. Terminating axons were packed with small clear vesicles (Fig. 4 A–D) however, dense core vesicles were also evident in some synapsing axons (Fig. 4B, arrowhead). Shared synapses were formed with postsynaptic densities on the dendritic shaft as well as on sessile spine necks (Fig. 4 C and D, arrows). A 3-dimensional model of the dendrites depicted in panels B–D was constructed following the collection of images from serial ultra-thin sections (Fig. 4E).


Materials and methods

This study was approved by our institutional review board for animal research, the Yale University Animal Care and Use Committee.

Slice preparation

Sprague-Dawley rats (Rattus norvegicus), 12-21 days old, were anesthetized with 1.2 g/kg urethane (Sigma, USA) intraperitoneally until unresponsive to tail pinch, and decapitated according to Yale University Animal Care and Use Committee guidelines. The OBs were extracted in chilled (4 ଌ) and oxygenated (95% O2, 5% CO2) artificial cerebrospinal fluid (ACSF). The ACSF contained 124 mM NaCl, 2 mM CaCl2, 3 mM KCl, 1.25 mM NaH2PO4, 26 mM NaHCO3, 1.3 mM MgSO4, and 10 mM dextrose at pH 7.4. Horizontal slices of 400 μm thickness were made using a rotorslicer (Dosaka, Japan) and immediately immersed in an oxygenated ACSF bath at 34 ଌ for 15-20 min. Slices were then kept in oxygenated ACSF at room temperature for up to 8 h.

Bicuculline was prepared as a stock solution dissolved in high pH ACSF adjusted with KOH. D-APV, 6-cyano-7-nitroquinoxaline-2,3-dione, saclofen, <"type":"entrez-nucleotide","attrs":<"text":"LY341495","term_id":"1257705759","term_text":"LY341495">> LY341495, and tetrodotoxin (TTX) were prepared as stock solutions in ddH2O. All stock solutions were stored under refrigeration except TTX, which was stored at � ଌ. All chemical reagents were from Sigma unless otherwise specified.

Current-clamp recordings of external tufted cells

Cells were recorded in whole-cell mode. The intracellular solution consisted of 130 mM K-gluconate, 10 mM HEPES, 0.2 mM EGTA, 4 mM MgATP, 0.3 mM Na3GTP, and 10 mM Na2phosphocreatine, adjusted to pH 7.3-7.4 with KOH. In our laboratory, we have traditionally used this solution, which contains no exogenous chloride ions, to amplify inhibition and have obtained stable recordings in mitral cells (Chen et al. 1997), granule cells (Xiong and Chen, 2002), and ETCs (Zhou et al. 2006a). The ACSF used for slice preparation was the same as that used for recordings. All experiments in this study were performed at 33-37 ଌ by heating ACSF using a TC-344B temperature controller (Warner Instruments, New Haven, CT, USA).

Cells were visually identified with an infrared camera (Hamamatsu, Japan, C2400-07ER) on an upright microscope (Olympus, BX50WI) using differential interference contrast microscopy and a 40× water immersion objective. ETCs were identified as cells having the largest somata at the deep glomerular border, most often with the dendritic trunk extending into the glomerulus. Current-clamp whole-cell recordings were made using Axoclamp 2A and 2B amplifiers (Axon Instruments, Union City, CA, USA) in bridge-balance current-clamp mode and Pclamp 9.0 for acquisition. Data were sampled at 10-20 kHz. Recording pipettes were pulled from 1.20 mm outer diameter/0.69 mm inner diameter glass with a P-97 Flaming/Brown micropipette puller (Sutter Instruments, San Rafael, CA, USA), with final resistances of 8-12 MΩ.

The olfactory nerve was stimulated by placing a large-tip pipette (1 MΩ) filled with ACSF or a concentric bipolar stimulating electrode (25 μm diameter tip) on the olfactory nerve layer surface each of these was connected to an electrical isolator that controlled the current amplitude of stimulation. The nerve was stimulated with one shock (0.05-0.2 ms width, 0.1 mA or less).

Single external tufted cell calcium imaging

For single-cell calcium imaging, 50 μM Calcium Green-1 hexapotassium salt (Invitrogen) was added to the intracellular solution. The dye was allowed to diffuse throughout the neuron for 15-20 min after entering whole-cell mode before starting the experiment.

For imaging, slices were epilluminated via a 150 W xenon arc lamp (Opti-Quip, Highland Mills, NY, USA) through a 460-500 nm excitation filter (HQ480/40x, Chroma Technology Corp., Bellows Falls, VT, USA) and dichroic mirror (Chroma Technology Corp., Q505LP). Fluorescence was collected by a 510-560 nm emission filter (Chroma Technology Corp., HQ535/50m). The fluorescence emission was captured by a PentaMax frame-transfer cooled CCD camera (Princeton Instruments, Trenton, NJ, USA) using Axon Imaging Workbench 2.2 (Axon Instruments). A 25 Hz frame rate was used and imaging was performed with an ND filter (¼) in the excitation path to decrease photobleaching and phototoxicity and allow more imaging trials. For analysis, monoexponential photobleaching was assumed and subtracted out postacquisition. Trials comparing spikes and bursts were interleaved and then averaged.

External tufted cell–interneuron paired recordings

Interneurons were recorded in the same manner as ETCs by targeting electrodes to smaller somata at the glomerular border. Pairs were found by random double-patch recordings of ETCs and smaller interneuron somata thought to be projecting primary dendrites to the same glomerulus. A synaptic connection was confirmed if postsynaptic depolarization with monosynaptic delay was evident after averaging a minimum of five trials of postsynaptic membrane potential recording in response to presynaptic suprathreshold activity. Subsets of interneurons, as described in the text, were anatomically indistinguishable, although single-spike-firing neurons had much smaller somata.

Multicellular calcium imaging of population responses to single external tufted cell stimulation

Slices were prepared as above and then stained with Oregon Green 488 BAPTA-1 or Calcium Green-1 (Invitrogen), both in acetoxymethyl (AM) ester form, using a double-labeling protocol (Peterlin et al. 2000) as follows. The AM dyes were prepared by dissolving 50 μg dye in 1% Pluronic F-127 (Invitrogen), 5% dimethylsulfoxide, and 5% Cremaphor-EL in a total volume of 100 μL pluronic and dimethylsulfoxide stock as a combination of 20% Pluronic in 100% dimethylsulfoxide. The slices, after the 34 ଌ incubation step above, were placed in individual wells of a well plate. A small volume (20 μL) of AM dye stock solution (387 μM for CG-1 AM) was placed on each slice and they remained in this solution for 2 min. Subsequently, 2 mL of oxygenated ACSF was added to each well to dilute the dye stock 100× to a final concentration of 3.87 μM CG-1 AM, 0.01% Pluronic F-120, 0.05% dimethylsulfoxide, and 0.05% Cremaphor-EL. Well plates were immediately transferred to a tissue culture incubator (37 ଌ) for 30 min, and then placed back in the regular oxygenated ACSF bath for 30 min until imaging experiments commenced.

The ETCs were targeted and recorded as above. The experiments were again performed at 33-37 ଌ. In these experiments, Mg 2+ was left out of the ACSF. Fluorescence imaging was performed as described earlier but the ¼ ND filter was not used. To limit photodamage, and thus false-negative results, we instead limited our imaging trials to less than 10. A 20 Hz frame rate was used.

For analysis, regions of interest (ROIs) that corresponded to soma-sized areas in all glomeruli were examined. Monoexponential photobleaching was assumed and subtracted out postacquisition. Trials comparing spikes and bursts were interleaved. Responses were considered successful only if clearly distinguishable from noise. The timings of calcium responses were correlated with electrophysiology, allowing one time frame of error. Responses that were more delayed were not counted. Responses showing very slow rises in 㥏/F (a τrise of seconds) were probably of glial origin and those (ROIs) were not included.

Statistical analysis

Statistical analysis was performed with QuickCalcs (GraphPad Software Inc., La Jolla, CA, USA). All analyses comprised simple comparisons of two means with SEs, each representing the same variable measured under different experimental conditions, with small sample sizes. Therefore, a non-directional Student's t-test was chosen for the determination of significance, and results are reported with the t-statistic value, with degrees of freedom as subscript, followed by the P-value. The significance criterion was P < 0.05. Numerical averages are presented in figures with SE values, and within the text as ± SD. Within-subject (same acute slice) factors were mainly associated with averaging interneuron measurements or ETC measurements, in that interneurons are known to be heterogeneous and ETCs may be heterogeneous themselves. Between-subject factors (different acute slices, different animals) include subtle connectivity or population differences at various depths of the OB and the age range of animals used (see above).


Results

Specific Reorganization of GABAA Receptors in α1 0/0 Mitral Cells.

Double and triple immunofluorescence staining for gephyrin, a marker of inhibitory postsynaptic sites, and the GABAA receptor α1-, α2-, α3-, and α5-subunits were performed in WT and α1 0/0 mice to investigate how the loss of the α1-subunit might affect the distribution of GABAergic synapses [Fig. 1 and supporting information (SI) Figs. 7 and 8]. In sections from both α1 0/0 and WT mice, numerous brightly stained gephyrin clusters were distributed across the external plexiform layer (EPL) and no difference in distribution was detectable between genotypes (Fig. 1 A1 and B2). In both cases, their density varied between 190 and 250 per 1,000 μm 2 (SI Table 1). Likewise, the dimension of gephyrin clusters as quantified by cumulative distribution analysis was also the same in both genotypes (SI Figs. 7A1 and 8A1 ). In contrast to gephyrin, a genotype effect on the distribution of α3-subunit-positive clusters was evident. In WT mice, staining was most prominent in the outer EPL (Fig. 1 A2), whereas the α3-subunit was redistributed in mutant mice to become uniform across the EPL (Fig. 1 B1), similar to the WT distribution of the α1-subunit (Fig. 1 C). These findings suggest that GABAergic synapses are preserved in α1 0/0 mice and more often contain α3-GABAA receptors than in WT.

Reorganization of GABAA receptor subtypes in α1 0/0 mice. (A–C) Double staining for gephyrin (A1 and B2) and the α3-subunit (A2 and B1) in WT and mutant (α1 0/0 ) mice reveals no change in gephyrin distribution and a stronger and more uniform α3-subunit immunoreactivity in the mutant, resembling the distribution of the α1-subunit in WT (C). (Scale bar: 50 μm.) (D and E) Triple staining of mitral cells for gephyrin (green), α1- (blue), and α3-subunit (red). In WT, α1-subunit-positive clusters colocalize with gephyrin on the soma and a few α3-subunit-positive clusters are present in the vicinity (arrowheads). In α1 0/0 mice, extensive colocalization of the α3-subunit with gephyrin results in a yellow staining in the overlay. (F) Quantification of the types of clusters found on the soma of mitral cells in WT and mutant mice. Colors correspond to the staining patterns shown in D and E. (Scale bars: 10 μm.)

Higher magnification showed the majority of α3 subunit-positive clusters to be colocalized with gephyrin, in both WT and mutant mice (SI Fig. 8 A and B ). Gephyrin clusters devoid of α3-subunit labeling were also detected, probably associated with other GABAA receptor subtypes. This possibility was tested by a systematic quantitative analysis of sections labeled for gephyrin and either α1, α2, α3, or α1/α3 (see SI Table 1). In WT mice, the total number of α subunit clusters associated with gephyrin was about the same as the total number of gephyrin clusters. The second most abundant subunit in WT is α3 this subunit might be overexpressed to compensate for the loss of α1. However, the number of α3 subunit-positive clusters in α1 0/0 mice was slightly, although not significantly, higher (+31% and + 24% in the inner and outer EPL, respectively). Nevertheless, α3-subunit clusters were more intensely stained and found to be larger than in WT (SI Fig. 7 B1 and B2 ), accounting for the difference in distribution seen at low magnification. No change in the distribution and abundance of α2- and α5-subunit-immunofluorescence was detected in mutant mice (SI Fig. 8 E–J ). These findings suggested that “orphan” gephyrin clusters corresponded to incomplete, nonfunctional postsynaptic sites.

A different result was obtained in the mitral cell body layer where mitral cell somatas receive a strong GABAergic innervation from granule cell dendrites to control neuronal excitability and output patterns. As in the EPL, there were no differences in the number of gephyrin clusters between the two genotypes (14.5 ± 5 clusters per mitral cell profile in WT versus 13.8 ± 6 in α1 0/0 mice mean ± SD, n = 59 and 54 cells, respectively not significant, U test). In WT mice, most of these clusters (74%) contained only the α1-subunit, 6% contained only the α3-subunit, and 17% contained both subunits. In contrast, in α1 0/0 mice, nearly all gephyrin clusters contained the α3-subunit (Fig. 1 D–F). Thus, an increase in abundance of the α3-subunit fully compensates for the absence of α1-subunit in GABAergic synapses formed on mitral cell somata. An important consequence is the presence of gephyrin clusters free of α subunits solely on mitral cell dendrites, which might be nonfunctional postsynaptic sites. These results suggest that the interchangeability of α1- and α3-subunits strongly depends on the location (somatic versus dendritic), and possibly the function, of the inhibitory synapses involved.

Preservation of Reciprocal Synapses in the EPL of α1 0/0 Mice.

We next used electron microscopy to investigate possible changes in the morphology of reciprocal dendrodendritic synapses in the EPL. Immunogold labeling for GABA showed no difference between mutant and WT mice (Fig. 2 A1 and A2). Likewise, labeling for gephyrin, which was concentrated at postsynaptic specializations of symmetric synapses (24), showed a similar distribution of gold particles in both genotypes (Fig. 2 B1 and B2). Finally, immunogold staining for α3-subunits revealed a much stronger immunoreactivity in α1 0/0 versus WT mice at symmetric synaptic specializations (Fig. 2 C1–C3 see SI Fig. 7C for quantification). Interestingly, labeling for the α3-subunit was also seen presynaptically at asymmetric junctions in both genotypes, as reported for the α1-subunit (25). These results clearly show that the absence of the α1-subunit does not result in a morphological impairment of GABAergic synapses or a redistribution of gephyrin to other sites. We next used electrophysiological methods applied on acute OB slices to assess the functional consequences of these anatomical alterations.

Ultrastructural characterization of dendrodendritic synapses in the EPL of α1 0/0 mice (postembedding immunogold labeling). (A1 and A2) GABA labeling in WT and mutant (α1 0/0 ) mice, depicting the normal morphology of dendrodendritic synapses between granule cell spines (sp) and mitral cell dendrites. Arrowheads point to the symmetric (GABAergic) synapses and arrows to the asymmetric (glutamatergic) synapses. (B1 and B2) Gephyrin labeling, showing the selective aggregation of gold particles on the postsynaptic site of the symmetric synapse (arrowheads) and the absence of labeling of the asymmetric synapse (arrows) in both genotypes. (C1–C3) α3-subunit labeling in both the symmetric (arrowheads) and asymmetric (crossed arrows) synapses in either genotype. (Scale bars: 200 nm.)

Less Frequent Inhibitory Synaptic Events with Slower Decay in α1 0/0 Mitral Cells.

First, we recorded spontaneous inhibitory postsynaptic currents (sIPSCs) from mitral cells under the whole-cell voltage-clamp configuration. The mitral cells were held at −70 mV and symmetrical Cl − concentrations were used ( SI Methods ) so that GABAA receptor-mediated currents were inward (Fig. 3 A and C). In the WT, sIPSCs occurred with a mean frequency of 1.86 ± 0.58 Hz and amplitude of 19.3 ± 0.6 pA (n = 8). In α1 0/0 mice, sIPSC frequency was 50% lower (Fig. 3 A and D 0.91 ± 0.64 Hz n = 8 P < 0.05, U test) but the amplitude remained unchanged (20.1 ± 3.5 pA not significant Fig. 3 B and E). The reduction in sIPSC frequency was accompanied by an increase in their decay time (Fig. 3 B): fast time constant was 7.8 ± 0.6 ms in WT and 25.2 ± 4.0 ms in α1 0/0 mice (Fig. 3 F P < 0.001, U test). The relative contribution of the fast to the slow component of the sIPSCs decay time was lower in the mutant mice (SI Fig. 9). In contrast, the 10–90% rise time did not differ between the two animal groups (1.87 ± 0.09 ms and 2.17 ± 0.30 ms for WT and α1 0/0 mice, respectively Fig. 3 G) indicating that the passive conductance properties of the mitral cells and the location of functional GABAergic synapses in α1 0/0 mice were similar. In contrast, sIPSCs recorded from granule cells were not significantly different in WT and α1 0/0 mice (n = 10 SI Fig. 10), thus indicating that the observed changes of inhibitory currents were restricted to mitral cells. From these anatomical and physiological evidence, we concluded that the specific loss of the α1-subunit from mitral cells led to a dramatic reduction of functional GABAergic synapses on mitral cell dendrites and to slower decaying sIPSCs. Because of the rarity of inhibitory synaptic events recorded in the presence of tetrodotoxin in α1 0/0 mice (<1 event per minute), we could not perform a quantitative investigation of miniature IPSCs. Nevertheless, average miniature IPSCs from mitral cells are shown in Fig. 3 C to compare their kinetics.

Synaptic GABAergic events in mitral cells are less frequent and decay slower in α1 0/0 than in WT mice. (A) Recordings of sIPSCs in a mitral cell from a WT (WT) (Left) or a mutant (α1 0/0 ) (Right) mouse, in the presence of 5 mM kynurenate and 20 μM gabazine. (B) Mean sIPSCs obtained from the cells presented in A. The traces are scaled in at Right. (C) Mean miniature IPSCs (mIPSCs) recorded as in A with 1 μM tetrodotoxin. (D) Distribution of sIPSC frequency in WT (solid circles) and α1 0/0 (open circles) mice. Columns represent the median of the distributions, red circles and error bars represent the mean and SEM, respectively. (E) Distribution of sIPSC amplitude. (F) Distribution of the fast component of sIPSC decay. See also SI Fig. 8 for further analyzes. (G) Distribution of sIPSC rise time (10–90% of the total amplitude). ∗, P < 0.05 #, P < 0.001, Mann–Whitney test, n = 9 and 8 cells for WT and α1 0/0 , respectively.

Slower Dendrodendritic Inhibition in α1 0/0 Mitral Cells.

To characterize further the inhibitory synaptic transmission in α1 0/0 mice, we measured evoked GABAergic responses mediated by dendrodendritic reciprocal synapses between granule and mitral cells. To evoke dendrodendritic inhibition (DDI), we applied a brief (50 ms) depolarizing step from −70 to + 10 mV that elicited a typical barrage of synaptic events in mitral cells (Fig. 4 A) ( SI Methods ). Recordings were first initiated in standard conditions and then in the presence of gabazine (20 μM) to isolate the GABAergic compound by subtraction. To quantify the DDI, we measured both the amplitude and the integral of the subtracted current. In α1 0/0 mice, this response was smaller (Fig. 4 A1 and B 1.88 ± 0.23 nA and 1.05 ± 0.19 nA for WT and α1 0/0 , respectively P < 0.05 with a Mann–Whitney test, n = 14 and 12 cells for WT and α1 0/0 , respectively). The decrease in amplitude was accompanied with broader responses characterized by longer half-width (Fig. 4 A2 and D from 675 ± 91 ms to 966 ± 85 ms P < 0.05 with a Mann–Whitney test) and longer rise time (Fig. 4 E time to peak: 43 ± 16 ms and 84 ± 15 ms for WT and α1 0/0 mice, respectively P < 0.01 with a Mann–Whitney test). As a result, the reduced amplitude combined with a longer duration led to unchanged current charges in mutant animals (Fig. 4 C 1.90 ± 0.32 nC and 1.42 ± 0.31 nC for WT and α1 0/0 , respectively). Thus, evoked inhibition between mitral cells and inhibitory interneurons was slower to rise and to decay, and had smaller amplitude in α1 0/0 mice. Yet, the total charges transfer of reciprocal GABAergic responses remained unchanged.

DDI is smaller and slower in the absence of α1-subunit. (A1) Average DDI in mitral cells from a WT and a mutant (α1 0/0 ) mouse. The voltage step is represented below the sweeps. DDI responses are calculated by subtracting the average response recorded in the presence of gabazine from the average response recorded in ACSF. (A2) Superimposition of the scaled sweeps from A1. (A3) Same traces as in A2 at a faster time scale to show the onset of the DDI response. (B) Distribution of DDI amplitude in WT (solid circles) and α1 0/0 (open circles) mice. Columns represent the median of the distributions, and red circles and error bars represent the mean and SEM, respectively. (C) Distribution of DDI charge. (D) Distribution of DDI half-width. (E) Distribution of DDI time to peak. ∗, P < 0.05 ∗∗, P < 0.01, Mann–Whitney test, n = 14 and 12 cells for WT and α1 0/0 , respectively.

Fewer GABAergic Events Degrade Fast Oscillations in a Network Model.

To infer the role of GABAergic synaptic inhibition in controlling synchronous network activity, we designed a physiologically based network model of the OB circuit that contains 100 heterogeneous MCs (26) and receiving olfactory nerve inputs. This network model includes the main synaptic interactions (lateral excitation and inhibition) and recurrent action (autoexcitation and recurrent inhibition) and takes into account two major features of the OB of α1 0/0 mice: the reduced number of functional dendrodendritic synapses and the prolongation of their recurrent inhibitory component (SI Fig. 11). The first feature was mimicked by a reduction in the inhibitory event occurrence probability (i.e., the average number of unitary events in a reciprocal or lateral IPSC, which obviously depends on the number of functional synapses involved in the inhibitory response see ref. 26), and the second characteristic by a three-fold increase in the decay time of unitary IPSC (uIPSC) (see Fig. 3 F). The reduction of the inhibitory event occurrence probability (uIPSC probability) was calculated to halve the amplitude of the recurrent inhibition as observed in vitro (see Fig. 4 B).

A network with a uIPSC decay time of 10 ms and another with a decay of 30 ms were subjected to changes in the uIPSC probability (Fig. 5). Both networks generated fast oscillations in the γ range. However, the frequency of oscillations in the network with slow uIPSCs was lower at all values of uIPSC probability. Therefore, a prolongation of the decay time constant of uIPSCs alone was sufficient to decrease the oscillation frequency of the network. Both networks were also sensitive to a reduction in the amplitude of the uIPSC probability (Fig. 5 A). Below a certain value of recurrent (and lateral) inhibition, the oscillation frequency followed the average mitral cells firing rate in both networks (Fig. 5 B). For the network with fast uIPSCs, this process led to a reduction of the oscillation frequency from 60 to 43 Hz (Fig. 5 B). Thus, a prolongation of uIPSC decay time, as well as a reduction of uIPSC occurrence probability, reduces network oscillation frequency. To assess the validity of these predictions, we recorded γ oscillations of the LFP measured near the mitral cell body layer in acute OB slices.

Simulation of the α1 0/0 phenotype in a network model. (A) Changes in the network oscillation frequency according to changes in release probability peak amplitude for a “WT”-like model (solid circles decay time of uIPSC of 10 ms) and a “α1 0/0 ”-like model (open circles decay time of 30 ms). The dashed lines represent mitral cells firing frequency under the same conditions. The arrows (blue for WT and green for α1 0/0 ) point to the values used in SI Fig. 11F . (B) Changes in the network oscillation frequency according to changes in inhibition for the same two networks as in A. Recurrent and lateral inhibition are changed proportionally. The red dashed line figure the threshold in inhibition amplitude below which the oscillation frequency equal the mitral cells firing frequency for both networks. The legends are the same for the two graphs.

Gamma Oscillations Are Slower in the OB Network of α1 0/0 Mice.

A brief stimulation of the olfactory nerve terminals (100 μs, 5–60 V) elicited robust fast oscillations in acute OB slices (Fig. 6 A and B) (for a review, see ref. 27). No significant difference was found in the stability of the LFP oscillations between WT and α1 0/0 OB slices (Fig. 6 C). Similarly, mitral cells synchrony tended to be lower in α1 0/0 mice, as also seen in our model (SI Fig. 11E ), but no significant difference was found at any stimulation strength (Fig. 6 D). In contrast, and as predicted by the theoretical model, the frequency of the induced oscillations was much lower in slices from α1 0/0 mice than in control slices, at all stimulation strengths (Fig. 6 E) and for several hundreds of milliseconds after the onset of stimulation (Fig. 6 H). This was not due to an effect on olfactory nerve inputs, as assessed by the measurement of the slope of the field excitatory postsynaptic potential (Fig. 6 F) measured in the glomerulus or to a reduced activity of mitral cells firing (Fig. 6 G). Indeed, the olfactory nerve-induced discharge of mitral cells was stronger in α1 0/0 than in WT mice. Our findings clearly indicate that a reduction in functional GABAA receptor-mediated inhibition between local interneurons and mitral cell dendrites, accompanied by slower kinetics, damped down LFP γ oscillations.

Network properties in WT and α1 0/0 mice. (A) LFP recordings in a slice from a WT (WT) mouse at 20 V (Upper) and 40 V (Lower). The star indicates the onset of olfactory nerve stimulation. (B) LFP recordings from α1 0/0 OB slice at 20 V (Upper) and 40 V (Lower). (C) Changes in the oscillation index over time, for a 60 V stimulation, from WT (solid circles) and α1 0/0 (open circles) mice. (D) Plot of the synchrony index against the stimulation strength. This index was always higher in WT mice, but this apparent difference is not significant. The small open and solid circles and dashed lines at the bottom of the plot represent the theoretical values of the index for a uniform spike phase distribution given the number of recorded spikes. (E) Frequency of LFP oscillations at various stimulation strengths, computed during the 200 ms after stimulation. (F) Evolution of the slope of field excitatory postsynaptic potential recorded next to the mitral cell layer in acute OB slices. (G) Poststimulus time histogram of mitral cell activity evoked with a 60 V olfactory nerve stimulation. (H) Evolution of LFP oscillation frequency over time evoked with a 60 V stimulation. ∗, P < 0.05 ∗∗, P < 0.01 #, P < 0.005 ANOVA with repeated measures n = 6 for both WT and α1 0/0 mice.


Introduction

Many neuronal networks in the mammalian CNS provide direct cell-to-cell communication, conduction of ionic currents and passage of small organic signaling molecules, through electrical synapses (Connors and Long, 2004). The vast majority of these synapses are gap junctions, specialized intercellular contacts with aggregates of transmembrane channels composed of a family of protein subunits termed connexins (Cxs) (Bennett et al., 1991 Dermietzel and Spray, 1993 Bruzzone et al., 1996 Goodenough et al., 1996 Kumar and Gilula, 1996 White and Paul, 1999 Bennett, 2000). The study of electrical synapses in the CNS needs comprehensive evidence showing functional significance by simultaneous physiological dual recordings between neighboring cells of certain neuronal type and structural identification of gap junctions between the examined cells. Such studies are considered to be less copious and, in fact, might be relatively rare.

In retinal ganglion cells, the major visual excitatory neurons that encode integrated signals from retinal interneurons in spike trains to sense visual information in higher brain centers, the occurrence of electrical synapses between neighboring cells has been proposed by electrophysiological recordings of distributed spike activity (Mastronarde, 1983a,b,1983c, 1989 Meister et al., 1995 Neuenschwander and Singer, 1996 Brivanlou et al., 1998 DeVries, 1999 Hu and Bloomfield, 2003). For a specific mammalian cell type, Y-type retinal ganglion cells [the physiological correlates of α-type ganglion cells (α-GCs)], synchronous spike activity with a short latency has been described in the cell population (Mastronarde, 1983a,b,c, 1989 DeVries, 1999 Hu and Bloomfield, 2003). The presence of electrical synapses between GCs has been supported by cytochemical findings of tracer diffusion after intracellular injection into individual cells (Vaney, 1991, 1994 Dacey and Brace, 1992 Xin and Bloomfield, 1997) and ultrastructural observation of gap junctions in α-GCs of the rat (Hidaka and Tauchi, 1993), cat (Kolb and Nelson, 1993) and parasol cells (a homolog of α-GC) of the primate (Jacoby et al., 1996). However, direct evidence that α-GCs are connected by dendrodendritic gap junctions is missing.

The recently discovered connexin36 (Cx36) (Condorelli et al., 1998 Söhl et al., 1998), a mammalian homolog of skate and perch Cx35 (O'Brien et al., 1996, 1998 White et al., 1999 Al-Ubaidi et al., 2000), was analyzed exclusively in inhibitory interneurons such as retinal AII (rod) amacrine cells (Feigenspan et al., 2001 Güldenagel et al., 2001 Mills et al., 2001 Deans et al., 2002) and cortical GABAergic interneurons (Deans et al., 2001 Hormuzdi et al., 2001 Amitai et al., 2002 Maier et al., 2002 Buhl et al., 2003). However, we have demonstrated that certain types of GCs express Cx36, supporting our previous findings performed on the AII cells (Hidaka et al., 2002). Our results proved that Cx36 is a molecular marker for gap junctions between α-GCs after electrophysiological examination.

In this study, we ultrastructurally demonstrate the occurrence of dendrodendritic electrical synapses between rat α-GCs after intracellular Neurobiotin injection and dual patch-clamp recordings from pairs of visually identified α-GCs. After intracellular staining of the cell pairs by dual recordings, Cx36 immunoreactivity provides anatomical evidence for the localization of gap junctions in dendrodendritic connections between α-GCs.


Contents

The term dendrites was first used in 1889 by Wilhelm His to describe the number of smaller "protoplasmic processes" that were attached to a nerve cell. [9] German anatomist Otto Friedrich Karl Deiters is generally credited with the discovery of the axon by distinguishing it from the dendrites.

Some of the first intracellular recordings in a nervous system were made in the late 1930s by Kenneth S. Cole and Howard J. Curtis. Swiss Rüdolf Albert von Kölliker and German Robert Remak were the first to identify and characterize the axon initial segment. Alan Hodgkin and Andrew Huxley also employed the squid giant axon (1939) and by 1952 they had obtained a full quantitative description of the ionic basis of the action potential, leading the formulation of the Hodgkin–Huxley model. Hodgkin and Huxley were awarded jointly the Nobel Prize for this work in 1963. The formulas detailing axonal conductance were extended to vertebrates in the Frankenhaeuser–Huxley equations. Louis-Antoine Ranvier was the first to describe the gaps or nodes found on axons and for this contribution these axonal features are now commonly referred to as the Nodes of Ranvier. Santiago Ramón y Cajal, a Spanish anatomist, proposed that axons were the output components of neurons. [10] He also proposed that neurons were discrete cells that communicated with each other via specialized junctions, or spaces, between cells, now known as a synapse. Ramón y Cajal improved a silver staining process known as Golgi's method, which had been developed by his rival, Camillo Golgi. [11]

During the development of dendrites, several factors can influence differentiation. These include modulation of sensory input, environmental pollutants, body temperature, and drug use. [12] For example, rats raised in dark environments were found to have a reduced number of spines in pyramidal cells located in the primary visual cortex and a marked change in distribution of dendrite branching in layer 4 stellate cells. [13] Experiments done in vitro and in vivo have shown that the presence of afferents and input activity per se can modulate the patterns in which dendrites differentiate. [2]

Little is known about the process by which dendrites orient themselves in vivo and are compelled to create the intricate branching pattern unique to each specific neuronal class. One theory on the mechanism of dendritic arbor development is the Synaptotropic Hypothesis. The synaptotropic hypothesis proposes that input from a presynaptic to a postsynaptic cell (and maturation of excitatory synaptic inputs) eventually can change the course of synapse formation at dendritic and axonal arbors. [14] This synapse formation is required for the development of neuronal structure in the functioning brain. A balance between metabolic costs of dendritic elaboration and the need to cover receptive field presumably determine the size and shape of dendrites. A complex array of extracellular and intracellular cues modulates dendrite development including transcription factors, receptor-ligand interactions, various signaling pathways, local translational machinery, cytoskeletal elements, Golgi outposts and endosomes. These contribute to the organization of the dendrites on individual cell bodies and the placement of these dendrites in the neuronal circuitry. For example, it was shown that β-actin zipcode binding protein 1 (ZBP1) contributes to proper dendritic branching. Other important transcription factors involved in the morphology of dendrites include CUT, Abrupt, Collier, Spineless, ACJ6/drifter, CREST, NEUROD1, CREB, NEUROG2 etc. Secreted proteins and cell surface receptors includes neurotrophins and tyrosine kinase receptors, BMP7, Wnt/dishevelled, EPHB 1-3, Semaphorin/plexin-neuropilin, slit-robo, netrin-frazzled, reelin. Rac, CDC42 and RhoA serve as cytoskeletal regulators and the motor protein includes KIF5, dynein, LIS1. Important secretory and endocytic pathways controlling the dendritic development include DAR3 /SAR1, DAR2/Sec23, DAR6/Rab1 etc. All these molecules interplay with each other in controlling dendritic morphogenesis including the acquisition of type specific dendritic arborization, the regulation of dendrite size and the organization of dendrites emanating from different neurons. [1] [15]

The structure and branching of a neuron's dendrites, as well as the availability and variation of voltage-gated ion conductance, strongly influences how the neuron integrates the input from other neurons. This integration is both temporal, involving the summation of stimuli that arrive in rapid succession, as well as spatial, entailing the aggregation of excitatory and inhibitory inputs from separate branches. [16]

Dendrites were once thought to merely convey electrical stimulation passively. This passive transmission means that voltage changes measured at the cell body are the result of activation of distal synapses propagating the electric signal towards the cell body without the aid of voltage-gated ion channels. Passive cable theory describes how voltage changes at a particular location on a dendrite transmit this electrical signal through a system of converging dendrite segments of different diameters, lengths, and electrical properties. Based on passive cable theory one can track how changes in a neuron's dendritic morphology impacts the membrane voltage at the cell body, and thus how variation in dendrite architectures affects the overall output characteristics of the neuron. [17] [18]

Electrochemical signals are propagated by action potentials that utilize intermembrane voltage-gated ion channels to transport sodium ions, calcium ions, and potassium ions. Each ion species has its own corresponding protein channel located in the lipid bilayer of the cell membrane. The cell membrane of neurons covers the axons, cell body, dendrites, etc. The protein channels can differ between chemical species in the amount of required activation voltage and the activation duration. [4]

Action potentials in animal cells are generated by either sodium-gated or calcium-gated ion channels in the plasma membrane. These channels are closed when the membrane potential is near to, or at, the resting potential of the cell. The channels will start to open if the membrane potential increases, allowing sodium or calcium ions to flow into the cell. As more ions enter the cell, the membrane potential continues to rise. The process continues until all of the ion channels are open, causing a rapid increase in the membrane potential that then triggers the decrease in the membrane potential. The depolarizing is caused by the closing of the ion channels that prevent sodium ions from entering the neuron, and they are then actively transported out of the cell. Potassium channels are then activated, and there is an outward flow of potassium ions, returning the electrochemical gradient to the resting potential. After an action potential has occurred, there is a transient negative shift, called the afterhyperpolarization or refractory period, due to additional potassium currents. This is the mechanism that prevents an action potential from traveling back the way it just came. [4] [19]

Another important feature of dendrites, endowed by their active voltage gated conductance, is their ability to send action potentials back into the dendritic arbor. Known as back-propagating action potentials, these signals depolarize the dendritic arbor and provide a crucial component toward synapse modulation and long-term potentiation. Furthermore, a train of back-propagating action potentials artificially generated at the soma can induce a calcium action potential (a dendritic spike) at the dendritic initiation zone in certain types of neurons. [ citation needed ]

Dendrites themselves appear to be capable of plastic changes during the adult life of animals, including invertebrates. Neuronal dendrites have various compartments known as functional units that are able to compute incoming stimuli. These functional units are involved in processing input and are composed of the subdomains of dendrites such as spines, branches, or groupings of branches. Therefore, plasticity that leads to changes in the dendrite structure will affect communication and processing in the cell. During development, dendrite morphology is shaped by intrinsic programs within the cell's genome and extrinsic factors such as signals from other cells. But in adult life, extrinsic signals become more influential and cause more significant changes in dendrite structure compared to intrinsic signals during development. In females, the dendritic structure can change as a result of physiological conditions induced by hormones during periods such as pregnancy, lactation, and following the estrous cycle. This is particularly visible in pyramidal cells of the CA1 region of the hippocampus, where the density of dendrites can vary up to 30%. [2]