Abstract

Adolescence is a time when the brain continues to mature. Specifically, the prefrontal cortex (PFC) goes through a process of disinhibition to inhibition as we age. Inputs to this region have a frequency dependent maturation pattern in male rats, but this has not been studied in females. We focused on frequency dependent responses in the medial PFC that are evoked by stimulation to the ventral hippocampus. This was conducted by measuring Local Field Potential responses in the medial PFC via in vivo electrophysiology. We found that stimulating with a 10 Hz train response showed no difference across age groups. In contrast, a 20 Hz train of stimula­tion revealed an age-dependent shift through increasing suppres­sion of the signal. Finally, a 40 Hz train stimulation evoked suppres­sion in all three age groups, but in different magnitudes. With these established patterns, we can compare a normal PFC maturation with factors such as chronic drug use and stress.

Introduction

The World Health Organization (2015) defines adolescence as the time after childhood, but before adulthood, which is about ages 10-19 years old. As we grow out of childhood, we increase our engagement with peers and yearn for acceptance from them; we think about who we are as a person as well as self-analyze (Guyer, Silk, & Nelson, 2016). During adolescence, many life events can evoke strong emotional responses that are not typically seen in adulthood. For example, many adolescents engage in behaviors to better themselves (e.g., making friends and gaining independence), but also engage in risky behaviors (e.g., drugs, unsafe driving, and sexual activity). Charles Darwin proposed in his book, Expression and Emotion in Man and Animals, that emotion helps us cope and respond properly to major events in life (Darwin, 1872).

Brain anatomy and development

Experts who study adolescent health and development agree that the greatest threats to young people are self-inflicted accidents like automobile accidents, violence, substance abuse, and sexual risk-taking (Williams, Hombeck, & Greeley, 2002). Early adolescence in humans is associated with a transformation of cognitive thought which develops into abstract reasoning as well as cognitive control (Graber & Petersen, 1991). This extensive emotional network is mediated by the prefrontal cortex (PFC) (Miller & Cohen, 2001). A 1997 study by Casey et al. looked at the development of this behavior and its corresponding activation in the PFC between children aged 7-12 and young adults aged 21-24. Each participant was scanned by a magnetic resonance imaging (MRI) machine to see how their brain responded to go/no-go tasks. Participants were shown a sequence of letters and were instructed that if they saw an “X”, they should not press the button. However, if they saw any other letter besides “X”, then they were to press the button. This task was designed to test attention and ability to override a response. They found that children had a more scattered pattern of activation in the PFC than adults. Specifically, children activated the dorsolateral region of the PFC as they inhibited the action to press the button when an “X” flashed on the screen. The adults did not have activation of the dorsolateral PFC when an “X” flashed and they did not press the button as much during this pre­sentation. The authors speculated that the dispersed pattern may relate to the fine-tuning process in the PFC in which relevant connections are not made until maturity. As this network matures during development, less activation is needed to overcome new material presented (Hare & Casey, 2005). Most developmental brain research has focused on the prefrontal cortex (PFC), amygdala, insula, and anterior cingulate cortex regions be­cause these regions work together to promote learning, assign meaning to certain life events, and integrate sensory information to guide behavior in a certain context (Ernst, Torrisi, Balderston, Grillon, & Hale, 2015).

One might argue that what makes us human is that we have a well-developed cerebrum (cerebral cortex) that allows for executive func­tion (Fuster, 2002). Some of these functions include our ability to store and recall events as memories, inhibit certain emotions, and the ability to solve problems (Frith & Dolan, 1996). There is a clear morphological difference, for example, when comparing the human brain with one from a rat (Fig. 1). However, in many respects, the rat brain has many similarities to ours. For instance, both structures have a cerebrum to control move­ments, an olfactory bulb for smell, and a hippocampus to help us with learning and memory functions (Purves et al., 2001).

However, the rat cerebrum is much simpler than a human’s. Our cerebrum is significantly larger and has numerous folds (gyri) and valleys (sulci) to increase its total surface area (Fig. 1). The larger cere­bral cortex of a human allows for higher cognitive function (Toro et al., 2008). In addition, the human cerebral cortex is divided into four major lobes; the occipital, parietal, temporal, and frontal lobes (Fig. 2).

For this study, we will focus on the frontal lobe which deals with reasoning, planning, parts of speech, movement, emotions, and prob­lem solving (Kimberg & Farah, 1993). We focused on the frontal cortex because it is the last region of the brain to develop (Casey et al., 2005). Specifically, we examined Brodmann areas, 8, 9, 10, 11, 44, 45, 46, and 47 (Fig. 3), which define the prefrontal cortex (PFC).

The PFC has three major divisions: the lateral, medial, and orbitofrontal (Fig. 4) (Masterman & Cummings, 1997). Each of these has important connections from the amygdala, hypothalamus, midbrain, and pons (Chatterjee, Kumar, Siddiqui, & Goyal, 2008). These specific regions are associated with certain higher-order functions, such as attention con­trol, inhibitory control, working memory, and problem solving (Diamond, 2013). For instance, the lateral prefrontal cortex is shown to play a role in language, attention, memory, and novelty processing, which is import­ant for learning about new contexts (Daffner et al., 2000). In contrast, the orbitofrontal cortex of the PFC plays a significant role in social and emotional behaviors (Gold, Berman, Randolph, Goldberg, & Weinberger, 1996). Specifically, it anticipates reward by processing the possible out­comes of the present context (Stuss & Benson, 1986). Finally, the medial prefrontal cortex (mPFC) is important for attention to cognitive tasks, spatial memory, and conflict resolution. In particular, the lower region of the mPFC (ventral-medial PFC) helps us make decisions (Spinella, Yang, & Lester, 2004).

The Hippocampus

Many studies have shown that certain disorders such as anxiety, depression, apathy, and disruptive behavioral disorders involve prefrontal lobe dysfunction (Chatterjee et al., 2008). Additional studies have shown that as all of these regions develop, they receive signals from dopaminergic terminals in the cortex (Thierry, Blan, Sobel, Stinus, & Glowinski, 1973), hippocampal (Carr & Sesack, 1996), and amygda­la neurons (Bacon, Headlam, Gabbott, & Smith, 1997). In fact, recent evidence has confirmed that the PFC receives significant input from the amygdala and the ventral hippocampus (Caballero, Granberg, & Tseng, 2016). For this study, we only focused on the medial prefrontal cortex, be­cause this region receives the most innervation during maturation (Benes et al., 1993). In particular, for this preliminary study we only focused on the ventral hippocampal-prefrontal cortex pathway.

The hippocampus resides in the medial temporal lobe (Gray, 1918). The entire hippocampal region helps with memory and cognition (Scoville & Milner, 1957) as well as emotional processing (Gray & McNaughton, 2000). However, lesion studies have shown that the hippocampus has two streams of processing: the dorsal and ventral streams (Swanson & Cowan, 1977).

The dorsal stream processes spatial memory (Moser, Mos­er, Forrest, Andersen, & Morris, 1995), which is memory that retains information about your environment, like your neighborhood layout. The ventral stream processes the emotional significance of the environment (Ferbinteanu & McDonald, 2001). For example, normally, a rat would be cautious and show stress before entering an unprotected region of a maze. However, Ferbinteanu and McDonald (2001) showed that rats with a lesioned ventral hippocampus did not fear entering into an unprotected arm of a maze to get to a food reward. As previously stated the ventral hippocampus plays a critical role in innervating the PFC. One of the main functions of the ventral hippocampus (vHipp)-PFC pathway is to help process our working memory (Freidman & Goldman-Rakic, 1988). However, this pathway does not fully develop until adulthood (Luna, Garver, Urban, Lazar, & Sweeney, 2004).

Neurotransmitters

The driving factor mediating this vHipp-PFC pathway are small chemical molecules called neurotransmitters. Neurotransmitters allow for communication between neurons in the brain as well as neurons and muscles in the periphery. The neurotransmitter molecules start in one end of a neuron (pre-synaptic terminal), are released into a gap called the synapse, and are accepted by the next neuron at a site called a receptor (Lodish, et al., 2000). These chemicals can have two different effects on the postsynaptic membrane: hyperpolarization (inhibitory effect) or depolarization (excitatory effect) (Trautwein, 1963). These effects are measured by the difference in voltage between the inside and outside of a neuron and the change in this voltage caused by postsynaptic receptor binding to a neurotransmitter (Purves, Augustine, & Fitzpatrick, 2001) (Fig. 6). This difference in voltage is known as the membrane potential. Most neurons have a resting potential of about -70 mV (Lewis, et al., 2011).

If hyperpolarization occurs, it makes the membrane potential more negative. This is caused by a shift of ions in and out of the cell, specifically if positive potassium ions leave the cell or negative chloride ions enter the cell (Hille & Catterall, 1999). With depolarization, the cell becomes less negative because positive sodium ions rush into the cell (Hille & Catterall, 1999). If the neuron membrane potential reaches its threshold (about 55 millivolts), the neuron’s axon will transmit all-or-none action potentials, signals that travel the length of the neuron’s axon (Burke, Kiernan, & Bostock, 2001). When hyperpolarization occurs, the post-synaptic membrane voltage increases in magnitude, thereby making the neuron less likely to reach the threshold and initiate action potentials Action potentials are voltage changes by which neurons transmit signals, thereby stimulating the release of neurotransmitters to communicate with another neuron that it innervates (Siegel et al, 1999). There are a number of different neurotransmitters and some of the major ones in the brain include glutamate, γ-aminobutyric acid (GABA), acetyl­choline, dopamine, serotonin, norepinephrine, epinephrine, and histamine (Purves et al., 2001). In this study, we focused on glutamate, GABA, and dopamine because these neurons project to the rat PFC and change during peri-adolescence (Caballero et al., 2016) (Fig 7).

Glutamate is an amino acid neurotransmitter that specializes in producing an excitatory response (Purves et al., 2001). If glutamate concentrations become too high, excitotoxity can occur, causing neurons to become overexcited and die (Rothman, 1983). On the other hand, GABA inhibits neurons so they are less likely to transmit action potentials (Purves et al., 2001). GABA is created through the breakdown of gluta­mate with vitamin B6 (Nikolaus, Antke, Beu, & Müller, 2010). GABA is also important because one of its precursors is derived from vitamin B6. Without vitamin B6, glutamate cannot be broken down into GABA and can cause adults to experience anxiety and infants can experience seizures (Petty, 1995). Dopamine plays a major role in executive function (Logue & Gould, 2014), motor control (Brooks, 2001), motivation arousal (Ikemoto & Panksepp, 1999), reinforcement (Holroyd & Coles, 2002), and reward (Berridge & Robinson, 1998) in the brain.

There are three major dopaminergic pathways in the brain: the mesocorticolimbic projection, the nigrostriatal pathway, and the tubero­infundibular pathway (Sian, Youdim, Riederer, & Gerlach, 1999). The mesocorticolimbic projection has two sub-regions: the mesocortical path­way and the mesolimbic pathway (Sian et al., 1999). The mesocortical pathway projects from the ventral tegmental area (VTA) to the prefrontal cortex, and dopamine in this pathway plays a role in cognitive control, motivation, and emotional response (Malenka, Nestler, & Hyman, 2009).

In this study, we examined the hippocampus-PFC pathway because it is modulated by at least three neurotransmitters: dopamine (Goldman-Rakic, Leranth, Williams, Mons, & Geffard, 1989), glutamate (Floresco, Seamans, & Phillips, 1997), and GABA (Caballero, Thomases, Flores-Barrera, Cass, & Tseng, 2014). When the PFC has fully matured, dopamine has full control over functions such as working memory, inhibi­tory control, and attention (Horvitz, 2000). Dopamine’s control is mediated by the amount of excitatory and inhibitory neurons innervating the PFC (Tseng, Chambers, & Lipska, 2009).

The excitatory effect of dopamine is mediated by dopamine receptor D1 which enhances glutamatergic transmission via the NMDA glutamate receptor; this can have different behavioral effects (O’Donnell, 2010). If D1 receptors in the PFC are activated, memory retrieval and working memory are enhanced (Seamans, Floresco, & Phillips, 1998). If both the D1 and NMDA receptors are activated in the PFC, appetitive behaviors, such as searching for food when you are hungry, are exhibited in adult rats (Baldwin, Sadeghian, & Kelley, 2002).

When the D1 receptors are activated in the mature adult PFC, there is a lasting depolarization effect in the pyramidal neurons. Howev­er, pyramidal neuron transmission is mediated by NMDA receptors and calcium-dependent signaling. This long-lasting effect is not fully present until late adolescence, or around P45 in rats (Tseng & O’Donnell, 2005). Therefore, the excitatory effects seen in the PFC are a product of D1 and NMDA receptor interactions (Baldwin et al., 2002). The importance of this effect is its strong impact on plasticity and the emergence of adult behav­iors during the transition from adolescence to adulthood.

(Purves et al, 2001).

The inhibitory effect of dopamine involves D2 receptors (Tseng & O’Donnell, 2004) and GABAergic interneurons in the PFC that contain D1 and D2 receptors (Vincent, Khan, & Benes, 1993). Inhibition in the PFC can also be caused by a facilitation in GABAergic neurons (Gorelo­va, Seamans, & Yang, 2002). However, during the juvenile age, P25-35, recordings show that the GABAergic interneurons only have D1 recep­tors, which increases the excitability of fast-spiking interneurons (FSI) (Tseng et al., 2006). Although fast-spiking interneurons can maintain an intense inhibitory signal to GABAergic neurons, this is not as effective lat­er in life. After late adolescence (around P50), there is a strong excitability of D2 receptors which in turn synapse onto GABAergic neurons in the PFC (Kalsbeek, Voorn, Buijs, Pool, & Uylings, 1988). The development of both D1 and D2 receptor control over GABAergic cells in the PFC allows for greater inhibitory control, which can also affect the timing of local neu­ron populations for skills like working memory (Lewis & Gonzalez-Burgos, 2006).

Another important neurotransmitter in adolescent development is glutamate (Gleich et al., 2015). Neurons that contain glutamate carry contextual and emotional information from the ventral hippocampus (Flo­resco et al, 1997) and amygdala (Garcia, Vouimba, Baudry, & Thompson, 1999). These hippocampal-PFC and amygdala-PFC pathways also con­tinue to develop during adolescence (Cressman et al., 2010; Seamans et al, 1998). In a 2013 study, Thomases et al. found that in three different age groups (juvenile, adolescence, and adulthood), there is a distinct dif­ference in PFC response to ventral hippocampal (vHipp) stimulation. This pattern shows that at a frequency of 20 Hz and higher, male rats P30-40 show a facilitation of the vHipp signal in the medial PFC. However, male rats P45 and older show a slight inhibition of this signal (Thomases, Cass, & Tseng, 2013).

These studies show that as the brain, specifically the hippo­campal-PFC pathway, develops from childhood to adulthood, there is an increase in the intensity of an overall inhibitory effect. This pathway is mediated by increased expression of a specific subunit of the NMDA re­ceptor, called GluN2B (Caballero et al, 2016). Recent studies have shown that NMDA receptors with GluN2B are important for adult PFC-dependent functions like working memory (Wang et al., 2013) and fear conditioning (Gilmartin, Kwapis, & Helmstetter, 2013). Another important factor of GluN2B in NMDA receptors is its ability to selectively amplify import­ant information from events that originate in the ventral hippocampus (Flores-Barrera et al., 2014).

All of the studies above have shown that the excitatory neurotransmitter glutamate plays an important role in how we perceive our world. Working memory and emotional context help our PFCs make decisions about our environment based on past experience (Kensinger, Clarke, & Corkin, 2003). On a molecular level, we can see that this skill develops as we age, as shown by increased amounts of GluN2b subunits and the strengthening of the vHipp-PFC pathway to control neuronal timing.

The final main neurotransmitter that affects PFC development is GABA. As previously mentioned, dopamine regulates GABAergic modulation, but the local GABAergic system in the PFC also undergoes significant changes (Uhlhaas & Singer, 2011). Specifically, the number of GABA interneurons that contain the proteins parvalbumin (PV), calratinin (CR), and calbindin (CB) changes significantly in the prefrontal cortex (Caballero, Flores-Barrera, Cass, & Tseng, 2014). The number of GABAergic interneurons in a particular neuron population can be measured by looking at levels of PV, CR, and CB, as these proteins make up more than 80% of GABAergic cells (Gabbot, Dickie, Vaid, Headlam, & Bacon, 1997).

Changes in these proteins can impact the functional character­istics of their interneurons which, in turn, can affect the inhibitory control of the PFC output (Kinney et al., 2006). This alteration in PFC output is mainly seen in PV-positive interneurons. Kinney et al. (2006) found that if glutamatergic transmission is blocked, PV levels decrease in the PFC. As discussed, glutamate is crucial in the development of a functional PFC. Based on evidence from the studies described above, glutamate will transmit a signal to GABAergic interneurons in the PFC which will produce an inhibitory effect. However, PV-positive FSIs are between the glutamate input signals to the GABAergic neuron. Therefore, changes in PV levels alters the effects of inhibitory control in the PFC.

Caballero et al. (2014) reported that PV levels follow a developmental pattern. They stained sections of the mPFC in juvenile, adolescent, and adult rats. Fluorescent immunostaining revealed that PV expression in neurons was most abundant in adolescence and adulthood compared to juvenile rats. Another characteristic of the stain was the pattern of expression. In juvenile rats (P25-35), PV-positive interneurons showed a small concentrated area of fluorescence in the mPFC. In the adolescents and adults (P45-55 and P65-75 respectively), there was a wider and more intense stain representation. Caballero et al. (2014) also examined signal recordings from a single PV-positive cell. They showed there was a stronger glutamatergic signal in PV-positive cells after P35 than in the P25-35 group. Linking these observations together, it can be said that the developmental increase in PV expression correlates with the increase in PV signaling and glutamatergic input during adolescent development. Subsequently, the GABAergic system plays a crucial role in producing an inhibitory effect in the PFC, but the system itself undergoes developmental changes as well. This is seen by an increase in glutama­tergic transmission on PV, fast-spiking interneurons, which produce a strong signal onto GABAergic interneurons to the PFC.

Overall, the mediation of glutamatergic neurons, PV-positive cells, and GABAergic transmission from adolescence to adulthood is summarized in Figure 8. This shows how upregulation of these factors allows for proper inhibitory control when higher frequency inputs arrive at these neurons.

Brainwaves

The action of neurotransmitters to alter membrane potential in the brain is the underlying cause of regular electrical patterns known as brainwaves (Tsien & Barrett, 2013). Brainwaves were first recorded in 1929 as cyclic wave-like changes in voltage, and thus were named brainwaves (Berger, 1929). These waves are categorized as delta, theta, alpha, beta, and gamma (Purves et al, 2001) (Fig 9). The slowest wave pattern is the delta wave, which has a frequency of 0.2-3 Hertz (Hz). This pattern is seen when we are in deep sleep (Botella-Soler, Valder­rama, Crepon, Navarro, & Le Van Quyen, 2012). The next wave, theta, oscillates at a frequency of 3-8 Hz, and is present during light sleep and extreme relaxation (Wickramasekera, 1977). Alpha waves have a frequency of 8-12 Hz, and they are evoked when one is in a relaxed state. They are most present when an individual wakes in the morning (Huang & Charyton, 2008). Beta brainwaves oscillate at a frequency of 12-30 Hz. They are present when a person is wide-awake and active during the day (Walter & Matthews, 1934). The final brainwave pattern, gamma, oscil­lates at 30-120 Hz, and is important for the formation of ideas, language, memory processing, and learning (Miltner, 1999).

Many human brainwave studies use a technique called an elec­troencephalography (EEG). This method measures brain activity using electrodes attached to the skin on the scalp (Britton et al., 2016). Results from this machine show the amplitude and frequency of brain waves (Timofeev, Bazhenov, & Seigneur, 2012). Although you can calculate where a signal is the strongest to see which brain region it is in, this does not tell you exactly where that signal originated. (NeuroCognitive Imaging Lab, 2017).

It has been shown that brainwave electrical activity early in one’s life controls several developmental processes, such as the differ­entiation of neurons, migration of neurons to their appropriate place in the brain, creating specific synapses, neurotransmitter specification, and strengthening and weakening of synapses (Zhou & Poo, 2004; Moody & Bosma, 2005). Immediately following birth, a neonate displays intermit­tent bursts of delta waves. This phenomenon is suppressed as we age (Drefus-Brisac & Larroche, 1971). In the adolescent phase of life (age 10- 19), it has been shown that during sleep, the brain produces delta brain waves at a lower amplitude than in adulthood (Feinberg, Higgins, Khaw, & Cambell, 2006).

In a recent review, studies have shown that the hippocampus can generate three distinct wave patterns: theta, sharp-wave ripples, and gamma waves, all of which correlate with specific behaviors (Colgin, 2016) (Fig 10). For example, theta waves in the rat hippocampus have been shown to not only be present during REM sleep, but also play an essential role in learning and memory (Landfield, McGaugh, & Tusa, 1972). On a cellular level, theta waves are rhythmically mediated by GAB­Aergic neurons projecting into the hippocampus (Freund & Antal, 1988).

The second wave pattern in the hippocampus is the sharp wave-ripple pattern. These waves have large amplitudes (height of wave) and occur irregularly (Schlingloff, Kali, Freund, Hajós, & Gulyas, 2014). This pattern emerges during slow-wave sleep (Buzsaki, 1986). They also have a functional role of consolidating significant memories and erasing traces that are insignificant during sleep (Lee & Wilson, 2002). The sharp part of the wave represents excitatory neural activity and starts in the CA3 region, transmitting its signal to the CA1 region (Buzsaki et al., 1986), whereas the ripples are locally generated in the CA1 region (Schlingloff et al., 2014). It has been proposed that the ripple formation plays a role in memory consolidation because during a sharp wave-ripple, CA1 cells are depolarized by the sharp wave and are also inhibited by the ripples (English et al., 2014). This inhibition raises the threshold for initiation of action potentials, thereby preventing most neurons from firing. Therefore, the ripples may only select cells that encode memories for consolidation to then be moved to long-term storage (Colgin, Kubota, Jia, Rex, & Lynch, 2004).

Finally, gamma waves are present in the hippocampus. This specific pattern correlates with a variety of behaviors like preparatory motor movements (Kristeva-Feige, Feige, Makeig, Ross, & Elbert, 1993), auditory detection (Jokeit & Makeig, 1994), auditory attention (Bertrand, 1998), and complex task processing (Spydell & Sheer, 1982). Gamma waves also have lower amplitudes than the theta and sharp wave-ripple rhythms (Buzsaki, Leung, & Vanderwolf, 1983).

The gamma frequency in the CA1 ranges from 30-120 Hz (Colgin et al., 2009). In fact, this range has been divided into two distinct frequencies. At the 30-55 Hz range, low gamma waves occur and are driven by CA3 input (Schomburg et al., 2014). The other type of gamma wave, fast gamma, has a higher frequency range from 60-120 Hz and is mediated by inputs from the medial entorhinal cortex onto the hippocam­pus (Schomburg, et al., 2014).

The role fast gamma waves play in memory is still poorly defined. Some studies have concluded that since these waves are in the entorhinal cortex, which processes sensory information, the fast gamma waves encode sensory information in memory (Kemere, Carr, Karlsson, & Frank, 2013). In contrast, other studies have found that fast gamma rhythms are involved in working memory rather than memory encoding (Yamamoto, Suh, Takeuchi, & Tonegawa, 2014).

Slow gamma waves are thought to be involved with memory retrieval because one of the functions of the CA3 region is to store and retrieve memories (Nakazawa et al., 2002). It is also known that slow gamma waves in the CA1 are synchronized by inputs from the CA3 region (Colgin et al., 2009). However, there is more than one finding relevant to the memory retrieval hypothesis. Some have shown that slow gamma waves are involved with memory retrieval when they are reactivated for memories of earlier experiences (Pfeiffer & Foster, 2015), whereas others have concluded that the memory retrieval from CA3 to CA1 is more intense when an animal is in a new environment (Kitanishi et al., 2015).

Knowing the range of hippocampal frequencies allows us to pick specific frequencies to stimulate in the vHipp. Specifically, it is known that at alpha waves (8-12 Hz), NMDA receptors are activated (Flint & Connors, 1996). When beta waves at 20 Hz and low gamma waves around 50 Hz are elicited, fast-spiking interneurons projecting to GABAer­gic neurons become active (Berke, 2011).

Adolescence is an important time to study brain function because it is vulnerable during this period. That is, if brain development is impaired, disorders such as schizophrenia, bipolar disorder, and anxiety can occur (Hoffman & Lewis, 2011). It has also been shown that the PFC can be impaired if cannabinoids (Cass et al., 2014), ketamine (Thomas es, Cass, Meyer, Caballero, & Tseng, 2014), or cocaine (Cass, Thom­ases, Caballero, & Tseng, 2013) are used during the adolescent period in rats (about 35-60 days after birth). Compared to control rats, those who received chronic drug treatment show disinhibition in the PFC at hippocampal stimulation frequencies of 20 and 40 Hz (Cass et al., 2013). However, these studies have only been conducted in male rats. Given the importance of understanding how the brain matures, it would be helpful to determine whether this is the same in both sexes.

Understanding brain function in both sexes is also important when prescribing drugs. In 2013, the FDA released a safety announce­ment for the public about the insomnia drug, zolpidem (Ambien, Edluar, and Zolpimist). Although this drug is not related to brain maturation, it is significant to mention since it has been shown that zolpidem remains in the bloodstream in females longer than males (Food and Drug Ad­ministration, 2013). As a consequence, a normal dose prescribed for women has a higher probability of remaining in the bloodstream, thereby potentially increasing the likelihood of a motor vehicle accident (Hansen, Boudreau, & Evel, 2015). Accordingly, the NIH will create appropriate poli­cies to take into account differences between male and female subjects in future studies (Clayton & Collins, 2014).

Given that studies with female brain maturation have not been described, we used female rats in three different age categories: pread­olescence, adolescence, and adulthood. This was to determine how the medial prefrontal cortex develops with ventral hippocampal stimulation. Based on what we have seen in male rats for their normal development, we hypothesized that as female rats age from preadolescence to adult­hood, more inhibitory control will be seen in the medial prefrontal cortex at higher ventral hippocampal stimulation frequencies.

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Appendices

Figure 1: Human versus rodent brain. Comparison of the adult human brain (top) and rat brain (bottom). The major difference is not only the overall organ size but most notably the size of the cerebral cortex. Note that in the human brain there are numerous folds (gyri and sulci) which increase surface area and presumably allow higher function to occur (Genetic Science Learning Center, 2013).

 

Figure 2: Outline of four major brain lobes. The domains and outlines of the four major lobes of the human brain. These regions include the occipital, parietal, tempo­ral, and frontal lobes (Kinser, 2000).

 

Figure 3: Brodmann Areas outlining the prefrontal cortex. Areas of the human brain as defined by the anatomist K. Brodmann (Finger, 2001). The regions in orange define the prefrontal cortex (Carter & Gray, 1918).

 

Figure 4: Three Major divisions of the prefrontal cortex. A comparison of the three major divisions of the prefrontal cortex (PFC) in human and rat brains. The medial portion of the PFC is related to social behaviors between organisms, such as interacting with peers and showing empathy. Both the dorsal and ventral portions of the lateral PFC (dlPFC and vlPFC) are related to social tasks. The vlPFC specifically encodes information of social reward and punishment to attach emotional value to objects and ideas. Both the dorsal and medial portions of the PFC are active when we judge the trustworthiness of someone (Bicks, Koike, Akbarian, & Morishita, 2015).

 

Figure 5: Dorsal and ventral streams of the hippocampus. The hippocampus can be separated functionally into dorsal (upper) and ventral (lower) pathways (Ban­nerman, et al., 2014). The dorsal stream helps gather and retain information about the environment around us (Moser et al., 1995). The ventral stream helps process spatial (environmental) memory (Ferbinteanu & McDonald, 2001). The ventral stream projects to the prefrontal cortex.

 

Figure 6: Steps during an action potential. There are three major steps in an ac­tion potential after the membrane potential reaches threshold, depolarization, repo­larization, and hyperpolarization. a) The electrical potential changes that occur in the cell during an action potential (Institute of Medicine (US) Committee on a National Neural Circuitry Database, 1991). b) A cell rests at a negative membrane potential of about -60 millivolts which means the inside of the cell is more negative than the out­side. c) If the cell reaches -55mV, due to the Na+ voltage gated channels being ac­tivated to open, Na+ ions rush in the cell down its electrochemical gradient causing the membrane voltage to become positive. d) Eventually voltage gated K+ channels are activated and K+ ions leave the cell, causing a negative potential inside the cell once more. e) Na+ channels close, but K+ channels are still open, causing a slightly more negative potential than resting (Byrne, 2011).

 

Figure 7: Glutamate, GABA, and Dopamine Pathways. Above are the three major neurotransmitters we focused on and where they project in the brain (Barth, Villring­er, & Sacher, 2015). A) The glutamatergic pathway is mainly excitatory (Purves et al., 2001). B) The GABAergic pathway is opposite in the sense that it is mainly inhib­itory (Purves et al., 2001). C) The dopaminergic pathway has many roles including executive function (Logue & Gould, 2014), motor control (Brooks, 2001), motivation arousal (Ikemoto & Panksepp, 1999), reinforcement (Holroyd & Coles, 2002), and reward (Berridge & Robinson, 1998).

 

Figure 8: Overview of cellular pathway changes in the prefrontal GABAergic system. Here Caballero et al. (2016) summarized what we know thus far about the development of inhibitory control through the male prefrontal GABAergic system. Early adolescence shows less glutamatergic input, to fewer FSIs, onto minimal GABAergic interneurons. In adulthood, the number of GABAergic interneurons increases in the PFC, PV expression increases, causing an increase in FSIs, and glutamatergic inputs increase to these FSI cells. Overall, this creates a more effi­cient system to handle excitatory inputs and to suppress the signal if needed.

 

Figure 9: The five major brainwave patterns. Brainwave patterns were deter­mined through EEG examinations (Fields, 2016). In this study we stimulated the hippocampus at alpha, beta, and gamma frequencies.

 

Figure 10: The four wave patterns generated in the hippocampus. Colgin (2016) defines the four wave patterns generated in the hippocampus as a) theta waves, which have control in REM sleep and learning and memory (Landfield, McGaugh, & Tusa, 1972). b) Sharp wave-ripples appear in large amplitudes and irregularly. They are important for consolidating important memories, and erasing others (Lee & Wilson, 2002). c) Slow gamma waves are a subset of the gamma wave pattern. The function is still debated between memory retrieval and reactivation of memories (Pfeiffer & Foster, 2015). d) The function of fast gamma waves is also controversial between encoding sensory information (Kemere et al., 2013) and working memory processing (Yamamoto et al., 2014).

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