+ Team Members: Brian Barnett Valerie Cohen Taylor Hearn Emily Jones Reshma Kariyil Alice Kunin Sen Kwak Jessica Lee Brooke Lubinski Gautam Rao Ashley.

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Team Members: Brian BarnettValerie CohenTaylor HearnEmily JonesReshma KariyilAlice KuninSen KwakJessica LeeBrooke LubinskiGautam RaoAshley Zhan

Research in Testing ADHD's Link to Impulsivity in NeuroscienceMentor: Matthew Roesch

Librarian:Francy Stilwell

TEAM RITALIN+1COMMENTS:

1Introduction Attention Deficit Hyperactivity Disorder (ADHD)

Affects 5-10% of all school age children Twentyfold increase in prescription of ADHD drugs in past 30 years Limited research on the neurobiology of the disorder Diagnoses based on qualitative observations Frequent misdiagnoses and rising medical costs**SPEAKER NOTES:ADHD, or Attention Deficit Hyperactivity Disorder, is a disorder characterized primarily by impulsivity and hyperactivity that influences ones ability to concentrate and regulate behavior. According to a recent article in the New York Times, there has been a twentyfold increase in the consumption of drugs for attention-deficit disorder in the past 30 years. Currently there is no well-established and experimentally verified neurological basis for ADHD, and diagnoses of the disorder are made mainly based on behavioral observations instead of quantitative measures. This results in numerous misdiagnoses, rising medical costs, and incorrect medication prescriptions. Prenatal Nicotine Exposure (PNE)PNE is linked to many psychiatric disorders

Women who smoke during pregnancy are three times as likely to have children diagnosed with ADHD

1 in 5 women still smoke during pregnancy

Several studies show behavioral, neuroanatomical, & neurochemical disturbances after PNE that are similar to ADHDBenefits of methylphenidate point to PNE as a valuable animal model of impulsivityPNE rats and humans with ADHD had similar deficits on behavioral tasks that measure impulsivity

**Obesity, conduct disorder, drug abuseHow do we know its nicotine? How do we know PNE causes the symptoms & not a hidden factor? How does it work?Neural pathfinding is guided by nAchR, so named because it can bind nicotineDA & NE pathways are involved in attention & impulsivityMPH = RitalinMPH affects the dopaminergic system, so this makes sensefocus less on MPH and more on validityAttention Deficit Hyperactivity Disorder (ADHD) & PNEPNE rats and humans with ADHD exhibit similar behavioral symptoms: inattention, hyperactivity, and impulsivityInattention: difficulty concentrating, distractibility, and problems completing tasksHyperactivity: high or excessive levels of motionImpulsivity: tendency toward rapid, unplanned actions without considering the negative consequences of these actions

Introduction**Which brings us to ADHD. Why is this such an issue?We hypothesize that this increase in diagnosis was largely due to qualitative diagnoses due to limited knowledge of the neurobiology of the disorderBecause of previous research on MPH and its effects on impulsivity, we turned our attention thereHuman Stop-signal tasks measure impulsivity

Mirabella G, Iaconelli S, Modugno N, Giannini G, Lena F, et al. (2013) Stimulation of subthalamic nuclei restores a near normal planning strategy in parkinsons patients. PLoS ONE 8(5): e62793. doi:10.1371/journal.pone.00627935Medial Prefrontal Cortex (mPFC)Introduction

Gass, J.T., & Chandler, L.J. (2013). The plasticity of extinction: contribution of the prefrontal cortex in treating addiction through inhibitory learning. Frontiers in psychiatry, 4(46): 1-13.**Structural abnormalities caused by PNEActive during impulsivity tasksHomologous area in ratsCan we tie impulsivity to PNE to neural activity?Explain neural recordings hereWe know as much about the cortex as we do about the bottom of the oceanmPFC is between eyebrowsThese coronal sections are for PFC, but not exactly for mPFCAlso talk about neural circuitry, specifically as it relates to impulsivity, here?Our ApproachUnderstanding of mPFC neural signaling is essential to treatment

Experimental system will elucidate foundation of behavior

Correlation between behavior and neural firing will allow us to pinpoint the signals involved in impulsive behavior

**SPEAKER NOTES:

Novelty of experiment: single-unit recordings from mPFC, correlate neural firing with behavior, SST in PNE rats

A full and proper understanding of mPFC circuitry is essential to the development of more effective treatment solutions related to impulse disorders such as ADHD.

Need an accessible experimental system to elucidate that biological underpinnings of this behavior (i.e., animal model of impulsivity).

The precise temporal and spatial resolution of single neuron recordings will allow us to pinpoint the signals involved in impulsive action and to determine how they are disrupted in animal models exhibiting ADHD-like symptoms.

Our GoalHypothesis: PNE rat model is a valid model for the study of ADHD-like symptoms

Show that PNE rats are more impulsive during performance on a stop-signal task that measures the ability you inhibit unwanted responses

Demonstrate that activity in mPFC is correlated with performance on the stop-signal task

Evaluate neural signals in mPFC in PNE rats during performance of the stop-signal task

**SPEAKER NOTES:Rat Breeding & Selection10 mothers total

Acclimation to nicotine 0.2 0.4 0.6 mg/mL

17 PNE and 23 control male pupsCross-fostered to control mother

Acclimate dams to nicotine in waterBreed ratsSelect pups

**Long-Evans rats selected for behavioral profileRats were acclimated to nicotine over a course of 6 weeks Give nicotine via water in proportions equal to 2 packs a day high enough to cause behavioral differences, low enough to prevent serious developmental delaysCross fosteringdidnt want to introduce any risk factors in rearing such as nicotine in breast milk and bad parenthood. Males only (brain & behavior homology)- decision-making circuits have been more extensively studied in males and PNE has more dramatic effects on males than femalesremove compare popsRat Breeding & SelectionNo significant differences in pregnancy duration, pups per litter, pup birth weight, or hyperactivity (t-test; p > 0.05)

Randomly selected 8 males each from 17 PNE pups (from 3 dams) and 23 control pups (from 3 dams)

Acclimate dams to nicotine in waterBreed ratsSelect pups

**Pregnancy duration & pups per litter show that the levels of nicotine we used were not lethal to fetal ratsCompared at selection to ensure that pups were about the same across all metrics- on day 30 the rats performed a locomotion task which indicated there were no differences between the PNE and control ratsremove compare popsStop-signal Task Training & Surgery

Task TrainingImplant electrodes

**Train for 2 hours every day (~150 trials per session)Mild water deprivation for motivationpost-op recovery to normal scoresDrivable electrodes so that we can advance through the brain to ensure that we can record in the target site and to assess the activity of different neurons over the course of the study.Get rid of btw group differences observedAlso add real pic of our electrode

Rat Stop-signal task measures impulsivityBryden, D. W., Burton, A. C., Kashtelyan, V., Barnett, B. R., & Roesch, M. R. (2012). Response inhibition signals and miscoding of direction in dorsomedial striatum. Front Integr Neurosci, 6, 69. doi: 10.3389/fnint.2012.00069Each trial began by illumination of house lights that instructed the rat to nose poke into the central port. Nose poking began with a 1000 ms delay period, after which a directional cue light either to the left or right of the nose poke flashed for 100 ms, indicating the direction in which the animal must respond to receive reward in a fluid well. These trials will be referred to as GO trials and occurred on 80% of trials. On the remaining 20% of trials, after exiting the central port, a second cue light illuminated opposite the first, instructing the animal that they must stop the already initiated movement and respond in the opposite direction. Illumination of the second light occurred between 0-100 ms after port exit.12

There were a total of four different trial-types: GO-left, GO-right, STOP-left-GO-right, and STOP-right-GO-left135075ControlRats performed significantly worse on STOP trials compared to GO trialsSTOP GO Percent Correct *(t-test; p < 0.05)*

Error bars: Standard error 145075Control*NicotinePNE Rats performed significantly worse on STOP trials compared to controlsSTOP GO Percent Correct* (t-test; p < 0.05)

PNE We conclude that PNE makes rats less able to suppress movement on STOP trials but were unimpaired on GO trials, suggesting that deficits were limited to trial types during which rats had to inhibit their movement15300750ControlRats were slower on correct STOP trialsSTOP GO STOP error MovementTime (ms)300750Control***NicotinePNE rats were significantly faster on all trial-typesSTOP GO STOP error MovementTime (ms)* (t-test; p < 0.05)PNE Speed-Accuracy Tradeoff: When rats were slower, they performed better

PNE r2 = 0.1289r2 = 0.1735p < 0.0001HAPPENED! These lines here represent a linear regression. 18SummaryBehaviorPNE rats were more impulsive (reduced stop accuracy)

PNE rats were faster on STOP and GO trials

When rats were slower they were better at inhibiting behavior (speed-accuracy tradeoff)

**Higher go correctness & faster go response timeHigher stop correctness & slow stop response timeThis may be related to a recent study showing that children with ADHD are better than non-diagnosed children at directed, uninterrupted, internally motivated work in a distraction-free environmentFrom neurons which encode this inhibitionNeural Recording & Analysis16 rats in total from the control and PNE groups performed 349 sessions, over which we collected neural firing data from 631 and 552 cells, respectively

Plexon

Neural RecordingHistologyData Analysis

**Thousands of action potentials per sessionElectrode implanted in mPFC based on skull landmarks & heights from atlas; progressed each day such that it starts & ends in the mPFCSingle unit extracellular recordings return waveforms must select range of waveforms (AP, after, shape) on channels that have cells to cut out noisehistology - verify mPFC, perfuse, slice, mount, stain, compare to atlas, won't go into detailThese figures and figures on next slide are NOT our data; just for demonstration

wrong numbers

Single cell example of a neuron that increased firing during the task

LeftNeuron not rat firing rate

explain how each time step matches with task events21

Activity was stronger on STOP trials when behavior had to be inhibited

LeftRightNot example rat, example neuron 22Average neural firing over all increasing-type neurons (Control: n = 121; PNE: n = 131)

PNEControlsay n=121, PNE=131Spell out PNE

23Average neural firing was modulated by response (solid versus dashed) on GO trials

PNEControl

24Average neural firing was stronger on STOP trials in both control and PNE rats

PNE(Wilcoxon; p < 0.001)Control

25PNE(Wilcoxon; p < 0.001)Control

However, overall firing was significantly reduced in PNE rats relative to controls

26

mPFC firing was positively correlated with percent correct (higher firing = better behavior)Next we asked if strength of neural activity was correlated with behavioral performance

Mention that each dot is a cell

27SummaryIncreasing-type cellsNeural activity was modulated by response direction

Neural activity was stronger during STOP trials

Neural activity was correlated with behavioral performance

Neural activity was significantly reduced in PNE rats compared to controls

**Higher go correctness & faster go response timeHigher stop correctness & slow stop response timeThis may be related to a recent study showing that children with ADHD are better than non-diagnosed children at directed, uninterrupted, internally motivated work in a distraction-free environmentFrom neurons which encode this inhibition

Other neurons decreased firing during performance of the task

In contrast to the neurons that increased firing rate during performance of the task, we also saw neurons that decreased firing rate during the taskHere we again see representative Raster plots, this time of the decreasing-type neuronsJust as before, each row in the upper plot represents a trial and each column lines up with a time point in the taskEach vertical line represents neuron firing, and in the lower plot these firings are summed into a histogramBefore, we saw neurons whose firing rate increased while the performed the task, but here we see a decrease in neural firing rate during the task

29Control PNE Average neural firing over all decreasing-type neurons (Control: n = 182; PNE: n = 174)

In the last slide, we looked an a representative decreasing-type neuron, here we look at the average neural firing rate of decreasing-type neurons at each time point during the taskAs with the increasing-type neurons, the solid line represents the neurons preferred direction and the dashed line represents the non-preferred directionHere we see slightly increased neural firing during performance of the task (slightly after 0 seconds) in the preferred direction as opposed to the non-preferred direction

30Control PNEDecreasing-type neurons also fired more strongly on STOP versus GO trials

(Wilcoxon; p < 0.05)

Comparing neural firing rate on STOP and GO trials for the decreasing-type neurons, we see similar results to the increasing-type neuronsDuring performance of the task, the decreasing-type neurons also had a greater firing rate on STOP trials versus GO trials in both Control and PNE groupsHere we also see an overall reduction of neural activity in PNE rats as compared to controlsThis reduction of activity is present during both task performance and baseline periods

31However, the activity of decreasing-type was not correlated with percent correct

As we did with the increasing-type neurons, we compared percent correct to firing rate for the decreasing-type cellsHowever, we did not find a significant correlation between these two variables

32Instead, neural activity was positively correlated with movement time (high firing = slower)

Instead of percent correct, we then plotted movement times versus firing rate for the decreasing-type neuronsIn Controls, we did see a positive correlation between these two variablesThis means that as the firing rate increased, so was the movement timeThis does not mean that the rats could consciously increase their neural firing rate to increase their movement time, just that on trials where firing rate was greater, so was movement time

33SummaryDecreasing-type cellsNeural activity was modulated by response direction

Neural activity was stronger during STOP trials

Neural activity was correlated with motor output in controls only

Neural activity was significantly reduced in PNE rats as compared to controls

**As we saw with the increasing-type neurons, decreasing-type neurons also had greater firing rate in the preferred directionAgain similarly to the increasing type neurons, decreasing-type neurons had greater firing rate on STOP trialsUnlike the increasing-type neurons, movement time was positively correlated with neural firing rate in decreasing-type, control neuronsFinally neural firing rate was significantly reduced in PNE rats as compared to controls during while performing the task and during baseline activity.

ConclusionsBehaviorPNE rats were more impulsive (reduced stop accuracy)

PNE rats were faster than controls on both STOP and GO trials

Neural recordingsNeural activity in mPFC was stronger during STOP trials during which rats had to inhibit behavior

Neural activity in mPFC was correlated with performance and speed

Neural activity of mPFC neurons was significantly attenuated in PNE rats as compared to controls

PNE rat model is a useful model to study the neural underpinnings of impulsive-like behavior observed in ADHD**To summarize the behavioral findings, we saw that PNE rats were more impulsive (as evidenced by their lower accuracy on STOP trials) and faster on both STOP and GO trialsTo summarize the neural recording findings, we saw a increased neural firing rate during STOP trials, which was when the rats had to inhibit their GO responseWe also found that neural activity in the mPFC was positively correlated with performance and speed in increasing and decreasing-type neurons respectively Finally, we observed a significant attenuation (or reduction) of neural activity in the mPFC of PNE rats as compared to ControlsAltogether, we believe this data suggests that the PNE rat model is a useful model for studying the neural underpinnings of the impulsive-like behavior observed in ADHD

Higher go correctness & faster go response timeHigher stop correctness & slow stop response timeThis may be related to a recent study showing that children with ADHD are better than non-diagnosed children at directed, uninterrupted, internally motivated work in a distraction-free environmentFrom neurons which encode this inhibition

Studies should target mPFC. Specifically, artificially increasing neural activity in mPFC should alleviate impulsivity in PNE rats.

Future Directions

Creative Commons Courtesy of Deisseroth labWired Based on our findings, we suggest that future studies of the PNE rat model should focus on the mPFCSpecifically, these studies should attempt to artificially increase the neural activity.This could be accomplished in multiple waysPharamacologically using stimulant drugs commonly prescribed for ADHD Electrically delivering a small electrical pulse to cause neurons to fireOptogeneticallly shining a specific wavelength of light into the brain to cause transgenic neurons to fire36Mentor - Dr. Matthew Roesch

Librarians - Ms. Francy Stilwell Mr. Jim Miller

Gemstone Staff - Dr. Frank CoaleDr. Kristan SkendallMrs. Vickie HillMrs. Leah Kreimer TobinMs. Faith RuskMr. James Trainor

Roesch Lab Members -Mr. Daniel BrydenMs. Amanda BurtonMs. Ronny GentryMr. Vadim KashtelyanMs. Nina Lichtenberg

Discussants - Dr. Ricardo AranedaDr. Gregory BissonetteDr. Erica GlasperDr. Elizabeth RedcayDr. Thomas Stalnaker

AcknowledgementsFunding: Howard Hughes Medical Institute, University of Maryland Gemstone Honors Program, and National Institute on Drug Abuse.ReferencesBryden, D. W., Burton, A. C., Kashtelyan, V., Barnett, B. R., & Roesch, M. R. (2012). Response inhibition signals and miscoding of direction in dorsomedial striatum. Front Integr Neurosci, 6, 69. doi: 10.3389/fnint.2012.00069Gass, J.T., & Chandler, L.J. (2013). The plasticity of extinction: contribution of the prefrontal cortex in treating addiction through inhibitory learning. Frontiers in psychiatry, 4(46): 1-13.Heath, C. J., & Picciotto, M. R. (2009). Nicotine-induced plasticity during development: modulation of the cholinergic system and long-term consequences for circuits involved in attention and sensory processing.Neuropharmacology, 56 Suppl 1, 254-262. doi: 10.1016/j.neuropharm.2008.07.020Linnet, K., Wisborg, K., Obel, C., Secher, N.J., Thomsen, P.H., Agerbo, E., & Henriksen, T.B. (2005) Smoking during pregnancy and the risk for hyperkinetic disorder in offspring. Pediatrics, 116(2), 462-467.Mirabella G, Iaconelli S, Modugno N, Giannini G, Lena F, et al. (2013) Stimulation of subthalamic nuclei restores a near normal planning strategy in parkinsons patients. PLoS ONE 8(5): e62793. doi:10.1371/journal.pone.0062793van Gaalen, M. M., van Koten, R., Schoffelmeer, A. N., & Vanderschuren, L. J. (2006). Critical involvement of dopaminergic neurotransmission in impulsive decision making.Biol Psychiatry, 60(1), 66-73. doi: 10.1016/j.biopsych.2005.06.005Wasserman, G. A., Liu, X., Pine, D. S., & Graziano, J. H. (2001). Contribution of maternal smoking during pregnancy and lead exposure to early child behavior problems.Neurotoxicol Teratol, 23(1), 13-21. doi: S0892-0362(00)00116-1 [pii]Zhu, J., Zhang, X., Xu, Y., Spencer, T. J., Biederman, J., & Bhide, P. G. (2012). Prenatal nicotine exposure mouse model showing hyperactivity, reduced cingulate cortex volume, reduced dopamine turnover, and responsiveness to oral methylphenidate treatment. J Neurosci, 32(27), 9410-9418. doi: 32/27/9410 [pii] 10.1523/JNEUROSCI.1041-12.2012

Questions?Questions?

**Questions?Questions?

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