Afferent GPi and Efferent from RMTg to VTA of LHb for Reward

Omission

Ziqing Zu

Nanjing Foreign Language School International Centre, Nanjing, Jiangsu, 210018, China

Keywords: Reward Omission, Globus Pallidus Internal Segment (GPi), Lateral Habenula (LHb), Glutamatergic Neurons,

Gamma-Aminobutyric Acid (Gabaergic) Neurons, Rostromedial Tegmental Nucleus (RMTg).

Abstract: Reward omission is an essential part in reinforcement learning that has not been fully appreciated, as most of

the studies have been focused on the positive reward prediction error (RPE). Therefore, this thesis investigates

into the globus pallidus internal segment (GPi), an important afferent of the lateral habenula (LHb), that is

responsible for reward omission coding. First, destroying the GPi enables us to find out whether it is the only

input for reward omission into the LHb, which is the main area for negative RPE. Then, it will be determined

whether Gamma-aminobutyric acid (GABAergic) neurons also involve in the omission signal transmission

besides glutamatergic neurons by optogenetically inhibiting GPi glutamatergic neurons. Furthermore, a

comparison between the efferent GABAergic neurons of the LHb in the rostromedial tegmental nucleus

(RMTg) and the ventral tegmental area (VTA) will be made.

1 INTRODUCTION

Numerous researches have already been done on the

investigation of understanding how brain neurons

code for RPE, which simply means the discrepancy

between expected and actual rewards signaled by the

dopamine (DA) neurons in the VTA (Schultz, Dayan,

Montague 1997). Also according to Schultz et al.

(Schultz, Dayan, Montague 1997, Schultz, Apicella,

Ljungberg 1993), when actual reward is greater than

expected, DA neurons will be activated (positive

RPE), while they will be depressed if reward is less

than the predicted reward (negative RPE). Despite the

fact that the entire neural circuit for RPE is still

unclear, there have been a myriad of researches into

the circuitry involved in positive RPE (Keiflin, Janak

2015), and even punishment prediction (Mattfeld,

Gluck, Stark 2011). However, as the other type of

negative prediction error besides punishment

prediction, the reward omission seems to be

neglected by many. Reward omission can be

understood as unexpected reduction in actual reward.

This is crucial for survival, since it also shows the

ability to update the reinforcement learning behavior

to adapt to changes in the environment (Bromberg-

Martin, Matsumoto, Hong, Hikosaka 2010).

Previous researches (Stamatakis, Van Swieten,

Basiri, Blair, Kantak, Stuber 2016, Lecca et al 2017,

Tooley et al 2018, Li, Pullmann, Jhou 2019) have

shown that ventral pallidum (VP), hypothalamus

(HT), and the GPi all project to the LHb, which is the

major region for the coding of reward omission

(Matsumoto, Hikosaka, 2007, Tian, Uchida 2015).

Furthermore, the VP (Tooley et al 2018) and the HT

(Stamatakis, Van Swieten, Basiri, Blair, Kantak,

Stuber 2016, Lecca et al 2017) are both proved to be

responsible for the punishment prediction, while the

GPi is not (Lazaridis et al 2019). However, in the

Lazaridis paper (Lazaridis et al 2019), the GPi, co-

releasing glutamatergic/GABAergic neurons, is said

not to encode negative value or develop a prediction

signal for any negative events. However, actually this

outcome is one-sided because he only mentioned the

aversion, leaving out omission entirely. As a result, it

is certain that the GPi codes for reward omission

(Hong, Hikosaka 2008), as many other research

articles have also come to the same positive

conclusion. What we do not know yet is whether the

GPi is the only input to the LHb for omission, or the

VP and the HT are also involved, apart from their

roles for punishment prediction.

Moreover, Shabel et al. (Shabel et al. 2012)

identified that both the excitatory glutamatergic

neurons and inhibitory GABAergic neurons from the

810

Zu, Z.

Afferent GPi and Efferent from RMTg to VTA of LHb for Reward Omission.

DOI: 10.5220/0011296800003443

In Proceedings of the 4th International Conference on Biomedical Engineering and Bioinformatics (ICBEB 2022), pages 810-816

ISBN: 978-989-758-595-1

GPi send projections to the LHb. Actually, in 2008,

neurons in the GPi had already been classified into

two types, the positive type and the negative type, by

Hong and Hikosaka (Hong, Hikosaka 2008). The

negative type, which will be activated when no

reward is presented, shows extremely similar firing

pattern to neurons in the LHb. As a result, presumably

it is the GPi glutamatergic neurons, that mainly, if not

entirely because of the coexisting GABAergic

neurons, send signals to its downstream LHb when

reward is omitted.

Apart from the afferent of the LHb, there have

been large amount of studies about its efferent. It has

been proved the RMTg, the immediate downstream

of the LHb, responsible for negative RPE (Jhou et al

2009), is mediated by the LHb glutamate

neurotransmitters during negative RPE (Graziane,

Neumann, Dong 2018). After that, the VTA-

projecting GABAergic neurons from the RMTg will

send inhibitory inputs (Eshe et al 2015) directly to

depress the DA neurons (Tian, Uchida 2015). While

other pathways from the LHb to the VTA DA neurons

including dorsal raphe nucleus etc. have also been

mentioned in Tian and Uchida paper (Tian, Uchida

2015), my focus is the GABAergic projection from

the RMTg to the VTA, making a comparison with the

GABAergic neurons in the VTA. Because the RMTg

is a small area close to the VTA, not many people

regard its GABAergic neurons as a distinct region

from the VTA GABAergic neurons. Nevertheless,

one of the differences between their functions can be

revealed by the coding of reward omission. As

mentioned above, the RMTg will be activated during

negative RPE (Graziane, Neumann, Dong 2018),

while the GABAergic neurons in the VTA show no

significant modulation by reward omission (Cohen et

al 2012). Therefore, understanding the circuitry will

give a brighter view of how RPE is regulated in the

main region VTA and others, hence increasing our

understanding about the complicated brain works, as

well as learning behavior.

The thesis will look deeply into the neural circuit

of omission, mainly the GPi input to the LHb to

determine whether it is the only input to the LHb for

reward omission, as well as what kind of

neurotransmitters are involved in the signaling

process. Additionally, the efferent pathway of the

LHb from the RMTg to the VTA during reward

omission will also be examined to provide a

comparison between the GABAergic neurons in the

RMTg and the VTA.

2 RESULTS

2.1 Positive Results

2.1.1 GPi is the Only Input into the LHb

Coding for Reward Omission

To determine the significance of GPi in reward

omission response, the GPi will be destroyed by

passing electricity through. Then, mice of the lesion

and control group that have already learnt the

association between the odour cue and water reward

will again be presented with the same odour cue, but

without the following water as reward (Figure 1A).

During this reward omission period, extracellular

recording of firing patterns will be taken at the LHb

and will be sorted afterwards (Figure 1B).

A B

Figure 1: Basic experimental procedure for the GPi lesion experiment. (A) Mice will first be trained to associate the odour

cue with the following water reward through a classical conditioning task. Then, during the experimental period, only the

odour cue will be delivered, while the actual result will be omitted. (B) Extracellular recording of the LHb will be made

during reward omission.

Afferent GPi and Efferent from RMTg to VTA of LHb for Reward Omission

811

As shown in Figure 2, the population spike of

neurons in the LHb of the control and lesion group of

mice responds differently to reward omission.

Normally, the excitatory glutamatergic neurons will

transmit the excitation elicited by the omitted reward

to the LHb, where the neurons will be also be

activated (Hong, Hikosaka 2013), as shown by the

control group (Figure 2A). However, on the contrary,

neurons in the LHb show no activity during reward

omission in the lesion group (Figure 2B), indicating

that they do not receive any signals for coding reward

omission.

The entirely disappeared response in the LHb

reveals that destroying the GPi has a complete effect

on reward omission coding, i.e. none of the other

neurons that project into the LHb send omission

signals. Hence, it can be concluded that the GPi is the

only input into the LHb coding for reward omission.

Figure 2: Expected result from the control group and the GPi lesion group of reward omission. (A) Unaffected population

spikes at the LHb during reward omission is recorded. (B) No firing of excitation is detected when no reward is presented to

the group of mice with lesioned GPi.

This result is anticipated according to the major

role of the GPi for reward omission (Matsumoto,

Hikosaka, 2007, Tian, Uchida 2015), and of the VP

and the HT for punishment prediction (Stamatakis,

Van Swieten, Basiri, Blair, Kantak, Stuber 2016,

Lecca et al 2017, Tooley et al 2018), which are

distinct and different. Therefore, it is not expected

that one brain region is responsible for more than one

coding process to ensure effectiveness and accuracy.

2.1.2 Neuron-type Determination in the GPi

for Reward Omission Coding

As mentioned above, the excitatory glutamatergic

neurons are estimated to be the only neuronal type

responsible for reward omission (Hong, Hikosaka

2008). To verify the correctness of this hypothesis,

we would like to let only the GABAergic neurons in

the GPi work when reward is omitted, while

inhibiting the glutamatergic ones. Then whether

neural activities will be detected can confirm whether

the GABAergic neurons are also involved in the

reward omission coding.

In this neuron-type determination experiment,

virus and the Cre-loxP system will be included for the

inhibition of neurons. Halorhodopsin (HR), a light-

gated anion channel, will specifically be expressed in

glutamatergic neurons (see Method). Then the reward

omission task (Figure 1A) will be performed again

after inhibiting the glutamatergic neurons in the GPi

via optogenetics, and neural activities at the LHb will

be recorded during omission (Figure 3).

Figure 3: Laser shone through the optic fibre for

optogenetically inhibit the GPi glutamatergic neurons, and

tetrodes for detecting neural activity at the LHb.

ICBEB 2022 - The International Conference on Biomedical Engineering and Bioinformatics

812

Only Glutamatergic Neurons in the Gpi Respond

to Reward Omission. If no neural activity is detected

at the LHb (Figure 4A), then it is clear that the

GABAergic neurons do not respond to reward

omission signals. This will lead to further

consideration of what is the purpose of the GPi

GABAergic neurons. It may suggest another circuit

including various downstream of the GPi, which

certainly needs plenty of researches into this field,

because it is unlikely that one distinctive type of

neuron is present in brain without any actual purpose.

Both Glutamatergic Neurons and Gabaergic

Neurons in the Gpi Respond to Reward Omission.

The other possible outcome is that depression is

recorded at the LHb because of the only activation of

GABAergic neurons (Figure 4B). This indicates that

the GABAergic neurons will also respond to reward

omission. Therefore, the interpretation of this

phenomenon may be the counterbalance of the co-

releasing neurotransmitters to prevent the neurons

being too activated.

A B

Figure 4: Neural activities detected at the LHb. (A) Only glutamatergic neurons code for reward omission in the GPi, deduced

by undetected neural activity induced by GABAergic neurons. (B) Both glutamatergic neurons and GABAergic neurons code

for reward omission in the GPi, deduced by a depression response of GABAergic neurons when reward is omitted.

2.2 Negative Results

2.2.1 GPi is Not the Only Input into the

LHb Coding for Reward Omission

Using the same method described, the result may also

be that still there are action potentials at the LHb,

which means the GPi is not the only upstream of the

LHb responsible for reward omission, and other

regions like the VP and the HT may also play a

nonnegligible part. Hence researches into the VP and

the HT regarding reward omission require to be done.

However, this outcome means a limitation for the

experiment that determines the neuron types in the

GPi. If it is true that other regions are also involved

in reward omission response, this means that even

inhibiting glutamatergic neurons in the GPi will not

get the expected recording, since other regions will

also be activated during reward omission. Therefore,

the neural activities in the LHb that are singly induced

by the GABAergic neurons in the GPi cannot be

detected, because of the interference from neurons of

other brain regions. It is also not practical to destroy

both the VP and the HT, because it almost means

destroying the entire system, which may lead to the

dysfunction of other brain works, such as learning

behavior and memory.

2.3 Difference in Functions of the

Gabaergic Neurons in the RMTg

and the VTA Regarding Reward

Omission

One aspect to distinguish the RMTg GABAergic

neurons from the VTA GABAergic neurons is their

different responses to reward omission signals. To test

excitations induced by omission signals from the LHb,

extracellular recording at the RMTg is done during

this period. As for detecting neurons in the VTA,

H129-ΔTK-tdT will be used to anterogradely label the

VTA neurons from the RMTg, and the DA neurons in

the VTA will be fluorescently labeled by AAV

carrying Green Fluorescent Protein (GFP) (see

Method).

By comparing the overlapping of the tdTomato-

labeled neurons and the GFP-labeled neurons, it is

expected that they are exactly the same, according the

Cohen et al. (Cohen et al 2012) that only DA neurons

Afferent GPi and Efferent from RMTg to VTA of LHb for Reward Omission

813

in the VTA respond to actual reward omission. The

consistency shows that no other neurotransmitter apart

from DA is responsible for reward omission in the

VTA. In the meantime, excitation of GABAergic

neurons in the RMTg should be recorded (Graziane,

Neumann, Dong 2018). Therefore, one of the

differences between the RMTg GABAergic neurons

and the VTA GABAergic neurons is that the former

codes for reward omission while the latter does not.

Hence it will be incorrect if one confuses the two

together.

However, if the labeling does not overlap with

each other entirely, one proper interpretation may be

that the VTA-projecting GABAergic neurons in the

RMTg are also involved in other brain activities like

punishment prediction. As a result, a more

considerate design of experiment to test this

hypothesis should be conducted in the future.

3 DISCUSSION

Because of the lack of investigation of reward

omission from previous researches, the thesis

explained some designed experiments regarding GPi

in reward omission coding and explained the

functional difference between GABAergic neurons in

the RMTg and the VTA.

The ‘blocking’ experiment will be used, i.e.

destroying the GPi to see whether there are still

responses in the LHb. If yes, then the GPi is not the

only input into the LHb coding for reward omission.

Hence further researches should look into the VP and

the HT to test their functions and responses in reward

omission, but not only limited to the punishment

related signals (Stamatakis, Van Swieten, Basiri,

Blair, Kantak, Stuber 2016, Lecca et al 2017, Tooley

et al 2018). Brain regions coding for reward omission

should not be neglected, because this is an

irreplaceable part of reinforcement learning.

If no, it can be concluded that the GPi fully

influences the activity of the LHb neurons in reward

omission. Only if the GPi has been proved to be the

only input into the LHb activated by reward omission

signals, then the optogenetics can be used to inhibit

the GPi glutamatergic neurons and record firing

patterns at the LHb to see whether GABAergic

neurons in the GPi also code for omission (Hong,

Hikosaka 2008, Hong, Hikosaka 2013). Some

reconsideration about how to determine the involved

neurons if the GPi is not the only source should be put

into the limitation. In addition, the results will elicit

more questions, for example, the role of GABAergic

neurons. Do they really help code for omission just to

ensure the neurons do not get too activated? Since

they cannot exist without any purpose, is it possible

that they lead to a whole new pathway into the VTA?

These are presently only guesses without evidence.

As for the efferent of the LHb, although the

RMTg is closely linked to the VTA, the function of

its GABAergic neurons should not be confused with

those in the VTA. One of the differences elaborated

here is the difference in coding for reward omission.

Certainly more considerate experiments should be

done to reveal their functional differences, since this

interpretation only partially considered the omission

response based on previous researches.

Large areas in reinforcement learning, including

reward omission coding, remains unexplored.

Therefore, hypotheses are expected to be made and

tested, and hopefully this thesis will be of some help.

4 METHODS

4.1 Animal

20 adult male mice will be used for the GPi lesion

experiment, 10 of which are used as lesion group, and

the rest are used as control group, containing 5 of

sham-lesion and 5 of no operation. The mice belong

to the sham-lesion and no operation group show no

difference in responding behavior at postsurgical

tests, so they will be regarded as the same in the

experiments. Mice in the lesion group and sham-

lesion group will be verified by histology.

For the neurotransmitter-determination

experiment, 10 adult male transgenic mice with

SLC17A6-Cre will be used.

For the GABAergic-neuron comparison

experiment, 10 adult male transgenic mice with

DAT-Cre will be used.

All animals were singly housed on a 12-hour

dark/12-hour light cycle.

4.2 Surgery

Electrolytic lesions will be made using a stainless-

steel electrode. The head plate that will be attached to

the skull are going to be used as the anode. After 10

days of training on the conditioned task, the 20 normal

mice will be chosen randomly to become either lesion

group or control group. Electricity will be delivered to

destroy the GPi (from bregma: -0.7mm posterior,

1.8mm lateral, 3.95 mm depth) in the lesion group,

while the sham-surgery group will have no current

delivered. During surgery, mice will be anesthetized

and placed in a stereotaxic frame. For the best result

ICBEB 2022 - The International Conference on Biomedical Engineering and Bioinformatics

814

of the surgery, monitoring the mice’s breathing rate

and maintaining the temperature of the mice are

necessary. Additionally, after recovery, all the mice

that go through the surgery will be presented with the

odour cue that they learnt in the association task

before. If the licking frequencies of mice remain high,

then they are ready for the experiment since their

memory has been tested unharmed by the surgery.

As for transgenic SLC17A6-Cre mice group, the

optic fibre will be implanted, together with the

electrode for the mimic stimulations, into the GPi, so

that light can be shone through to activate the HR.

4.3 Viral Injection

During the same surgery, adeno-associated virus

(AAV), carrying the transcription stop gene flanked

by double loxP sites with the same orientation and a

following HR, will be injected into the GPi region of

the transgenic SLC17A6-Cre mice.

The same method should be used to inject AAV,

carrying the transcription stop gene flanked by double

loxP sites with the same orientation and a following

GFP, into the VTA (from bregma, AP: −2.9 to −3.1

mm; ML: +0.35 mm; DV: −4.65 mm) of the

transgenic DAT-Cre mice.

Meanwhile, H129-ΔTK-tdT will be injected into

the RMTg (coordinate relative to bregma: AP −6.8

mm; ML ± 0.3 mm; DV −8.4 mm) for anterograde

monosynaptic tracing (Zeng et al 2017).

The expression of AAV in specific neurons is

highly selective and efﬁcient, and both the HR and

the GFP expression is uniform across specifically

targeted neurons. The amount of virus injected should

be accurately controlled, so that the virus cannot

diffuse into nearby brain regions.

4.4 Behavior Task

Before the surgery, all mice will be trained in a

classical conditioning task. The task will be a head-

fixation one, so the animals will be head-restrained

using a head plate and habituated for 15 minutes for

1-2 days before training. Each behavioral trial begins

with an odour cue (CS) for 1 second, followed by a

1-second delay and a drop of water as the reward

(US). After training, mice will perform the licking

behavior during the delay between the cue and

reward, indicating that they have learned the

association between the odour and water. When the

lick rates constantly reaches a standard frequency, the

surgeries can be conducted.

After the surgery and recovery (about 10 days),

mice will be water-deprived for the experiments. The

body weight was maintained above 85% of their full

body weight. Licks were detected by breaks of an

infrared beam placed in front of the water tube.

4.5 Electrophysiology

After 10 days of resting, the recording tetrode will be

implanted to the normal and the transgenic

SLC17A6-Cre mice through the craniotomy above

the LHb to a depth of 1.8mm below bregma. For the

transgenic DAT-Cre mice, the recording tetrode

should be implanted to the RMTg (coordinate the

same as above). All electrode wires are connected to

an electrode interface board for relaying

electrophysiological signals to the data system. For

the extracellular recording, spikes will be sorted via

specific softwares for analysis.

4.6 Histology

After the experiments, 2 mice from the lesion group

and 2 from the sham-surgery group will be sacrificed.

Their brains will be examined for the extent of lesion

by histology. Basically, coronal brain slices will be

made, and the area influenced will be recorded.

5 CONCLUSION

By observing the afferent and efferent circuitry of the

LHb, we hope to gain a better understanding about

the mechanism coding for reward omission. It is

identified whether the GPi is the only input coding for

reward omission, and whether its GABAergic

neurons, apart from the glutamatergic neurons, are

also involved in omission signal transmission.

Additionally, to help distinguish the difference

between the GABAergic neurons in the RMTg and

the VTA, their functional difference regarding reward

omission response was presented.

However, it is certain that more considerate and

further researches should be done to investigate into

the field of RPE, including reward omission. As there

are still many unidentified parts and new questions

elicited by the experiments in this thesis, which were

mentioned above, improvements and more profound

considerations are expected to be made.

ACKNOWLEDGEMENT

I thank professor Kunes, and teaching assistance

Wang and Zhang for the helpful discussion they

provide for completion of this thesis.

Afferent GPi and Efferent from RMTg to VTA of LHb for Reward Omission

815

REFERENCES

Bromberg-Martin, E. S., Matsumoto, M., Hong, S., &

Hikosaka, O. (2010). A pallidus-habenula-dopamine

pathway signals inferred stimulus values. Journal of

neurophysiology, 104(2), 1068–1076.

https://doi.org/10.1152/jn.00158.2010

Cohen, J. Y., Haesler, S., Vong, L., Lowell, B. B., &

Uchida, N. (2012). Neuron-type-specific signals for

reward and punishment in the ventral tegmental area.

Nature, 482(7383), 85–88. https://doi.org/10.1038/

nature10754

Eshel, N., Bukwich, M., Rao, V., Hemmelder, V., Tian, J.,

& Uchida, N. (2015). Arithmetic and local circuitry

underlying dopamine prediction errors. Nature,

525(7568), 243–246. https://doi.org/10.1038/

nature14855

Graziane, N. M., Neumann, P. A., & Dong, Y. (2018). A

Focus on Reward Prediction and the Lateral Habenula:

Functional Alterations and the Behavioral Outcomes

Induced by Drugs of Abuse. Frontiers in synaptic

neuroscience, 10, 12. https://doi.org/10.3389/

fnsyn.2018.00012

Hong, S., & Hikosaka, O. (2008). The globus pallidus

sends reward-related signals to the lateral habenula.

Neuron, 60(4), 720–729. https://doi.org/10.1016/

j.neuron.2008.09.035

Hong, S., & Hikosaka, O. (2013). Diverse sources of

reward value signals in the basal ganglia nuclei

transmitted to the lateral habenula in the monkey.

Frontiers in human neuroscience, 7, 778.

https://doi.org/10.3389/fnhum.2013.00778

Jhou, T. C., Fields, H. L., Baxter, M. G., Saper, C. B., &

Holland, P. C. (2009). The rostromedial tegmental

nucleus (RMTg), a GABAergic afferent to midbrain

dopamine neurons, encodes aversive stimuli and

inhibits motor responses. Neuron, 61(5), 786–800.

https://doi.org/10.1016/j.neuron.2009.02.001

Keiflin, R., & Janak, P. H. (2015). Dopamine Prediction

Errors in Reward Learning and Addiction: From

Theory to Neural Circuitry. Neuron, 88(2), 247–263.

https://doi.org/10.1016/j.neuron.2015.08.037

Lazaridis, I., Tzortzi, O., Weglage, M., Märtin, A., Xuan,

Y., Parent, M., Johansson, Y., Fuzik, J., Fürth, D.,

Fenno, L. E., Ramakrishnan, C., Silberberg, G.,

Deisseroth, K., Carlén, M., & Meletis, K. (2019). A

hypothalamus-habenula circuit controls aversion.

Molecular psychiatry, 24(9), 1351–1368.

https://doi.org/10.1038/s41380-019-0369-5

Lecca, S., Meye, F. J., Trusel, M., Tchenio, A., Harris, J.,

Schwarz, M. K., Burdakov, D., Georges, F., &

Mameli, M. (2017). Aversive stimuli drive

hypothalamus-to-habenula excitation to promote

escape behavior. eLife, 6, e30697.

https://doi.org/10.7554/eLife.30697

Li, H., Pullmann, D., & Jhou, T. C. (2019). Valence-

encoding in the lateral habenula arises from the

entopeduncular region. eLife, 8, e41223.

https://doi.org/10.7554/eLife.41223

Matsumoto, M., & Hikosaka, O. (2007). Lateral habenula

as a source of negative reward signals in dopamine

neurons. Nature, 447(7148), 1111–1115.

https://doi.org/10.1038/nature05860

Mattfeld, A. T., Gluck, M. A., & Stark, C. E. (2011).

Functional specialization within the striatum along

both the dorsal/ventral and anterior/posterior axes

during associative learning via reward and

punishment. Learning & memory (Cold Spring

Harbor, N.Y.), 18(11), 703–711.

https://doi.org/10.1101/lm.022889.111

Schultz, W., Apicella, P., & Ljungberg, T. (1993).

Responses of monkey dopamine neurons to reward and

conditioned stimuli during successive steps of learning

a delayed response task. The Journal of neuroscience:

the official journal of the Society for Neuroscience,

13(3), 900–913.

https://doi.org/10.1523/JNEUROSCI.13-03-

00900.1993

Schultz, W., Dayan, P., & Montague, P. R. (1997). A

neural substrate of prediction and reward. Science

(New York, N.Y.), 275(5306), 1593–1599.

https://doi.org/10.1126/science.275.5306.1593

Shabel, S. J., Proulx, C. D., Trias, A., Murphy, R. T., &

Malinow, R. (2012). Input to the lateral habenula from

the basal ganglia is excitatory, aversive, and

suppressed by serotonin. Neuron, 74(3), 475–481.

https://doi.org/10.1016/j.neuron.2012.02.037

Stamatakis, A. M., Van Swieten, M., Basiri, M. L., Blair,

G. A., Kantak, P., & Stuber, G. D. (2016). Lateral

Hypothalamic Area Glutamatergic Neurons and Their

Projections to the Lateral Habenula Regulate Feeding

and Reward. The Journal of neuroscience: the official

journal of the Society for Neuroscience, 36(2), 302–

311. https://doi.org/10.1523/JNEUROSCI.1202-

15.2016

Tian, J., & Uchida, N. (2015). Habenula Lesions Reveal

that Multiple Mechanisms Underlie Dopamine

Prediction Errors. Neuron, 87(6), 1304–1316.

https://doi.org/10.1016/j.neuron.2015.08.028

Tooley, J., Marconi, L., Alipio, J. B., Matikainen-Ankney,

B., Georgiou, P., Kravitz, A. V., & Creed, M. C.

(2018). Glutamatergic Ventral Pallidal Neurons

Modulate Activity of the Habenula-Tegmental

Circuitry and Constrain Reward Seeking. Biological

psychiatry, 83(12), 1012–1023. https://doi.org/

10.1016/j.biopsych.2018.01.003

Zeng, W. B., Jiang, H. F., Gang, Y. D., Song, Y. G., Shen,

Z. Z., Yang, H., Dong, X., Tian, Y. L., Ni, R. J., Liu,

Y., Tang, N., Li, X., Jiang, X., Gao, D., Androulakis,

M., He, X. B., Xia, H. M., Ming, Y. Z., Lu, Y., Zhou,

J. N., … Luo, M. H. (2017). Anterograde

monosynaptic transneuronal tracers derived from

herpes simplex virus 1 strain H129. Molecular

neurodegeneration, 12(1), 38. https://doi.org/10.1186/

s13024-017-0179-7

ICBEB 2022 - The International Conference on Biomedical Engineering and Bioinformatics

816