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Spatial Learning Promotes Adult
Neurogenesis in Specific Regions of
the Zebrafish Pallium
Laura S. Mazzitelli-Fuentes
1
,
2
,
3
, Fernanda R. Román
1
,
2
,
4
, Julio R. Castillo Elías
1
,
5
,
Emilia B. Deleglise
1
,
2
,
3
and Lucas A. Mongiat
1
,
2
*
1
Departamento de Física Médica, Centro Atómico Bariloche, Comisión Nacional de Energía Atómica, San Carlos de Bariloche,
Argentina,
2
Consejo Nacional de Investigaciones Científicas y, Técnicas, Argentina,
3
Instituto Balseiro, Centro Atómico Bariloche,
San Carlos de Bariloche, Argentina,
4
Centro Regional Universitario Bariloche, Universidad Nacional del Comahue, San Carlos de
Bariloche, Argentina,
5
Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Autónoma de Buenos
Aires, Argentina
Adult neurogenesis could be considered as a homeostatic mechanism that accompanies
the continuous growth of teleost fish. As an alternative but not excluding hypothesis, adult
neurogenesis would provide a form of plasticity necessary to adapt the brain to
environmental challenges. The zebrafish pallium is a brain structure involved in the
processing of various cognitive functions and exhibits extended neurogenic niches
throughout the periventricular zone. The involvement of neuronal addition as a
learning-related plastic mechanism has not been explored in this model, yet. In this
work, we trained adult zebrafish in a spatial behavioral paradigm and evaluated the
neurogenic dynamics in different pallial niches. We found that adult zebrafish improved
their performance in a cue-guided rhomboid maze throughout five daily sessions, being the
fish able to relearn the task after a rule change. This cognitive activity increased cell
proliferation exclusively in two pallial regions: the caudal lateral pallium (cLP) and the rostral
medial pallium (rMP). To assessed whether learning impinges on pallial adult neurogenesis,
mitotic cells were labeled by BrdU administration, and then fish were trained at different
periods of adult-born neuron maturation. Our results indicate that adult-born neurons are
being produced on demand in rMP and cLP during the learning process, but with distinct
critical periods among these regions. Next, we evaluated the time course of adult
neurogenesis by pulse and chase experiments. We found that labeled cells decreased
between 4 and 32 dpl in both learning-sensitive regions, whereas a fraction of them
continues proliferating over time. By modeling the population dynamics of neural stem cells
(NSC), we propose that learning increases adult neurogenesis by two mechanisms: driving
a chained proliferation of labeled NSC and rescuing newborn neurons from death. Our
findings highlight adult neurogenesis as a conserved source of brain plasticity and shed
light on a rostro-caudal specialization of pallial neurogenic niches in adult zebrafish.
Keywords: neural stem/progenitor cells, plasticity, telencephalon, danio rerio (zebrafish), spatial learning and
memory
Edited by:
Ma Salomé Sirerol Piquer,
Center for Biomedical Research on
Neurodegenerative Diseases
(CIBERNED), Spain
Reviewed by:
Kenji Shimamura,
Kumamoto University, Japan
María Esmeralda Castelló,
Instituto de Investigaciones Biológicas
Clemente Estable (IIBCE), Uruguay
*Correspondence:
Lucas A. Mongiat
lucas.mongiat@cab.cnea.gov.ar
Specialty section:
This article was submitted to
Stem Cell Research,
a section of the journal
Frontiers in Cell and Developmental
Biology
Received: 21 December 2021
Accepted: 29 March 2022
Published: 11 May 2022
Citation:
Mazzitelli-Fuentes LS, Román FR,
Castillo Elías JR, Deleglise EB and
Mongiat LA (2022) Spatial Learning
Promotes Adult Neurogenesis in
Specific Regions of the
Zebrafish Pallium.
Front. Cell Dev. Biol. 10:840964.
doi: 10.3389/fcell.2022.840964
Frontiers in Cell and Developmental Biology | www.frontiersin.org May 2022 | Volume 10 | Article 8409641
ORIGINAL RESEARCH
published: 11 May 2022
doi: 10.3389/fcell.2022.840964
INTRODUCTION
Brain plasticity allows neuronal circuits to adapt to
environmental demands, promoting the ability to cope with
the surrounding world. Adult neurogenesis, the generation and
integration of new neurons in the brain of adult organisms,
constitute a major source of brain plasticity (Mongiat and
Schinder, 2011;Sailor et al., 2017;Toda and Gage, 2018). The
occurrence of neurogenesis in adult brains extends throughout
the vertebrate subphylum, although its magnitude varies greatly
along phylogeny (Kaslin et al., 2008;Grandel and Brand, 2013;
Alunni and Bally-Cuif, 2016;Zupanc, 2021). In mammals, adult
neurogenesis is restricted mostly to the hippocampal dentate
gyrus and the olfactory bulb (Lledo et al., 2006), whereas in teleost
fish adult-born neurons are generated throughout their brain
(Kaslin et al., 2008).
The zebrafish (Danio rerio) possesses a great neurogenic
potential evidenced by constitutive neural stem cell (NSC)
proliferation in almost all subdivisions of their brain,
generating a variety of adult-born neurons (Zupanc et al.,
2005;Adolf et al., 2006;Grandel et al., 2006). One of the main
brain regions in which adult neurogenesis has been studied in
zebrafish is the dorsal telencephalon, or pallium. In contrast to
other vertebrates, the telencephalon of ray-finned fish develops by
an eversion of the neural tube (Folgueira et al., 2012). In
consequence, both pallial hemispheres are separated and
enclosed by a T-shaped ventricle. In this structure, the
neuronal progenitors are localized in the periventricular zone
(Adolf et al., 2006;Grandel et al., 2006). In the zebrafish pallium,
there are different kinds of neural progenitor subtypes. Some of
them, notably radial glia (RG) of the pallium, are considered
NSCs, resembling the pallial RG in the mouse adult neurogenic
niches (Than-Trong and Bally-cuif, 2015). These NSCs can be
classified according to their proliferation activity, such as
quiescent and active NSCs. At any time, the active NSCs
correspond to ~5% of total RG in the periventricular zone
(März et al., 2010). In turn, the active NSCs can suffer
symmetric or asymmetric divisions to maintain the NSC
reservoir and give rise to progeny with neurogenic potential
(Than-Trong et al., 2020). Moreover, there is a different subset
of neuronal progenitors in the pallial periventricular zone. These
cells are negative for astroglial markers and exhibit intense
mitotic activity with neurogenic commitment (Rothenaigner
et al., 2011;Than-Trong et al., 2020). Previous studies
proposed that this neuronal progenitor population resembles
the Transit Amplifying Progenitors described in rodents (März
et al., 2010).
After adopting neuronal phenotype, the new neurons migrate
radially a few micrometers into the pallial parenchyma and
become integrated into the adult pallial networks. This
neurogenic process leads to an outside-in architecture, where
neurons generated in early development are positioned at the
center of the pallium, while a layered gradient of newer neurons is
distributed towards the periphery (Furlan et al., 2017). The new
neurons mature and integrate into the pallial neuronal networks
(Grandel et al., 2006;Rothenaigner et al., 2011;Lange et al., 2020;
Than-Trong et al., 2020). Recently, Lange and coworkers
performed single-cell sequencing of NSC’s progeny to
characterize the intrinsic heterogeneity of adult-born neurons
in the zebrafish telencephalon, revealing a striking homology with
the neuronal types found in the mammalian forebrain (Lange
et al., 2020). Therefore, adult neurogenesis contributes to a
continuous rearrangement of zebrafish’s pallial networks.
Several studies have been conducted to decipher the
organization of the teleost pallium based on anatomical
characterization and the expression of molecular markers
(Wullimann and Mueller, 2004;Vargas et al., 2009;Mueller,
2011;Harvey-Girard et al., 2012;Ganz et al., 2015). Current
knowledge on the functional role of the different pallial regions, is
complemented with a series of functional studies involving
distinct learning paradigms in combination with the detection
of neuronal activity (by different proxies) and/or lesions on
specific regions (Portavella et al., 2004;Durán et al., 2010;
Trotha et al., 2014;Elliott et al., 2017;Lal et al., 2018;Ausas
et al., 2019). All these works indicate that the teleost dorsomedial
telencephalic region (medial pallium, MP) is homologus to the
basolateral amygdala of mammals, whereas the dorsolateral
telencephalic region (lateral pallium, LP) is homologus to the
mammalian hippocampus. From these studies emerge a strong
relation between the teleost pallium and cognitive activity,
suggesting plastic changes on pallial networks. In particular,
adult neurogenesis could play a relevant role by shaping the
neuronal circuits during learning. In rodents, it is known that
behavioral paradigms such as odor-related and hippocampus-
dependent learning increase the survival of immature adult-born
neurons (Lledo et al., 2006;Anderson et al., 2011;Aasebø et al.,
2018). However, to our knowledge, the role of cognitive activity
on pallial network remodeling has not been explored in
teleosts yet.
In this study, we trained adult zebrafish in a cognitive task to
evaluate the impact of sustained neuronal activity on pallial adult
neurogenesis. We found that learning may lead to plastic network
remodeling driven by adult neurogenesis, specifically in the
rostral MP and caudal LP regions.
RESULTS
Adult Zebrafish Learn in the Cue-Guided
Rhomboid Maze
We hypothesized that sustained pallial neuronal activity,
triggered as a consequence of a learning routine, would
enhance the rate of adult neurogenesis in the circuits
underlying the cognitive function. For this purpose, we looked
for a learning paradigm involving the function of specific pallial
structures, together with a sustained cognitive challenge. We
adapted a cue-guided rhomboid maze, developed for goldfish,
in order to train adult zebrafish in learning a spatial task by
relating external cues with their internal-directional information.
Otherwise noticed, 10 ± 1 months-old adult AB-wild type
zebrafish (Danio rerio) were used throughout this work.
During training, fish were located randomly at one of the two
possible start sites in each trial. The fish had to learn the
relationship between the cues’position and the exit to solve
Frontiers in Cell and Developmental Biology | www.frontiersin.org May 2022 | Volume 10 | Article 8409642
Mazzitelli-Fuentes et al. Adult Neurogenesis Modulation by Learning
FIGURE 1 | Training adult zebrafish in a rhomboid maze boosts cell proliferation in the rMP and the cLP. (A). Experimental device. The maze contains two starting
boxes, and two possible exits, one of which is blocked with a glass barrier. Fish were trained to find the correct exit, orientating themselves with cues placed on two walls.
On the edges of the tank, two glass enclosures contained fish’s conspecifics as social reward. On each trial, fish were placed in a start box, and, once they reached the
central arena, a correct choice was scored if they swam through the exit, and a failure if they bumped against the glass barrier. Each daily session consisted of 24
trials. (A’)Behavioral schedule. Cue patterns and exit position (arrow) are specified above. Fish were habituated to the experimental tank for 2 days, and subsequently
trained for five consecutive days. (B). Learning curves for Trained and Control individual s. Trained fish reach the learning criterion after five consecutive sessions. Controls
do not exhibit a learning curve (Two-way RM ANOVA, Treatment effect: F
(1, 14)
= 25.78 with p= 0.0002, Session effect: F
(4, 56)
= 3.422 with p= 0.0143. Bonferroni’s
multiple comparisons test, **** depicts p<0.0001. Trained, N = 8; Control N = 8). Dashed line at 70% correct choices depicts learning criterion; dashed line at 50%
correct choices indicates random choice. (C). Simple linear regression for Trained and Control individual s (ANCOVA, F
(1, 77)
= 9.010. **** depicts p<0.0001. Trained, N =
8; Control N = 8). Dashed line indicates 95% confidence intervals. (D). Left: Sagitta l schematic view of zebrafish forebrain, indicating the position of the cross sections on
the right. Right: Cross sections of zebrafish telencephalon along rostro-caudal axis (R: rostral, RM: rostro-medial, MC: medio-caudal, C: caudal). The colored regions
depict MP and LP. (E). PCNA
+
cells in LP. (Two-way ANOVA, Treatment effect: F
(1, 37)
= 3.873 with p= 0.0566, Pallium region effect: F
(3, 37)
= 20.27 with p<0.0001.
Bonferroni’s multiple comparisons test, ** denotes p<0.001. Trained, N = 6; Control, N = 6). (F). Cross sections of telencephalic pallium immunostained for PCNA in cLP
of Trained and Control individuals. Scale bar, 50 μm. Scale bar in higher magnifications, 20 μm. Black arrows indicate representative PCNA
+
cells. (G). PCNA
+
cells in
MP. (Two-way ANOVA, Treatment effect: F
(1, 38)
= 7.796 with p= 0.0082, Pallium region effect: F
(3, 38)
= 2.332 with p= 0.0895. Bonferroni’s multiple comparisons test, *
denotes p<0.05. Trained, N = 6; Control, N = 6). (H). Cross sections of telencephalic pallium immun ostained for PCNA in rMP of Trained and Control individuals. Scale
bar, 50 μm. Scale bar in higher magnifications, 20 μm. Black arrows indicate representative PCNA
+
cells.
Frontiers in Cell and Developmental Biology | www.frontiersin.org May 2022 | Volume 10 | Article 8409643
Mazzitelli-Fuentes et al. Adult Neurogenesis Modulation by Learning
the maze; for example, turn right if cues are located at the same
side of the start compartment and turn left if they are at the
opposite side (Figure 1A). Thus, on each trial the fish must take a
left-right decision based on cues’position. To encourage the
completion of the task, we placed several conspecifics in outer
compartments as social reward. To assess the ability of zebrafish
to learn the task, fish were trained for five consecutive sessions (1
session/day, 24 trials/session, Figure 1A’). The Control group
consisted on fish which were subjected to the same training
routine, with the exception that the glass barrier was randomly
placed in any of the exits to avoid learning. The Control group
exhibited a ~50% correct choices throughout the sessions,
remaining close to the chance level (Figure 1B,C,
Supplementary Video S1). In contrast, the Trained group
increased their performance in a daily manner until they
exceeded a 75% of correct choices (Percentage of correct
choices for Session 5, Mean ± SE: Control 50.00 ± 2.362;
Trained 78.65 ± 2.992; N = 8, Supplementary Video S2). It
should be noticed that all trained subjects accomplished the
learning criterion and were included in further analysis. Here,
we introduce the cue-guided rhomboid maze as a novel
behavioral paradigm to assess spatial learning ability in adult
zebrafish.
Learning-Induced Cell Proliferation in Adult
Zebrafish Pallium
Previous studies in goldfish reported that learning in the cue-
guided rhomboid maze induces a selective increase of metabolic
activity in the LP of trained subjects (Durán et al., 2015;Ocaña
et al., 2017). Thus, we aimed to test whether learning in the
rhomboid maze task would have any effect on cell proliferation in
this neurogenic niche. It must be noticed that the Control group is
subjected to manipulations, environment conditions and social
reward in the same way as Trained subjects. Hence, changes in
proliferation and/or neurogenesis should be related to the
learning process.
To evaluate mitotic activity, we determined the expression of
the Proliferating Cell Nuclear Antigen (PCNA) throughout the
rostro-caudal axis of the pallium (Figures 1D–H,Supplementary
Figures S1A–E). Expression of PCNA in the pallium was
detected from the rostral to the caudal regions, in the
periventricular zone. Supporting our hypothesis we found a
learning-related increase in the PCNA detection in the LP,
only restricted to its caudal region (cLP, ~180%; Figures
1E,F). Unexpectedly, we also observed a relevant learning-
related gain in PCNA levels in the rostral region of MP (rMP,
~220%, Figures 1G,H).
It is known that senescence leads to cognitive deterioration, a
fact that has also been proven for zebrafish (Ruhl et al., 2015;
Adams and Kafaligonul, 2018;Yang et al., 2018). Thus, we
explored whether aged zebrafish (21 months-old) could learn
in the cue-guided rhomboid maze and, consequently, increase
proliferation rates in the pallium. As observed for adult-young
zebrafish, senescent individuals improve their task performance
in a daily manner (Supplementary Figure S2). In agreement with
our previous observations, aged fish exhibit an enhancement of
PCNA expression exclusively in the rMP (~180%) and the cLP
(~250%) of Trained fish (Supplementary Figure S2).
Interestingly, we observed a slight improvement in the
learning curve and in the basal levels of proliferation, in the
aged zebrafish (Figure 1 and Supplementary Figure S2).
Our results indicate that cognitive activity, carried out on the
cue-guided rhomboid maze, induces an increase in cell
proliferation in two delimited neurogenic regions of the
pallium of adult zebrafish.
Enhanced Adult Neurogenesis by Learning
in the Rhomboid Maze
Adult neurogenesis is a plastic phenomenon that can be
modulated by network activity at different levels, such as
NSCs proliferation, migration, differentiation and survival of
new neurons. However, the role of cognitive activity on adult
neurogenesis modulation has not been explored in zebrafish, yet.
We hypothesized that sustained neuronal activity triggered as a
consequence of learning impinges on immature adult-born
neurons to promote pallial network remodeling. To approach
this question we treated adult fish (~10 months-old) with BrdU, a
thymidine analogue, to label NSCs during the S-phase of mitotic
cell division. We allowed BrdU-labeled neurons to develop over a
12-day period. Then, fish were randomly divided into Trained
and Control (mocked) groups, and subjected to sustained
training in the rhomboid maze from 12 to 30 dpl, a period in
which we estimate that adult-born neurons are maturing
(Figure 2A). To maintain the cognitive challenge during the
training period, we changed the cues and the learning rule at the
beginning of each week. Trained subjects exhibited a good
learning curve, reaching the established criterion at the fifth
session of the first week, and were able to relearn the task
after the rule shift during the following weeks (Figure 2B,
Percentage of correct choices for Session 5, Mean ± SE:
Control 57.81 ± 2.54; Trained 76.56 ± 3.14, N = 8). Notably,
after the first week of training, the subjects showed a better
performance when relearning the task, evidenced by an increase
in the learning curve slope of Trained fish (Figure 2C, Simple
linear regression, 1
st
week vs. 2 weeks: p= 0.0343; 1
st
week vs.
3
rd
week: p= 0.0096).
After completing the training schedule, we assessed the fate of
BrdU-labeled cells by immunodetection of the neuronal marker
NeuN. The effect of learning on adult neurogenesis was evaluated
by quantifying the number of adult-born neurons (BrdU
+
NeuN
+
)
throughout the pallial rostro-caudal axis. We found that the cLP
of Trained subjects exhibited an increase (~ 250%) in the number
of 30 dpl BrdU-labeled neurons as compared to Control group,
whereas the other rostro-caudal LP regions shown similar levels
of 30 dpl adult-born neurons between both experimental groups
(Figures 2D,F, BrdU
+
NeuN
+
in cLP, Mean ± SE: Control 44.39 ±
12.71, N = 5; Trained 112.28 ± 16.41, N = 7). Similarly, in the MP
we observed an increase of BrdU-labeled neurons (>300%)
exclusively in the rostral region of the MP (Figures 2G,I,I’,
BrdU
+
NeuN
+
in rMP, Mean ± SE: Control 57.73 ± 26.00, N =
5; Trained 204.50 ± 56.36, N = 7). Since network activity may
regulate adult-born neurons development, we decided to evaluate
Frontiers in Cell and Developmental Biology | www.frontiersin.org May 2022 | Volume 10 | Article 8409644
Mazzitelli-Fuentes et al. Adult Neurogenesis Modulation by Learning
FIGURE 2 | Sustained training of zebrafish from 12–30 dpl increases adult neurogenesis exclusively in the cLP and the rMP. (A). Experimental schedule. Fish were
immersed in BrdU, and training started at 12 dpl. Training consisted of 15 sessions, distributed in three slots. Every five sessions both cues and exit position were
changed. A 2-day interval was fixed between slots. At 30 dpl fish were euthanised for histology. (B). Learning curves for Trained and Control individuals (Two-way RM
ANOVA, Treatment effect: F
(1, 14)
= 67.71 with p<0.0001, Session effect: F
(14, 196)
= 6.805 with p<0.0001. Bonferroni’s multiple comparisons test, * depicts p<
0.05, **p<0.01, ****p<0.0001.Trained, N = 8; Control N = 8). (C). Simple linear regression for each training window for Trained fish (ANCOVA, first vs. 2nd week: F
(1,76)
=
4.647; 1st vs. 3rd week: F
(1,76)
= 7.068, * indicates p<0.05, **, p<0.01. Trained, N = 8; Control N = 8). (D). BrdU
+
NeuN
+
cell quantification in LP (Two-way ANOVA,
Treatment effect: F
(1, 41)
=2.766withp= 0.103, Pallium region effect: F
(3, 41)
=4.493withp= 0.0098. Bonferroni’s multiple comparisons test, **p<0.01. Trained, N = 7;
Control N = 6). (E). Top: Neuronalfate (%BrdU
+
NeuN
+
/BrdU
+
cells) in caudalLP (Unpaired ttest, t
(10)
= 0.5091, n. s.Trained, N = 7; Control N = 5).Bottom: Cell migration in
caudal LP (Mann Whitney test, U = 2419, n. s. Trained, N = 7; Control N = 6). (F). Adult-born neurons (BrdU/NeuN) in cLP for Trained and Control individuals. Scale bar,
(Continued )
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Mazzitelli-Fuentes et al. Adult Neurogenesis Modulation by Learning
if learning affects neuronal differentiation, assessed as the
percentage of labeled cells which adopt neuronal phenotype
(BrdU-labeled cells that express the neuronal marker NeuN,
BrdU
+
NeuN
+
/BrdU
+
), as well as the migration distance of
BrdU-labeled cells, measured from the ventricular boundary
into the final position in the pallial parenchyma
(Supplementary Figure S3). We analyzed only the regions in
which learning promotes adult neurogenesis. Neither of these
parameters were affected by learning, except for the migration
distance in rMP, which was lower in Trained subjects (Figures
2E,H). The difference in migration distance may account for
late recruited BrdU-labeled progenitors, which were product of
conservative division and now are being activated by learning, a
concept that we are exploring below. Thus, it is expected that
younger BrdU-labeled neurons remains close to the
periventricular zone. These results indicate that training in
the rhomboidal maze task during a 12–30 dpl time frame
promotes adult neurogenesis in the cLP and in the rMP,
shedding light on the potential relevance of these pallial
regions during learning.
Critical Period for Learning-Induced Adult
Neurogenesis
Our previous results indicate that learning has an immediate
effect on cell proliferation in the cLP and rMP neurogenic regions
(Figure 1). Also we found a learning-related increase of adult-
born neurons in the in the same pallial regions after a 12–30 dpl
training (Figure 2). The neurogenic process involves several
checkpoints where network activity and systemic signaling
regulate distinct developmental processes in a time-dependent
manner (Mu et al., 2010). On these basis, we evaluated if learning
has an impact on adult-born neurons at different maturation
periods. We did not observe significant changes between the
Control and Trained groups at any rostro-caudal region of LP
when training occurred during an earlier maturation stage of
adult-born neurons (3–14 dpl, Figures 3A–D,F). On the other
hand, we found that learning stimulates an increase (~200%) in
the levels of rMP 30 dpl adult-born neurons (Figures 3G,I,I’,
BrdU
+
NeuN
+
in rMP, Mean ± SE: Control 94.20 ± 17.61; Trained
188.30 ± 36.01, N = 8). Furthermore, we evaluated neuronal fate
and observed a significant increase in the percentage of newborn
neurons only in the cLP. The final position of the labeled neurons
(migration distance) showed no differences at any region
(Figures 3E,H).
Next, we assessed adult neurogenesis after training fish during
a late period, at 31–42 dpl (Figures 4A–C). Both experimental
groups exhibited similar levels of neurogenesis (Figure 4D). Our
results indicate that adult neurogenesis in the rMP and the cLP is
sensitive to training in the rhomboid maze, during restricted
periods (Figure 4E). The critical period for learning-induced
adult neurogenesis is slightly shorter in the cLP as compared to
the rMP. This modulation of adult neurogenesis by network
activity could be attributed to two possible non-excluding
mechanisms: 1) activity-related increase in the survival of
adult-born neurons, avoiding cell death programs; 2) activity-
related chained recruitment of BrdU-labeled cells, which were
product of conservative divisions.
Chained Proliferation of Labeled NSCs and
Adult-Born Cell Death Modulate Adult
Neurogenesis in the Pallium
In rodents, it is well established that network activity promotes
synaptic integration of adult-born neurons and, in consequence,
favor the neuronal survival (Ryu et al., 2016). Hitherto, this
hypothesis has not been explored in teleost fish, yet. On the
other hand, Than-Trong and coworkers (2020) proposed that
adult neurogenesis relies on different kinds of NSCs, a reservoir
pool involved in the self-renewal of NSCs (rNSC), and an
operational group with neurogenic function (oNSC) (Than-
Trong et al., 2020). The oNSCs can divide either in a
symmetric or asymmetric way to produce new neurons and to
preserve the NSC pool. In this context, our adult neurogenesis
results would rely on learning-induced sequential recruitment of
BrdU-labeled cells or, alternatively, on an activity-dependent
rescue from death. Therefore, we assessed a time course for
neuronal survival and proliferation of EdU-labeled cells at four
temporal points: 4, 16, 32 and 64 dpl (Figure 5A).
We found a ~37% neuronal survival in the cLP when
comparing 4 vs. 32 dpl (Figures 5B,D, Number of EdU
+
cells
in cLP: 4 dpl 144.7 ± 21.53, N = 8; 32 dpl 54.16 ± 11.47, N = 3),
whereas for rMP the survival of EdU-labeled cells during the
same period was ~55% (Figures 5E,G, Number of EdU
+
cells in
rMP: 4 dpl 245.6 ± 31.45, N = 8; 32 dpl 131.8 ± 23.84, N = 4). The
decrease in the number of labeled cells in both pallial regions
could indicate the death of a portion of these cells. Furthermore,
we assessed the sequential recruitment of EdU-labeled cells by
PCNA expression. We found a relevant fraction (44.03 ± 10,02%)
of mitotic EdU-labeled cells at 4 dpl in the cLP (Figure 5C),
which diminished considerably at later times. In contrast, in the
rMP we found a portion of EdU
+
proliferating cells from 4 to 32
dpl (26.54 ± 6.21%), while we observed scarce proliferation in
labeled cells at 64 dpl. (Figure 5F). Hence, a considerable portion
of proliferating cells retain EdU labeling and continues dividing
in the cLP and the rMP (Figure 5H). Our results point to a
complex regulation of adult neurogenesis in the pallium of
zebrafish, where chained proliferation of NSCs and death of
immature neurons are balanced to contribute to the neuronal
addition on these networks.
FIGURE 2 | 20 μm. (G).BrdU
+
NeuN
+
cell quantification in MP. (Two-way ANOVA, Treatment effect: F
(1, 43)
=9.564withp= 0.0035, Palliumregion effect: F
(3, 43)
=0.889with
p= 0.455. Bonferroni’s multiple comparisons test,*p<0.05. Trained,N = 7; Control N = 6). (H).Top:Neuronalfate(%BrdU
+
NeuN
+
/BrdU
+
cells)in rMP (Mann-Whitney test,U
= 11.5, n. s. Trained, N = 7; Control N = 4). Bottom: Cell migration in rMP (Mann Whitney test, U = 602, * depicts p<0.05. Trained, N = 7; Control, N = 4). (I). Adult-born
neurons (BrdU/NeuN) in rMP for Trained and Control individuals. Scale bar, 20 μm. (I’). Higher magnification of the boxed square in I (merge panel). Single focal plane and
orthogonal views after three-dimension reconstruction.
Frontiers in Cell and Developmental Biology | www.frontiersin.org May 2022 | Volume 10 | Article 8409646
Mazzitelli-Fuentes et al. Adult Neurogenesis Modulation by Learning
FIGURE 3 | Training zebrafish during an early period (3–14 dpl) increases adult neur ogenesis in the rMP. (A). Experimental design. (B). Learning curves for Trained
and Control individuals (Two-way RM ANOVA, Treatment effect: F
(1, 14)
= 126.1 with p<0.0001, Session effect: F
(9, 126)
= 5.254 with p<0.0001. Bonferroni’s multiple
comparisons test, *** depicts p<0.001, ****, p<0.0001. Trained, N = 8; Control N = 8). (C). Simple linear regression for each training window for Trai ned fish (ANCOVA,
F
(1, 76)
= 1.516, n. s. Trained, N = 8; Control N = 8). (D). BrdU
+
NeuN
+
cell quantification in LP. (Two-way ANOVA, Treatment effect: F
(1, 54)
= 10.63 with p= 0.0019,
Pallium region effect: F
(3, 54)
= 8.642 with p<0.0001. Bonferroni’s multiple comparisons test, not significant differences. Trained, N = 8; Cont rol N = 8). (E). Top: Neuronal
fate (%BrdU
+
NeuN
+
/BrdU
+
cells) in cLP. (Unpaired ttest, t
(14)
= 4.749, *** depicts p<0.001. Trained, N = 8; Control N = 8). Bottom: Cell migration in cLP (Mann Whitney
test, U = 6492, n. s. Trained, N = 8; Control N = 8). (F). Adult-born neurons (BrdU
+
NeuN
+
) in cLP for Trained and Control individuals. Scale bar, 20 μm. (G). BrdU
+
NeuN
+
cell quantification in MP. (Two-way ANOVA, Treatment effect: F
(1, 56)
= 15.34 with p= 0.0002, Pallium region effect: F
(3, 56)
= 2.685 with p= 0.0553. Bonferroni’s multiple
comparisons test, * depicts p<0.05. Trained, N = 8; Control N = 8). (H). Top: Neuronal fate (%BrdU
+
NeuN
+
/BrdU
+
cells) in rMP (Unpaired ttest, t
(14)
= 1.396, n. s.
Trained, N = 8; Control N = 8). Bottom: Cell migration in rMP (Mann Whitney test, U = 2088, n. s. Trained, N = 8; Control N = 8). (I). Adult-born neurons (BrdU
+
NeuN
+
)in
rMP for Trained and Control individuals. Scale bar, 20 μm. (I’). Higher magnification of the boxed square in I (merge panel). Single focal plane and orthogonal views after
three-dimension reconstruction.
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Mazzitelli-Fuentes et al. Adult Neurogenesis Modulation by Learning
A Population Dynamics Model Mimics the
Learning-Induced Adult Neurogenesis in
the MP
Recently, Than-Trong and coworkers (2020) performed an intra-
vital imaging analysis to track the fate of NSCs in the MP. Based
on the experimental results and a computational model, the
authors estimated the proportions of symmetric and
asymmetric divisions, and possible fates adopted by activated
NSCs. Based on the division rates observed by Than-Trong and
coworkers, we adapted their model to assess the dynamics of
neuronal addition under different conditions: Control and
FIGURE 4 | Training adult zebrafish during a late period (31–42 dpl) has no effect on pallial neurogenesis. (A). Experimental design. (B). Learning curves for Trained
and Control individuals. (Two-way RM ANOVA, Treatment effect: F
(1, 12)
= 108.0 with p<0.0001, Session effect: F
(9, 108)
= 6.800 with p<0.0001. Bonferroni’s multiple
comparisons test, **p<0.01, ***p<0.001, ****p<0.0001. Trained, N = 7; Control N = 7). (C). Simple linear regression for each training window for Trained fish (ANCOVA,
F
(1, 66)
= 5.914, * indicates p<0.05. Trained, N = 7; Control N = 7). (D). BrdU
+
NeuN
+
cell quantification in LP (left) and MP (right) (Kruskal–Wallis test with: Left panel,
p= 0.1984; Right panel, p= 0.316. Dunn’s multiple comparisons test, not significant differences were found. Trained, N = 7; Control, N = 7). (E). Neuronal increase ratio
(Trained/Control) in rMP and cLP for each learning time frame.
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Mazzitelli-Fuentes et al. Adult Neurogenesis Modulation by Learning
FIGURE 5 | Balance of adult neurogenesis driven by chained proliferation and loss of adult-born cells. (A). Experimental design. Fish were i. p. injected with EdU
and euthanised for histology at three times points: 4, 16, 32 and 64 dpl. (B). EdU
+
cell quantification in cLP in 4, 16, 32 and 64 dpl. (Kruskal–Wallis test, followed by post-
hoc Dunn’s test, K-W st = 9.048, ** depicts p<0.01. 4 dpl, N = 8; 16 dpl, N = 4; 32 dpl, N = 3, 64 dpl, N = 6). (C). Number of proliferating EdU cells (top) and % of
proliferating EdU cells (bottom) (Kruskal–Wallis test, followed by post-hoc Dunn’s test, K-W st = 13.80 and K-W st = 12.88, respectively. * depicts p<0.05, **, p<
0.01. 4 dpl, N = 8; 16 dpl, N = 4; 32 dpl, N = 3, 64 dpl, N = 6). (D). EdU/PC NA in cLP for 4 dpl and 32 dpl. Scale bar, 20 μm. (E). EdU
+
cell quantification in rMP in 4, 16, 32
and 64 dpl. (Kruskal–Wallis test, followed by post-hoc Dunn’s test, K-W st = 7.88, * depicts p<0.05. 4 dpl, N = 8; 16 dpl, N = 4; 32 dpl, N = 4, 64 dpl, N = 6). (F). Number
of proliferating EdU cells (top) and % of proliferating EdU cells (bottom) (Kruskal–Wallis test, followed by post-hoc Dunn’s test, K-W st = 9.571 and K-W st = 8.827,
respectively. ** depicts p<0.01. 4 dpl, N = 8; 16 dpl, N = 4; 32 dpl, N = 3, 64 dpl, N = 6). (G). EdU/PCNA in rMP for 4 dpl and 32 dpl. Scale bar, 20 μm. (H). Scheme
summarizing EdU/PCNA results in cLP and rMP.
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Mazzitelli-Fuentes et al. Adult Neurogenesis Modulation by Learning
FIGURE 6 | A population NSC dynamics model mimics the learning-induced adult neurogenesis in the rMP. (A). Scheme outlining NSC population dynamics
model. ki indicates rates of division/differentiation. The learning effect on NSC proliferation was simulated by adding a learning factor (λ) during training windows. rNSC:
reservoir neural stem cell; oNSC: operative neural stem cell; n: neuron. (B). Number of cellular divisions at steady state, calculated to estimate the initial populations of
BrdU-labeled cells. (C). Population dynamics under Control condition. (D). Left: Stochastic simulations to estimate the population of adult-born neurons in Control
and Trained subjects during two training periods (3–14 dpl) and three training periods (12–30 dpl). Middle: BrdU-labeled cells division under Control and Training
conditions. Right: Stochastic simulations to estimate the population of adult-born neurons considering a checkpoint (at 15 dpl) for neuronal death, together with a
learning-induced rescue. (E). Adult-born neurons for Control subjects at 30 dpl, with and without neuronal death (Unpaired t-test, t
(38)
= 73.10, **** depicts p<0.0001, N = 20).
(F). Neuronal increase by learning under different conditions (Two-way ANOVA, Period effect: F
(6, 239)
=430.7withp<0.0001, Condition effect: F
(1, 239)
= 1,342 with p<0.0001.
Post-hoc Sidak’s test **** depicts p<0.0001- N = 20 for simulation, N = 5 for data).
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Mazzitelli-Fuentes et al. Adult Neurogenesis Modulation by Learning
Trained at different learning periods (Figures 6A,B). After
30 days, the model evolves to a proportion ~60% of adult-born
neurons from the initial cohort of “labeled”NSCs in the rMP
(Figure 6C), a value slightly lower to what is shown in our
experiments (Panels E, H from Figures 2,3). Next, we calculated
the number of chained divisions that each cell of the original NSC
pool goes through. The model indicates an average of ~1.7
divisions during the 30-day period (Figure 6D), a value that
supports the chained proliferation of labeled-NSCs by discarding
a relevant BrdU dilution in the progeny. Then, based on our
PCNA results (see Figure 1), we hypothesized that learning
would burst the activation and proliferation of BrdU-labeled
NSCs, which were a product of NSC-conservative divisions
from the original labeled pool. We aimed to emulate the
neuronal population dynamics in rMP when learning occurs
from 3–14 dpl (2 weeks of training) and from 12–30 dpl
(3 weeks of training), the experimental conditions in which
learning promotes adult neurogenesis. Thus, during these
training windows, the proliferation rate of NSCs is affected by
a learning factor (λ). We observed that learning increased the
number of adult-born neurons at the expense of the operative
NSC pool (Figure 6C). However, in contrast to the changes
observed in our experiments (See Figure 4E), in the simulation
both training conditions (3–14 and 12–30 dpl) exhibited a similar
outcome in the number of new neurons (Figure 6D). Since we
observed neuronal loss in the rMP from 4 to 32 dpl (indicated by
~45% reduction in the number of EdU-labeled cells), we
incorporated to our model a checkpoint starting at 15 dpl to
allow the survival or death of new neurons, together with a
learning-related rescue (See methods). In Control conditions the
death of adult-born neurons maintains a 67.1 ± 5.4% of survival
(Figure 6D,E). As expected, the incorporation of neuronal death
to the model increases the difference in the number of adult-born
neurons when training occurs during 12–30 dpl in comparison
with 3–14 dpl (Figure 6D). This learning-induced adult
neurogenesis profile mimics our experimental results, but with
a lower difference than our experimental data. This result, led us
to interrogate the model under different conditions, as
duplication of the learning factor (2X λ), duplication of all the
division/differentiation rates (2X k
i
), 2X λ+ neuronal death, and
2X k
i
+ neuronal death (Figure 6F,Supplementary Figure S5A).
The only conditions where the model mimicked the experimental
data profiles were the ones in which neuronal death was taken
into account, being the 2X λ+ neuronal death the most accurate
condition. A long-term simulation (500 days) showed that adult
neurogenesis is additive to pallial networks, even when
considering neuronal death (Supplementary Figure S5B).
Thus, the model supports that learning-induced adult
neurogenesis in rMP relies on both mechanisms: a boost in
chained NSC proliferation and rescue from neuronal loss.
DISCUSSION
Teleost fish grow throughout their lives, therefore their organs
must adapt to their increasing body size (Jerison, 1973).
Consequently, adult neurogenesis could be considered as a
mechanism that underlies the constant growth of the fish
brain, in agreement with the numerical matching hypothesis
(Zupanc, 2021). As an alternative but not excluding
hypothesis, adult neurogenesis would provide neural networks
with an extra degree of plasticity to adapt the brain to changes in
the environment. Previous studies in teleosts suggest functional
specialization of neurogenic niches (Zupanc and Horschke, 1995;
Kaslin et al., 2008;Iribarne and Castelló, 2014;Lindsey et al.,
2014;Olivera-Pasilio et al., 2014;Sato et al., 2017;Labusch et al.,
2020). These studies demonstrate that different brain regions
involved in the processing of sensory activity are neurogenic, and
sustained sensory stimulation leads to an increase in newborn
neurons only in the related niches. In the same way, in rodents
and birds it has been shown that behavioral challenges involving
information processing in neurogenic brain nuclei enhance adult
neurogenesis in a stimulus-dependent fashion (Goldman and
Nottebohm, 1983;Barnea et al., 1994;Leuner et al., 2004;Alonso
et al., 2006;Tashiro et al., 2007). These works highlight the
relevance of adult neurogenesis on learning-related changes in a
structure-to-function manner. Here, we challenged zebrafish with
a cognitive paradigm to explore the addition of adult-born
neurons to pallial circuits. The subjects were trained in a
spatial learning paradigm to integrate their positional
information with visual cues to solve the task. To avoid
egocentric responses, the start compartments were randomly
chosen and multiple maze rotations were performed during
sessions. Therefore, on each trial, the fish must make a
decision based on spatial information. Adult zebrafish
exhibited good performance on this behavioral test, even after
sequential rule-change sessions. We observed that training fish in
this paradigm increases cell proliferation in circumscribed pallial
subregions. The Control group, mocked with a random exit, was
subjected to all the experimental manipulations (isolation,
handling, environment, exploration, and social reward) as the
Trained group. Hence, we conclude that the observed differences
in adult neurogenesis are a consequence of the learning process.
The Trained subjects evidenced a region-specific increase in the
rate of proliferation when compared to Control fish. This finding
suggests that the new neurons could underlie plastic changes in
the pallium as a consequence of the cognitive challenge.
Our results indicate a rostro-caudal specialization in the pallial
circuits, shedding light on the relevance of the cLP (encompassing
the caudal Dlv and Dld) and the rMP (the rostral portion of Dm)
during the execution of the cognitive task implemented here.
Behavioral studies involving distinct teleost fish related the LP to
navigation and spatial learning (Durán et al., 2015;Elliott et al.,
2017;Ocaña et al., 2017;Fotowat et al., 2019). Both of these
cognitive functions are processed by the mammalian
hippocampus. Furthermore, the zebrafish LP region expresses
several molecular markers resembling the ones expressed by the
mammalian hippocampus (Mueller and Wullimann, 2009;Ganz
et al., 2015). Our results are in agreement with the involvement of
the teleost LP in processing spatial information and reveal a
rostro-caudal specialization of this structure, being the cLP the
only region in which this spatial task heightens the addition of
new neurons. In this regard, Ocaña and coworkers (2017)
reported progressive changes in metabolic activity throughout
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Mazzitelli-Fuentes et al. Adult Neurogenesis Modulation by Learning
the rostro-caudal LP as a response to training goldfish in the same
paradigm. In their work, oxidative metabolism activity was
analyzed during learning showing that rostral and medial
sections of Dlv exhibit transient activation at early stages,
whereas the caudal Dlv shows sustained activity throughout
the training period. In our experiments we found no
differences between the dorsal and ventral LP (Dld and Dlv,
data not shown) and only observed learning-related effects on
adult neurogenesis in the cLP. Very likely, the signaling involved
in oxidative metabolism during this paradigm could be different
than the factors involved during neurogenesis in the LP,
explaining the discrepancies. Unexpectedly, we also found a
learning-related induction of adult neurogenesis in the rMP, a
brain region that has been poorly studied in teleosts. Interestingly,
Lau and coworkers (2011) have proposed that Dm acts as a brain
center whose activity discriminates a choice behavior in zebrafish
(Lau et al., 2011). In their work the authors analyzed neuronal
activity by c-fos expression in the pallium, but only at a rostral
level (rMP, slice 71 of the zebrafish atlas (Wullimann et al.,
1996)). On this basis, we hypothesize that the rMP learning-
related increase in adult neurogenesis could be attributed to the
role of this neural center on decision-making. However, future
experiments should be conducted to test this idea.
The pallium of fish is considered a simple structure with
specialized regions at the transversal level. However, here we
observed a rostro-caudal specialization in the MP and the LP of
Control fish, evidenced by gradients of PCNA (Figure 1), with
higher proliferation activity in the rMP and the cLP, being both
regions prone to be modulated by learning. Interestingly, our
results highlight the specialization of neural circuits along the
pallial rostro-caudal axis, a concept that should be taken into
account in future studies.
To evaluate the learning effects on adult neurogenesis, we
labeled proliferating progenitor cells with the thymidine analog
BrdU and fish were trained at different periods after progenitor
labeling (3–14, 12–30, 31–42 dpl). After a single thymidine analog
pulse (BrdU or EdU), most of the label will be incorporated by the
active NSC (5% of total NSCs, (März et al., 2010;Than-Trong
et al., 2020),) and by a fraction of neuronal progenitors (~6–26%
(März et al., 2010;Rothenaigner et al., 2011)). After short chase
times, most adult-born neurons will be the product of neurogenic
divisions by the committed neuronal progenitors. While, the late
recruitment of adult-born neurons (here described as chained
proliferation) would result from conservative NSC divisions at
the time of BrdU administration, which will go through
consecutive mitosis and differentiation beyond neurogenic fate.
We found an increase of BrdU-labeled neurons in the rMP and
cLP of Trained subjects. Our results support adult neurogenesis as
an evolutionary conserved source of learning-related brain
plasticity. Interestingly, the neurogenesis observed in these
pallial regions differs in their learning-sensitive critical periods,
where the cLP has a shorter temporal window as compared to the
rMP. The distinct critical periods between these pallial regions
could be attributed to different composition of NSC and
progenitor cells between both niches. Or alternative, could be
explained by neuronal populations with a distinct maturation
pace. In rodents, several activity-dependent critical periods have
been reported during development of adult-born neurons (Ge
et al., 2007;Tashiro et al., 2007;Alvarez et al., 2016); however to
our knowledge this is the first evidence reported in a
teleost model.
The observed increase in adult neurogenesis after the cognitive
challenge could underlie two distinct, yet not exclusive,
mechanisms: 1) rescue of immature neurons from death
programs; or 2) an expansion of the labeled NSC reservoir by
chained recruitment of BrdU-labeled cells. Here, we found that
both processes could contribute to adult neurogenesis
homeostasis in the zebrafish pallium (Figure 6). In rodents,
adult neurogenesis generates neurons in abundance, and their
survival depends on an activity-dependent synaptic integration of
new neurons to rescue them from death programs (Ryu et al.,
2016). In line with this idea, we found a decrease in the number of
adult-born neurons in cLP and rMP over a 64-days lapse (Figures
5B,E). Accordingly, Ampatzis and coworkers (2012) showed
significant apoptotic activity assessed by TUNEL method in
different regions of adult zebrafish pallium (~100–200 TUNEL
profiles/mm
2
, a value close to the daily adult neurogenesis
contribution) (Ampatzis et al., 2012). On the other hand,
supporting the chained proliferation, we found significant
amounts of EdU
+
PCNA
+
cells in both pallial subregions
(Figures 5C,F). Whereas the rMP maintains a steady level of
cell proliferation over the 4–32 days period, the cLP shows an
early boost of proliferation activity, which declined by day 16. The
differences in the proliferation dynamics between both sub-
regions could be attributed to heterogeneous cellular
compositions (März et al., 2010;Lindsey et al., 2012;Dirian
et al., 2014;Anand and Mondal, 2017). Thus, at 4 dpl double-
labeled cells in rMP and cLP may correspond to fast-cycling cells
(potentially intermediate amplifier progenitors or transitory
amplifying cells), which proliferate over a short period. In cLP,
there is scarce proliferation activity detected after 4 dpl. However,
in the rMP, a relevant portion of EdU
+
cells continues
proliferating at 16 and 32 dpl. These may correspond to slow-
cycling cells, which re-entered the cell cycle after a quiescent state
(Alunni et al., 2010;Olivera-Pasilio et al., 2014). The fast decrease,
after 4 dpl (Figure 5C), in chained proliferation observed in cLP
could explain the absence of learning effects when subjects were
trained at 3–14 dpl. While the late boost (12–30 dpl) of adult
neurogenesis in this region (Figure 2D), could be attributed to an
activity-dependent rescue from cell death programs. On the other
hand, in rMP both chained proliferation and death rescue seem to
be synergistic to the learning-related increase of 12–30 dpl adult-
born neurons.
In agreement with our observations and supporting a chained
proliferation of pallial NSCs, a persisting proliferation of BrdU-
labeled cells (~40 dpl) in the zebrafish telencephalon was also
reported by other authors (Grandel et al., 2006;März et al., 2010).
The chained proliferation of labeled NSCs has also been proposed
by Prickaerts and collaborators (Prickaerts et al., 2004). In their
words, “the effect of proliferation alone, on every day after
injection, is added to the number of cells counted as well as
the survival of those cells which were labeled earlier in the week
and have not continued to proliferate”. Therefore, our results
argue in favor of complex regulation of adult neurogenesis in
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Mazzitelli-Fuentes et al. Adult Neurogenesis Modulation by Learning
which learning promotes the chained division of NSCs, together
with activity-dependent survival. However, it is not clear whether
new-born neuron integration and survival is related to NSC
proliferation in a causative manner, a question that should be
addressed in future research. The concept of chained-
proliferation is supported by our NSC population dynamics
model, in which proliferation and death act in a synergistic
way to induce pallial circuit modifications by adult
neurogenesis. Although the model reproduces the adult
neurogenesis profiles observed in our experimental conditions,
the proportion of adult-born neurons as well as its learning-
induced increase exhibit lower values when compared to our
experimental data. We speculate that these discrepancy could be
related to different factors, such as different division/
differentiation (k
i
) rates in our fish as compared to the ones
calculated in the Than-Trong work, underestimation of the
learning factor (λ), or the impact of neuronal death
implemented in our model.
Taken together our results indicate that learning in a cognitive
paradigm, involving spatial and positional information together with
decision making, induces the addition of new neurons into specific
pallial circuits. However, from our experiments, it is not clear whether
neurons generated during training would participate in encoding
information related to the learning process itself, since these new
neurons could still be in an immature stage. If this is true, then the
learning-induced neurogenesis would prepare the related neuronal
circuits by adding new neurons for future challenges. In line with this
idea,itwasrecentlyshownthatsilencing hippocampal adult-born
neurons, which were immature during learning, impairs remote
memory reconsolidation in rats, indicating a learning-related
priming of immature neurons (Lods et al., 2021). This idea, as well
as elucidating the timing for maturation and synaptic integration of
adult-born neurons should be explored in future works.
CONCLUSION
The addition of adult-born neurons by adult neurogenesis
represents a major source of brain plasticity. Although
zebrafish possess high levels of adult neurogenesis broadly
distributed throughout their brain, the involvement of
neuronal addition as a cognitive-related plastic mechanism has
not been explored in this model, yet. The zebrafish pallium has
numerous well described neurogenic niches, and has been proved
to be critical for the execution of spatial and emotional learning
tasks. In this work, we trained adult zebrafish in a cue-guided
maze and found an improvement in their performance in a daily
manner throughout five sessions. This cognitive challenge
induces an increase in proliferation activity only in two
restricted pallial areas, the cLP and the rMP. In addition,
adult-born neurons in rMP and cLP are being produced on
demand during the learning process but with distinct critical
periods. Finally, based on a NSC population dynamics model we
propose that adult neurogenesis is regulated in a complex manner
by promoting NSC proliferation together with neuronal death
programs. We propose that both processes are prone to be
regulated by learning-induced network activity.
METHODS
Subjects and housing. All experiments were carried out using
10 ± 1 months-old AB-wild type zebrafish (Danio rerio) line in
AB background, except for the experiment shown in
Supplementary Figure S2, in which 21 months-old individuals
were used. Adult zebrafish were housed in a zebrafish standalone
rack system (ZS560, Aquaneering Inc.), were fish were kept in
small groups (5 fish/l) with aerated and filtered water at a
constant temperature of 27 ± 0.5°C, pH = 7.2 ± 0.2. The
aquarium room was subjected to a 14:10 h light/dark cycle.
Dry food and Artemia salina were provided three-times a day.
During the experimental period fish were housed individually in
1.4 L tanks. Both sexes were used indistinguishably. Experimental
procedures were conducted in accordance with the National
regulations and following the Universities Federation for
Animal Welfare Handbook on the Care and Management of
Laboratory and other Research Animals. This work has the
consent of the Comisión Nacional de Energía Atómica’s
IACUC, protocol #05-2018-02.
Behavioral paradigm. Subjects were trained in a square tank (30
× 30 cm) containing the experimental rhomboid maze in the
center, as was previously described (Ingle and Sahagian, 1973).
ThemazewasmadeoutofgreenPVC(10×10cm),toforma
diamond-shaped box with two circular starting compartments
in opposite corners. The remaining corners of the box served as
exits. One of them was kept open, while the other was blocked
with a transparent glass barrier.Spatialcues,consistingof
removable striped panels, were placed on two walls of the
box. On the edges of the tank,andbehindthestarting
compartments, two glass enclosures containing conspecifics
(two per enclosure) were used as social reward. The
experimental tank was illuminated with two LED lamps,
located above the tank.
Two days prior to training, subjects were habituated to the
experimental apparatus. During habituation fish were allowed to
swim through both exits of the apparatus. Neither the cues nor
the glass barrier were used during habituation. For individual
habituation sessions conspecifics were also placed in the tank
enclosures. After habituation, the training sessions were carried
out. Each training session consisted of an acclimation period
(5 min) followed by a maze solving period (5 min), which
included chasing and capturing the fish with a small plastic
vessel. Each session consisted of 24-trial trials, and was
divided into two slots, one in the morning and the other in
the afternoon to avoid exhaustion. For each trial, fish were
randomly placed in either of the starting compartments (50%
each one), and allowed to enter the central arena by removing a
sliding PVC barrier. The initial decision of the fish was registered.
A correct choice was scored when it swam through the exit, and a
failure if it bumped against the glass barrier. In case of a failure,
the experimenter waited until the fish found the correct exit. Once
out of the maze, the fish were allowed to explore the tank and
conspecifics for 10 s. Learning criterion was established at 70% of
correct choices. The maze, cues and glass barrier were
consistently rotated every five trials to avoid the use of
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Mazzitelli-Fuentes et al. Adult Neurogenesis Modulation by Learning
external cues. In the Control group, the glass barrier was
randomly placed in any of the exits. Other from that,
conditions remained the same as the Trained group.
BrdU labeling. To label cycling cells, zebrafish were immersed in
5 mM 5-bromo-2′-deoxyuridine (Sigma) solution overnight. The
BrdU was dissolved in aquarium water. Fish were immersed in
groups up to 16 individuals, at a 50 ml/fish ratio. The following
days after immersion, they were successively rinsed with system
water and reincorporated to the fish facility.
EdU labeling. To label cycling cells, fish were anaesthetised in
0.01% tricaine methanosulfonate (MS222, Sigma) and a single 5-
ethynyl-2′-deoxyuridine (EdU) injection (40 μL, 10 mM) was
delivered intraperitoneally (i.p.). Individuals were subsequently
allowed to recover in a holding tank, and returned to the fish facility.
Brain preparation and sectioning. After the last session, fish were
deeply anaesthetised in 0.02% tricaine methanosulfonate (MS222,
Sigma), brains were dissected and fixed in 4% PFA in 10 mM PBS
overnight. Tissue was overprotected by immersion in 30% sucrose
for 2 days, immediately frozen in liquid nitrogen and stored at
−20°C. Telencephalic frontal sections of 20 μm were cut on a cryostat
(Microm, HM 550), and mounted on positively charged slides. Slides
were air-dried for 24 h prior to inmunofluorescence.
To analyze the pallium throughout the rostro-caudal axis, we
selected four sections for each individual, designated as rostral,
rostro-medial, medio-caudal and caudal. Sections were chosen
according to the topological atlas Neuroanatomy of the Zebrafish
Brain (Wullimann et al., 1996), see Supplementary Figure S1.
Immunofluorescence. Slides were rinsed three times with Tris-
buffered saline (TBS) (pH = 7.4) for 5 min, incubated with
100 mM ammonium chloride for 20 min and rinsed three
more times with 0.3% TritonX-100/TBS for 5 min. Then,
slides were blocked with 6% bovine serum albumin (BSA), 6%
normal goat serum (NGS) in TBS for 1 h and incubated overnight
at 4°C with primary antibodies diluted in 6% BSA, 6% NGS in
TBS. Then, they were washed with 0.3% TritonX-100/TBS four
times for 5 min, and incubated with secondary antibodies coupled
to Alexa Fluor 488 or 594 (1:500 dilution) for 2 h at room
temperature (RT). Sections were then washed three times
(5 min each) in 0.3% TritonX-100/TBS, and mounted using
Fluorescence Mounting Medium (Abcam). Sections were
stored at 4 °C. When double immunostaining was performed
both primary, or secondary, antibodies were incubated at the
same time. For BrdU and PCNA immunodetection antigen
retrieval was performed before blocking: 30 min in 2 N HCl at
37°C, followed by 10 min neutralization in 0.1 M borate buffer
(pH = 8,5). Primary antibodies used were: rat monoclonal anti-
BrdU 1:500 (ab6326, Abcam), mouse monoclonal anti-PCNA 1:
300 (PC10, sc-56, Santa Cruz Biotechnology, Inc.), mouse
monoclonal anti-NeuN 1:500 (ab104224, Abcam), mouse
monoclonal anti-NeuroD1 1:500 (ab60704, Abcam).
Secondary antibodies used were: goat polyclonal anti-Rat IgG
Alexa Fluor 488 (ab150165, Abcam), goat polyclonal anti-Mouse
IgG Alexa Fluor 488 (ab150117, Abcam), goat polyclonal anti-Rabbit
IgG Alexa Fluor 594 (ab150084, Abcam), goat polyclonal anti-
Mouse IgG Alexa Fluor 594 (ab150120, Abcam). The images
were acquired by using an epifluorescence microscope Nikon
Eclipse e800 and an ad-hoc built two-photon microscope.
Colocalization of fluorescent markers were performed on
single-plane images acquired in the two-photon microscope.
Images were processed in FIJI (ImageJ v1.53). Immunostained
sections in which the tissue was broken or folded were excluded
from the analysis.
Population dynamics model. In this work we performed a
population dynamics simulation based on the work of Than-
Trong and coworkers (2020) with modifications. Briefly, the model
contemplates two NSC populations, the reservoir pool (rNSCs) and
the operative pool (oNSCs). Both kind of NSCs divided and
differentiated following the rates reported by Than-Trong: 1) rNSC
→rNSC + oNSC: (k
1
= 0.007/day); 2) oNSC →death: (k
2
=0.017/day);
3) oNSC →oNSC + oNSC: (k
3
= 0.006/day); 4) oNSC →oNSC + n:
(k
4
= 0.018/day); 5) oNSC →n+n:(k
5
=0.004/day);6)oNSC→n:
(k
6
= 0.013/day). To adapt the model to our experiments, we firstly
determined the system dynamics at equilibrium to establish the basal
proportions of rNSC (r) and oNSC (o). Based on the reaction rates
described above we developed differential equations to evaluate the
temporal progression of r and o populations:
As rNSC→rNSC + oNSC: dr
dt 0, at equilibrium r
eq
= r(t
0
)
Whereas do
dt k1r−(k3+k5+k6−k2)of(r, o),
at equilibrium do
dt f(req,o
eq)0,
with oeq 1
4req
Once established the contribution of r
eq
and o
eq
, we developed
a stochastic simulation to determine the proportions of reactions
associated to cellular divisions (d
i
), which will be used as target for
“BrdU labeling”simulation (Figure 6C). Hence, from this
simulation we established the following parameters: d
1
= 0.5,
d
3
= 0.11, d
4
= 0.32, d
5
= 0.07.
According to this, given an initial population (P
0
)of“BrdU-
labeled”NSCs we established the progeny fate after a single division:
r(t0)P0d1
o(t0)P0(d1+2d3+d4)
n(t0)P0(d4+2d5)
Next, we compute the population dynamics through a 30 days
period (see Figure 6C).
To address the way in which learning activity impinges on
population dynamics, we applyed a learning factor (λ) to the rates
of division and differentiation (k
i
) of the reactions that took place
only during training periods (See Figure 6D). Based on our
experiments of learning and proliferation (Figure 1 and
Supplementary Figure S2), we estimated a λ=3.
Neuronal death was incorporated under the hypothesis that
adult-born neurons mature over time to reach a checkpoint (at
day 15th), in which a portion of these neurons die with a probability
p
death
= 0.550, in accordance with the results shown in Figure 5.
Next, we implemented an activity-dependent rescue to decrease
neuronal death up to ten times during learning.
Frontiers in Cell and Developmental Biology | www.frontiersin.org May 2022 | Volume 10 | Article 84096414
Mazzitelli-Fuentes et al. Adult Neurogenesis Modulation by Learning
All the stochastic simulations were implemented in Python
3.8.5 using NumPy 1.19.2, and the codes are available in https://
gitlab.com/n806/stochasticsimulation_learning_and_neurog.
Statistical analysis. Every data set was tested by the Grubbs
outlier test, with alpha = 0.05. Normality was assessed using the
Shapiro-Wilk test, with a p-value of 0.05. Homoscedasticity was
analyzed by the Levene test, with a p-value of 0.05. When data
met criteria, unpaired t-test or Two-way ANOVA with
Bonferroni post-hoc test were used as indicated. In cases
where data did not meet normality criteria, nonparametric
tests used were Mann-Whitney or Kruskal–Wallis. Behavioral
results were analyzed by Two-way ANOVA for repeated
measures as well as by linear regressions. In all cases,
statistical significance was assumed when p<0.05. Unless
otherwise specified, data are presented as mean ± SE. Box
plots indicate median (line), 25–75% percentile (box limits),
maximum and minimum values (whiskers). Simple linear
regression slopes were compared with an ANCOVA test. All
the statistical analyses performed in this work are detailed in the
supplementary information file.
DATA AVAILABILITY STATEMENT
The original contributions presented in the study are included in
the article/Supplementary Material, further inquiries can be
directed to the corresponding author.
ETHICS STATEMENT
This study was conducted in accordance with the National
regulations and following the Universities Federation for
Animal Welfare Handbook on the Care and Management of
Laboratory and Other Research Animals. The experimental
procedures were reviewed and approved by the Comisión
Nacional de Energía Atómica’s IACUC, protocol #05-2018-02.
AUTHOR CONTRIBUTIONS
The working hypothesis and experimental design were conducted
by LM-F and LM. Training fish in the rhomboidal maze was
performed by LM-F and ED. FR was responsible for the EdU
pulse and chase experiments and the evaluation of adult-born
neurons’migration distance. Immunofluorescence and two-
photon microscopy were conducted by LM-F and FR. The
population dynamics model was performed by JC. All the
authors participated in the results discussion and
interpretation. The manuscript was written by LM and LM-F.
FUNDING
This work was funded by: 1) Wellcome Trust Foundation, Seed
Award in Science 210219/Z/18/Z; 2) ANPCyT-MinCyT PICT
2018-1031; 3) ANPCyT-MinCyT PICT 2019-0225; all to LM.
LM-F, FR, and ED are supported by Ph.D. fellowships from
CONICET. JC is supported by a master’s fellowship from
Instituto Balseiro. LM is a research member of CONICET.
ACKNOWLEDGMENTS
We thank Alex Fainstein, Axel Bruchhausen, Maximiliano
Guyón, and Maia Brunstein for sharing the two-photon
microscope and for their time spent aiding in trouble fixing.
Finally, we want to thank Maria Soledad Espósito and Luciano
Marpegan for their careful reading of the manuscript; their
suggestions and comments have improved our work.
SUPPLEMENTARY MATERIAL
The Supplementary Material for this article can be found online at:
https://www.frontiersin.org/articles/10.3389/fcell.2022.840964/
full#supplementary-material
REFERENCES
Aasebø, I. E. J., Kasture, A. S., Passeggeri, M., and Tashiro, A. (2018). A Behavioral
Task with More Opportunities for Memory Acquisition Promotes the Survival
of New Neurons in the Adult Dentate Gyrus. Sci. Rep. 8, 1–11. doi:10.1038/
s41598-018-25331-w
Adams, M. M., and Kafaligonul, H. (2018). Zebrafish-A Model Organism for
Studying the Neurobiological Mechanisms Underlying Cognitive Brain Aging
and Use of Potential Interventions. Front. Cel. Dev. Biol. 6, 1–5. doi:10.3389/
fcell.2018.00135
Adolf, B., Chapouton, P., Lam, C. S., Topp, S., Tannhäuser, B., Strähle, U., et al.
(2006). Conserved and Acquired Features of Adult Neurogenesis in the
Zebrafish Telencephalon. Dev. Biol. 295, 278–293. doi:10.1016/j.ydbio.2006.
03.023
Alonso, M., Viollet, C., Gabellec, M.-M., Meas-Yedid, V., Olivo-Marin, J.-C., and
Lledo, P.-M. (2006). Olfactory Discrimination Learning Increases the Survival
of Adult-Born Neurons in the Olfactory Bulb. J. Neurosci. 26, 10508–10513.
doi:10.1523/JNEUROSCI.2633-06.2006
Alunni, A., and Bally-Cuif, L. (2016). A Comparative View of Regenerative
Neurogenesis in Vertebrates. Development 143, 741–753. doi:10.1242/dev.
122796
Alunni, A., Hermel, J.-M., Heuzé, A., Bourrat, F., Jamen, F., and Joly, J.-S. (2010).
Evidence for Neural Stem Cells in the Medaka Optic Tectum Proliferation
Zones. Devel. Neurobio. 70, 693–713. doi:10.1002/dneu.20799
Alvarez, D. D., Giacomini, D., Yang, S. M., Trinchero, M. F., Temprana, S. G.,
Büttner, K. A., et al. (2016). A Disynaptic Feedback Network Activated by
Experience Promotes the Integration of New Granule Cells. Science 354,
459–465. doi:10.1594/PANGAEA.85856810.1126/science.aaf2156
Ampatzis, K., Makantasi, P., and Dermon, C. R. (2012). Cell Proliferation Pattern
in Adult Zebrafish Forebrain Is Sexually Dimorphic. Neuroscience 226,
367–381. doi:10.1016/j.neuroscience.2012.09.022
Anand, S. K., and Mondal, A. C. (2017). Cellular and Molecular Attributes of
Neural Stem Cell Niches in Adult Zebrafish Brain. Devel. Neurobio. 77,
1188–1205. doi:10.1002/dneu10.1002/dneu.22508
Anderson, M. L., Sisti, H. M., Curlik, D. M., Shors, T. J., Curlik, D. M., and Shors , T.
J. (2011). Associative Learning Increases Adult Neurogenesis During a Critical
Period. Eur. J. Neurosci. 33, 175–181. doi:10.1111/j.1460-9568.2010.07486.x
Frontiers in Cell and Developmental Biology | www.frontiersin.org May 2022 | Volume 10 | Article 84096415
Mazzitelli-Fuentes et al. Adult Neurogenesis Modulation by Learning
Ausas, M. S., Mazzitelli-Fuentes, L., Roman, F. R., Crichigno, S. A., De Vincenti, A.
P., and Mongiat, L. A. (2019). Social Isolation Impairs Active Avoidance
Performance and Decreases Neurogenesis in the Dorsomedial
Telencephalon of Rainbow Trout. Physiol. Behav. 198, 1–10. doi:10.1016/j.
physbeh.2018.10.006
Barnea, A., Nottebohm, F., Barnea, A., and Nottenbhom, F. (1994). Seasonal
Recruitment of Hippocampal Neurons in Adult Free-Ranging Black-Capped
Chickadees. Proc. Natl. Acad. Sci. U.S.A. 91, 11217–11221. doi:10.1073/pnas.91.
23.11217
Dirian, L., Galant, S., Coolen, M., Chen, W., Bedu, S., Houart, C., et al. (2014).
Spatial Regionalization and Heterochrony in the Formation of Adult Pallial
Neural Stem Cells. Dev. Cel. 30, 123–136. doi:10.1016/j.devcel.2014.05.012
Durán, E., Ocaña, F. M., Broglio, C., Rodríguez, F., Salas, C., Durán, E., et al. (2010).
Lateral but Not Medial Telencephalic Pallium Ablation Impairs the Use of
Goldfish Spatial Allocentric Strategies in a “Hole-Board”Task. Behav. Brain
Res. 214, 480–487. doi:10.1016/j.bbr.2010.06.010
Elliott, S. B., Harvey-Girard, E., Giassi, A. C. C., and Maler, L. (2017).
Hippocampal-Like Circuitry in the Pallium of an Electric Fish: Possible
Substrates for Recursive Pattern Separation and Completion. J. Comp.
Neurol. 525, 8–46. doi:10.1002/cne.24060
Folgueira, M., Bayley, P., Navratilova, P., Becker, T. S., Wilson, S. W., and Clarke,
J. D. (2012). Morphogenesis Underlying the Development of the Everted
Teleost Telencephalon. Neural Dev. 7, 32. doi:10.1186/1749-8104-7-32
Fotowat, H., Lee, C., Jun, J. J., and Maler, L. (2019). Neural Activity in a
Hippocampus-Like Region of the Teleost Pallium Is Associated with Active
Sensing and Navigation. Elife 8, 1–25. doi:10.7554/elife.44119
Furlan, G., Cuccioli, V., Vuillemin, N., Dirian, L., Muntasell, A. J., Coolen, M., et al.
(2017). Life-Long Neurogenic Activity of Individual Neural Stem Cells and
Continuous Growth Establish an Outside-In Architecture in the Teleost
Pallium. Curr. Biol. 27, 3288–3301. doi:10.1016/j.cub.2017.09.052
Ganz, J., Kroehne, V., Freudenreich, D., Machate, A., Geffarth, M., Braasch, I., et al.
(2015). Subdivisions of the Adult Zebrafish Pallium Based on Molecular Marker
Analysis. F1000Res 3, 308–318. doi:10.12688/f1000research.5595.1
Ge, S., Yang, C.-h., Hsu, K.-S., Ming, G.-l., and Song, H. (2007). A Critical Period
for Enhanced Synaptic Plasticity in Newly Generated Neurons of the Adult
Brain. Neuron 54, 559–566. doi:10.1016/j.neuron.2007.05.002
Goldman, S. A., and Nottebohm, F. (1983). Neuronal Production, Migration, and
Differentiation in a Vocal Control Nucleus of the Adult Female Canary Brain.
Proc. Natl. Acad. Sci. U.S.A. 80, 2390–2394. doi:10.1073/pnas.80.8.2390
Grandel, H., and Brand, M. (2013). Comparative Aspects of Adult Neural Stem Cell
Activity in Vertebrates. Dev. Genes Evol. 223, 131–147. doi:10.1007/s00427-
012-0425-5
Grandel, H., Kaslin, J., Ganz, J., Wenzel, I., and Brand, M. (2006). Neural Stem Cells
and Neurogenesis in the Adult Zebrafish Brain: Origin, Proliferation Dynamics,
Migration and Cell Fate. Dev. Biol. 295, 263–277. doi:10.1016/j.ydbio.2006.
03.040
Harvey-Girard, E., Giassi, A. C. C., Ellis, W., and Maler, L. (2012). Organization of
the Gymnotiform Fish Pallium in Relation to Learning and Memory: IV.
Expression of Conserved Transcription Factors and Implications for the
Evolution of Dorsal Telencephalon. J. Comp. Neurol. 520, 3395–3413.
doi:10.1002/cne.23107
Ingle, D., and Sahagian, D. (1973). Solution of a Spatial Constancy Problem by
Goldfish. Psychobiology 1, 83–84. doi:10.3758/BF03326873
Iribarne, L., and Castelló, M. E. (2014). Postnatal Brain Development of the Pulse
Type, Weakly Electric Gymnotid Fish Gymnotus Omarorum. J. Physiology-
Paris 108, 47–60. doi:10.1016/j.jphysparis.2014.05.001
Jerison, H. J. (1973). Evolution of the Brain and Intelligence. 1973rd ed. New York:
Elsevier. Academic Press. Available at: https://www.sciencedirect.com/book/
9780123852502/evolution-of-the-brain-and-intelligence#book-description.
Kaslin, J., Ganz, J., and Brand, M. (2008). Proliferation, Neurogenesis and
Regeneration in the Non-Mammalian Vertebrate Brain. Phil. Trans. R. Soc.
B363, 101–122. doi:10.1098/rstb.2006.2015
Labusch, M., Mancini, L., Morizet, D., and Bally-Cuif, L. (2020). Conserved and
Divergent Features of Adult Neurogenesis in Zebrafish. Front. Cel Dev. Biol. 8,
1–28. doi:10.3389/fcell.2020.00525
Lal, P., Tanabe, H., Suster, M. L., Ailani, D., Kotani, Y., Muto, A., et al. (2018).
Identification of a Neuronal Population in the Telencephalon Essential for Fear
Conditioning in Zebrafish. BMC Biol. 16, 1–18. doi:10.1186/s12915-018-0502-y
Lange, C., Rost, F., Machate, A., Reinhardt, S., Lesche, M., Weber, A., et al. (2020).
Single Cell Sequencing of Radial Glia Progeny Reveals Diversity of Newborn
Neurons in the Adult Zebrafish Brain. Development 147, 1855951. doi:10.1242/
dev.185595
Lau,B.Y.B.,Mathur,P.,Gould,G.G.,andGuo,S.(2011).Identification of a
Brain center Whose Activity Discriminates a Choice Behavior in
Zebrafish. Proc.Natl.Acad.Sci.U.S.A.108, 2581–2586. doi:10.1073/
pnas.1018275108
Leuner, B., Mendolia-Loffredo, S., Kozorovitskiy, Y., Samburg, D., Gould, E., and
Shors, T. J. (2004). Learning Enhances the Survival of New Neurons beyond the
Time when the hippocampus Is Required for Memory. J. Neurosci. 24,
7477–7481. doi:10.1523/JNEUROSCI.0204-04.2004
Lindsey, B. W., Darabie, A., and Tropepe, V. (2012). The Cellular Composition of
Neurogenic Periventricular Zones in the Adult Zebrafish Forebrain. J. Comp.
Neurol. 520, 2275–2316. doi:10.1002/cne.23065
Lindsey, B. W., Di Donato, S., Kaslin, J., and Tropepe, V. (2014). Sensory-specific
Modulation of Adult Neurogenesis in Sensory Structures Is Associated with the
Type of Stem Cell Present in the Neurogenic Niche of the Zebrafish Brain. Eur.
J. Neurosci. 40, 3591–3607. doi:10.1111/ejn.12729
Lledo, P.-M., Alonso, M., and Grubb, M. S. (2006). Adult Neurogenesis and
Functional Plasticity in Neuronal Circuits. Nat. Rev. Neurosci. 7, 179–193.
doi:10.1038/nrn1867
Lods, M., Pacary, E., Mazier, W., Farrugia, F., Mortessagne, P., Masachs, N., et al.
(2021). Adult-born Neurons Immature during Learning Are Necessary for
Remote Memory Reconsolidation in Rats. Nat. Commun. 12. doi:10.1038/
s41467-021-22069-4
März, M., Chapouton, P., Diotel, N., Vaillant, C., Hesl, B., Takamiya, M., et al.
(2010). Heterogeneity in Progenitor Cell Subtypes in the Ventricular Zone of
the Zebrafish Adult Telencephalon. Glia 58, NA. doi:10.1002/glia.20971
Mongiat, L. A., and Schinder, A. F. (2011). Adult Neurogenesis and the Plasticity of
the Dentate Gyrus Network. Eur. J. Neurosci. 33, 1055–1061. doi:10.1111/j.
1460-9568.2011.07603.x
Mu, Y., Lee, S. W., and Gage, F. H. (2010). Signaling in Adult Neurogenesis. Curr.
Opin. Neurobiol. 20, 416–423. doi:10.1016/j.conb.2010.04.010
Mueller, T. (2011). The Conserved Bauplan of the Teleostean Telencephalon. Brain
Behav. Evol. 78, 259–260. doi:10.1159/000331869
Mueller, T., and Wullimann, M. F. (2009). An Evolutionary Interpretation of
Teleostean Forebrain Anatomy. Brain Behav. Evol. 74, 30–42. doi:10.1159/
000229011
Ocaña, F. M., Uceda, S., Arias, J. L., Salas, C., Rodríguez, F., and Rodríguez, F.
(2017). Dynamics of Goldfish Subregional Hippocampal Pallium Activity
Throughout Spatial Memory Formation. Brain Behav. Evol. 90, 154–170.
doi:10.1159/000478843
Olivera-Pasilio, V., Peterson, D. A., and Castelló, M. a. E. (2014). Spatial
Distribution and Cellular Composition of Adult Brain Proliferative Zones in
the Teleost, Gymnotus Omarorum. Front. Neuroanat. 8, 1–19. doi:10.3389/
fnana.2014.00088
Portavella, M., Torres, B., and Salas, C. (2004). Avoidance Response in
Goldfish: Emotional and Temporal Involvement of Medial and Lateral
Telencephalic Pallium. J. Neurosci. 24, 2335–2342. doi:10.1523/
JNEUROSCI.4930-03.2004
Prickaerts, J., Koopmans, G., Blokland, A., and Scheepens, A. (2004). Learning and
Adult Neurogenesis: Survival with or without Proliferation? Neurobiol. Learn.
Mem. 81, 1–11. doi:10.1016/j.nlm.2003.09.001
Rothenaigner, I., Krecsmarik, M., Hayes, J. A., Bahn, B., Lepier, A., Fortin, G., et al.
(2011). Clonal Analysis by Distinct Viral Vectors Identifies Bona Fide Neural
Stem Cells in the Adult Zebrafish Telencephalon and Characterizes Their
Division Properties and Fate. Development 138, 1459–1469. doi:10.1242/dev.
058156
Ruhl, T., Jonas, A., Seidel, N. I., Prinz, N., Albayram, O., Bilkei-Gorzo, A., et al.
(2015). Oxidation and Cognitive Impairment in the Aging Zebrafish.
Gerontology 62, 47–57. doi:10.1159/000433534
Ryu, J. R., Hong, C. J., Kim, J. Y., Kim, E.-K., Sun, W., and Yu, S.-W. (2016). Control
of Adult Neurogenesis by Programmed Cell Death in the Mammalian Brain.
Mol. Brain 9, 43. doi:10.1186/s13041-016-0224-4
Sailor, K. A., Schinder, A. F., and Lledo, P.-M. (2017). Adult Neurogenesis Beyond
the Niche: Its Potential for Driving Brain Plasticity. Curr. Opin. Neurobiol. 42,
111–117. doi:10.1016/j.conb.2016.12.001
Frontiers in Cell and Developmental Biology | www.frontiersin.org May 2022 | Volume 10 | Article 84096416
Mazzitelli-Fuentes et al. Adult Neurogenesis Modulation by Learning
Sato, Y., Yano, H., Shimizu, Y., Tanaka, H., and Ohshima, T. (2017). Optic Nerve
Input-Dependent Regulation of Neural Stem Cell Proliferation in the Optic
Tectum of Adult Zebrafish. Devel. Neurobio. 77, 474–482. doi:10.1002/dneu.
22423
Tashiro, A., Makino, H., and Gage, F. H. (2007). Experience-Specific Functional
Modification of the Dentate Gyrus Through Adult Neurogenesis: A Critical
Period During an Immature Stage. J. Neurosci. 27, 3252–3259. doi:10.1523/
JNEUROSCI.4941-06.2007
Than-Trong,E.,Kiani,B.,Dray,N.,Ortica,S.,Simons,B.,Rulands,S.,etal.
(2020). Lineage Hierarchies and Stochasticity Ensure the Long-Term
Maintenance of Adult Neural Stem Cells. Sci. Adv. 6, eaaz5424–15.
doi:10.1126/sciadv.aaz5424
Than-Trong, E., and Bally-cuif, L. (2015). Radial Glia and Neural Progenitors in the
Adult Zebrafish Central Nervous System. Glia 63, 1406–1428. doi:10.1002/glia.
22856
Toda, T., and Gage, F. H. (2018). Review: Adult Neurogenesis Contributes to
Hippocampal Plasticity. Cell Tissue Res. 373, 693–709. doi:10.1007/s00441-017-
2735-4
Trotha, J. W., Vernier, P., Bally-Cuif, L., von Trotha, J. W., Vernier, P., Bally-cuif,
L., et al. (2014). Emotions and Motivated Behavior Converge on an Amygdala-
Like Structure in the Zebrafish. Eur. J. Neurosci. 40, 3302–3315. doi:10.1111/ejn.
12692
Uceda,S.,Ocaña,F.M.,Martín-Monzón,I.,Rodríguez-Expósito,B.,Durán,
E., Rodríguez, F., et al. (2015). Spatial Learning-Related Changes in
Metabolic Brain Activity Contribute to the Delimitation of the
Hippocampal Pallium in Goldfish. Behav. Brain Res. 292, 403–408.
doi:10.1016/j.bbr.2015.06.018
Vargas, J. P., López, J. C., and Portavella, M. (2009). What Are the Functions of Fish
Brain Pallium? Brain Res. Bull. 79, 436–440. doi:10.1016/j.brainresbull.2009.
05.008
Wullimann, M. F., and Mueller, T. (2004). Teleostean and Mammalian Forebrains
Contrasted: Evidence from Genes to Behavior. J. Comp. Neurol. 475, 143–162.
doi:10.1002/cne.20183
Wullimann, M. F., Rupp, B., and Reichert, H. (1996). Neuroanatomy of the
Zebrafish Brain: A Topological Atlas. 1st ed. Basel: Birkhäuser Basel. doi:10.
1007/978-3-0348-8979-7Neuroanatomy of the Zebrafish Brain
Yang, P., Kajiwara, R., Tonoki, A., and Itoh, M. (2018). Successive and Discrete
Spaced Conditioning in Active Avoidance Learning in Young and Aged
Zebrafish. Neurosci. Res. 130, 1–7. doi:10.1016/j.neures.2017.10.005
Zupanc, G. K. H. (2021). Adult Neurogenesis in the Central Nervous System of
Teleost Fish: From Stem Cells to Function and Evolution. J. Exp. Biol. 224.
doi:10.1242/JEB.226357
Zupanc, G. K. H., Hinsch, K., and Gage, F. H. (2005). Proliferation, Migration,
Neuronal Differentiation, and Long-Term Survival of New Cells in the Adult
Zebrafish Brain. J. Comp. Neurol. 488, 290–319. doi:10.1002/cne.20571
Zupanc, G. n. K. H., and Horschke, I. (1995). Proliferation Zones in the Brain of
Adult Gymnotiform Fish: A Quantitative Mapping Study. J. Comp. Neurol. 353,
213–233. doi:10.1002/cne.903530205
Conflict of Interest: The authors declare that the research was conducted in the
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