Brain morphology of native and invasive Cichla piquiti, the blue peacock bass (Cichliformes: Cichlidae), with ecomorphological insights

Pedro Henrique Marinho-Nunes¹ , Thiago Nilton Alves Pereira² and Fernando Mayer Pelicice³

PDF: Download Here | Cite this article

Associate Editor: George Mattox

Section Editor: William Crampton

Editor-in-chief: José Birindelli

Abstract​

---

Introduction​

---

The vertebrate Central Nervous System (CNS) is a complex anatomical structure that coordinates motor, physiological, behavioral, and endocrine functions (Northcutt, 1984). Its organization reflects the functional and morphological polarization of neurons (Nieuwenhuys, 1966; Butler, Hodos, 2005), enabling the reception, integration, and processing of both internal and external stimuli. Although the brain follows a conserved structural plan comprising the prosencephalon, mesencephalon, and rhombencephalon, it exhibits notable anatomical variation across taxa (Nieuwenhuys, 1966; Meek, Nieuwenhuys, 1998; Nieuwenhuys et al., 1998).

Beyond its structural features, the CNS also plays a central role in regulating cognitive processes (Roth, Dicke, 2005). These processes have been extensively investigated in mammals, but are often underestimated in other vertebrates (Brown, 2015). Cognition is generally linked to both absolute and relative brain size (Gignac, Bates, 2017) and neural efficiency (Kandel, Spencer, 1968), with significant ecological and behavioral implications (Ebbesson, Braithwaite, 2012). Among these measures, brain size is one of the most widely applied parameters for evaluating cognitive performance. It is frequently assessed using the Encephalization Quotient (E_Q), a metric that integrates brain size relative to body size (Bauchot, Bauchot, 1978; Jerison, 1985; Bauchot et al., 1989a; Lisney, Collin, 2006; Peñaherrera Aguirre et al., 2021).

Morphoanatomical variation in the brain is shaped by both ecological and evolutionary factors. In fishes, brain morphology represents a key framework for investigating evolutionary relationships (Pereira, Castro, 2016; Abrahão et al., 2018; Rosa et al., 2021; Oliveira, Graça, 2024), ecomorphological patterns (Huber et al., 1997; Shumway, 2010; Kotrschal et al., 2017; Leão‐Reis et al., 2025), and even the taxonomic description of new species (Chamon et al., 2018; Espíndola et al., 2018; Abrahão et al., 2019). Despite this broad potential, relatively few studies have focused on Neotropical fishes in recent years (Marinho-Nunes et al., 2025a). For example, previous research has demonstrated that brain differentiation is linked to functional diversity and sympatric speciation in African cichlids (Huber et al., 1997). However, comparable studies remain scarce, particularly for species from the Neotropical region.

Neotropical cichlids have been characterized by behavioral and ecomorphological plasticity (Ribeiro et al., 2007; Maan, Sefc, 2013; Novakowski et al., 2016; Lehtonen et al., 2023), indicating that the group may represent an interesting model to investigate brain structure. Peacock-basses, Cichla Bloch & Schneider, 1801, in particular, have shown ecological and morphological shifts under conditions of environmental change (Gilbert et al., 2020; Gaspar et al., 2024), which enable adjustments in feeding, reproduction, and general behavior (Gomiero, Braga, 2004; Fugi et al., 2008; Capra, Bennemann, 2009; Marto et al., 2015; Guedes et al., 2024). Cichla is a group composed of generalist top predators (piscivores) that build nests and exhibit complex parental care (Winemiller et al., 2021) usually living in structured environments and forming small aggregations. Species show conspicuous coloration patterns (Pelicice et al., 2022) that may serve as social signaling or communication (Reiss et al., 2012). These traits, together, have favored the colonization of large reservoirs and other environments across the Amazon basin and elsewhere (Sastraprawira et al., 2020; Franco et al., 2021; Andrade, Pelicice, 2022; Franco et al., 2022a,b), with ecological consequences (Pelicice, Agostinho, 2009; Franco et al., 2021; Khaleel et al., 2021; Souza et al., 2021).

Ecological plasticity in Cichla has been associated with its demographic success and invasiveness, but no study has examined the brain morphology of this genus, despite its value for topics such as taxonomy, evolution, behavior, ecology, and cognitive perspectives. Brain variation in fishes has been reported when comparing isolated populations of the same species (Kotrschal et al., 2017; Liu et al., 2021). Intraspecific morphological differences between males and females are also possible (Angulo, Langeani, 2017; Abrahão et al., 2021), as are ontogenetic modifications. Given the taxonomic uncertainties about Cichla (Willis et al., 2012; Winemiller et al., 2021), together with its recognized ecological performance (Carvalho et al., 2021; Gaspar et al., 2024), the investigation of brain morphoanatomy may provide valuable information and insights about this group. It must also be considered that brain anatomy in Neotropical cichlids remains virtually unstudied, with few published works (Oliveira, Graça, 2020, 2024; Leão‐Reis et al., 2025).

To fill this gap, this is the first study to characterize brain morphology in Cichla. We focused on Cichla piquiti Kullander & Ferreira, 2006, a species endemic to the Tocantins-Araguaia basin (Kullander, Ferreira, 2006), but introduced elsewhere (Franco et al., 2022b). Specimens from native (i.e., Tocantins-Araguaia basin) and non-native populations (i.e., Grande River, upper Paraná basin) were described in terms of gross brain morphology and compared to investigate variations in morphology, documenting developmental changes and comparing qualitative and quantitative variation between sexes and populations. Additionally, we calculated the Encephalization Quotient (E_Q) to provide insights into potential associations between cognitive performance and the invasive success of the species. Based on prior research in fish neuroanatomy, we tested two hypotheses: (1) individuals from distinct environments exhibit distinct brain morphology, and (2) C. piquiti presents high E_Q values, potentially associated with enhanced behavioral plasticity and invasive success.

Material and methods

---

Biological data. Native populations were sampled from two sites: (1) the area influenced by the Luiz Eduardo Magalhães Hydroelectric Plant (UHE Lajeado), Porto Nacional municipality, Tocantins River drainage, 10°42’25”S 48°26’08”W; and (2) the Javaés River, in proximity to the Canguçu Research Center, Araguaia River drainage, 09°58’58”S 50°02’43”W. Non-native populations were collected from (3) the area influenced by the Furnas Reservoir, Grande River, Paraná River drainage, 20°43’59”S 45°44’12”W.

Specimens were euthanized with eugenol diluted in 10% alcohol, fixed in 10% formaldehyde, and subsequently deposited in the Laboratório de Ictiologia Sistemática (Neamb/UFT), where they are catalogued.

A total of 37 specimens of Cihla piquiti were analyzed. From the Araguaia River, the sample comprised three adult females, three adult males, and one immature male; from the Furnas Reservoir, eight immature females and eleven immature males; and from the Tocantins River, three immature females and eight immature males. All specimens were measured with a precision caliper (0.01 mm) and weighed on an analytical balance (0.001 g). Standard length (SL), total length (TL), and total weight (TW) were recorded for each individual.

The examined material was deposited in the fish collection at the Laboratório de Ictiologia Sistemática, Universidade Federal do Tocantins (UNT), Porto Nacional, Brazil:

– Area 1: Lajeado Hydroelectric Reservoir, Tocantins River, Tocantins basin (10.706949° S, 48.435552° W): Cichla piquiti Kullander & Ferreira, 2006 – UNT 11327 (3: 81.40–100.00 mm SL); UNT 18940 (1: 155.30 mm SL); UNT 19753 (1: 47.50 mm SL); UNT 20100 (3: 87.0–87.90 mm SL); UNT 4543 (1: 58.30 mm SL); UNT 6287 (2: 87.10–97.10 mm SL).

– Area 2: Canguçu Research Center, Pium, Tocantins – Javaés River, Araguaia basin (9.982830° S, 50.045148° W): Cichla piquiti Kullander & Ferreira, 2006 – UNT 22471 (2: 252.0–375.0 mm SL); UNT 22472 (5: 250.0–320.0 mm SL); UNT 2397 (1: 124.30 mm SL).

– Area 3: Furnas Hydroelectric Reservoir, Minas Gerais – Grande River, Paraná basin (20.552624° S, 46.814970° W): Cichla piquiti Kullander & Ferreira, 2006 – UNT 22487 (7: 90.1–171.7 mm SL); UNT 23004 (12: 95.7–151.4 mm SL).

Anatomical description and comparison. Brain dissection and extraction followed the protocol of Marinho-Nunes et al. (2025b). The measurements are presented in different formats because they were obtained using different methods, i.e., brain were weighed using an analytical balance with a precision of 0.0001 g, and morphometric measurements were recorded, including brain weight (BW), total brain length (BL), brain width (BWd), and brain height (BH), using a Leica MC160 stereomicroscope equipped with an attached camera, with a measurement precision of 0.0001 mm. Total brain volume (BV) was estimated using the formula V = 1/6 π H W L (where H = height, W = width, L = length of the brain), commonly referred to as the “half-ellipsoid method” (Huber et al., 1997; Van Staaden et al., 1995; White, Brown, 2015). The Encephalization Quotient (E_Q) was calculated for each species as the ratio between the actual brain weight and the expected brain weight for an animal of a given body mass, using the formula E_Q = EaEe⁻¹, where Ea is the actual brain weight and Ee is the expected brain weight, following the approach of Bauchot, Bauchot (1978) and Bauchot et al. (1989b).

For image acquisition, a Leica MC160 stereomicroscope equipped with a multi-capture system (auto-montage) was used to improve image resolution. The brains were immobilized by complete immersion in alcohol gel to prevent displacement during image acquisition. To reduce surface irregularities of the medium and minimize light refraction, 70% ethanol was added to the surface of the alcohol gel, ensuring greater optical uniformity during image recording. Brains were illustrated manually using layered drawings and stippling techniques to depict shading and depth, with Sketchbook® v. 6.0.7. Anatomical nomenclature followed Waibl et al. (2012).

Neuroanatomical comparisons and descriptions focused on the following structures: bulbus olfactorius, telencephalon, tectum mesencephali, hypophysis, hypothalamus, saccus vasculosus, lobus inferior hypothalami, cerebellum, eminentia granularis, lobus vagi, lobus gustativus, medulla oblongata, and the lamellae fossa nasalis. In adult specimens, the lamellae were stained with Alcian Blue to enhance visualization due to their natural translucency.

The Sturges method was applied to classify standard length (SL) into non-arbitrary categories for comparisons of brain development across size classes (Sturges, 1926). Seven SL classes were defined, although class 6 (300–350 mm) contained no specimens (Tab. 1).

TABLE 1 | Standard length (SL) classes used to determine sample size and size range.

Locality
Class	Range (mm)	Araguaia	Tocantins	Furnas
1	50–100	–	11	4
2	100–150	2	1	11
3	150–200	–	–	12
4	200–250	1	–	–
5	250–300	3	–	–
6	300–350	–	–	–
7	350–400	1	–	–

Statistical analyses. All statistical analyses were conducted in RStudio v. 2023.01.1 (RStudio Team, 2022). Data normality was assessed using the Shapiro-Wilk test. For analyses involving brain structure volumes, the relative volume (RV) was calculated as RV = log (Volume) / log (Standard length).

Differences in Encephalization Quotients (E_Q) among populations were tested using Analysis of Variance (ANOVA), with locality as a factor. Differences in E_Q between males and females were tested using a student’s t-test (Gotelli, Ellison, 2013).

A Principal Component Analysis (PCA) was performed to investigate variation in brain structures among localities, using the relative volumes of the bulbus olfactorius, telencephalon, tectum mesencephali, lobus inferior hypothalami, cerebellum, lobus gustativus, and medulla oblongata. An additional PCA was conducted comparing only specimens from Furnas and Tocantins to minimize potential allometric effects, since the Araguaia specimens were adults and considerably larger. PCA scores were further examined to assess patterns between males and females (Gotelli, Ellison, 2013).

A Permutational Analysis of Variance (PERMANOVA) was conducted to evaluate differences in brain structure among sampling localities and between sexes, using multivariate Euclidean distances as the dissimilarity metric. The coefficient of determination (R²) was used to quantify the proportion of variation explained by locality, and statistical significance was assessed through permutation-based p-values. To ensure that observed differences were not attributable to unequal within-group dispersion, a test for homogeneity of multivariate dispersions (PERMDISP) was also performed.

To assess potential differences in the number of lamellae fossa nasalis among sampled localities, the Kruskal-Wallis test was applied as a nonparametric method to compare medians across three or more groups. When significant differences were detected, Dunn’s post hoc test was performed to conduct pairwise multiple comparisons among localities.

Results​

---

Qualitative analysis: morphological descriptions. The brain morphology of Cichla piquiti is described comparatively across developmental stages and localities, following an anteroposterior sequence. The descriptions are based on the morphological variation observed between specimens at early developmental stages (Fig. 1) and specimens at advanced developmental stages (Fig. 2) from different sampling localities. We chose not to describe the material by comparing juveniles and adults (based on sexual maturity), as complete brain formation occurs prior to sexual maturation, resulting in juveniles that already exhibit a fully developed brain. The relationship between size (SL) and the development of brain structures is detailed in the subsequent paragraphs.

FIGURE 1| Brain of Cichla piquiti in early development stage. A. Dorsal view; B. Lateral view; C. Ventral view. Scale bar = 2 mm. Abbreviations: Bo, bulbus olfactorius; Cb, cerebellum; Ch, chiasma opticum; Eg, eminentia granularis; Hyp, hypophysis; Hpl, hypothalamus; III, nervus oculomotorius; IV, nervus trochlearis; IX, nervus glossopharyngeus; Lg, lobus gustativus; Lih, lobus inferior hypothalami; Lv, lobus vagi; Mo, medulla oblongata; NI, nervus olfactorius; NII, nervus opticus; Nlla, nervus linea lateralis anterior; Nllp, nervus linea lateralis posterior; Nso, nervus spino-occipitales; Sv, saccus vasculosus; Tl, telencephalon; Tm, tectum mesencephali; V, nervus trigeminus; VI, nervus abducens; VII, nervus facialis; VIII, nervus octavus; Vq, Ventriculus quartus; X, nervus vagus.

FIGURE 2| Brain of Cichla piquiti in advanced development stage illustrated. A. Dorsal view; B. Lateral view; C. Ventral view. Scale bar = 2 mm. Abbreviations: Bo, bulbus olfactorius; Cb, cerebellum; Ch, chiasma opticum; Eg, eminentia granularis; Hyp, hypophysis; Hpl, hypothalamus; III, nervus oculomotorius; IV, nervus trochlearis; IX, nervus glossopharyngeus; Lg, lobus gustativus; Lih, lobus inferior hypothalami; Lv, lobus vagi; Mo, medulla oblongata; NI, nervus olfactorius; NII, nervus opticus; Nlla, nervus linea lateralis anterior; Nllp, nervus linea lateralis posterior; Nso, nervus spino-occipitales; Sv, saccus vasculosus; Tl, telencephalon; Tm, tectum mesencephali; V, nervus trigeminus; VI, nervus abducens; VII, nervus facialis; VIII, nervus octavus; Vq, Ventriculus quartus; X, nervus vagus.

In early developmental stages, the lamellae fossa nasalis form tongue-shaped (linguiform lamellae) projections, which may appear either fully developed or still undergoing development (Figs. 3A–B). In advanced developmental stages, the lamellae assume a leaf-like morphology with a slight invagination, resulting in lateral margins that are elevated relative to the medial margins (Fig. 3C). All lamellae in advanced developmental stages specimens were fully developed.

FIGURE 3| A. Nasal lamellae (lamellae fossa nasalis) of early development stage Cichla piquiti (UNT 22487_2; 116.00 mm SL); B. Magnified nasal lamellae of early development stage Cichla piquiti; C. Nasal lamellae of advanced development stage Cichla piquiti (UNT 22471_1; 270.00 mm SL) stained with alcian blue. Scale bars = 2 mm.

The number of lamellae in the nasal fossa ranged from 12 to 26, with variation associated with specimen size and sampling locality. In Furnas specimens, lamellae counts varied between 14 and 16, corresponding to Class 2 individuals (100–150 mm SL) and one Class 3 specimen (171 mm SL). Native populations (Tocantins and Araguaia) generally exhibited higher numbers. A single Araguaia specimen from Class 2 (124 mm SL) had 16 lamellae, whereas larger specimens (132–370 mm SL; Classes 2–7) exhibited 21–25 lamellae. Tocantins specimens from Class 1 (n = 9) had 12–17 lamellae, and one Class 3 specimen (155 mm SL) presented 22 lamellae.

Prosencephalon and telencephalon. The bulbus olfactorius is oval in shape, with an anterior portion that is narrower than the posterior portion, which connects directly to the telencephalon (Figs. 4C–D). This structure is relatively small compared with the entire brain, accounting for approximately 1% of total brain volume in adult specimens. In early developmental stages (between 50–200 mm SL), although smaller than all other paired structures, it is proportionally larger, as regions such as the telencephalon remain less developed at early stages (Figs. 4A–D).

FIGURE 4| Anterior region of the Cichla piquiti encephalon. (A, C: UNT 4543_1; 58.30 mm SL); (B, D: UNT 22471_1; 270.50 mm SL); A. Dorsal view of early development stage; B. Dorsal view of advanced development stage; C. Lateral view of early development stage; D. Lateral view of advanced development stage. Abbreviations: Bo, bulbus olfactorius; Tl, telencephalon; Tm, tectum mesencephali. Scale bars = 2 mm.

The morphology of the telencephalon differed between early and advanced developmental stages. At early developmental stages (between 50–200 mm SL), according to the defined size classes, the structure is compact, with the two hemispheres clearly separated by a fissure, allowing visualization of the ventral surface (Fig. 4A). In early developmental stages (< 200 mm SL), the dorsal surface of the telencephalon exhibits a height comparable to that of the dorsal surfaces of the tectum mesencephali and cerebellum (Fig. 4C). In advanced developmental stages (> 200 mm SL), the telencephalon expands dorsally, the interhemispheric fissure becomes reduced to a shallow sulcus, and the structure assumes a coracoid shape, with the anterior portion wider than the posterior (Fig. 4B). The posterior region is positioned dorsally beyond its own dorsal margin, making the superior surface higher than that of the tectum mesencephali (Fig. 4D).

Ontogenetic variation was also observed among localities. In Furnas, all Class 1 and 2 (50–150 mm SL) individuals exhibited an incompletely developed telencephalon; only one Class 3 specimen (170 mm SL) displayed a fully developed structure. In contrast, all Araguaia specimens, including juveniles (two Class 2 individuals: 124 mm and 132 mm SL), exhibited a developed telencephalon. Among Tocantins specimens, only the smallest individuals (50–81 mm SL) showed the structure in development, whereas from 87 mm SL onwards, including Class 1 and 2 specimens, the telencephalon was fully developed.

Diencephalon. The lobus inferior hypothalami is a paired structure, with the anterior hemispheres separated by the hypothalamus and saccus vasculosus, while the posterior portions are connected, forming a sulcus between them (Figs. 5A–B). In early developmental stages specimens, the structure is rectangular in ventral view, with straight anterior and posterior margins (Fig. 5C). In advanced developmental stages, it is reniform. In the lateral view, however, no distinct differences were observed between early and advanced developmental stages (Figs. 5C–D).

FIGURE 5| Brain of Cichla piquiti. (A, C, E: UNT 4543_1; 58.30 mm SL); (B, D, F: UNT 22471_1; 270.50 mm SL); A. Dorsal of early development stage; B. Dorsal anterior region of an advanced development stage; C. Lateral anterior region of early development stage; D. Lateral anterior region of an advanced development stage. Abbreviations: Bo, bulbus olfactorius; Cb, cerebellum; Ch, chiasma opticum; Eg, eminentia granularis; Hpl, hypothalamus; Lg, lobus gustativus; Lih, lobus inferior hypothalami; Lv, lobus vagi; Mo, medulla oblongata; Sv, saccus vasculosus; Tl, telencephalon; Tm, tectum mesencephali; Vq, Ventriculus quartus. Scale bars = 2 mm.

Ontogenetic and locality-based variation was also observed. In Furnas, all Class 1 and 2 (50–150 mm SL) individuals exhibited a lobus inferior hypothalami still in development, with only one Class 3 specimen (171 mm SL) presenting a fully developed lobus inferior hypothalami. In contrast, all Araguaia specimens, including juveniles, showed this structure fully developed. Among Tocantins specimens, individuals exceeding 80 mm SL consistently displayed a developed lobus inferior hypothalami.

The hypophysis, hypothalamus, and saccus vasculosus lie on the ventral region of the diencephalon (Fig. 6). These structures are relatively small compared with other brain components and exhibited no variation in shape between early and advanced developmental stages or among the populations analyzed. The hypophysis has a concave posterior margin, with width exceeding length; it connects to the chiasma opticum, although this connection is delicate, making the structure easily detachable. The hypothalamus is coracoid in shape, with the anterior portion wider than the posterior, and is visibly divided into two lateral regions by a median fissure. The saccus vasculosus is ovoid, located ventrally to the posterior margin of the hypothalamus, with its posterior margin in contact with the medial region of the lobus inferior hypothalami. Its growth is comparatively reduced relative to other diencephalic structures, such that in advanced developmental stages, the saccus vasculosus is proportionally smaller than the other developed components of the diencephalon.

FIGURE 6| Ventral median region of the brain of early development stage Cichla piquiti (UNT 6287_2; 97.00 mm SL. Abbreviations: Hpl, hypothalamus; Hyp, hypophysis;Lih, lobus inferior hypothalami; Sv, saccus vasculosus. Scale bar = 2 mm.

Mesencephalon. The tectum mesencephali is the most prominent brain structure in Cichla piquiti. In early developmental stages (< 200 mm SL), the compact arrangement of the brain within the neurocranium results in a slightly flattened dorsal surface, with a height comparable to that of the dorsal surfaces of the telencephalon and cerebellum (Fig. 5C). In adults advanced developmental stages (> 200 mm SL), the dorsal surface becomes concave as the structure assumes an oval shape. In the lateral view, the tectum mesencephali is diagonally inclined, with the anterior region positioned ventrally relative to the posterior region (Fig. 5D).

Rhombencephalon, metencephalon and myelencephalon. The cerebellum exhibited the greatest morphological variation between early and advanced developmental stages specimens. At early developmental stages (< 200 mm SL), it is compact, with a height of approximately two-fifths of its total length. The lateral margins show two indentations: the first corresponds to a groove formed by an elevated fold, and the second to a lateral compression (Figs. 7A, D). In some Class 1 juveniles (50–100 mm SL), a slight lateral compression is still visible in dorsal view (Fig. 7B). In fully developed specimens, the cerebellum becomes oval, with height reaching approximately four-fifths of its total length, and its anteroventral margin connects to the lobus gustativus (Figs. 7C, F).

FIGURE 7| Brain of Cichla piquiti (A, D: UNT 4543_1; 58.30 mm SL); (B, D: UNT 11327_3; 96.60 mm SL); (C, F: UNT 22471_1; 270.50 mm SL); arrow 1 = first indentation and arrow 2 = second indentation. A. Dorsal view, posterior region of the brain of early development stage rotated 45° to the left; B. Dorsal view, posterior region of the brain of early development stage rotated 45° to the left; C. Dorsal view, posterior region of the brain of advanced development stage; D. Lateral view, posterior region of the brain of early development stage; E. Lateral view, posterior region of the brain of a non-reproductive early development stage; and F. Lateral view, posterior region of the brain of an advanced development stage. Abbreviations: Cb, cerebellum; Eg, eminentia granularis; Lg, lobus gustativus; Lih, lobus inferior hypothalami; Lv, lobus vagi; Mo, medulla oblongata; Tl, telencephalon; Tm, tectum mesencephali; Vq, Ventriculus quartus. Scale bars = 2 mm.

Ontogenetic and population-based differences were also observed. All Araguaia specimens, including Classes 2, 3, and 7 (132–370 mm SL), presented a fully developed cerebellum. In Furnas, all individuals except one Class 3 (171 mm SL) specimen exhibited a structure still in development. In Tocantins, only two Class 1 individuals displayed the cerebellum in development; from 81 mm SL onward, specimens showed only slight lateral compression, and above 90 mm SL, all individuals had a fully developed cerebellum.

The lobus facialis and lobus trigeminalis are inconspicuous. The only structures clearly distinguishable from the lobus gustativus are the lobus vagi and the eminentia granularis. The eminentia granularis is oval, with its height approximately twice its length, and is located laterally on the anteroventral region of the cerebellum in both developmental stages, but is more conspicuous advanced stages (Figs. 8B–D). The lobus vagi is positioned ventral to the cerebellum. In early stages, the Ventriculus quartus is scarcely visible in the dorsal median region of the lobus gustativus (Fig. 8C), but becomes more distinct in advanced developmental stages (> 200 mm SL) (Fig. 8D).

FIGURE 8| Posterior regions of the brain of Cichla piquiti. (A, C: UNT 11327_3; 96.60 mm SL); (B, D: UNT 22471_1; 270.50 mm SL); A. Dorsal view of early development stage; B. Dorsal view of an advanced development stage; C. Lateral view of early development stage; D. Lateral view of an advanced development stage. Abbreviations: Cb, cerebellum; Eg, eminentia granularis; Lg, lobus gustativus; Lih, lobus inferior hypothalami; Lv, lobus vagi; Mo, medulla oblongata; Tl, telencephalon; Tm, tectum mesencephali; Vq, Ventriculus quartus. Scale bars = 2 mm.

In the ventral region of the lobus gustativus, cranial nerves are observed in an anteroposterior sequence: nervus oculomotorius, nervus trochlearis, nervus trigeminus, nervus abducens, nervus facialis, nervus octavus, nervus glossopharyngeus, nervus vagus, nervus lineae lateralis anterior,and nervus lineae lateralis posterior. With the exception of the nervus abducens, which emerges ventrally from the metencephalon, the nervus olfactorius (emerging from the anterior region of the telencephalon) and the nervus opticus (emerging ventrally from the mesencephalon), all other cranial nerves emerge laterally from the metencephalon.

Morphological variation was evident between juveniles in early post-embryonic stages (Classes 1 and 2; 50–150 mm SL), larger juveniles, and adults (Classes 2–7; 150–400 mm SL), particularly in the telencephalon, lobus inferior hypothalami, and cerebellum. Among these structures, the cerebellum develops first, although some fully developed specimens still exhibited a slight lateral compression. Development of the lobus inferior hypothalami progressed sequentially, with the telencephalon reaching maturity finally.

Population-level differences were also observed. Furnas specimens exhibited delayed brain development compared with Tocantins specimens. The only Furnas individual with a fully developed brain measured 171 mm SL; all other individuals between 90–109 mm SL retained the three structures in development, and one specimen at 116 mm SL presented a developed cerebellum but with subtle lateral compression. In contrast, Tocantins specimens attained full brain development at smaller sizes. Only three individuals (46–81 mm SL) exhibited three brain structures still under development. In specimens larger than ~81 mm SL, developmental differences were restricted to the telencephalon, which remained incompletely developed in some individuals up to 100 mm SL. From approximately 87 mm SL onward, all examined specimens exhibited fully developed brains.

Quantitative analysis. Encephalization quotient (E_Q). The mean Encephalization Quotient (E_Q) values for the sampled localities were: Araguaia = 1.09, Furnas = 1.02, and Tocantins = 0.97. Linear regression analysis revealed a significant positive correlation between body mass and brain size (p = 0.001, adjusted R² = 0.67), indicating that brain size and growth are strongly associated with body mass (Fig. 9A). Analysis of variance (ANOVA) showed no statistically significant differences in E_Q among the three localities (p = 0.0652; Fig. 9B). Similarly, a Student’s t-test revealed no significant differences in E_Q between males and females (p = 0.1945).

FIGURE 9| A. Linear regression between brain weight and body weight. Variables were log10 transformed; B. Analysis of variance comparing the Encephalization Quotient (E_Q) among the three localities.

Relative size of brain structures. The volumes estimated using the half-ellipsoid method are presented in Tab. 2, along with the corresponding height, width, and length measurements of each structure. It should be noted that the calculated volumes (mm³) do not represent the exact anatomical volumes, as the formula assumes an ideal ellipsoidal shape. Since not all brain structures conform precisely to this geometry, the resulting values should be interpreted as approximations.

TABLE 2 | Data on the volumes obtained for each of the examined specimens, where, F: Female; M: Male; SL: Standard length (mm); BW: Body weight (g); EW: Brain weight (g); VE: Encephalon volume (mm³); VBO: Volume of the bulbus olfactorius (mm³); VTM: Volume of the tectum mesencephali (mm³); VCB: Volume of the cerebellum (mm³); VMO: Volume of the medulla oblongata (mm³); VLG: Volume of the lobus gustativus (mm³); VLIH: Volume of the lobus inferior hypothalami (mm³); VEG: Volume of the eminentia granullaris (mm³); and Lam: Number of lamellae in the nasal fossa.

Specimen	Locality	Sex	SL	BW	EW	VE	VBO	VTL	VTM	VCB	VMO	VLG	VLIH	VEG	Lam
UNT17443_1	Araguaia	F	132.00	40.70	0.2250	314.0498	0.6681	34.9685	106.0810	9.7995	5.6586	13.2756	11.6919	0.5414	21
UNT22471_1	Araguaia	F	270.50	647.20	0.5331	866.8127	1.7956	69.8897	166.7444	26.8029	13.0201	41.1602	32.2996	2.7689	24
UNT22471_2	Araguaia	M	370.50	976.70	0.5392	706.5639	0.9027	58.3530	133.5272	18.2135	8.3747	27.8535	26.4143	2.1584	25
UNT22472_2	Araguaia	M	250.00	483.80	0.4852	643.9162	2.0461	59.7834	145.4941	25.9723	11.5899	29.8383	23.7408	2.3792	21
UNT22472_3	Araguaia	F	260.50	397.60	0.4059	601.1100	1.9873	39.7147	140.9538	16.1983	11.0431	24.3979	19.5694	1.2422	26
UNT22472_5	Araguaia	M	260.50	380.00	0.4912	771.2062	2.3943	59.1339	154.0825	24.1190	9.2942	24.8764	25.5258	1.7250	25
UNT2397_1	Araguaia	M	124.30	31.57	0.1432	233.8236	0.3868	15.3822	59.1278	10.4922	2.5141	15.6616	9.8241	0.4717	16
UNT22487_1	Furnas	M	171.70	95.00	0.2051	360.8521	0.7176	18.4394	81.3679	10.6212	3.6547	15.6693	12.7070	1.3759	15
UNT22487_2	Furnas	M	116.20	25.00	0.1304	250.2207	0.4738	11.6626	64.1395	4.7343	5.6138	13.1639	6.4646	0.3725	16
UNT22487_3	Furnas	M	92.40	14.00	0.0827	181.0442	0.3198	11.9274	52.4350	4.3292	2.0701	12.5734	5.7042	0.4154	14
UNT22487_4	Furnas	F	97.40	15.00	0.0848	138.9585	0.5324	12.8472	50.2478	3.7298	2.0780	7.7134	3.7788	0.6261	15
UNT22487_5	Furnas	F	90.10	14.00	0.0816	166.5404	0.1689	9.7745	48.4689	2.1933	2.0202	7.2274	4.0439	0.3047	14
UNT22487_6	Furnas	M	105.70	21.00	0.0819	149.6664	0.1269	9.3760	45.1096	4.9700	5.1044	9.2090	3.6452	0.3201	14
UNT22487_7	Furnas	M	109.90	23.00	0.0852	156.3202	0.5851	7.0204	41.7917	3.9484	5.2582	9.9217	4.5229	0.2081	15
UNT11327_1	Tocantins	F	81.40	9.80	0.0848	178.7991	0.9324	12.6456	49.8993	6.5702	2.0597	7.4576	6.0029	0.2940	15
UNT11327_2	Tocantins	M	100.00	18.21	0.1013	228.9603	0.4163	16.8993	53.8943	6.6648	5.1005	11.5312	6.9151	0.4697	17
UNT11327_3	Tocantins	F	96.60	15.61	0.1088	217.7280	0.7655	17.0919	57.3227	7.4582	2.9101	10.4848	8.0324	0.3280	16
UNT18940_1	Tocantins	M	155.30	65.42	0.1938	324.8040	1.1488	30.3841	112.4101	14.4622	5.7058	15.5893	13.3523	0.7424	22
UNT20100_1	Tocantins	M	87.00	13.28	0.1149	133.6407	0.6518	12.3574	47.1834	6.5024	2.8132	10.5683	8.3157	0.4312	16
UNT20100_2	Tocantins	M	87.90	13.06	0.0965	181.3640	0.6907	14.7925	44.8749	6.1451	3.5338	9.9700	7.0380	0.4208	14
UNT20100_3	Tocantins	M	81.30	10.61	0.0911	164.4040	0.6903	12.1274	40.0302	7.0621	3.0811	7.4965	5.6025	0.5591	15
UNT4543_1	Tocantins	M	58.30	4.20	0.0381	91.4663	0.6126	8.2435	29.4167	5.2747	1.5413	6.8891	3.9618	0.1597	12
UNT6287_1	Tocantins	F	87.10	13.52	0.1020	186.9333	0.8873	14.8906	57.2802	5.4529	2.8843	8.0338	6.4636	0.2929	15
UNT6287_2	Tocantins	M	97.10	16.43	0.7800	174.1208	1.0412	13.4234	38.6533	10.4244	3.6496	11.0913	10.0510	0.4415	16
UNT23004_1	Furnas	F	137.40	47.90	0.1793	302.6809	0.4636	13.0364	82.2626	7.5787	4.9821	17.6945	9.7248	0.6316	18
UNT23004_2	Furnas	F	150.70	63.85	0.3047	508.9405	0.3775	21.2288	101.2495	18.1485	7.9827	24.1430	12.2760	2.1437	17
UNT23004_3	Furnas	F	108.90	23.65	0.1388	265.0994	0.5117	14.7297	61.2870	8.8259	3.6677	12.4148	7.6134	0.6287	15
UNT23004_4	Furnas	M	115.60	29.85	0.1566	274.0925	0.6130	16.9328	71.3619	9.0623	2.1110	11.6522	7.5941	0.6812	14
UNT23004_5	Furnas	M	151.40	66.70	0.2493	441.4521	0.8842	23.8006	112.6752	10.7115	5.2572	11.8835	15.4137	0.6532	16
UNT23004_6	Furnas	F	135.50	48.90	0.2133	306.7103	0.5884	15.6894	82.1979	8.0939	4.4517	15.8642	12.9390	0.7192	15
UNT23004_7	Furnas	M	124.00	36.81	0.1564	287.0161	0.5894	11.7631	59.8831	8.3902	4.6528	6.1632	10.4794	0.7328	15
UNT23004_8	Furnas	M	128.00	39.45	0.1347	253.8859	0.5591	14.2173	61.4636	11.2000	2.1751	11.6995	6.1272	0.9455	15
UNT23004_9	Furnas	F	114.40	29.50	0.1670	241.7730	0.3928	13.6543	50.6332	6.6960	2.9928	10.4543	9.6191	0.6738	13
UNT23004_10	Furnas	F	112.70	25.95	0.1432	230.7820	0.5409	13.3581	52.7963	6.1773	3.0516	9.5426	7.6904	0.2706	15
UNT23004_11	Furnas	M	112.90	25.72	0.1410	278.6862	0.3617	12.4490	66.2134	7.0521	2.7457	9.1057	5.7072	0.5098	16
UNT23004_13	Furnas	M	95.70	16.77	0.0998	201.4605	0.3508	11.3077	47.8728	5.3933	2.1433	12.0324	6.3116	0.9882	15

The proportional representation of brain structures was generally similar among populations (Fig. 10). The tectum mesencephali was consistently the largest structure, while the bulbus olfactorius and eminentia granullaris remained the smallest across all localities. Among the regions that showed noticeable variation, the telencephalon differed the most, corresponding to 18.9% in Araguaia, 12.5% in Furnas, and 15.6% in Tocantins. The tectum mesencephali also exhibited moderate variation, ranging from 50.8 to 58.4%. The remaining structures, including the cerebellum, lobus gustativus, medulla oblongata, and lobus inferior hypothalami, showed only minor fluctuations among populations.

FIGURE 10| Proportion of brain structure volumes relative to total brain volume.

Population analysis. The Principal Component Analysis (PCA) revealed differences in brain structure among the three localities, with the formation of three groups in the multivariate space (Fig. 11). Larger volumes of the tectum mesencephali, telencephalon, lobus inferior hypothalami, and cerebellum were associated with Araguaia, with PC1 accounting for 75.81% of the total variation. PC2 explained 8.68% of the variation, with higher volumes of the medulla oblongata and lobus gustativus in Furnas, whereas a larger bulbus olfactorius volume was associated with Tocantins.

FIGURE 11| Results of a Principal Component Analysis (PCA) conducted to investigate variation in brain structure among specimens from the three sampled localities. VTo = volume of tectum mesencephali; VTl = volume of telencephalon; VBo = volume of bulbus olfactorius; VCc = volume of cerebellum; VLih = volume of lobus inferior hypothalami; VLG = volume of lobus gustativus; and VMo = volume of medulla oblongata.

The second PCA, restricted to Furnas and Tocantins specimens, revealed population-level differences only along PC2, which explained 18.23% of the variance (Fig. 12). In this analysis, volume of the bulbus olfactorius was positively associated with Tocantins, whereas medulla oblongata and lobus gustativus volumes were associated with Furnas. These results suggest that variation in telencephalon, cerebellum, lobus inferior hypothalami, and tectum mesencephali volumes is more strongly influenced by fish size than locality. In both PCA analyses, sex was included as a factor; however, no clustering was observed, with males and females showing extensive overlap in the distribution of data.

FIGURE 12| Results of a Principal Component Analysis (PCA) conducted to investigate variation in brain structures among specimens from Tocantins and Furnas. VTo = volume of tectum mesencephali; VTl = volume of telencephalon; VBo = volume of bulbus olfactorius; VCc = volume of cerebellum; VLih = volume of lobus inferior hypothalami; VLG = volume of lobus gustativus; and VMo = volume of medulla oblongata.

The multivariate distances differed significantly among the three sampled localities (PERMANOVA: R² = 0.4206; p < 0.01); when sex was considered, no significant difference was found (R² = 0.00819; p = 0.884). No significant difference in data dispersion was detected among localities (PERMDISP: p = 0.2960). Restricting the analysis to Furnas and Tocantins, localities differed with marginal statistical significance (PERMANOVA: R² = 0.0959; p = 0.05), with no significant differences in data dispersion between the two localities (PERMDISP: p = 0.1120).

The number of lamellae (lamellae fossa nasalis) differed significantly among localities (Kruskal-Wallis: p < 0.0005). Differences were found between Araguaia and Furnas (Dunn post-hoc: p = 0.0003) and between Araguaia and Tocantins (p = 0.015), with a higher number of lamellae observed in the Araguaia population (Fig. 13).

FIGURE 13| Boxplot comparing the number of lamellae fossa nasalis among the three sampled localities.

Discussion​

---

Our analyses provide the first description of the brain of Cichla piquiti and its post-larval (i.e., juvenile and adult) developmental changes, revealing a conservative neuroanatomical pattern, particularly in the telencephalon, lobus inferior hypothalami, and cerebellum. Quantitative assessments further revealed neuro-morphological differences among populations from distinct localities. The study also presents data on the Encephalization Quotient (E_Q) of C. piquiti, offering insights into the species’ cognitive capacities and behavioral performance in novel environments.

The post-larval morphological stages and statistical analyses revealed a developmental pattern in which the rhombencephalon structures develop first, followed by the mesencephalon and finally, the prosencephalon, a sequence observed in most vertebrates (Nieuwenhuys, 1966; Meek, Nieuwenhuys, 1998). The rhombencephalon houses structures central to agility, respiration, and motor coordination, such as the cerebellum and medulla oblongata, which may be particularly important during early developmental stages, when survival and feeding efficiency are critical (Finger, Morita, 1985; Morita, Finger, 1985). Moreover, analyses of ossification patterns in some fishes show that the first bones to develop are functionally related to feeding and respiration, as well as the branchial arches (e.g., Marinho (2023) for Moenkhausia pittieri Eigenmann, 1920 (= Makunaima pittieri). These structures are coordinated by stimuli originating from the rhombencephalon, from which the nerves nervus trigeminus, nervus abducens, nervus facialis, nervus glossopharyngeus, and nervus vagus project (Meek, Nieuwenhuys, 1998; Striedter, 2005).

The relative proportions of brain structures in Cichla piquiti are notably distinct, with the tectum mesencephali comprising the largest portion of brain volume (~54–58%), in contrast to the bulbus olfactorius, which represents less than 1%. This disproportion suggests that vision plays a dominant role in the sensory processing of these fish, whereas their olfactory system is relatively undeveloped. Species of Cichla are visually oriented predators that inhabit the littoral zones of aquatic environments (Fernandes et al., 2025), where conditions favor light incidence and habitat complexity (Winemiller et al., 2021; Andrade, Pelicice, 2022). In such habitats, vision becomes an especially efficient sensory modality, as low turbidity enhances the availability of visual cues, a pattern also observed in other neotropical cichlids (Oliveira, Graça, 2020, 2024; Leão‐Reis et al., 2025). Furthermore, C. piquiti displays polychromatism, exhibiting changes in body and fin coloration throughout its lifespan (Pelicice et al., 2022). Given that cichlids are tetrachromatic (Carleton, Kocher, 2001; Dalton et al., 2010), it is likely that C. piquiti relies on vision not only for foraging but also for social interactions, including intraspecific communication, mate choice, individual recognition, and territory defense or acquisition (Siepen, Caprona, 1986; Carleton et al., 2008; Dalton et al., 2010).

No sexual dimorphism was observed in the brain morphology of the analyzed specimens, considering both the size and the shape of structures. Additionally, no correlations were found between the brain developmental rates and its respective structures across sexes. In Cichla piquiti, maturity is similar between males and females (FMP, unpub. data), and reproductive behaviors such as nest building and offspring care are shared by both sexes (Andrade, Pelicice, 2022), indicating that males and females are subject to similar selective pressures on brain function. Differences in the growth rate of brain structures have been reported in Microglanis garavelloi Shibatta & Benine, 2005, where females’ brains grow faster, as they reach maturity at smaller sizes than males, thus exhibiting faster physiological and morphological maturation (Abrahão et al., 2021).

No statistically robust differences were found in the relative size of brain structures among the three sampled populations. However, the Principal Component Analyses formed three distinct groups. Furthermore, when qualitatively assessed, the post-embryonic development of the telencephalon, lobus inferior hypothalami, and cerebellum appeared delayed in the Furnas specimens, as only one individual (171 mm SL) exhibited all brain structures fully developed. Kotrschal et al. (2017) reported strong correlations between the volume of specific brain structures and evolutionary pressures, showing that the presence of predators and competitors influenced the relative size of brain structures in isolated populations of Poecilia reticulata Peters, 1859. Considering this, the reduced number of predators or competitors for juvenile Cichla piquiti in the invaded ecosystem may be related to the delayed development of these structures. In the Furnas Reservoir, only four potential predators or competitors have been recorded: Salminus hilarii Valenciennes, 1850; Hoplias malabaricus (Bloch, 1794); Hoplias intermedius (Günther, 1864); and Hoplerythrinus unitaeniatus (Spix & Agassiz, 1829) (Nobile et al., 2024), a number considerably lower than the predator diversity reported in the Tocantins and Araguaia rivers (Chamon et al., 2022). It is important to note that this hypothesis warrants further investigation, as multiple factors (e.g., fish size, food deprivation) may contribute to variation in brain structure.

Our findings support the hypotheses that individuals from populations exposed to distinct environmental conditions exhibit modifications in brain morphology. Differences in brain morphology of Cichla piquiti under distinct environmental conditions were observed, as well as a developmental pattern consistently present in juveniles, involving modifications in the telencephalon, lobus inferior hypothalami, and cerebellum. This pattern of structural modifications follows a posteroanterior sequence, indicating that the posterior regions are more relevant during the early developmental stages. It is important to note that statistical differences among populations were influenced by allometric effects related to specimen size, since the exclusion of adult individuals (Araguaia population) reduced the robustness of statistical significance. Nevertheless, qualitative differences among groups were still evident. Future studies with larger sample sizes, encompassing different species and a broader range of environments, are essential to further clarify the evolutionary processes underlying the Central Nervous System diversification in fishes.

The mean Encephalization Quotients (E_Q) of Cichla piquiti were 1.09, 1.02, and 0.97 for specimens from Araguaia, Furnas, and Tocantins, respectively; these values exceed the average value of 0.46 estimated for Actinopterygii (Triki et al., 2021). High E_Q values are usually associated with small-bodied fishes, because the relationship between brain size and body size in fishes follows a negative allometric pattern, relative brain size decreases as body size increases. Consequently, smaller species tend to exhibit relatively larger brains (higher EQ) than larger-bodied species (Bauchot et al., 1977; Peñaherrera Aguirre et al., 2021; Triki et al., 2021); however, Cichla piquiti is a large-sized predator (i.e., first maturity between 30 and 40 cm, and maximum total length at 62 cm; FMP, unpub. data). E_Q is strongly related to an organism’s cognitive performance, reflecting how the organism responds to environmental cues. Although the use of E_Q to estimate cognitive performance in endothermic taxa has been criticized, it has proven reliable in fishes (Triki et al., 2021). Buechel et al. (2018) and Triki et al. (2022b) associate cognitive performance (defined as the ability to acquire, process, and retain information and act upon it (Shettleworth, 2001) with relative brain size. Brain mass relative to body size reflects the energetic demand of the central nervous system compared to other systems (Jerison, 1973, 1985; Triki et al., 2018, 2021, 2022a,b; Peñaherrera Aguirre et al., 2021). Some studies suggest that using E_Q alone to assess cognitive investment should be approached with caution, since certain brain regions may have functions more critical for specific organisms and therefore are larger (Peñaherrera Aguirre et al., 2021; Triki et al., 2021). For example, Elasmobranchii have been reported with E_Q values above 1.0 (Lisney, Collin, 2006); however, a substantial proportion of their brain volume is composed of the bulbus olfactorius and cerebellum, regions primarily associated with sensory processing and motor coordination rather than integrative or higher-order cognitive functions (Ebbesson, Braithwaite, 2012). In contrast, considering that more than half of C. piquiti brain consists of the telencephalon and tectum mesencephali (Fig. 10), structures fundamental to cognitive processing, brain size can be translated into cognitive performance.

Moreover, some studies indicate that high E_Q values are found in generalist species, both in feeding and reproduction; the ability to adjust diet in response to available resources in a different environment, or to reproduce in a novel habitat, reflects reversal learning enabled by cognitive processes (Sol et al., 2005a,b; Ebbesson, Braithwaite, 2012; Pike et al., 2018). The cleaner wrasse (Labroides sp.) has been used as a model for cognitive studies in fishes, showing high rates of learning and feeding innovations that are associated with relative brain size (Bshary, Grutter, 2002; Wismer et al., 2014; Triki et al., 2018). Several authors have reported the remarkable success of Cichla species as invaders of new environments, characterized by high reproductive rates, and behavioral and ecological adaptations (Neal et al., 2017; Khaleel et al., 2021; Franco et al., 2022a,b; Gaspar et al., 2024). It is therefore reasonable to suppose that this invasive success is facilitated by some phenotypic plasticity associated with cognitive performance. In this context, our results support the hypothesis that the phenotypic plasticity of C. piquiti may be related to its high E_Q values, thereby enabling the occupation of different ecological niches in habitats under selective pressures that are relatively distinct from those in its native range.

It is important to emphasize that the E_Q of most fish species remains unknown, and therefore, our inferences regarding the cognitive capacity of Cichla piquiti are still preliminary. The lack of data on relative brain size in other fish species hampers comparisons between the E_Q of species with high invasion success vs. those with lower levels of phenotypic plasticity. Nevertheless, we highlight the risks associated with the introduction of C. piquiti into non-native environments, since its high adaptability, probably driven by cognitive performance, confers high invasiveness. Numerous studies have documented severe negative effects caused by the introduction of Cichla species, including native population declines, local extinctions, and ecosystem disruption (Pelicice, Agostinho, 2009; Neal et al., 2017; Sharpe et al., 2017; Valverde et al., 2020; Franco et al., 2021; Leal et al., 2021; Franco et al., 2022a,b).

In conclusion, our study provides the first comprehensive description of the brain of Cichla piquiti, revealing a conserved neuroanatomical pattern throughout post-larval development and highlighting how environmental conditions may influence neuro-morphological variation among populations. The developmental sequence observed in juveniles, coupled with the predominance of visual-processing structures and the high E_Q values recorded for this species, suggests that cognitive performance and phenotypic plasticity play important roles in its ecological success, particularly in invaded environments. Although statistical differences among populations were affected by allometric variation, qualitative patterns remained evident, indicating that environmental pressures may shape the development of key brain regions. Taken together, these findings advance our understanding of Central Nervous System diversification in Neotropical fishes and underscore the ecological risks associated with the introduction of C. piquiti, whose cognitive capacity and adaptability may enhance its invasive potential.

Acknowledgments​

---

The authors are grateful to the Graduate Program in Biodiversity, Ecology, and Conservation for the logistical and structural support provided for the development of this work. We also sincerely thank the Associate Editor for conducting the review process, whose guidance and comments were essential to improving the quality of the manuscript. We extend our deepest gratitude to Dr. André Casas and Dr. Valter Azevedo-Santos for their valuable contributions throughout the preparation of this manuscript.

References​

---

Abrahão VP, Ballen GA, Pastana MNL, Shibatta OA. Ontogeny of the brain of Microglanis garavelloi Shibatta and Benine 2005 (Teleostei: Siluriformes: Pseudopimelodidae). J Morphol. 2021; 282(4):489–99. https://doi.org/10.1002/jmor.21321

Abrahão VP, Pastana M, Marinho M. On a remarkable sexual dimorphic trait in the Characiformes related to the olfactory organ and description of a new miniature species of Tyttobrycon Géry (Characiformes: Characidae). PLoS ONE. 2019; 14(12):e0226130. https://doi.org/10.1371/journal.pone.0226130

Abrahão VP, Pupo FM, Shibatta OA. Comparative brain gross morphology of the Neotropical catfish family Pseudopimelodidae (Osteichthyes, Ostariophysi, Siluriformes), with phylogenetic implications. Zool J Linn Soc. 2018; 184(3):750–72. https://doi.org/10.1093/zoolinnean/zly011

Andrade GDS, Pelicice FM. Coexistence of endemic peacock basses (Cichla) in a Neotropical reservoir (Cichlidae: Cichliformes). Neotrop Ichthyol. 2022; 20(3):e220039. https://doi.org/10.1590/1982-0224-2022-0039

Angulo A, Langeani F. Gross brain morphology of the armoured catfish Rineloricaria heteroptera, Isbrücker and Nijssen (1976), (Siluriformes: Loricariidae: Loricariinae): A descriptive and quantitative approach. J Morphol. 2017; 278(12):1689–705. https://doi.org/10.1002/jmor.20742

Bauchot R, Bauchot ML. Coefficient de condition et indice pondéral chez les Téléostéens. Cybium. 1978; 3(4):3–16.

Bauchot R, Randall JE, Ridet JM, Bauchot ML. Encephalization in tropical teleost fishes and comparison with their mode of life. J Hirnforsch. 1989a; 30(6):645–69.

Bauchot R, Ridet J-M, Bauchot M-L. The brain organization of butterflyfishes. Environ Biol Fishes. 1989b; 25(1–3):205–19.

Brown C. Fish intelligence, sentience and ethics. Anim Cogn. 2015; 18(1):1–17. https://doi.org/10.1007/s10071-014-0761-0

Bshary R, Grutter AS. Experimental evidence that partner choice is a driving force in the payoff distribution among cooperators or mutualists: the cleaner fish case. Ecol Lett. 2002; 5(1):130–36. https://doi.org/10.1046/j.1461-0248.2002.00295.x

Buechel SD, Boussard A, Kotrschal A, van der Bijl W, Kolm N. Brain size affects performance in a reversal-learning test. Proc R Soc B. 2018; 285(1871):20172031. https://doi.org/10.1098/rspb.2017.2031

Butler AB, Hodos W. Comparative vertebrate neuroanatomy: evolution and adaptation. 2nd ed. Hoboken: Wiley-Interscience; 2005. https://doi.org/10.1002/0471733849

Capra LG, Bennemann ST. Low feeding overlap between Plagioscion squamosissimus (Heckel, 1840) and Cichla monoculus (Spix & Agassiz, 1831), fishes introduced in tropical reservoir of South Brazil. Biol Limnol. 2009; 21(3):343–48.

Carleton KL, Kocher TD. Cone opsin genes of African cichlid fishes: tuning spectral sensitivity by differential gene expression. Mol Biol Evol. 2001; 18(8):1540–50. https://doi.org/10.1093/oxfordjournals.molbev.a003940

Carleton KL, Spady TC, Streelman JT, Kidd MR, McFarland WN, Loew ER. Visual sensitivities tuned by heterochronic shifts in opsin gene expression. BMC Biol. 2008; 6(1):22. https://doi.org/10.1186/1741-7007-6-22

Carvalho TL, Ferreira EA, Pelicice FM, Fernandes R. Comparative functional responses predict the predatory impact of the highly invasive fish Cichla kelberi. Hydrobiologia. 2021; 848(9):2203–11. https://doi.org/10.1007/s10750-020-04440-6

Chamon CC, Pereira TNA, Mendonça MB, Akama A. New species of the genus Spectracanthicus (Loricariidae, Hypostominae, Ancistrini) from the Rio Javaés (Rio Araguaia basin), with a description of gross brain morphology. J Fish Biol. 2018; 92(2):438–51. https://doi.org/10.1111/jfb.13526

Chamon CC, Serra JP, Camelier P, Zanata AM, Fichberg I, Marinho MMF. Building knowledge to save species: 20 years of ichthyological studies in the Tocantins-Araguaia River basin. Biota Neotrop. 2022; 22(2):e20211296. https://doi.org/10.1590/1676-0611-bn-2021-1296

Dalton BE, Cronin TW, Marshall NJ, Carleton KL. The fish eye view: are cichlids conspicuous? J Exp Biol. 2010; 213(13):2243–55. https://doi.org/10.1242/jeb.037671

Ebbesson LOE, Braithwaite VA. Environmental effects on fish neural plasticity and cognition. J Fish Biol. 2012; 81(7):2151–74. https://doi.org/10.1111/j.1095-8649.2012.03486.x

Espíndola VC, Tencatt LFC, Pupo FM, Villa-Verde L, Britto MR. From the inside out: a new species of armoured catfish Corydoras with the description of poorly-explored character sources (Teleostei, Siluriformes, Callichthyidae). J Fish Biol. 2018; 92(5):1463–86. https://doi.org/10.1111/jfb.13602

Fernandes R, Pelicice FM, Ferreira EA, Menezes CWF, Tavares VNS. The effect of turbidity on predator-prey interactions between invasive fish species. Environ Biol Fishes. 2025; 108(10):1503–13. https://doi.org/10.1007/s10641-025-01741-4

Finger TE, Morita Y. Two gustatory systems: facial and vagal gustatory nuclei have different brainstem connections. 1985; 227(4688):776–78. https://doi.org/10.1126/science.3969566

Franco ACS, García-Berthou E, Santos LN. Ecological impacts of an invasive top predator fish across South America. Sci Total Environ. 2021; 761:143296. https://doi.org/10.1016/j.scitotenv.2020.143296

Franco ACS, Lorini ML, Minsky EMC, Figueiredo MSL, Santos LN. Far beyond the Amazon: global distribution, environmental suitability, and invasive potential of the two most introduced peacock bass. Biol Invasions. 2022a; 24(9):2851–72. https://doi.org/10.1007/s10530-022-02814-6

Franco ACS, Petry AC, Tavares MR, Guimarães TFR, Santos LN. Global distribution of the South American peacock basses Cichla spp. follows human interference. Fish Fish. 2022b; 23(2):407–21. https://doi.org/10.1111/faf.12624

Fugi R, Luz-Agostinho, Karla DG, Agostinho AA. Trophic interaction between an introduced (peacock bass) and a native (dogfish) piscivorous fish in a Neotropical impounded river. Hydrobiologia. 2008; 607:143–50. https://doi.org/10.1007/s10750-008-9384-2

Gaspar MRC, Agostinho AA, Catelani PA, Fernandes R, Franco ACS, Novaes JLC et al. Phenotypic and behavioral variation as a mechanism behind the invasive potential of a predatory neotropical fish. Hydrobiologia. 2024; 852:2133–47. https://doi.org/10.1007/s10750-024-05663-7

Gignac GE, Bates TC. Brain volume and intelligence: the moderating role of intelligence measurement quality. Intelligence. 2017; 64:18–29. https://doi.org/10.1016/j.intell.2017.06.004

Gilbert MC, Akama A, Fernandes CC, Albertson RC. Rapid morphological change in multiple cichlid ecotypes following the damming of a major clearwater river in Brazil. Evol Appl. 2020; 13(10):2754–71. https://doi.org/10.1111/eva.13080

Gomiero LM, Braga FMS. Cannibalism as the main feeding behavior of tucunares introduced in southeast Brazil. Braz J Biol. 2004; 64(3):625–32. https://doi.org/10.1590/S1519-69842004000400009

Gotelli NJ, Ellison AM. A primer of ecological statistics. Vol. 1. 2nd ed. Sunderland, MA: Sinauer Associates; 2013.

Guedes GHS, Franco ACS, Santos LN, Santos AFGN, Araújo FG. Cannibalism facilitates and sustains the invasion of top-predator fish (Cichlidae: Cichla) in human-modified ecosystems. Freshw Biol. 2024; 69(7):1001–15. https://doi.org/10.1111/fwb.14261

Huber R, Van Staaden MJ, Kaufman LS, Liam KF. Microhabitat use, trophic patterns, and the evolution of brain structure in African cichlids. Brain Behav Evol. 1997; 50:167–82.

Jerison HJ. Evolution of the brain and intelligence. New York and London: Academic Press. 1973.

Jerison HJ. Animal intelligence as encephalization. Philos Trans R Soc Lond. 1985; 308(1135):21–35. https://doi.org/10.1098/rstb.1985.0007

Kandel ER, Spencer WA. Cellular neurophysiological approaches in the study of learning. Physiol Rev. 1968; 48(1):65–134. https://doi.org/10.1152/physrev.1968.48.1.65

Khaleel AG, Ismail N, Ahmad-Syazni K. Introduction of invasive peacock bass (Cichla spp.), its rapid distribution and future impact on freshwater ecosystem in Malaysia. Ribarstvo, Croatian J Fish. 2021; 79(1):33–46. https://doi.org/10.2478/cjf-2021-0004

Kotrschal A, Deacon AE, Magurran AE, Kolm N. Predation pressure shapes brain anatomy in the wild. Evol Ecol. 2017; 31(5):619–33. https://doi.org/10.1007/s10682-017-9901-8

Kullander SO, Ferreira EJG. A review of the South an American cichlid genus Cichla, with descriptions of nine new species (Teleostei: Cichlidae). Ichthyol Explor Freshw. 2006; 17(2):185–92.

Leal LB, Hoeinghaus DJ, Compson ZG, Agostinho AA, Fernandes R, Pelicice FM. Changes in ecosystem functions generated by fish populations after the introduction of a non-native predator (Cichla kelberi) (Perciformes: Cichlidae). Neotrop Ichthyol. 2021; 19(3):e210041. https://doi.org/10.1590/1982-0224-2021-0041

Leão-Reis R, Magalhães KX, Pereira TNA, Muriel-Cunha J, Akama A. Neuroanatomical diversity in Teleocichla with new volumetric and histological insights into the encephalon of Teleocichla monogramma Kullander, 1988. Anat Rec. 2025; 1–16. https://doi.org/10.1002/ar.70095

Lehtonen TK, Candolin U, Wong BBM. Environmental variation promotes colour morph-specific behavioural differences in a cichlid fish. Anim Behav. 2023; 197:123–30. https://doi.org/10.1016/j.anbehav.2023.01.005

Lisney TJ, Collin SP. Brain morphology in large pelagic fishes: a comparison between sharks and teleosts. J Fish Biol. 2006; 68(2):532–54. https://doi.org/10.1111/j.0022-1112.2006.00940.x

Liu M, Liu Y, Wang X, Wang H. Brain morphological adaptations of Gambusia affinis along climatic gradients in China. J Zool Syst Evol Res. 2021; 59(8):2150–60. https://doi.org/10.1111/jzs.12544

Maan ME, Sefc KM. Colour variation in cichlid fish: developmental mechanisms, selective pressures and evolutionary consequences. Semin Cell Dev Biol. 2013; 24(6–7):516–28. https://doi.org/10.1016/j.semcdb.2013.05.003

Marinho MMF. Ontogeny of the skeleton of Moenkhausia pittieri (Ostariophysi: Characiformes) with discussion on functional demands and ossification patterns in the Characidae. Zool J Linn Soc. 2023; 197(2):474–513. https://doi.org/10.1093/zoolinnean/zlac029

Marinho-Nunes PH, Amui GSC, Gomes JF, Silva AS, Pereira TNA. Synthesis of studies on comparative brain morphology in freshwater fishes in Brazil: a 25-year review. Pap Avulsos Zool. 2025a; 65:e202565023. https://doi.org/10.11606/1807-0205/2025.65.023

Marinho-Nunes PH, Amui GSC, Pereira TNA. Protocol for encephalon extraction of cichlids for morphological studies (Teleostei: Percomorpha: Cichliformes). Zoomorphology. 2025b; 144(3):1–13. https://doi.org/10.1007/s00435-025-00750-2

Marto VCO, Akama A, Pelicice FM. Feeding and reproductive ecology of Cichla piquiti Kullander & Ferreira, 2006 within its native range, Lajeado reservoir, rio Tocantins basin. Neotrop Ichthyol. 2015; 13(3):625–36. https://doi.org/10.1590/1982-0224-20140165

Meek J, Nieuwenhuys R. Holosteans and Teleosts. In: The central nervous system of vertebrates. 1st ed. New York: Springer Science & Business Media; 1998. p.759–937. https://doi.org/10.1007/978-3-642-18262-4_15

Morita Y, Finger TE. Reflex connections of the facial and vagal gustatory systems in the brainstem of the bullhead catfish, Ictalurus nebulosus. J Comp Neurol. 1985; 231(4):547–58. https://doi.org/10.1002/cne.902310411

Neal JW, Bies JM, Fox CN, Lilyestrom CG. Evaluation of proposed speckled peacock bass Cichla temensis introduction to Puerto Rico. N Am J Fish Manag. 2017; 37(5):1093–106. https://doi.org/10.1080/02755947.2017.1345806

Nieuwenhuys R. Comparative anatomy of olfactory centres and tracts. Prog Brain Res. 1966; 23:1–64. https://doi.org/10.1016/S0079-6123(08)60662-7

Nieuwenhuys R, ten Donkelaae HJ, Nicholson C. The central nervous system of vertebrates. 1st ed. New York: Springer Science & Business Media; 1998. https://doi.org/10.1007/978-3-642-18262-4

Nobile AB, Azevedo-Santos VM, Soares CL, Manzano FV, Oliveira C, Lima FP. Ichthyofauna of the Marimbondinho River, Furnas reservoir, Minas Gerais, Brazil. Oecol Austr. 2024; 28(1):71–80. https://doi.org/10.4257/oeco.2024.2801.07

Northcutt RG. Evolution of the vertebrate central nervous system: patterns and processes. Integr Comp Biol. 1984; 24(3):701–16. https://doi.org/10.1093/icb/24.3.701

Novakowski GC, Cassemiro FAS, Hahn NS. Diet and ecomorphological relationships of four cichlid species from the Cuiabá River basin. Neotrop Ichthyol. 2016; 14(3):e150151. https://doi.org/10.1590/1982-0224-20150151

Oliveira RC, Graça WJ. Encephalon gross morphology of the cichlid Geophagus sveni (Cichlidae: Geophagini): comparative description and ecological perspectives. J Fish Biol. 2020; 97(5):1363–74. https://doi.org/10.1111/jfb.14495

Oliveira RC, Graça WJ. Evolutionary trends in encephalic morphology among Geophagini cichlid fish: phylogenetic insights and associations with ecological and behavioral traits. Hydrobiologia. 2024; 851(15):3711–34. https://doi.org/10.1007/s10750-024-05531-4

Pelicice FM, Agostinho AA. Fish fauna destruction after the introduction of a non-native predator (Cichla kelberi) in a Neotropical reservoir. Biol Invasions. 2009; 11(8):1789–801. https://doi.org/10.1007/s10530-008-9358-3

Pelicice FM, Andrade GS, Borges LEO. Polychromatism in native populations of peacock basses Cichla kelberi and Cichla piquiti (Cichlidae). Environ Biol Fishes. 2022; 105(8):1129–37. https://doi.org/10.1007/s10641-022-01313-w

Peñaherrera Aguirre M, Fernandes HB, Woodley of Menie MA. Relative brain size, encephalization quotient. Encyclopedia of Evolutionary Psychological Science. Cham: Springer International Publishing; 2021. p.6560–62. https://doi.org/10.1007/978-3-319-19650-3_3098

Pereira TNA, Castro RMC. The brain of Brycon orbignyanus (Valenciennes, 1850) (Teleostei: Characiformes: Bryconidae): gross morphology and phylogenetic considerations. Neotrop Ichthyol. 2016; 14(3):e150051. https://doi.org/10.1590/1982-0224-20150051

Pike TW, Ramsey M, Wilkinson A. Environmentally induced changes to brain morphology predict cognitive performance. Philos Trans R Soc B. 2018; 373(1756):20170287. https://doi.org/10.1098/rstb.2017.0287

Reiss P, Able KW, Nunes MS, Hrbek T. Color pattern variation in Cichla temensis (Perciformes: Cichlidae): resolution based on morphological, molecular, and reproductive data. Neotrop Ichthyol. 2012; 10(1):59–70. https://doi.org/10.1590/S1679-62252012000100006

Ribeiro F, Orjuela RL, Magalhães MF, Collares-Pereira MJ. Variability in feeding ecology of a South American cichlid: a reason for successful invasion in mediterranean-type rivers? Ecol Freshw Fish. 2007; 16(4):559–69. https://doi.org/10.1111/j.1600-0633.2007.00252.x

Rosa AC, Martins FO, Langeani F. Gross brain morphology of Hypoptopomatinae and Neoplecostominae (Siluriformes: Loricariidae): comparative anatomy and phylogenetic implications. J Zool Syst Evol Res. 2021; 59(1):111–47. https://doi.org/10.1111/jzs.12424

Roth G, Dicke U. Evolution of the brain and intelligence. Trends Cogn Sci. 2005; 9(5):250–57. https://doi.org/10.1016/j.tics.2005.03.005

RStudio Team. RStudio: integrated development environment for R. RStudio. 2022.

Sastraprawira SM, Iqbal IH, Shahimi S, Pati S, Edinur HA, John AB et al. A review on introduced Cichla spp. and emerging concerns. Heliyon. 2020; 6(11):e05370. https://doi.org/10.1016/j.heliyon.2020.e05370

Sharpe DMT, De León LF, González R, Torchin ME. Tropical fish community does not recover 45 years after predator introduction. Ecology. 2017; 98(2):412–24. https://doi.org/10.1002/ecy.1648

Shettleworth SJ. Animal cognition and animal behaviour. Anim Behav. 2001; 61(2):277–86. https://doi.org/10.1006/anbe.2000.1606

Shumway CA. The evolution of complex brains and behaviors in African cichlid fishes. Curr Zool. 2010; 56(1):144–56. https://doi.org/10.1093/czoolo/56.1.144

Siepen G, Caprona M-Dominique C. The influence of parental color morph on mate choice in the cichlid fish Cichlasoma nigrofasciatum. Ethology. 1986; 71(3):187–200. https://doi.org/10.1111/j.1439-0310.1986.tb00583.x

Sol D, Duncan RP, Blackburn TM, Cassey P, Lefebvre L. Big brains, enhanced cognition, and response of birds to novel environments. PNAS. 2005a; 102(15):5460–65. https://doi.org/10.1073/pnas.0408145102

Sol D, Lefebvre L, Rodríguez-Teijeiro JD. Brain size, innovative propensity and migratory behaviour in temperate Palaearctic birds. Proc R Soc B. 2005b; 272(1571):1433–41. https://doi.org/10.1098/rspb.2005.3099

Souza CP, Rodrigues-Filho CAS, Barbosa FAR, Leitão RP. Drastic reduction of the functional diversity of native ichthyofauna in a neotropical lake following invasion by piscivorous fishes. Neotrop Ichthyol. 2021; 19(3):e210033. https://doi.org/10.1590/1982-0224-2021-0033

Van Staaden MJ, Huber R, Kaufman LS, Liem KF. Brain evolution in cichlids of the African Great Lakes: Brain and body size, general patterns, and evolutionary trends. Zoology. 1995; 98(3):165–78.

Striedter GF. Principles of brain evolution. Sunderland: Sinauer Associates; 2005.

Sturges HA. The choice of a class interval. J Am Stat Assoc. 1926; 21(153):65–66.

Triki Z, Aellen M, van Schaik CP, Bshary R. Relative brain size and cognitive equivalence in fishes. Brain Behav Evol. 2021; 96(3):124–36. https://doi.org/10.1159/000520741

Triki Z, Fong S, Amcoff M, Kolm N. Artificial mosaic brain evolution of relative telencephalon size improves inhibitory control abilities in the guppy (Poecilia reticulata). Evolution. 2022a; 76(1):128–38. https://doi.org/10.1111/evo.14405

Triki Z, Granell-Ruiz M, Fong S, Amcoff M, Kolm N. Brain morphology correlates of learning and cognitive flexibility in a fish species (Poecilia reticulata). Proc R Soc B. 2022b; 289(1978). https://doi.org/10.1098/rspb.2022.0844

Triki Z, Wismer S, Levorato E, Bshary R. A decrease in the abundance and strategic sophistication of cleaner fish after environmental perturbations. Glob Chang Biol. 2018; 24(1):481–89. https://doi.org/10.1111/gcb.13943

Valverde MP, Sharpe DMT, Torchin ME, Buck DG, Chapman LJ. Trophic shifts in a native predator following the introduction of a top predator in a tropical lake. Biol Invasions. 2020; 22(2):643–61. https://doi.org/10.1007/s10530-019-02119-1

Waibl H, Gasse H, Constantinescu GM, Hashimoto G, Simoens P. Nomina anatomica veterinaria. 5th revised ed. Hannover: Editorial Committee of the World Association of Veterinary Anatomists; 2012.

White GE, Brown C. Variation in brain morphology of intertidal gobies: A comparison of methodologies used to quantitatively assess brain volumes in fish. Brain Behav Evol. 2015; 85(4):245–56. https://doi.org/10.1159/000398781

Willis SC, Macrander J, Farias IP, Ortí G. Simultaneous delimitation of species and quantification of interspecific hybridization in Amazonian peacock cichlids (genus Cichla) using multi-locus data. BMC Evol Biol. 2012; 12:96. https://doi.org/10.1186/1471-2148-12-96

Winemiller KO, Winemiller LCK, Montaña CG. Peacock Bass: diversity, ecology and conservation. London: Academic Press; 2021. https://doi.org/10.1016/C2020-0-01799-8

Wismer S, Pinto AI, Vail AL, Grutter AS, Bshary R. Variation in cleaner wrasse cooperation and cognition: influence of the developmental environment? Ethology. 2014; 120(6):519–31. https://doi.org/10.1111/eth.12223

Authors

---

Pedro Henrique Marinho-Nunes¹ , Thiago Nilton Alves Pereira² and Fernando Mayer Pelicice³

^[1]    Programa de Pós-Graduação em Zoologia, Laboratório de Ecologia e Conservação, Instituto de Ciências Biológicas da Universidade Federal do Pará, Rua Augusto Corrêa, 01, 66075-110, Guamá, Belém, PA, Brazil. pedromarino2001@gmail.com (corresponding author).

^[2]    Programa de Pós-Graduação em Biodiversidade, Ecologia e Conservação, Laboratório de Ictiologia Sistemática da Universidade Federal do Tocantins, S. Jardim dos Ipês 2, 77500-000, Porto Nacional, TO, Brazil. thiago.na@mail.uft.edu.br.

^[3]    Programa de Pós-Graduação em Biodiversidade, Ecologia e Conservação, Laboratório de Ecologia da Universidade Federal do Tocantins, S. Jardim dos Ipês 2, Porto Nacional, TO, Brazil. fmpelicice@gmail.com.

Authors’ Contribution

---

Pedro Henrique Marinho-Nunes: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing-original draft, Writing-review and editing.

Thiago Nilton Alves Pereira: Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing-original draft, Writing-review and editing.

Fernando Mayer Pelicice: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Software, Validation, Writing-original draft, Writing-review and editing.

Ethical Statement​

---

All procedures were conducted in compliance with ethical and legal requirements, under approval of the Ethics Committee on Animal Use and Experimentation of the Universidade Federal de Tocantins (CEUA/UFT, protocol 23.101.001.818/2019–25) and with collection authorized by ICMBio (license number 270453; responsible researcher: Dr. Paulo H. F. Lucinda).

Competing Interests

---

The author declares no competing interests.

Data availability statement

---

The data supporting the findings of this study are available from the corresponding author, upon reasonable request.

AI statement

---

The authors state that Copilot (version GPT‑5, Smart Mode) was employed for grammar checking of the manuscript.

Funding

---

PHMN is supported by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Proc. 88887.950265/2024–00, and by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Proc. 140633/2025–1. TNAP is supported by CNPq Universal, Proc. 425484/2018–1, and FMP is supported by CNPq research grants, Proc. 309025/2023–0.

How to cite this article

---

Marinho-Nunes PH, Pereira TNA, Pelicice FM. Brain morphology of native and invasive Cichla piquiti, the blue peacock bass (Cichliformes: Cichlidae), with ecomorphological insights. Neotrop Ichthyol. 2026; 24(1):e250198. https://doi.org/10.1590/1982-0224-2025-0198

Copyright​

---

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Distributed under

Creative Commons CC-BY 4.0

© 2025 The Authors.

Diversity and Distributions Published by SBI

Accepted December 28, 2025

Submitted November 16, 2025

Epub April 27, 2026