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Xu S, Ma X, Xiao Y, Zhang T, Ma C, Ma Z. 7,8-DHF Modulates Aggressive Behavior in Sebastes schlegelii: Phenotype-Dependent Responses in Aggression-Dimorphic Individuals. Animals (Basel) 2025; 15:1463. [PMID: 40427340 PMCID: PMC12108537 DOI: 10.3390/ani15101463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2025] [Revised: 05/13/2025] [Accepted: 05/14/2025] [Indexed: 05/29/2025] Open
Abstract
Aggressive behavior is regulated by intricate neural circuits and molecular mechanisms, notably through the interaction of brain-derived neurotrophic factor (BDNF) with its receptor, tropomyosin receptor kinase B (TrkB), which influences neuroplasticity and related behavioral phenotypes. We investigate the role of the BDNF signaling pathway in fish aggression using juvenile black rockfish (Sebastes schlegelii), which exhibit distinct aggressive phenotypes. The TrkB agonist 7,8-dihydroxyflavone (7,8-DHF) was administered intraperitoneally at doses of 1.25, 2.5, and 5 mg/kg to assess its effects on the behavioral characteristics of high-aggression (H-agg) and low-aggression (L-agg) phenotypes. Our findings indicate the following: (1) The effects of 7,8-DHF are dose-dependent, with 2.5 mg/kg identified as the effective threshold dose for H-agg individuals; (2) in the H-agg group, this dose significantly reduced locomotor acceleration, angular velocity, and activity frequency, while prolonging the first movement latency; (3) in the L-agg group, only angular velocity was significantly decreased with the 2.5 mg/kg treatment, with no significant changes observed in other behavioral parameters. This study provides the first evidence for differential behavioral responses to 7,8-DHF in S. schlegelii, demonstrating dose-dependent aggression suppression in H-agg phenotypes and threshold-specific responses in L-agg phenotypes. These insights into the neuro-molecular basis of fish aggression can guide phenotype-specific management in aquaculture, potentially improving stress management, reducing injuries and mortality, and boosting productivity.
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Affiliation(s)
- Shufei Xu
- Key Laboratory of Environment Controlled Aquaculture, Ministry of Education, Dalian 116023, China; (S.X.); (X.M.); (Y.X.)
- College of Marine Technology and Environment, Dalian Ocean University, Dalian 116023, China
| | - Xinna Ma
- Key Laboratory of Environment Controlled Aquaculture, Ministry of Education, Dalian 116023, China; (S.X.); (X.M.); (Y.X.)
- College of Marine Technology and Environment, Dalian Ocean University, Dalian 116023, China
| | - Yang Xiao
- Key Laboratory of Environment Controlled Aquaculture, Ministry of Education, Dalian 116023, China; (S.X.); (X.M.); (Y.X.)
- College of Marine Technology and Environment, Dalian Ocean University, Dalian 116023, China
| | - Tao Zhang
- Tianzheng Industrial Co., Ltd., Dalian 116021, China;
| | - Chao Ma
- State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116081, China;
| | - Zhen Ma
- Key Laboratory of Environment Controlled Aquaculture, Ministry of Education, Dalian 116023, China; (S.X.); (X.M.); (Y.X.)
- College of Fisheries and Life Science, Dalian Ocean University, Dalian 116023, China
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Haimson B, Mizrahi A. Integrating innate and learned behavior through brain circuits. Trends Neurosci 2025; 48:319-329. [PMID: 40169295 DOI: 10.1016/j.tins.2025.03.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2024] [Revised: 02/28/2025] [Accepted: 03/07/2025] [Indexed: 04/03/2025]
Abstract
Understanding how innate predispositions and learned experiences interact to shape behavior is a central question in systems neuroscience. Traditionally, innate behaviors, that is, those present without prior learning and governed by evolutionarily conserved neural circuits, have been studied separately from learned behaviors, which depend on experience and neural plasticity. This division has led to a compartmentalized view of behavior and neural circuit organization. Increasing evidence suggests that innate and learned behaviors are not independent, but rather deeply intertwined, with plasticity evident even in circuits classically considered 'innate'. In this opinion, we highlight examples across species that illustrate the dynamic interaction between these behavioral domains and discuss the implications for unifying theoretical and empirical frameworks. We argue that a more integrative approach, namely one that acknowledges the reciprocal influences of innate and learned processes, is essential for advancing our understanding of how neuronal activity drives complex behaviors.
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Affiliation(s)
- Baruch Haimson
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Adi Mizrahi
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel; Department of Life Sciences, The Hebrew University of Jerusalem, Israel.
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Borland JM. A review of the effects of different types of social behaviors on the recruitment of neuropeptides and neurotransmitters in the nucleus accumbens. Front Neuroendocrinol 2025; 77:101175. [PMID: 39892577 DOI: 10.1016/j.yfrne.2025.101175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2024] [Revised: 01/25/2025] [Accepted: 01/26/2025] [Indexed: 02/04/2025]
Abstract
There is a lack of understanding of the neural mechanisms regulating the rewarding effects of social interactions. A significant contributor to this lack of clarity is the diversity of social behaviors and animal models utilized to investigate mechanisms. Other sources of the lack of clarity are the diversity of brain regions that can regulate social reward and the diversity of signaling pathways that regulate reward. To provide some clarity into the mechanisms of social reward, this review focused on the brain region most implicated in reward for multiple stimuli, the nucleus accumbens, and surveyed (systematically reviewed) studies that investigated the relationship between social interaction and five signaling systems implicated in the regulation of reward and social behavior: oxytocin, vasopressin, serotonin, opioids and endocannabinoids. Moreover, all of these studies were organized by the type of social behavior studied: affiliative interactions, play behavior, aggression, social defeat, sex behavior, pair-bonding, parental behavior and social isolation. From this survey and organization, this review concludes that oxytocin, endocannabinoids and mu-opioid receptors in the nucleus accumbens positively regulate the rewarding social behaviors, and kappa-opioid receptors negatively regulate the rewarding social behaviors. The opposite profile is observed for these signaling systems for the aversive social behaviors. More studies are needed to investigate the directional role of the serotonin system in the nucleus accumbens in the regulation of many types of social behaviors, and vasopressin likely does not act in the nucleus accumbens in the regulation of the valence of social behaviors. Many of these different signaling systems are also interdependent of one another in the regulation of different types of social behaviors. Finally, the interaction of these signaling systems with dopamine in the nucleus accumbens is briefly discussed.
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Luo S, Zhang S, Ji D, Jiang S, Wang X, Chen B, Chen Y, Pei X, Dai C, Jiang D, Liu W, Yang Y, Song E, Wei D, Kong D, Liu Y, Wei D. A Signal-Harmonizing Hybrid Neural Pathway Enabled by Bipolar-Chemo-Synapse Spiking Interneuron. J Am Chem Soc 2025; 147:10570-10578. [PMID: 40082394 DOI: 10.1021/jacs.5c00198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/16/2025]
Abstract
To realize human-machine fusion, a hybrid neural pathway operating in the same modality with biological systems becomes imperative, which requires an interneuron unit to encode information in biorecognizable spike sequences and tune the frequency upon excitatory and inhibitory neurotransmitters. Existing artificial interneurons cannot encode information upon different neurotransmitters, and the activation threshold and frequency responsivity do not align with those of biological counterparts, leading to limited success in constructing a signal-harmonizing hybrid neural pathway for neuroprosthetics, neurorehabilitation, and other neuroelectronic applications. Herein, we develop a bipolar-chemosynapse interneuron to encode the spike frequency in a highly bionic paradigm. Bipolar synapses dynamically respond to excitatory and inhibitory neurotransmitters and translate time-series chemical signals into the spike sequence, achieving the lowest activation threshold (6.25 μM) and the highest frequency responsivity (0.55 Hz μM-1) to date, close to the biological counterpart. A signal-harmonizing hybrid sensorimotor pathway mediated by excitatory and inhibitory neurotransmitters is constructed for the first time, which encodes upstream mechanical stimuli, modulates the downstream leg swing frequency of a mouse, and balances neural activity accordingly.
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Affiliation(s)
- Shi Luo
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai 200433, China
| | - Shen Zhang
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai 200433, China
| | - Daizong Ji
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai 200433, China
| | - Shuai Jiang
- Shanghai Key Laboratory of Vascular Lesions Regulation and Remodeling, Department of Vascular Surgery, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai 201399, China
| | - Xuejun Wang
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai 200433, China
| | - Bo Chen
- Shanghai Key Laboratory of Vascular Lesions Regulation and Remodeling, Department of Vascular Surgery, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai 201399, China
| | - Yiheng Chen
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai 200433, China
| | - Xinjie Pei
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai 200433, China
| | - Changhao Dai
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai 200433, China
| | - Dingding Jiang
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai 200433, China
| | - Wentao Liu
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai 200433, China
| | - Yuetong Yang
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai 200433, China
| | - Enming Song
- Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and Perception, Institute of Optoelectronics, Fudan University, Shanghai 200433, China
| | - Dapeng Wei
- Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China
| | - Derong Kong
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai 200433, China
| | - Yunqi Liu
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai 200433, China
| | - Dacheng Wei
- State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Fudan University, Shanghai 200433, China
- Laboratory of Molecular Materials and Devices, Fudan University, Shanghai 200433, China
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