کشف روندهای فعلی و شناسایی مسیرهای پژوهشی آینده در علوم اعصاب

Purpose: Neuroscience, a field characterized by its vast scope and thematic diversity, requires systematic efforts to map its conceptual structure and analyze evolving research trends. A lack of clarity in these areas risks misallocation of resources and the perpetuation of redundant studies. This study addresses this gap by employing bibliometric methods to identify the conceptual architecture of neuroscience, pinpoint emerging subdomains, and evaluate critical dimensions within the Clarivate Analytics database. The primary objectives are to delineate the intellectual landscape of neuroscience research and highlight its interdisciplinary potential to guide future scientific inquiry.
Methodology: This applied research integrates co-word and network analysis to examine four decades of neuroscience literature (1985–2024). Data were extracted from Clarivate Analytics on February 24, 2025, using a targeted search strategy with MeSH descriptors in the title fields, including terms such as:
TI=(Neurosciences) OR TI= (Cognitive Neuroscience) OR TI=(Neuroanatomy) OR TI=(Neurobiology) OR TI=(Neurochemistry) OR TI=(Neuroendocrinology) OR TI=(Neuropathology) OR TI=(Neuropharmacology) OR TI=(Neurophysiology)
The search yielded 19,701 documents containing 69,740 author keywords, which were standardized to 27,529 unique terms after deduplication and normalization. Analytical tools such as VOSviewer, UCINET, and BibExcel were employed for data processing. A symmetric matrix was generated in BibExcel, transformed into a correlation matrix, and filtered using a threshold of 38 to produce a 188 × 188 matrix (with diagonal values set to zero). Cluster analysis using the K-means method in VOSviewer visualized the co-occurrence network, while UCINET was used to calculate network metrics.
Findings: The findings revealed a general growth trend in neuroscience publications, although a decline was observed in recent years. Keyword analysis identified neuroscience, Alzheimer's disease, and neuropathology as the most frequent terms, with neuroscience serving as the field's conceptual anchor. Cluster analysis uncovered six thematic groups: Neurotransmitters (1), Cognitive Disorders (2), Cognitive Neuroscience (3), Neural Connections (4), Neuromarketing (5), and Pain and Neurodevelopmental Disorders (6). Among these, Cognitive Disorders (2) demonstrated the highest centrality, reflecting their broad interdisciplinary influence and connectivity within the research network, while Pain and Neurodevelopmental Disorders (6) exhibited the highest density, indicating strong intra-cluster cohesion. Strategic diagram analysis positioned Cognitive Disorders (2) and Cognitive Neuroscience (3) as dominant, cohesive themes occupying the network's core due to their extensive linkages and centrality. In contrast, Neuromarketing (5) and Pain and Neurodevelopmental Disorders (6) occupied peripheral positions, representing specialized but less influential niches. Neural Connections (4) emerged as a rapidly evolving subfield, whereas Neurotransmitters (1) resided in the fourth quadrant, signaling untapped potential for future development despite its current underrepresentation.
Conclusion: The study concludes that the dynamism of neuroscience stems from its interdisciplinary nature, with a significant capacity to drive innovation across medicine, education, marketing, and spatial design. The centrality of cognitive disorders and cognitive neuroscience underscores their foundational role, combining high cohesion, cross-disciplinary influence, and conceptual interconnectedness. These clusters dominate the research network and exhibit robust internal synergy, enabling them to address complex questions such as the mechanisms of neurodegenerative diseases and models of cognitive processing. Meanwhile, emerging areas like neural connectivity and neuromarketing underscore the field's expansion into novel domains, facilitated by advanced machine learning and neuroimaging methodologies. The increasing adoption of hybrid analytical tools—particularly within these clusters—reflects a broader shift toward integrating computational and experimental paradigms in neuroscience research. The results highlight how neuroscience connects traditional disciplines with innovative applications. For example, its intersection with medicine advances diagnostic tools for conditions such as Alzheimer's disease, while collaborations with marketing explore consumer behavior through neuromarketing frameworks. Similarly, linkages with spatial design and education demonstrate neuroscience’s potential to optimize learning environments and urban planning through neuroscientific insights. However, the study identifies gaps in underdeveloped areas, such as neurotransmitter research, which remains underrepresented despite its fundamental importance and warrants targeted investment to unlock its transformative potential. Strategic diagram analysis reinforces the importance of modern, data-driven approaches in parsing neuroscience's complexity. The convergence of diverse methodologies—from bibliometric mapping to network analysis—enables researchers to navigate the extensive literature and identify highly influential trajectories. This integrative approach reduces redundancy and fosters innovation by highlighting underserved niches, such as neurodevelopmental disorders, and emerging frontiers, such as neural connectivity. This study maps the conceptual evolution of neuroscience, highlighting its dual focus on established domains and emerging innovations. By delineating clusters of influence, cohesion, and growth, it provides a roadmap for prioritizing research efforts, fostering interdisciplinary collaboration, and leveraging advanced tools to address pressing scientific and societal challenges. The findings affirm neuroscience's role as a catalyst for breakthroughs across sectors—from healthcare to technology—while emphasizing the need for sustained investment in both its core pillars and emerging frontiers.