Research: HPCN Pillar
Research Lines of the HPCN Pillar
CRAI develops integrated scientific frameworks for the study of biological regulation, human–environment coevolution, and neurobiological variability.
Regulation · Coevolution · Neurodiversity · Phytochemical Matrices
CRAI’s research lines converge in the analysis of interdependent biological systems whose stability and variability emerge from contextual regulatory dynamics.
The centre examines how human profiles are configured and transformed through continuous interaction with ecological and phytochemical matrices, understanding regulation as a dynamic and environment-dependent process.
Research integrates neurobiology, evolutionary ecology, and the analysis of complex plant matrices within a unified methodological architecture aimed at modelling functional configurations rather than isolated entities.
This shared framework enables the interpretation of behavioural and cognitive fluctuations as expressions of dynamic regulatory states, ensuring conceptual coherence and interdisciplinary projection.
Evolutionary bases of human-plant interaction
This research line examines the historical-evolutionary interaction between human systems and complex plant matrices.
It analyses how the co-configuration between human neurobiology and phytochemical environments has influenced regulatory, cognitive, and adaptive processes throughout evolution.
Its objective is to develop a conceptual framework that enables the understanding of human–plant modulation within dynamic ecological contexts, with projection toward individualised, systems-based approaches.
Key words:
Human–plant coevolution; Evolutionary biology; Neurobiological regulation; Complex phytochemistry; Functional ecology; Adaptive systems; Neurodiversity.
This line is developed through specific projects focused on analyzing human–plant modulation within complex evolutionary and regulatory contexts.
Flagship project:
Sustainability and Ecological Modulation of Medicinal Plants
This research line examines how ecological conditions influence the configuration of complex phytochemical systems in medicinal plants.
It studies the relationship between environmental variability and metabolic dynamics in order to identify the ecological determinants of functional phytochemical profiles.
The approach integrates ecophysiology, sustainability, and systemic regulation to develop production models that are biologically and environmentally coherent.
Key words:
Functional ecology; Mycorrhizal interactions; Biotic and abiotic stress; Plant metabolomics; Environmental variability; Phytochemical systems; Regenerative agriculture.
This line is articulated through projects focused on developing agrobiotechnological strategies aimed at enhancing the stability and functional coherence of phytochemical matrices in medicinal plants.
Flagship project:
Dynamics of Regulation and Resilience in Complex Plant Systems
This research line examines the role of medicinal plants within the dynamics of ecosystem resilience and environmental adaptation.
It analyses how ecologically informed management of plant systems can contribute to the functional stability of productive landscapes and restored environments.
The line integrates principles of evolutionary ecology and ecological regulation to develop models linking biodiversity, environmental variability, and long-term biological coherence.
Key words:
Ecosystem resilience; Evolutionary ecology; Functional biodiversity; Ecological restoration; Plant systems; Environmental variability; Agroecology.
This line is developed through projects focused on ecological adaptation and the regeneration of plant systems in response to climate variability and environmental pressure.
Flagship project:
Strategic Projection
These research lines converge in the development of integrated models aimed at understanding human variability and ecological interactions as expressions of evolutionarily configured regulatory dynamics. Their articulation enables the projection of coherent interpretative frameworks with the potential to generate long-term scientific, environmental, and conceptual applications.
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