Calcium as a Trigger and Regulator of Systemic Alarms and Signals along the Phloem Pathway

Do plants pay attention? A possible phenomenological-empirical approach

Attention is the important ability of flexibly controlling limited cognitive resources. It ensures that organisms engage with the activities and stimuli that are relevant to their survival. Despite the cognitive capabilities of plants and their complex behavioural repertoire, the study of attention in plants has been largely neglected. In this article, we advance the hypothesis that plants are endowed with the ability of attaining attentive states. We depart from a transdisciplinary basis of philosophy, psychology, physics and plant ecophysiology to propose a framework that seeks to explain how plant attention might operate and how it could be studied empirically. In particular, the phenomenological approach seems particularly important to explain plant attention theoretically, and plant electrophysiology seems particularly suited to study it empirically. We propose the use of electrophysiological techniques as a viable way for studying it, and we revisit previous work to support our hypothesis. We conclude this essay with some remarks on future directions for the study of plant attention and its implications to botany.

Osmotic stress decreases complexity underlying the electrophysiological dynamic in soybean

Studies on plant electrophysiology are mostly focused on specific traits of single cells. Inspired by the complexity of the signalling network in plants, and by analogy with neurons in human brains, we sought evidence of high complexity in the electrical dynamics of plant signalling and a likely relationship with environmental cues. An EEG-like standard protocol was adopted for high-resolution measurements of the electrical signal in Glycine max seedlings. The signals were continuously recorded in the same plants before and after osmotic stimuli with a -2 MPa mannitol solution. Non-linear time series analyses methods were used as follows: auto-correlation and cross-correlation function, power spectra density function, and complexity of the time series estimated as Approximate Entropy (ApEn). Using Approximate Entropy analysis we found that the level of temporal complexity of the electrical signals was affected by the environmental conditions, decreasing when the plant was subjected to a low osmotic potential. Electrical spikes observed only after stimuli followed a power law distribution, which is indicative of scale invariance. Our results suggest that changes in complexity of the electrical signals could be associated with water stress conditions in plants. We hypothesised that the power law distribution of the spikes could be explained by a self-organised critical state (SOC) after osmotic stress.