Extending cognition: a vegetal rejoinder to extensionless thought and to extended cognition

In this paper, we propose a crucial supplement to the framework of plant cognition, namely extending cognition. We argue that plants and other organisms with an open-ended body plan actively extend their cognition when growing tissues or organs. Their cognition expands with their body expansion. After considering the defining features of extending cognition, we present a model where growth, along with aspects of plant physiology (e.g. biochemical exudates), as well as the "negative extension" of growing away from obstacles or stressful environments, are the building blocks for a more refined understanding of plant cognition. We conclude by outlining the general implications of the theory of extending cognition and indicating directions for future research.

Approximate entropy: a promising tool to understand the hidden electrical activity of fruit

Fruits, like other parts of the plant, appear to have a rich electrical activity that may contain information. Here, we present data showing differences in the electrome complexity of tomato fruits through ripening and discuss possible physiological processes involved. The complexity of the signals, measured through approximate entropy, varied along the fruit ripening process. When analyzing the fruits individually, a decrease in entropy values was observed when they entered the breaker stage, followed by a tendency to increase again when they entered the light red stage. Consequently, the data obtained showed a decrease in signal complexity in the breaker stage, probably due to some physiological process that ends up predominating to the detriment of others. This result may be linked to processes involved in ripening, such as climacteric. Electrophysiological studies in the reproductive stage of the plant are still scarce, and research in this direction is of paramount importance to understand whether the electrical signals observed can transmit information from reproductive structures to other modules of plants. This work opens the possibility of studying the relationship between the electrical activity and fruit ripening through the analysis of approximate entropy. More studies are necessary to understand whether there is a correlation or a cause-response relationship in the phenomena involved. There is a myriad of possibilities for the applicability of this knowledge to different areas, from understanding the cognitive processes of plants to achieving more accurate and sustainable agriculture.

The Electrome of a Parasitic Plant in a Putative State of Attention Increases the Energy of Low Band Frequency Waves: A Comparative Study with Neural Systems

Selective attention is an important cognitive phenomenon that allows organisms to flexibly engage with certain environmental cues or activities while ignoring others, permitting optimal behaviour. It has been proposed that selective attention can be present in many different animal species and, more recently, in plants. The phenomenon of attention in plants would be reflected in its electrophysiological activity, possibly being observable through electrophytographic (EPG) techniques. Former EPG time series obtained from the parasitic plant Cuscuta racemosa in a putative state of attention towards two different potential hosts, the suitable bean (Phaseolus vulgaris) and the unsuitable wheat (Triticum aestivum), were revisited. Here, we investigated the potential existence of different band frequencies (including low, delta, theta, mu, alpha, beta, and gamma waves) using a protocol adapted from neuroscientific research. Average band power (ABP) was used to analyse the energy distribution of each band frequency in the EPG signals, and time dispersion analysis of features (TDAF) was used to explore the variations in the energy of each band. Our findings indicated that most band waves were centred in the lower frequencies. We also observed that C. racemosa invested more energy in these low-frequency waves when suitable hosts were present. However, we also noted peaks of energy investment in all the band frequencies, which may be linked to extremely low oscillatory electrical signals in the entire tissue. Overall, the presence of suitable hosts induced a higher energy power, which supports the hypothesis of attention in plants. We further discuss and compare our results with generic neural systems.

Systemic Signals Induced by Single and Combined Abiotic Stimuli in Common Bean Plants

To survive in a dynamic environment growing fixed to the ground, plants have developed mechanisms for monitoring and perceiving the environment. When a stimulus is perceived, a series of signals are induced and can propagate away from the stimulated site. Three distinct types of systemic signaling exist, i.e., (i) electrical, (ii) hydraulic, and (iii) chemical, which differ not only in their nature but also in their propagation speed. Naturally, plants suffer influences from two or more stimuli (biotic and/or abiotic). Stimuli combination can promote the activation of new signaling mechanisms that are explicitly activated, as well as the emergence of a new response. This study evaluated the behavior of electrical (electrome) and hydraulic signals after applying simple and combined stimuli in common bean plants. We used simple and mixed stimuli applications to identify biochemical responses and extract information from the electrical and hydraulic patterns. Time series analysis, comparing the conditions before and after the stimuli and the oxidative responses at local and systemic levels, detected changes in electrome and hydraulic signal profiles. Changes in electrome are different between types of stimulation, including their combination, and systemic changes in hydraulic and oxidative dynamics accompany these electrical signals.

Ariadne’s thread and the extension of cognition: A common but overlooked phenomenon in nature?

Over recent decades, our philosophical and scientific understanding of cognition has changed dramatically. We went from conceiving humans as the sole truly cognitive species on the planet to endowing several organisms with cognitive capacities, from considering brains as the exclusive seat of cognition to extending cognitive faculties to the entire physical body and beyond. That cognition could extend beyond the organism’s body is no doubt one of the most controversial of the recent hypotheses. Extended cognition (ExC) has been discussed not only to explain aspects of the human cognitive process, but also of other species such as spiders and more recently, plants. It has been suggested that ExC could offer insights for the grounding of environmentally extended cognitive traits in evolved ecological functions. Here, we reviewed the ecological literature for possible ExC examples that satisfy the mutual manipulability criterion, which can be used to establish experimentally the boundaries of cognitive systems. Our conclusion is that ExC might be far more common than previously thought, and present in organisms as diverse as plants, fungi, termites, spiders, mammals, and slime moulds. Experimental investigation is needed to clarify this idea which, if proven correct, could illuminate a new path into understanding the origins and evolution of cognition.

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.

Machine Learning for Automatic Classification of Tomato Ripening Stages Using Electrophysiological Recordings

The physiological processes underlying fruit ripening can lead to different electrical signatures at each ripening stage, making it possible to classify tomato fruit through the analysis of electrical signals. Here, the electrical activity of tomato fruit (Solanum lycopersicum var. cerasiforme) during ripening was investigated as tissue voltage variations, and Machine Learning (ML) techniques were used for the classification of different ripening stages. Tomato fruit was harvested at the mature green stage and placed in a Faraday's cage under laboratory-controlled conditions. Two electrodes per fruit were inserted 1 cm apart from each other. The measures were carried out continuously until the entire fruits reached the light red stage. The time series were analyzed by the following techniques: Fast Fourier Transform (FFT), Wavelet Transform, Power Spectral Density (PSD), and Approximate Entropy. Descriptive analysis from FFT, PSD, and Wavelet Transform were used for PCA (Principal Component Analysis). Finally, ApEn, PCA1, PCA2, and PCA3 were obtained. These features were used in ML analyses for looking for classifiable patterns of the three different ripening stages: mature green, breaker, and light red. The results showed that it is possible to classify the ripening stages using the fruit's electrical activity. It was also observed, using precision, sensitivity, and F1-score techniques, that the breaker stage was the most classifiable among all stages. It was found a more accurate distinction between mature green × breaker than between breaker × light red. The ML techniques used seem to be a novel tool for classifying ripening stages. The features obtained from electrophysiological time series have the potential to be used for supervised training, being able to help in more accurate classification of fruit ripening stages.

Belowground interactions affect shoot growth in Eucalyptus urophylla under restrictive conditions

Plant-plant interactions like competition or facilitation between seedlings can have profound implications on their establishment and posterior development. These interactions are variable and depend upon the presence of neighbouring plants and environmental factors. In this work, we studied the effects of the interaction by the roots of Eucalyptus urophylla seedlings from a population under various environmental stressful conditions: water deficit, nutrient deficit, low light, low temperature, and high temperature. To evaluate it, we measured some growth and morphological parameters. We demonstrated that shoot parameters such as the number of leaves, leaf area, and dry weight of the leaves were the most affected parameters due to the belowground plant-plant interaction under various environmental conditions. We did not find evidence for competition among the plants, especially under restrictive conditions. Therefore, the study corroborates the stress-gradient hypothesis, which states that plants' differences under stressful conditions lead to facilitative interactions. It has implications for plant ecology and forestry techniques.

Fruit Herbivory Alters Plant Electrome: Evidence for Fruit-Shoot Long-Distance Electrical Signaling in Tomato Plants

The electrical activity of tomato plants subjected to fruit herbivory was investigated. The study aimed to test the hypothesis that tomato fruits transmit long-distance electrical signals to the shoot when subjected to herbivory. For such, time series classification by machine learning techniques and analyses related to the oxidative response were employed. Tomato plants (cv. “Micro-Tom”) were placed into a Faraday's cage and an electrode pair was inserted in the fruit's peduncle. Helicoverpa armigera caterpillars were placed on the fruit (either green and ripe) for 24 h. The time series were recorded before and after the fruit's exposure of the caterpillars. The plant material for chemical analyses was collected 24 and 48 h after the end of the acquisition of electrophysiological data. The time series were analyzed by the following techniques: Fast Fourier Transform (FFT), Wavelet Transform, Power Spectral Density (PSD), and Approximate Entropy. The following features from FFT, PSD, and Wavelet Transform were used for PCA (Principal Component Analysis): average, maximum and minimum value, variance, skewness, and kurtosis. Additionally, these features were used in Machine Learning (ML) analyses for looking for classifiable patterns between tomato plants before and after fruit herbivory. Also, we compared the electrome before and after herbivory in the green and ripe fruits. To evaluate an oxidative response in different organs, hydrogen peroxide, superoxide anion, catalase, ascorbate peroxidase, guaiacol peroxidase, and superoxide dismutase activity were evaluated in fruit and leaves. The results show with 90% of accuracy that the electrome registered in the fruit's peduncle before herbivory is different from the electrome during predation on the fruits. Interestingly, there was also a sharp difference in the electrome of the green and ripe fruits' peduncles before, but not during, the herbivory, which demonstrates that the signals generated by the herbivory stand over the others. Biochemical analysis showed that herbivory in the fruit triggered an oxidative response in other parts of the plant. Here, we demonstrate that the fruit perceives biotic stimuli and transmits electrical signals to the shoot of tomato plants. This study raises new possibilities for studies involving electrical signals in signaling and systemic response, as well as for the applicability of ML to classify electrophysiological data and its use in early diagnosis.

Detection of Different Hosts From a Distance Alters the Behaviour and Bioelectrical Activity of Cuscuta racemosa

In our study, we investigated some physiological and ecological aspects of the life of Cuscuta racemosa Mart. (Convolvulaceae) plants with the hypothesis that they recognise different hosts at a distance from them, and they change their survival strategy depending on what they detect. We also hypothesised that, as an attempt of prolonging their survival through photosynthesis, the synthesis of chlorophylls (a phenomenon not completely explained in these parasitic plants) would be increased if the plants don't detect a host. We quantified the pigments related to photosynthesis in different treatments and employed techniques such as electrophysiological time series recording, analyses of the complexity of the obtained signals, and machine learning classification to test our hypotheses. The results demonstrate that the absence of a host increases the amounts of chlorophyll a, chlorophyll b, and β-carotene in these plants, and the content varied depending on the host presented. Besides, the electrical signalling of dodders changes according to the species of host perceived in patterns detectable by machine learning techniques, suggesting that they recognise from a distance different host species. Our results indicate that electrical signalling might underpin important processes such as foraging in plants. Finally, we found evidence for a likely process of attention in the dodders toward the host plants. This is probably to be the first empirical evidence for attention in plants and has important implications on plant cognition studies.

Extended cognition in plants: is it possible?

Plants do not possess brains or neurons. However, they present astonishingly complex behaviors such as information acquisition, memory, learning, decision making, etc., which helps these sessile organisms deal with their ever-changing environments. As a consequence, they have been proposed to be cognitive and intelligent, an idea which is becoming increasingly accepted. However, how plant cognition could operate without a nervous central system remains poorly understood and new insights on this topic are urgently needed. According to the Extended Cognition hypothesis, cognition may also occur beyond the limits of the body, encompassing objects from the environment. This was shown possible in humans and spiders, who actively manipulate their external environment to extend their cognitive capacity. Here, we propose that extended cognition may also be found in plants and could partly explain the complexity of plant behavior. We suggest that plants can extend their cognitive abilities to the environment they manipulate through the root influence zone and the mycorrhizal fungi that associate with them. The possibility of a cognitive process involving organisms from different kingdoms is exciting and worthwhile exploring as it may provide key insights into the origin and evolution of cognition.