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General Issues in the Cognitive Analysis of Plant Learning and Intelligence
Abstract
In this chapter, we identify issues related to the terms behavior, intelligence, and cognition. We also point out problems with inconsistencies in the definitions of learning phenomena and whether plant intelligence needs to be interpreted in cognitive terms. As an alternative to the cognitive model of plant intelligence, we encourage researchers to consider a model combining the radical behaviorism of B. F. Skinner with the ecological psychology of J. J. Gibson where the focus of both perspectives is on the functional analysis of behavior and the recognition of alternative paths to the emergence of intelligence over the course of natural history.
... [114][115][116] Climbers are ecological perceivers of possible interactions and key invariant environmental information, such as the opportunity to reach a support that is worth climbing, where perception of affordances and support-tree location mechanisms constitute the climber-support coupled system, considered as a continuous cyclic loop. 33,42,[117][118][119][120][121][122][123] In functional terms, plant orientation toward a potential support is similar to an animal running toward its prey, 2,12,122-126 suggesting the ability to process the features of the support, with a goaldirected and anticipatory behavior. 127 This study is the first one related to support-tree location by climbing plants in Chilean temperate rainforests. ...
... However, studies in the climbing plant species of this temperate rainforest are still lacking when it comes to clonal genetic diversity, population structure, 157-159 physiological shoots integration, [160][161][162] community clonal growth and foraging. - [163][164][165][166] Plant behavior, 6,167-169 intelligence 11,123,149,167,169,170 and cognition 2,171 concepts have been discussed metaphorically and literally. 44,45,122,126,150,172 Nonetheless, a prevailing misconstruction is that a precise scientific study is not viable without an unambiguous definition, even though the definition and the field of research could evolve together. ...
Climbing plants rely on suitable support to provide the light conditions they require in the canopy. Negative phototropism is a directional search behavior proposed to detect a support-tree, which indicates growth or movement away from light, based on light attenuation. In a Chilean temperate rainforest, we addressed whether the massive woody climber Hydrangea serratifolia (H. et A.) F. Phil (Hydrangeaceae) presents a support-tree location pattern influenced by light availability. We analyzed direction and light received in two groups of juvenile shoots: searching shoots (SS), with plagiotropic (creeping) growth vs. ascending shoots (AS), with orthotropic growth. We found that, in accordance with light attenuation, SS and AS used directional orientation to search and then ascend host trees. The light available to H. serratifolia searching shoots was less than that of the general forest understory; the directional orientation in both groups showed a significant deviation from a random distribution, with no circular statistical difference between them. Circular-linear regression indicated a relationship between directional orientations and light availability. Negative phototropism encodes the light environment’s heterogeneous spatial and temporal information, guiding the shoot apex to the most shaded part of the support-tree base, the climbing start point.
... It is possible to record from a distance if zoom lenses are used. Moreover, it is also possible to record the behavior of plants over long periods during the day or at night (e.g., Abramson & Calvo, 2018;Abramson & Chicas-Mosier, 2016;Ponkshe et al., 2023). ...
Active, real-time observation of behavior is a time-consuming task, which is heavily resource-limited. At the same time, simultaneous observation of several individuals is often paramount to increase statistical rigor and eliminate potential temporal or environmental bias, especially in natural settings. This paper describes a low-cost video recording system created by using “off-the-shelf” components. The system is easy to use and can automatically record a wide variety of behavior and related ecological interactions and evolutionary processes. The system is sensitive enough to record the behavior of a broad range of animals from planarians, and small insects to humans. It can also be used to measure the behavior of plants. The system will also work during daylight hours or at night and can run continuously and autonomously for 48 hours, or longer if the video capture is motion-triggered or if bigger capacity batteries and data storage facilities are used.
... Finally, in addition to anticipation and prediction (Calvo Garzón and Keijzer 2011;Calvo 2016;Calvo and Friston 2017;Karpiński and Szechyńska-Hebda 2010;Marder 2012;Nick 2021;Trewavas 2005a, b), other equally complex attributes emerge from the investigation of plant intelligence, such as consciousness and cognition (Abramson and Calvo 2018;Calvo Garzón and Keijzer 2011;Struik et al. 2008;Trewavas 2016a, b;Trewavas and Baluška 2011), memory (Calvo et al. 2020;Cvrčková et al. 2009;Calvo Garzón and Keijzer 2011;Karpiński and Szechyńska-Hebda 2010;Trewavas 2003), learning, decision, choice, intentional behaviours (Calvo et al. 2020;Trewavas 2003Trewavas , 2005aTrewavas , 2016aTrewavas , 2017, and attention (Marder 2012(Marder , 2013Parise et al. 2022). This is somewhat similar to bacteria, a group that deserves a systematic review of its own: processes such as cognition (Shapiro 2007;Lyon 2015), memory (Bialecka-Fornal et al. 2020), social intelligence and communication (Jacob et al. 2004;Kaiser 2013) are frequently described among species of the group. ...
Since antiquity, plant life and complexity have aroused the curiosity of many scholars, including aspects of plant intelligence. While historically the topic of intelligence in plants in academia has been approached with scepticism, more recently this matter has gained evidence, especially in popular science literature. Based on a systematic literature review of scientific journals, this work had two objectives: (1) to describe the history and state-of-the-art of the research on plant intelligence; (2) to evaluate whether the academic literature has followed, in quantity and profile, the current profusion of the theme in popular science vehicles. The results showed that the academic production on the subject in scientific journals, although rich in arguments that account for intelligence in plants, is still not very expressive in comparison with the popular science boost in visibility. Such evidence indicates the persistence of academic resistance to the attribution of this trait to plants. Finally, we discuss implications of this trend for science and for human-nature relationships from a philosophical standpoint.
... The study of plant learning presents unique hurdles, as minute variables like changes in soil characteristics or variations in light intensities and frequencies, or in spectral composition, can have profound influences on plant morphogenesis and physiology (Bantis et al., 2018;Lazzarin et al., 2020). In a previous publication, we explored broader issues, such as inconsistent definitions of learning phenomena, lack of automation, and absence of universally accepted behavioral taxonomies (Abramson & Calvo, 2018 In this current paper, we delve into the granular "nut and bolts" issues that specifically relate to replicating Gagliano et al.'s experiment, leaving aside issues related to the learning protocols and controls used in the original study. Our goal is three-fold: ...
To facilitate the study of learning in plants we share our experiences of trying to replicate Gagliano et al. (2016) pea plant experiment. In the course of our efforts, we identified eleven issues that must be addressed when attempting to replicate these experiments. The issues range from germination and transplantation of seedlings to experimental design and apparatus issues. We propose a number of solutions to overcome these hurdles.
... We are as yet unable to report conclusive evidence for or against associative learning in plants. To draw ecologically meaningful conclusions it will also be important to extend these experiments beyond the lab (Abramson & Calvo, 2018;Affifi, 2018). ...
... For the purpose of this commentary, we will tackle the issue from an exclusively behaviorist perspective. For extensions to the framework of ecological psychology (Lobo et al., 2018), see Abramson and Calvo (2018). ...
... In addition, individuality can also be observed by a plant's ability to recognize self from non-self as well as kin [34]. Scientists and philosophers who advocate for plant intelligence argue that the main reasons why the idea is controversial are due to historical perceptions about plants and their hierarchical place in relation to other organisms that still predominate in society [7], non-consensus in terminological definitions, and traditional views of the cognitive sciences [35]. Traditional cognitive theories of intelligence are built on foundations that exclude plants because they are implicitly or explicitly zoocentric [36,37] and neurocentric [38]. ...
Background
Evidence suggests that plants can behave intelligently by exhibiting the ability to learn, make associations between environmental cues, engage in complex decisions about resource acquisition, memorize, and adapt in flexible ways. However, plant intelligence is a disputed concept in the scientific community. Reasons for lack of consensus can be traced back to the history of Western philosophy, interpretation of terminology, and due to plants lacking neurons and a central nervous system. Plant intelligence thus constitutes a novel paradigm in the plant sciences. Therefore, the perspectives of scientists in plant-related disciplines need to be investigated in order to gain insight into the current state and future development of this concept.
Methods
This study analyzed opinions of plant intelligence held by scientists from different plant-related disciplines, including ethnobiology and other biological sciences, through an online questionnaire.
Results
Our findings show that respondents’ personal belief systems and the frequency of taking into account other types of knowledge, such as traditional knowledge, in their own field(s) of study, were associated with their opinions of plant intelligence. Meanwhile, respondents’ professional expertise, background (discipline), or familiarity with evidence provided on plant intelligence did not affect their opinions.
Conclusions
This study emphasizes the influential role of scientists’ own subjective beliefs. In response, two approaches could facilitate transdisciplinary understanding among scientists: (1) effective communication designed to foster change in agreement based on presented information; and (2) holding space for an interdisciplinary dialogue where scientists can express their own subjectivities and open new opportunities for collaboration.
... The behaviorist approach avoids thorny philosophical issues of defining "cognition" in the context of sometimes minimal biological systems, or attempts to map their capacities onto familiar neural concepts, paradigms, and architectures developed for standard model species. We provide an overview of the conceptual and methodological tools that classical behaviorism has to offer the field of functional synthetic morphology, referring the reader to in-depth discussions of neglected aspects of invertebrate learning and the learning of plants [59][60][61][62][63] as precedents for even more profound extensions. We also discuss several methodological and conceptual issues that a bioengineer will face when designing learning experiments with novel organisms and provide practical strategies to help design a research program with novel organisms. ...
The fields of developmental biology, biomedicine, and artificial life are being revolutionized by advances in synthetic morphology. The next phase of synthetic biology and bioengineering is resulting in the construction of novel organisms (biobots), which exhibit not only morphogenesis and physiology but functional behavior. It is now essential to begin to characterize the behavioral capacity of novel living constructs in terms of their ability to make decisions, form memories, learn from experience, and anticipate future stimuli. These synthetic organisms are highly diverse, and often do not resemble familiar model systems used in behavioral science. Thus, they represent an important context in which to begin to unify and standardize vocabulary and techniques across developmental biology, behavioral ecology, and neuroscience. To facilitate the study of behavior in novel living systems, we present a primer on techniques from the behaviorist tradition that can be used to probe the functions of any organism – natural, chimeric, or synthetic – regardless of the details of their construction or origin. These techniques provide a rich toolkit for advancing the fields of synthetic bioengineering, evolutionary developmental biology, basal cognition, exobiology, and robotics.
... In light of the inconsistent results being reported, at the Minimal Intelligence Lab, we currently aim to test independently the capacity for replication of Gagliano et al.'s (2016) results. Likewise, it is important that we further improve the research designs by taking these experiments out of the lab if we aim to yield ecologically meaningful conclusions (Abramson & Calvo, 2018;Affifi, 2018). ...
Unlike animal behavior, behavior in plants is traditionally assumed to be completely determined either genetically or environmentally. Under this assumption, plants are usually considered to be noncognitive organisms. This view nonetheless clashes with a growing body of empirical research that shows that many sophisticated cognitive capabilities traditionally assumed to be exclusive to animals are exhibited by plants too. Yet, if plants can be considered cognitive, even in a minimal sense, can they also be considered conscious? Some authors defend that the quest for plant consciousness is worth pursuing, under the premise that sentience can play a role in facilitating plant's sophisticated behavior. The goal of this article is not to provide a positive argument for plant cognition and consciousness, but to invite a constructive, empirically informed debate about it. After reviewing the empirical literature concerning plant cognition, we introduce the reader to the emerging field of plant neurobiology. Research on plant electrical and chemical signaling can help shed light into the biological bases for plant sentience. To conclude, we shall present a series of approaches to scientifically investigate plant consciousness. In sum, we invite the reader to consider the idea that if consciousness boils down to some form of biological adaptation, we should not exclude a priori the possibility that plants have evolved their own phenomenal experience of the world.
This article is categorized under: Cognitive Biology > Evolutionary Roots of Cognition
Philosophy > Consciousness
Neuroscience > Cognition
... There seems to be a "mad dash" for researchers to interpret almost any behavior as cognitive. This occurs despite the fact that there is no generally accepted definition of cognition and no set of independent guidelines for a researcher or student to independently assess whether a behavior is cognitive or not (Abramson, 2013;Abramson & Calvo, 2018;Abramson & Wells, 2018). In our view, this state of affairs is hurting psychology as a science. ...
The field of psychology has witnessed an increase in its reliance on empiricism to the point that many researchers operate with a complete disregard for the role of philosophy in their pursuit of knowledge. The resultant segmentation of the field and decline in such important areas as comparative psychology can be attributed to this trend, indicating the need for the role of both philosophical and scientific knowledge to be rightly applied and understood. A return to a proper utilization of philosophy in guiding empirical questions and interpreting results is offered as a means of revitalizing the field of comparative psychology. The philosophical approach of Aristotle and Thomas Aquinas is discussed as a means to do so, as it provides a valuable perspective in guiding research and enabling the scientist to interpret results in an integrated and informative manner, whereby the phenotypic comparisons of humans and non-humans can be understood coherently.
... In numerous situations the obtained theoretical models match empiri-al 2017; Baluska et al. 2018; van Duijn 2018). Most others object that this inference is hasty (Allen 2017;Abramson and Calvo 2018). This leads to a debate about what cognition is, which sometimes bears fruit (Buckner 2015), but often is inconclusive (Allen 2017; van Duijn 2018). ...
Usually we take for granted that we have a body and that it can be used to behave upon the world. This pre-reflective consciousness is made up by two major components, i.e., the sense of ownership (SoO) and the sense of agency (SoA). While the first is the feeling of being the owner of my body parts, the second is the experience of acting and controlling an action. Although SoO and SoA usually come together, they can occur independently and can be selectively disrupted. We investigate the relationship between SoO and SoA by means the rubber hand illusion procedure, in particular the rubber hand illusion based on active and passive movements. We argue for the idea that, if SoA and SoO co-occur in experience, the first feeling strengthens the second one. We use a cross-modal approach, testing two different conditions in performing a double touch with the index finger, one endowed with an acoustic feedback and the other being completely silent. Furthermore, we test also the onset time of the ownership sensation in the two conditions in order to understand if the sense of agency occurs differently in the case of lack of a perceptual feedback.
... Simple organisms allow for a much more thorough examination of the evolution of a purely metabolism-or maintenance-related behaviour into something else. The inclusion of simple organisms in the cognitive domain can cause tension between scientists and philosophers alike, but exploring the reasons behind disagreements is often fruitful and can lead to new insight (Abramson & Calvo, 2018;Wynne, 2004). ...
Although human decision making seems complex, there is evidence that many decisions are grounded in simple heuristics. Such heuristic models of decision making are widespread in nature. To understand how and why different forms of information processing evolve, it is insightful to study the minimal requirements for cognition. Here, we explore the minimally cognitive behaviour of the acellular slime mould, Physarum polycephalum, in order to discuss the ecological pressures that lead to the development of information processing mechanisms. We discuss evidence for memory, basic forms of learning and economically irrational choice in P. polycephalum. We compare P. polycephalum’s behaviour with a number of other non-neuronal organisms in order to question the evolutionary need for complex nervous systems to develop cognitive traits. By highlighting a few examples of common mechanisms, we conclude that all organisms contain the building blocks for more complex information processing. Returning the debate about cognition to the biological basics demystifies some of the confusion around the term ‘cognition’.
... Acknowledgments Aspects of this manuscript were adopted from our previous work on this issue (Abramson, 1994(Abramson, , 1997Abramson & Chicas-Mosier, 2016;Abramson & Calvo, 2018). ...
The burgeoning field of invertebrate behavior is moving into what was the realm of human psychology concepts. This invites comparative studies not only between invertebrate and vertebrate species but also among the diverse taxa within the invertebrates, diverse even when considering only the insects. In order to make lasting progress two issues must be addressed. The first is inconsistent use of fundamental terms defining learning. The second is a focus on similarities, giving little attention to dissimilarities. In addition, much work is needed on whether behavioral similarities are grounded in the same neuronal architecture when considering disparate phyla. These concerns identify are “inconvenient truths” that weaken comparative behavioral analysis.
... Plants perceive and act, and to alternate appropriately between these two modes calls for both the assessment and contextual integration of a number of parameters, and for the capacity to learn. Fortunately, we now know that plants can do both [4,40]. In fact, we have considered, for simplicity's sake, the perception of a single modality (the perception of salt), but salt-avoidance behaviour cannot be assimilated into a response to environmental stimuli on a one-to-one basis. ...
In this article we account for the way plants respond to salient features of their environment under the free-energy principle for biological systems. Biological self-organization amounts to the minimization of surprise over time. We posit that any self-organizing system must embody a generative model whose predictions ensure that (expected) free energy is minimized through action. Plants respond in a fast, and yet coordinated manner, to environmental contingencies. They pro-actively sample their local environment to elicit information with an adaptive value. Our main thesis is that plant behaviour takes place by way of a process (active inference) that predicts the environmental sources of sensory stimulation. This principle, we argue, endows plants with a form of perception that underwrites purposeful, anticipatory behaviour. The aim of the article is to assess the prospects of a radical predictive processing story that would follow naturally from the free-energy principle for biological systems; an approach that may ultimately bear upon our understanding of life and cognition more broadly.
The purpose of this contribution is threefold. First, is to acquaint neuroscientists with the area of psychology known as comparative psychology. Comparative psychology is the oldest of the organized social sciences with the term appearing as early as 1808. Many of the myriad issues of experimental design routinely faced by comparative psychologists are directly applicable to neuroscience. These issues include consistent definitions of psychological phenomena, the use of Morgan’s canon to reduce unbridled anthropomorphism, and observation oriented modeling as a new statistical procedure to increase replication. Second, is a discussion of early comparative methods that may be of value to contemporary neuroscientists. Third, how the comparative approach can help the neuroscientist limit unfounded generalizations across species and develop more animal-friendly behavioral testing options tailored for the species or strain of interest. The articles closes with some recommendations on how comparative psychologists and neuroscientists can work more closely together.
This book assembles recent research on memory and learning in plants. Organisms that share a capability to store information about experiences in the past have an actively generated background resource on which they can compare and evaluate coming experiences in order to react faster or even better. This is an essential tool for all adaptation purposes. Such memory/learning skills can be found from bacteria up to fungi, animals and plants, although until recently it had been mentioned only as capabilities of higher animals. With the rise of epigenetics the context dependent marking of experiences on the genetic level is an essential perspective to understand memory and learning in organisms.
Plants are highly sensitive organisms that actively compete for environmental resources. They assess their surroundings, estimate how much energy they need for particular goals, and then realize the optimum variant. They take measures to control certain environmental resources. They perceive themselves and can distinguish between ‘self’ and ‘non-self’. They process and evaluate information and then modify their behavior accordingly.
The book will guide scientists in further investigations on these skills of plant behavior and on how plants mediate signaling processes between themselves and the environment in memory and learning processes.
According to F. Adams [this journal, vol. 68, 2018] cognition cannot be realized in plants or bacteria. In his view, plants and bacteria respond to the here-and-now in a hardwired, inflexible manner, and are therefore incapable of cognitive activity. This article takes issue with the pursuit of plant cognition from the perspective of an empirically informed philosophy of plant neurobiology. As we argue, empirical evidence shows, contra Adams, that plant behavior is in many ways analogous to animal behavior. This renders plants suitable to be described as cognitive agents in a non-metaphorical way. Sections two to four review the arguments offered by Adams in light of scientific evidence on plant adaptive behavior, decision-making, anticipation, as well as learning and memory. Section five introduces the ‘phyto-nervous’ system of plants. To conclude, section six resituates the quest for plant cognition into a broader approach in cognitive science, as represented by enactive and ecological schools of thought. Overall, we aim to motivate the idea that plants may be considered genuine cognitive agents. Our hope is to help propel public awareness and discussion of plant intelligence once appropriately stripped of anthropocentric preconceptions of the sort that Adams' position appears to exemplify.
In this report we explore the guidance of circumnutation of climbing bean stems under the light of general rho/tau theory, a theory that aims to explain how living organisms guide goal-directed movements ecologically. We present some preliminary results on the control of circumnutation by climbing beans, and explore the possibility that the power of movement in plants, more generally, is controlled under ecological principles.
In complex and ever-changing environments, resources such as food are often scarce and unevenly distributed in space and time. Therefore, utilizing external cues to locate and remember high-quality sources allows more efficient foraging, thus increasing chances for survival. Associations between environmental cues and food are readily formed because of the tangible benefits they confer. While examples of the key role they play in shaping foraging behaviours are widespread in the animal world, the possibility that plants are also able to acquire learned associations to guide their foraging behaviour has never been demonstrated. Here we show that this type of learning occurs in the garden pea, Pisum sativum. By using a Y-maze task, we show that the position of a neutral cue, predicting the location of a light source, affected the direction of plant growth. This learned behaviour prevailed over innate phototropism. Notably, learning was successful only when it occurred during the subjective day, suggesting that behavioural performance is regulated by metabolic demands. Our results show that associative learning is an essential component of plant behaviour. We conclude that associative learning represents a universal adaptive mechanism shared by both animals and plants.
In this article we consider the possibility that plants exhibit anticipatory behavior, a mark of intelligence. If plants are able to anticipate and respond accordingly to varying states of their surroundings, as opposed to merely responding online to environmental contingencies, then such capacity may be in principle testable, and subject to empirical scrutiny. Our main thesis is that adaptive behavior can only take place by way of a mechanism that predicts the environmental sources of sensory stimulation. We propose to test for anticipation in plants experimentally by contrasting two empirical hypotheses: “feature detection” and “predictive coding.” We spell out what these contrasting hypotheses consist of by way of illustration from the animal literature, and consider how to transfer the rationale involved to the plant literature.
The central nervous system (CNS) underlies memory, perception, decision-making, and behavior in numerous organisms. However, neural networks have no monopoly on the signaling functions that implement these remarkable algorithms. It is often forgotten that neurons optimized cellular signaling modes that existed long before the CNS appeared during evolution, and were used by somatic cellular networks to orchestrate physiology, embryonic development, and behavior. Many of the key dynamics that enable information processing can, in fact, be implemented by different biological hardware. This is widely exploited by organisms throughout the tree of life. Here, we review data on memory, learning, and other aspects of cognition in a range of models, including single celled organisms, plants, and tissues in animal bodies. We discuss current knowledge of the molecular mechanisms at work in these systems, and suggest several hypotheses for future investigation. The study of cognitive processes implemented in aneural contexts is a fascinating, highly interdisciplinary topic that has many implications for evolution, cell biology, regenerative medicine, computer science, and synthetic bioengineering.
“A developmental change is usually not a behavior.” In the light of plant biology tradition this is somewhat puzzling# hinting at the need to examine what is understood as developmental change by animal and plant biologists. Growth and production of vegetative organs may not be perceived as a “change” by plant biologists, because it is just something plants do all the time. Moreover, the magic word “usually” leaves some interpretation freedom. Perhaps this statement should be rephrased to distinguish between developmental processes following a strict, genetically determined plan, such as early animal embryogenesis, or development of a single flower, and those involving decisions made within broader limits permitted by a species-specific developmental algorithm. The latter, in our opinion, should be admitted as behavior.
A summary definition of some 70 descriptions of intelligence provides a definition for all other organisms including plants that stresses fitness. Barbara McClintock, a plant biologist, posed the notion of the ‘thoughtful cell’ in her Nobel prize address. The systems structure necessary for a thoughtful cell is revealed by comparison of the interactome and connectome. The plant root cap, a group of some 200 cells that act holistically in responding to numerous signals, likely possesses a similar systems structure agreeing with Darwin’s description of acting like the brain of a lower organism. Intelligent behavior requires assessment of different choices and taking the beneficial one. Decisions are constantly required to optimize the plant phenotype to a dynamic environment and the cambium is the assessing tissue diverting more or removing resources from different shoot and root branches through manipulation of vascular elements. Environmental awareness likely indicates consciousness. Spontaneity in plant behavior, ability to count to five and error correction indicate intention. Volatile organic compounds are used as signals in plant interactions and being complex in composition may be the equivalent of language accounting for self and alien recognition by individual plants. Game theory describes competitive interactions. Interactive and intelligent outcomes emerge from application of various games between plants themselves and interactions with microbes. Behavior profiting from experience, another simple definition of intelligence, requires both learning and memory and is indicated in the priming of herbivory, disease and abiotic stresses.
This article provides an overview of the early Mimosa pudica literature; much of which is in journals not easily accessible to the reader. In contrast to the contemporary plant learning literature which is conducted primarily by plant biologists, this early literature was conducted by comparative psychologists whose goal was to search for the generality of learning phenomena such as habituation, and classical conditioning using experimental designs based on animal conditioning studies. In addition to reviewing the early literature, we hope to encourage collaborations between plant biologists and comparative psychologists by familiarizing the reader with issues in the study of learning faced by those working with animals. These issues include no consistent definition of learning phenomena and an overreliance on the use of cognition. We suggested that greater collaborative efforts be made between plant biologists and comparative psychologists if the study of plant learning is to be fully intergraded into the mainstream behavior theory.
Early forms of psychology assumed that mental life was the appropriate subject matter for psychology, and introspection was an appropriate method to engage that subject matter. In 1913, John B. Watson proposed an alternative: classical S-R behaviorism. According to Watson, behavior was a subject matter in its own right, to be studied by the observational methods common to all sciences. Unfortunately, by around 1930, Watson's behaviorism had proved inadequate. Many researchers and theorists then adopted a view in which various organismic entities were inferred to mediate the relation between S and R: mediational S-O-R neobehaviorism. This general view has remained influential, although the details of the various versions have differed over the years. The behavior analysis of B. F. Skinner took an entirely different approach. Particularly important was the study of verbal behavior. Although behaviorism is often conventionally defined as an approach that seeks to explain behavior without directly appealing to mental or cognitive processes, this definition needs considerable clarification, especially as it pertains to Skinner's behavior analysis and his view of behaviorism as a philosophy of science.
‘Plant neurobiology’ has emerged in recent years as a multidisciplinary endeavor carried out mainly by steady collaboration within the plant sciences. The field proposes a particular approach to the study of plant intelligence by putting forward an integrated view of plant signaling and adaptive behavior. Its objective is to account for the way plants perceive and act in a purposeful manner. But it is not only the plant sciences that constitute plant neurobiology. Resources from philosophy and cognitive science are central to such an interdisciplinary project, if plant neurobiology is to maintain its target well-focused. This manifesto outlines a road map for the establishment and development of a new subject—the Philosophy of Plant Neurobiology—, a new field of research emerging at the intersection of the philosophy of cognitive science and plant neurobiology. The discipline is herewith presented, introducing challenges and novel lines of engagement with the empirical investigation, and providing an explanatory framework and guiding principles that will hopefully ease the integration of research on the quest for plant intelligence.
Three views of behaviorism are examined in an effort to clarify its meaning. The views are composites of what readers might hear or read in the professional literature of psychology. View 1 is un-self-consciously critical of behaviorism and might represent the view taken by a contemporary cognitive psychologist. View 2 appears to support behaviorism but actually represents only a methodological behaviorism and an epistemological dualism. View 3 represents a radical, thoroughgoing behaviorism. The radical behaviorism of View 3 regards any differences between Views 1 and 2 as superficial-both are mediational and mentalistic and therefore objectionable. In contrast to Views 1 and 2, radical behaviorism emphasizes the functional analysis of verbal behavior, which leads to a thoroughgoing, behavioral conception of knowledge and explanatory practices in psychology.
A truly embodied-embedded approach to behavior promises a radical change in how scientists conceptualize cognitive agents (both biological and nonbiological) and how they proceed to understand the behavioral order of such agents, both empirically and theoretically. This chapter views that cashing in the promissory note requires that perceiving, acting and knowing be studied as emergent properties of an organism (O)-environment (E) system. The six principles described in the present chapter are proposed as an appropriate framework for that study. It presumes that the persistent application of the principles should enable cognitive and psychological science to repay the many loans of intelligence thus far accrued.
Cognitive psychology and behaviorism are often held to be competing, mutually exclusive paradigms in contemporary psychology. The present paper argues that cognitive psychology is actually quite compatible with the most widely recognized version of behaviorism, here designated as mediational S- O-R neobehaviorism. The paper argues this case by suggesting that neobehaviorist theoretical terms have tended to be interpreted as 'hypothetical constructs.' Such an interpretation permits neobehaviorist theoretical terms to refer to a wide variety of nonbehavioral acts, states, mechanisms, and processes, with extensive 'surplus meaning.' Consequently, an interpretation of neobehaviorist theoretical terms as hypothetical constructs can readily accommodate the kind of mental entities postulated by cognitive psychology.
Selected writings of B. F. Skinner are compared to 5 current topics in mainstream psychology, including the role of the unconscious, human language, the role of dispositions in psychology, human perceptions of conformity and bias, and mindfulness. The striking similarities between Skinner's work and these 5 current topics support Richelle's (1993) prediction that psychologists may eventually discover that Skinner was a forerunner in the theory and practice of psychology.
Empirically analyzing empirical evidence
One of the central goals in any scientific endeavor is to understand causality. Experiments that seek to demonstrate a cause/effect relation most often manipulate the postulated causal factor. Aarts et al. describe the replication of 100 experiments reported in papers published in 2008 in three high-ranking psychology journals. Assessing whether the replication and the original experiment yielded the same result according to several criteria, they find that about one-third to one-half of the original findings were also observed in the replication study.
Science , this issue 10.1126/science.aac4716
Cognitive psychology is the name for a class of positions that embrace mentalism: appeals to explicitly nonbehavioral states, mechanisms, processes, structures, and the like, operating in an explicitly nonbehavioral dimension of the mind, as causally effective antecedents in explanations of behavior. The present article reviews the background and nature of cognitive psychology, especially as contrasted with behaviorism. Of particular interest are the theoretical and philosophical differences between cognitive psychology and behaviorism, for instance, as those differences concern their respective explanatory practices. We conclude that cognitive psychology has conceptual affinities with mediational neobehaviorism, and that the radical behaviorism of B. F. Skinner differs from them both.
Contents: Setting the Stage: Behaviorisms and Cognitivisms. Issues Surrounding the Old and the New Learning Theory. Representational and Non-Representational Levels of Functioning: A Possible Conciliation.
This article offers some personal reflections on the difficulty of teaching the behaviorist perspective in the psychology classroom. The problems focus on the inadequacy of introductory textbooks-which mischaracterize behaviorism, only present the most extreme behaviorist positions, make no mention of the neobehaviorist perspective, fail to discuss that there is no accepted criteria for determining what type of behavior is cognitive, and provide a definition of cognition that is, not only inconsistent across texts, but so broad as to overshadow the behaviorist contributions. Suggestions are provided for instructors on how to present to their students an accurate portrayal of behaviorism.
Use of the terms cognition and behavior and their variants can be traced back to the middle-ages. What is not widely known is how the terms were first used in the literature. This article identifies variations of terms for cognition and behavior and traces the first use of the terms using the Oxford English Dictionary (OED). A systematic search of the OED was conducted, identifying terms in the cognition and behavior families. Terms are defined and the year the term first appeared in the literature is identified. Terms are sorted and grouped chronologically by first appearance to determine their first use in the literature as noted in the OED. Results indicated more words are related to cognition than behavior. The first term related to cognition to appear was cogitation in circa 1225; while the first term related to behavior was port, which appeared circa 1330. Each family of terms experienced tremendous growth during the first appearance of terms. The cognition family saw 60% of its terms appear in the 17(th) and 19(th) centuries. The behavior family saw nearly 75% of its terms make their first appearance during the 15(th) through the 17(th) centuries.
This research examines the employment of cognitive or mentalist words in the titles of articles from three comparative psychology journals (Journal of Comparative Psychology, International Journal of Comparative Psychology, Journal of Experimental Psychology: Animal Behavior Processes; 8,572 titles, >100,000 words). The Dictionary of Affect in Language, coupled with a word search of titles, was employed to demonstrate cognitive creep. The use of cognitive terminology increased over time (1940-2010) and the increase was especially notable in comparison to the use of behavioral words, highlighting a progressively cognitivist approach to comparative research. Problems associated with the use of cognitive terminology in this domain include a lack of operationalization and a lack of portability. There were stylistic differences among journals including an increased use of words rated as pleasant and concrete across years for Journal of Comparative Psychology, and a greater use of emotionally unpleasant and concrete words in Journal of Experimental Psychology: Animal Behavior Processes.
Since the beginning of the 20th century, intelligence has been conceptualized as a qualitatively unique faculty (or faculties) with a relatively fixed quantity that individuals possess and that can be tested by conventional intelligence tests. Despite the logical errors of reification and circular reasoning involved in this essentialistic conceptualization, this view of intelligence has persisted until the present, with psychologists still debating how many and what types of intelligence there are. This paper argues that a concept of intelligence as anything more than a label for various behaviors in their contexts is a myth and that a truly scientific understanding of the behaviors said to reflect intelligence can come only from a functional analysis of those behaviors in the contexts in which they are observed. A functional approach can lead to more productive methods for measuring and teaching intelligent behavior. Few topics have sparked such heated debate within the academic community and society at large as that of intelligence and intelligence testing. Some of the contentious issues in the debate include the very definition of intelligence, the controversy concerning IQ and race, the ever present nature-nurture problem (Weinberg, 1989), and even the question of whether intelligence exists (Howe, 1990). The debate was reignited most recently by the publication in 1994 of The Bell Curve: Intelligence and Class Structure in American Life by Richard J. Herrnstein and Charles Murray. The sturm und drang created by the publication of this book was, among other things, the motivation behind the creation of a task force in 1995 by the Board of Scientific Affairs of the American Psychological Association to prepare an authoritative report on the current status of research on intelligence and intelligence testing. The flurry of response generated by The Bell Curve, both in the academic. 16 SCHLINGER community and in the media, also prompted a letter to the Wall Street Journal in December, 1994, in which 50 professors "all experts in intelligence and allied fields" signed a statement, titled "Mainstream Science on Intelligence."1 The purpose of this statement was to respond to the public outcry over the suggestions and social implications of The Bell Curve by outlining "conclusions regarded as mainstream among researchers on intelligence, in particular, on the nature, origins, and practical consequences of individual and group differences in intelligence" ("Mainstream Science on Intelligence," 1994). One of the reasons for the persistent concern about intelligence is that intelligence tests have been used to support nativistic theories in which intelligence is viewed as a qualitatively unique faculty with a relatively fixed quantity. Historically, proponents of nativistic theories have succeeded in persuading those with political power that standardized tests reliably measure intelligence; and these tests have been used to make important decisions about vast numbers of individuals including immigrants, U.S. soldiers during the first World War, normal school children, and the developmentally disabled. Not surprisingly, there exists a substantial literature documenting the history of the intelligence testing movement (e.g., Bolles, 1993; Fancher, 1985; Gould, 1981; Herrnstein & Murray, 1994; Kamin, 1974).
The nervous system of animals serves the acquisition, memorization and recollection of information. Like animals, plants also acquire a huge amount of information from their environment, yet their capacity to memorize and organize learned behavioral responses has not been demonstrated. In Mimosa pudica-the sensitive plant-the defensive leaf-folding behaviour in response to repeated physical disturbance exhibits clear habituation, suggesting some elementary form of learning. Applying the theory and the analytical methods usually employed in animal learning research, we show that leaf-folding habituation is more pronounced and persistent for plants growing in energetically costly environments. Astonishingly, Mimosa can display the learned response even when left undisturbed in a more favourable environment for a month. This relatively long-lasting learned behavioural change as a result of previous experience matches the persistence of habituation effects observed in many animals.
Once considered only a human behavior, reports of tool use by a variety of animals have accumulated. Likewise, various definitions of tool use have also amassed. Although some researchers argue that understanding the evolutionary drivers of tool use is more important than identifying and describing these behaviors, the central issue of defining what constitutes tool use has not been fully addressed. Here we analyze prominent definitions of tool use and review the application of these definitions in scientific and educational literature. We demonstrate that many behaviors recently described as tool use do not meet criteria for prevalent definitions, while other neglected behaviors may constitute a form of tool use. These examples show how the use of inconsistent definitions of tool use in research can result in different conclusions from the same observations. Our aim is to demonstrate that a universally acceptable definition of tool use based on traditional, evolutionary, and operational understanding of behavior is needed. The rationale is that this review will stimulate the consistent and explicit use of specific terminology in tool use research. This would help define specific examples of each natural observation from a common measuring stick, allowing better comparative studies and classification of these unique behaviors.
In this article, I explore plant semiosis with a focus on plant learning. I distinguish between the scales and levels of learning conceivable in phytosemiosis, and identify organism-scale learning as the distinguishing question for plant semiosis. Since organism-scale learning depends on organism-scale semiosis, I critically review the arguments regarding whole-plant functional cycles. I conclude that they have largely relied on Uexküllian biases that have prevented an adequate interpretation of modern plant neurobiology. Through an examination of trophic growth in plant roots, I expose some conceptual difficulties in attributing functional cycles to whole-plants. I conclude that the mapping of resource areas in the root system is a learning activity requiring higher-scale sign activity than is possible at the cellular scale, strongly suggesting the presence of organism-scale functional cycles. I do, however, question whether all perception-action cycles in organisms are accompanied with organism-scale semiosis.
Serious criticisms of psychology’s research practices and data analysis methods date back to at least the mid-1900s after the Galtonian school of thought had thoroughly triumphed over the Wundtian school. In the wake of Bem’s (2011) recent, highly publicized study on psi phenomena in a prestigious journal, psychologists are again raising serious questions about their dominant research script. These concerns are echoed in the current paper, and Observation Oriented Modeling (OOM) is presented as an alternative approach toward data conceptualization and analysis for the social and life sciences. This approach is rooted in philosophical realism and an attitude toward data analysis centered around causality and common sense. Three example studies and accompanying data analyses are presented and discussed to demonstrate a number of OOM’s advantages over current researcher practices.
A proposal for a new way to do cognitive science argues that cognition should be described in terms of agent-environment dynamics rather than computation and representation.
While philosophers of mind have been arguing over the status of mental representations in cognitive science, cognitive scientists have been quietly engaged in studying perception, action, and cognition without explaining them in terms of mental representation. In this book, Anthony Chemero describes this nonrepresentational approach (which he terms radical embodied cognitive science), puts it in historical and conceptual context, and applies it to traditional problems in the philosophy of mind. Radical embodied cognitive science is a direct descendant of the American naturalist psychology of William James and John Dewey, and follows them in viewing perception and cognition to be understandable only in terms of action in the environment. Chemero argues that cognition should be described in terms of agent-environment dynamics rather than in terms of computation and representation. After outlining this orientation to cognition, Chemero proposes a methodology: dynamical systems theory, which would explain things dynamically and without reference to representation. He also advances a background theory: Gibsonian ecological psychology, “shored up” and clarified. Chemero then looks at some traditional philosophical problems (reductionism, epistemological skepticism, metaphysical realism, consciousness) through the lens of radical embodied cognitive science and concludes that the comparative ease with which it resolves these problems, combined with its empirical promise, makes this approach to cognitive science a rewarding one. “Jerry Fodor is my favorite philosopher,” Chemero writes in his preface, adding, “I think that Jerry Fodor is wrong about nearly everything.” With this book, Chemero explains nonrepresentational, dynamical, ecological cognitive science as clearly and as rigorously as Jerry Fodor explained computational cognitive science in his classic work The Language of Thought.
Bradford Books imprint
Charles Darwin was always pleased to exalt plants in the scale of organised beings, drawing particular attention to the sensory properties of their roots. He even went so far as to say that the root tip acts like a plant brain, located within the anterior end of the plant body. What impressed Darwin was the ability of the root to perceive, often simultaneously, multiple vectorial stimuli, and then make a ‘decision’ about which bending response to follow. According to J.G. Miller’s ‘living systems theory’ (LST), developed mainly for human organisms and human societies, there are similar sets of 20 subsystems supporting each level of organisation, from cellular to organismic. If LST is a universal theory, it should apply to plant organisms also. About half of all the LST subsystems concern the processing of information. In the present plant-neurobiological context, the information-processing subsystem of particular interest is ‘channel and net’. In the light of recent discoveries from plant cell biology, earlier designations of structures to this subsystem are confirmed. They reinforce the idea that plants possess a form of nervous system — even though Darwin denied this particular proposition-which, moreover, makes use of molecules and organelles similar to those found in the neurotransmission systems of animals. The LST approach to plant life converges upon that already recognised for animals and, hence, provides a coherent conceptualisation for the structuring of the two major kingdoms of plants and animals.
In 1988, Jerry Fodor and Zenon Pylyshyn challenged connectionist theorists to explain the systematicity of cognition. In a highly influential critical analysis of connectionism, they argued that connectionist explanations, at best, can only inform us about details of the neural substrate; explanations at the cognitive level must be classical insofar as adult human cognition is essentially systematic. More than twenty-five years later, however, conflicting explanations of cognition do not divide along classicist-connectionist lines, but oppose cognitivism (both classicist and connectionist) with a range of other methodologies, including distributed and embodied cognition, ecological psychology, enactivism, adaptive behavior, and biologically based neural network theory. This volume reassesses Fodor and Pylyshyn's "systematicity challenge" for a post-connectionist era. The contributors consider such questions as how post-connectionist approaches meet Fodor and Pylyshyn's conceptual challenges; whether there is empirical evidence for or against the systematicity of thought; and how the systematicity of human thought relates to behavior. The chapters offer a representative sample and an overview of the most important recent developments in the systematicity debate. Contributors Ken Aizawa, William Bechtel, Gideon Borensztajn, Paco Calvo, Anthony Chemero, Jonathan D. Cohen, Alicia Coram, Jeffrey L. Elman, Stefan L. Frank, Antoni Gomila, Seth A. Herd, Trent Kriete, Christian J. Lebiere, Lorena Lobo, Edouard Machery, Gary Marcus, Emma Martín, Fernando Martínez-Manrique, Brian P. McLaughlin, Randall C. O'Reilly, Alex A. Petrov, Steven Phillips, William Ramsey, Michael Silberstein, John Symons, David Travieso, William H. Wilson, Willem Zuidema © 2014 Massachusetts Institute of Technology. All rights reserved.
During the 1980's and 1990's Fodor, McLaughlin, and Pylyshyn claimed that thought is in various respects systematic. Further, they argued that so-called “Classical” syntactically and semantically combinatorial representations provide a better explanation of the systematicity of thought than do non-combinatorial representations or non-Classical combinatorial representations. During the 1990’s, part of what made the systematicity arguments problematic was the subtlety of the idea of providing a better explanation. In what sense is the Classical account better than its rivals? During what we might call the Post-Connectionist era of roughly the last ten years, however, theoretical shifts have made it even more difficult to bring considerations of the systematicity of thought to bear on the nature of cognition. Post-Connectionist cognitive science has come to focus less on cognition. This chapter reviews these changes in the cognitive science landscape regarding systematicity.
Charles Darwin was always pleased to exalt plants in the scale of organised beings, drawing particular attention to the sensory properties of their roots. He even went so far as to say that the root tip acts like a plant brain, located within the anterior end of the plant body. What impressed Darwin was the ability of the root to perceive, often simultaneously, multiple vectorial stimuli, and then make a 'decision' about which bending response to follow. According to J.G. Miller's 'living systems theory' (LST), developed mainly for human organisms and human societies, there are similar sets of 20 subsystems supporting each level of organisation, from cellular to organismic. If LST is a universal theory, it should apply to plant organisms also. About half of all the LST subsystems concern the processing of information. In the present plant-neurobiological context, the information-processing subsystem of particular interest is 'channel and net'. In the light of recent discoveries from plant cell biology, earlier designations of structures to this subsystem are confirmed. They reinforce the idea that plants possess a form of nervous system - even though Darwin denied this particular proposition-which, moreover, makes use of molecules and organelles similar to those found in the neurotransmission systems of animals. The LST approach to plant life converges upon that already recognised for animals and, hence, provides a coherent conceptualisation for the structuring of the two major kingdoms of plants and animals.
It is difficult to reconcile formal learning theories with the intricate, complex, and adaptive organism-environment transactions which we observe in invertebrates. While it may turn out that the delicate behavioral chiaroscuros are “nothing more than” the stark operational definitions found in Kimble (1961), when invertebrate transactions are watched for extended periods of time there is little rapport between the textbook and the observations. This is not a plea for naturalistic research so much as a comment on the lack of a conceptualization which could encompass the adaptive repertoires shown by invertebrates. This volume reviews behavior modification of invertebrates and permits itself rather broad latitude concerning what may or may not turn out to be “grade A certified” learning. It will be shown that behavior modification occurs at all levels of invertebrate phylogeny and that some quite complex paradigms are successfully performed by quite simple systems.
Studies of sensory guidance of movement in animals show that large nervous systems are not necessary for accurate control, suggesting that guidance may be based on some simple principles. In search for those principles, a theory of guidance of movement is described, which has its roots in Gibson's pathfinding work on visual control of locomotion (J. J. Gibson, 1958/this issue). The theory is based on the use of the simple but powerful variable tau, the time-to-closure of a gap at the current gap closure rate (whatever the gap's dimension—distance, angle, force, etc.); and on the principle of tau-coupling (keeping two Ts in constant ratio). In this article, I show how tau-coupling could be used to synchronize movements and regulate their kinematics. Supportive experimental results are reported. I also show theoretically how sensory-taus, defined on sensory input arrays, can specify motion-taus through tau-coupling; how the braking procedure of keeping tau.dot stable is a particular case of tau.coupling; and how tools for steering (e.g., limbs, whole bodies, cars, or aircraft) could be built from tau-couplings, which would enable steering control in a variety of situations, including steering straight and curved courses to goals, steering and controlling speed at the same time, steering around obstacles, and asymptoting on surfaces as when landing. Some movements also involve intrinsic guidance from within, and a hypothesis on intrinsic guidance by tau is introduced, supported by experiments spanning different activities.
The book from which these sections are excerpted (N. Chomsky, Rules and Representations, Columbia University Press, 1980) is concerned with the prospects for assimilating the study of human intelligence and its products to the natural sciences through the investigation of cognitive structures, understood as systems of rules and representations that can be regarded as “mental organs.” These mental structui′es serve as the vehicles for the exercise of various capacities. They develop in the mind on the basis of an innate endowment that permits the growth of rich and highly articulated structures along an intrinsically determined course under the triggering and partially shaping effect of experience, which fixes parameters in an intricate system of predetermined form. It is argued that the mind is modular in character, with a diversity of cognitive structures, each with its specific properties arid principles. Knowledge of language, of the behavior of objects, and much else crucially involves these mental structures, and is thus not characterizable in terms of capacities, dispositions, or practical abilities, nor is it necessarily grounded in experience in the standard sense of this term.Various types of knowledge and modes of knowledge acquisition are discussed in these terms. Some of the properties of the language faculty are investigated. The basic cognitive relation is “knowing a grammar”; knowledge of language is derivative and, correspondingly, raises further problems. Language as commonly understood is not a unitary phenomenon but involves a number of interacting systems: the “computational” system of grammar, which provides the representations of sound and meaning that permit a rich range of expressive potential, is distinct from a conceptual system with its own properties; knowledge of language must be distinguished from knowledge of how to use a language; and the various systems that enter into the knowledge and use of language must be further analyzed into their specific subcomponents.
The history of experimental psychology in America is typically told as a series of two Kuhnian revolutions separating three periods of normal science dominated by the mentalist, then behaviorist, and finally today's cognitivist paradigm. Models of revolution developed by T. S. Kuhn, I. B. Cohen, and R. Porter are described and used to formulate questions and criteria for investigating revolutions in experimental psychology. The history of the behaviorist and cognitivist "revolutions" as seen by contemporaries shows that each was in fact a period of rapid but continuous and nonrevolutionary change. An alternative, narrative framework for telling psychology's story is suggested in terms of guiding themata and the progressive development of four research traditions: representationalist, realist, connectionist, and reductionist.
The triarchic theory of human intelligence provides a broader basis for understanding intelligence than do many, if not most theories of intelligence. The theory is called “triarchic” because it consists of three parts. The first part relates intelligence to the internal world of the individual, specifying the mental mechanisms that lead to more or less intelligent behaviour. This part of the theory specifies three kinds of mental processes that are instrumental in learning how to do things, planning what things to do and how to do them, and in actually doing the things. The second part of the theory specifies at what point in a persons’ experience with tasks or situations intelligence is most critically involved in handling of those tasks or situation In particular, this part of the theory emphasises the roles of dealing with novelty and of automatising mental processing in intelligence. The third part of the theory relates intelligence to the external world of the individual, specifying three kinds of macroprocesses — adaptation, selection and shaping — that characterise intelligent behaviour in the everyday world. This part of the theory thus emphasises the role of environmental context in determining what constitutes intelligent behaviour in a given milieu.
A theory of affordances is outlined according to which affordances are relations between the abilities of animals and features of the environment. As relations, affordances are both real and perceivable but are not properties of either the environment or the animal. I argue that this theory has advantages over extant theories of affordances and briefly discuss the relations among affordances and niches, perceivers, and events.
Contemporary literature distinguishes two ways to defend the claim that cognition is a matter of representations: first, cognition involves representation-hungry tasks; second, cognition involves a complex form of informational covariation between subcomponents of a system with an adaptive function. Each of these conceptions involves a different notion of representation, and promotes a particular view of the architecture of cognition. But despite the differences, each of them aims to support the claim that cognition is a matter of representations on architectural constraints. The objectives of this article are twofold: first, it is argued that architectural constraints do not entail either of those two ways to defend the claim that cognition is a matter of representations; second, it is claimed that both notions of representation share an objectionable common element—namely, the idea of a model that grounds the representational reading—that must be abandoned, in favor of a more economical explanation in terms of causal relations, in order to get a clear view of cognition.
Modern cognitive psychology presents itself as the revolutionary alternative to behaviorism, yet there are blatant continuities between modern cognitivism and the mechanistic kind of behaviorism that cognitivists have in mind, such as their commitment to methodological behaviorism, the stimulus-response schema, and the hypothetico- deductive method. Both mechanistic behaviorism and cognitive behaviorism remain trapped within the dualisms created by the traditional ontology of physical science— dualisms that, one way or another, exclude us from the "physical world." Darwinian theory, however, put us back into nature. The Darwinian emphasis upon the mutuality of animal and environment was further developed by, among others, James, Dewey, and Mead. Although their functionalist approach to psychology was overtaken by Watson's behaviorism, the principle of animal-environment dualism continued to figure (though somewhat inconsistently) within the work of Skinner and Gibson. For the clearest insights into the mutuality of organism and environment we need to set the clock back quite a few years and return to the work of Darwin and the early functionalist psychologists.