In visual word recognition tasks, digit primes that are visually similar to letter string targets  are known to facilitate letter identification relative to visually dissimilar digits ; in contrast, with letter primes, visual similarity effects have been elusive. In the present study we show that the visual similarity effect with letter primes can be made to come and go, depending on whether it is necessary to discriminate between visually similar letters. The results support a Bayesian view which regards letter recognition not as a passive activation process driven by the fixed stimulus properties, but as a dynamic evidence accumulation process for a decision that is guided by the task context.The online version of this article (doi:10.3758/s13423-015-0826-3) contains supplementary material, which is available to authorized users. To read a word, the letters comprising the word must be identified. There is a general consensus that the word recognition process involves abstract letter identities, which allows skilled readers to recognize letters across variations in allography  and font . Beyond this general consensus however, the letter recognition process in current visual word recognition models is not very well specified . Recently, using the same target words, Kinoshita, Robidoux, Mills, and Norris : These primes facilitate the recognition of the target word (MATERIAL), much more than primes that contain visually dissimilar digits/symbols , visually similar letters , visually dissimilar digits , and visually dissimilar letters . Critically, the substituted letters and digits were matched on confusability with the target letter. Despite being matched on the degree of visual similarity, the amount of priming effects produced by digit (leet) primes was dependent on visual similarity, but the amount of priming produced by letter primes was not.In Kinoshita et al.’s  masked pletters must be distinguished from each other so that the task requires that each letter  contributes evidence only for itself, and not for other letters . That is, whether the visual similarity between two symbols  produces priming is not determined solely by the degree of physical similarity between them, but is modulated by the nature of evidence required to make the decision – here, by whether the symbol H or 4 is contained in the set of target symbols from which the symbol A needs to be distinguished.Kinoshita et al. argued that this puzzling dissociation is explained naturally by a Bayesian view of word recognition  always consisted of three-letter strings comprised of the letters A, B, I, and S . The critical manipulations concerned the nature of primes in the “Same” condition (where the referent and the target strings were the same), crossed with the nature of “Different” targets (Target context). There were four critical within-participant prime conditions resulting from a factorial manipulation of Prime type (Letter or Digit) and Similarity . In addition to the four critical conditions, we included an Identity prime condition as a check on our manipulation. Target Context was a between-participant manipulation. In the Overlapping Target Context, the targets on “Different” trials were comprised of the Similar prime letters; in the Distinct Target Context, they were comprised of letters that did not overlap with the Similar or Dissimilar letter primes . The dependent variables were response latency and error rate.The critical stimuli were 24 letter-string targets, with each item consisting of three uppercase letters with no repetitions. Each target contained the letters A, I, S, or B. These letters were chosen because they had digits that resembled them , which were used to construct the Similar Digit primes . In addition to the visually similar digits, for each of the letters, we chose a visually dissimilar digit , a visually similar letter , and a visually dissimilar letter . These letters were chosen from a wider range of items selected by consulting Mueller and Weidermann’s  letter cFor each target string, five primes were generated. The four critical prime conditions were a factorial combination of the factors Similarity (Similar vs. Dissimilar) and Prime Type (Letter vs. Digit). In the Similar-Letter condition, the prime was constructed by substituting each letter in the target with its associated similar letter . In the Dissimilar-Letter condition, the prime was constructed by substituting the associated dissimilar letters . The same procedure was used to generate the Similar- , and Dissimilar-Digit primes . The fifth, Identity, prime  condition was included as a manipulation check and will not be discussed in the analysis.On the “Same” trials, each target was simply the referent presented 1.2 times larger . On the “Different” trials, the targets consisted of three letters that were different from the referent. In the Overlapping Target Context, the “Different” targets consisted of the letters that appeared in the Similar letter primes ; in the Distinct Target Context, the “Different” targets consisted of the letters C, Z, E, and Y, which were not used in any primes or referents .The entire set of stimuli is listed in the Participants were tested individually or in pairs, seated approximately 60 cm away from the stimuli presented on a flat-screen monitor. Each participant completed 240 test trials consisting of 120 “Same” and 120 “Different” trials, presented in two half blocks with each half block containing an equal number of “Same” and “Different” trials, and an equal number of trials from each prime conditions. There was a self-paced break between the blocks. The trial order was randomly generated for each participant.Participants were instructed that on each trial they would be presented with a referent, followed by a target, and that their task was to decide whether the target was the same as or different from the referent, as quickly and accurately as possible. No mention was made of the prime. They were instructed to press a key marked “+” on a response pad for “Same” response and a key marked “−” for a “Different” response.Stimulus presentation and data collection were controlled by the DMDX experimental software  in 10-point Courier New Font for 1 s. The referent disappeared, and the forward mask was replaced by the prime presented in uppercase letters in 10-point Courier New Font for 40 ms, which in turn was replaced by the target presented in uppercase letters in 12-point Courier New Font until the participant’s response. The prime and the target were presented in different-sized fonts to avoid physical continuity. Participants were given feedback (“Wrong response” message on the screen) only when they made an error on the trial.The mean reaction times (RTs) for the correct trials and the error rates for the five prime conditions in the two contexts (differing in the nature of the “Different” targets used) for the “Same” trials are shown in Table The RT data were analyzed using linear mixed effects modeling Baayen, . The preThe data were submitted to a linear mixed–effects model using the lme4  + (Similarity | target), which confirmed the presence of a Similarity by Context interaction for Letter primes , but not for Digit primes . As the predictions from the activation-based and Bayesian accounts related to the simple effects of similarity for the four Prime Type by Context conditions, we further fit the reaction times from each cell to a model of the form invRT~Similarity + PrevRT + (Similarity | Subject) + (Similarity | target). The results are consistent with the Bayesian account, but not the activation-based account. For digit primes, both the Distinct Target Context and Overlapping Target Context produced significant Similarity effects . For Letter primes, the Distinct Target Context produced a significant Similarity effect  while the Overlapping Target Context did not .The results of the model are summarized in Table The error data were analyzed using a logit mixed model Jaeger,  with theThe “Different” trials were not analyzed, as the predictions concern only the “Same” trials.The present study used a same-different letter string match task and showed that it is possible to obtain an effect of visual similarity with letter primes, depending on context. When the “Different” targets were made up of letters from the primes (the Overlapping Target Context), visually similar letter primes  produced no more priming than visually dissimilar letter primes , consistent with the lexical decision task  need to be distinguished as in the Overlapping target context, the form of the letter H does not contribute evidence for the presence of the visually similar letter A, because it serves as evidence for the competing hypothesis that the input is the letter H. In contrast, in the Distinct target context, the letter H need not be distinguished from the letter A, and hence its visual similarity to the letter A can contribute towards the evidence that the input is the letter A. This modulation of similarity effects by Target context was specific to the letter primes: Digit primes showed a robust effect of similarity, irrespective of target context, since digits never appeared in the referents or targets in either target context – that is, it was never necessary to consider a hypothesis that the input was a digit.One alternative explanation of the observed results is in terms of response bias. That is, in the Overlapping context in which the letters HRL appeared as “Different” targets, the prime HRL caused a bias towards responding “Different” and this offset the priming benefit due to its similarity to the referent/target ABI. As noted in the Introduction, there is extensive evidence against the response bias explanation for absence of priming


Advances in neuroscience are underpinned by large, multicenter studies and a mass of heterogeneous datasets. When investigating the relationships between brain anatomy and brain functions under normal and pathological conditions, measurements obtained from a broad range of brain imaging techniques are correlated with the information on each subject’s neurologic states, cognitive assessments and behavioral scores derived from questionnaires and tests. The development of ontologies in neuroscience appears to be a valuable way of gathering and handling properly these heterogeneous data – particularly through the use of federated architectures. We recently proposed a multilayer ontology for sharing brain images and regions of interest in neuroimaging. Here, we report on an extension of this ontology to the representation of instruments used to assess brain and cognitive functions and behavior in humans. This extension consists of a ‘core’ ontology that accounts for the properties shared by all instruments supplemented by ‘domain’ ontologies that conceptualize standard instruments. We also specify how this core ontology has been refined to build domain ontologies dedicated to widely used instruments and how various scores used in the neurosciences are represented. Lastly, we discuss our design choices, the ontology’s limitations and planned extensions aimed at querying and reasoning across distributed data sources. In neurosciences, imaging plays a central role providing information about brain structure and function. In particular, magnetic resonance imaging (MRI) generates anatomical and functional information on the healthy or diseased brain and is a cornerstone of cognitive neuroscience  relate aspects of brain morphology to human behavior and cognitive performance levels and (ii) investigate the underlying neural mechanisms. The NeuroLOG projectThere are several international efforts addressing the representation of “cognitive neurosciences” information. For our purposes, to model instruments we need to combine abstract and concrete terms. Indeed, if we consider the NCBO BioPortal  several ontologies were relevant: from the 369 published ontologies, 104 concern methods and tools for evaluating brain functions  and 148 refer to brain functions .We analyzed the nine most relevant ontologies , in order to determine how pivotal concepts such as ‘Instrument’ and ‘Assessment’ were modeled. We concluded that these ontologies do not describe the internal structure of instruments because the latter are considered as physical objects  or a ‘Medical Device’ (UMLS)). The NIFSTD ontology  adopts the most interesting approach, in which a classification of “Assessments” (inherited from BIRNLex) is provided as a subclass of “Protocol application” which in turn is a subclass of “Planned process” . However the part addressing assessment instruments is neither complete nor fully consistent. Instruments are assessments without explicit models. Moreover, the notion of sub-instrument is not present and then no explicit relation exists between the global score provided and the underlying sub-instruments scores that compose it. Variables measured by an instrument are not introduced and finally there is no explicit distinction between the tool for investigation (i.e. instrument), the investigation process (i.e. instrument assessment) and the score obtained. These models represent neither the internal structure of instruments nor the resulting scores, assessment actions and variables used to refer to the qualities measured. We strongly consider that models with these characteristics are required and should be managed consistently across the broad range of existing instruments. Our aim with our instrument ontology was to formally represent all these concepts.Our prime objective is to facilitate the sharing of cognitive and behavioral scores in the federated systems that underpin multicenter research studies and clinical trials in the neurosciences. As with the ADNI and HCP initiatives, the intention is to correlate cognitive and behavioral scores with imaging markers and biomarkers.Many different “assessment instruments” are used in the neurosciences. This diversity is driven by the need to capture the many facets of human brain function and behavior and the very broad spectrum of symptoms associated with brain dysfunction. It also results from clinicians’ and psychologists’ on-going efforts to improve existing instruments and introduce new ones, in order to assess brain functions in ever greater detail  and relations  for structuring any kind of domain by specialization. DOLCE is supplemented here by a few formal ontologies, such as a formal ontology of artifacts  for each domain concerned. Lastly, at the most specific level, core domain ontologies are in their turn refined via the introduction of specialized, domain-specific concepts . This multilevel abstraction approach consists in applying the same set of generic principles to the conceptualization of domains covered by application ontologies. The main objective here is to facilitate the development and maintenance of ontologies and to ensure a high degree of cross-domain consistency ).The ontology presented here includes modules situated both at the intermediate level of core domain ontologies and at the most specific level of domain ontologies. Our core domain ontology . Its implementation (specification and use) as a component of a specific federated architecture for facilitating data sharing in distributed data centers has been described in  modeling three specific instruments that are widely used in clinical practiceHere, we provide a brief reminder of the main structuring principles and concepts that underlie important modules reused in the present work. An excerpt of our foundational concepts’ taxonomy is shown in Fig. universals (e.g. “being a car”).The DOLCE ontology  are typical Endurants. Besides Physical objects, DOLCE considers a class of Non-physical Objects. The distinction between Physical Objects and Non-physical Objects corresponds to the difference between two realities or modes of existence. Basically, Non-Physical Objects exist insofar as agents conventionally create them and speak about them. The domain of Non-Physical Objects covers entities whose existence depends on either an individual  or a community of agents .Endurantsprimarily directly related to time. Perdurants are generated by Endurants: the latter temporarily participate in (participatesInDuring) the former.Perdurants are entities “occurring in time”, which are Endurants and Perdurants have Qualities that we perceive and/or measure (e.g. the weight of a printed copy of this article and the time spent reading this article). Note that Qualities are inherent to the entity that bears them, since they are characteristic of their bearer and present throughout its existence.mereological sums (sums of parts) of Qualia. For instance, the Region of colors named ‘red’ may be considered as having for parts the Qualia named “Scarlet” and “Crimson”. The sum of all Qualia associated with a Quality kind is called a  Space. Spaces in DOLCE are similar to Gärdenfors’ conceptual spaces .Qualities temporarily occupy positions within Regions. Some Regions called Qualia  are defined as atomic Regions (e.g. “25 g in weight” and “20 min in duration”). Other Regions are Four sub-domains of Particulars are distinguished see Fig. :Endurantability and action at our disposal (and these are not present in DOLCE). Similarly, to model the act of taking a patient’s temperature with a thermometer, we need the generic notions of instrument and measurement instrument. In the remainder of this section, we complete DOLCE with some generic modules needed to conceptualize our application domain.As is commonly the case, the development of ontologies in a particular domain requires the prior extension of the foundational resources. For example, in order to conceptualize the assessment of a subject’s ability to walk a certain distance, we need to have the generic notions of document. The IEC module is a core ontology in the domain of information and information-bearing entities. It extends DOLCE by introducing three main kinds of entities:Inscriptions (e.g. printed texts and computer files) are physical knowledge forms materialized by a substance  and inscribed on a physical support (e.g. a sheet of paper or a hard disk). In addition to their materiality, one important characteristic of Inscriptions lies in their “intentional” nature (meaning that these entities count as other entities). For example, Inscriptions count as Expressions.Expressions  are non-physical knowledge forms ordered by a communication language. Expressions are physicallyRealizedBy Inscriptions and, like Inscriptions, they are intentional entities conveying contents for agents.Conceptualizations consist of the ultimate means by which agents can reason about a world. Two kinds of Conceptualizations are distinguished: Propositions, as a means of describing states of affairs, and Concepts, as a means of classifying entities. Note that, as for the practical semioticsIn the present work, we consider intangible  instruments as contents of documents specifying rules for measuring the subject’s state, behavior or brain function. These instruments contrast with physical instruments (e.g. thermometers and computed tomography (CT) scanners). To model these conceptual contents, we reused the Inscription & Expression & Conceptualization (IEC) module  and then in controlling it in a rational way  are distinct from Conceptual Actions .According to another classification dimension, Physical Actions . However, participation roles do not define the essence of the entities playing these roles. For example, an entity playing the role of an Agent needs to possess a disposition (or capacity) to intentionally control events. This type of disposition may be owned by various entities: a human being, an organization, a robot or a sophisticated sensor. Entities playing the role of an Instrument are generally technical artifacts that have been intentionally produced for that very purpose. These artifacts may be physical sensors or conceptual measurement procedures. In the next section, we introduce a set of concepts to reflect the essence of the artifacts.Various entities participate in these Actions in different ways, in the sense that they have different roles. As a complement to DOLCE, our “Participation role” module specializes the participation relation participatesInDuring to account for specific ways in which Endurants participate temporally in Actions . In turn, these relations are used to define entities intentionally made or produced for some reason” , we reuse concepts from our ontological module “Function &Artifact”  are considered: to convey an emotion and be of aesthetic interest (for works of art) or enable their author (or another agent) to do something . The latter are Artifacts to which a Function is ascribed, given that a Function is defined as an “” Kassel .Within Technical Artifacts, Private Artifacts are distinguished from Social Artifacts according to whether the function in question is ascribed by an individual or a community of agents.Artifacts are commonly defined as “Hilpinen . To be a” Kassel . Accordiorigin of their existence  rather than a mode of existence  to assess a subject’s behavior and cognitive performance. To model these situations, we consider two main entities: the actions carried out  and the instruments used. In Section 3.1, we detail the part of the core ontology that conceptualizes these two entities. Instruments are structurally and functionally complex entities. They are composed of items (named “instrument variables”) that measure specific aspects of the subject’s neurologic state, behavior or cognitive performance in the domain explored by the instrument. The administration of instruments is thus further decomposed into variable assessments, which consist in asking questions or requesting tasks to be completed. These assessments yield in scores, which are derived from the subject’s responses or behavior. In Section 3.2, we add to our presentation of the core ontology by conceptualizing “instrument variables” and “variable assessments’.Instrument-Based Assessment actions consist in acquiring data from Subjects by administering an instrument.The conceptualization of these actions has a pivotal role in our ontology by connecting a large number of entities see Fig. : a Healtitems that prompt the performance of measurements; these actions and their results are detailed in Section 3.2. In our ontology, we adopt a common classification of Instrument-based Assessments that depends on the type of acquired data . However, this classification does not induce formal rules about who is allowed or not to administering them.There are generally two main forms of Assessments. The first are called Test-Based Assessments and solicit an authentic production from the Subject, e.g. a reflex, a performance . The second are called Questionnaire-Based Assessments and consist of an interview or an inventory. In all cases, these are complex actions whose structure is based on that of the instrument administered. At the finest level of decomposition, one finds Intangible, i.e. propositional contents, including “clearly defined methods and instructions for administration or responding, a standard format for data collection, and well-documented methods for scoring, analysis, and interpretation of results” .Functional, i.e. tools enabling to explore entities related to the Subject’s state. These categories of entities correspond to the Instrument's Domain(s).Social, i.e. intentionally created, adopted for use, adapted and maintained by a community that ascribes them with the status of a standard.Instrument-Based Assessments are organized around the administration of an “Assessment Instrument” . These Instruments are intentionally designed to assess the subject’s state under one or more dimensions. According to our theory of artifacts (cf. Section 2.4), Instruments clearly are Technical Artifacts that may be described in three respects. Instruments are:As intangible, propositional content, an Instrument is expressed in language and is physically inscribed on a medium of some kind. Indeed, Instruments are usually physically materialized by several documents.Structurally, an Instrument appears as a list of items, each of which corresponds to a specific aspect of the subject’s state. Questions or tasks are associated with each item assessing the subject’s performance levels. We refer to these parts as “Instrument Variables”, in order to emphasize that they are measurement tools and that they bear values (which vary from one subject to another). But some Instruments have a more complex structure. Given that (i) brain function is constituted by a number of smaller elementary processes and (ii) the most complexvs. Multi-domain Instrument). The WAIS-III is a typical example of a Multi-domain Instrument; it explores a whole set of domains, like “verbal comprehension”, “working memory”, “perceptual organization” and “processing speed”. This reflects Wechsler’s definition of intelligence as “the aggregate or global capacity of the individual to act purposefully, to think rationally and to deal effectively with his environment”  are reifiedIn this section, we showed how instruments and the administration of instruments were conceptualized. The following section focuses on the Instrument Variables and the latter’s two main functions: (i) to describe precisely what is being explored and measured and (ii) to relate the scores to the context in which the assessment is made.An Instrument is composed ultimately of Instrument Variables  that prescribe a specific measure. As with the conceptualization of Instruments, we consider two main entities: Variables and the measuring actions associated with them  Fig. .Fig. 3CoVariables are Artifacts  with specific functions. As for Instruments at the most general level, our conceptualization neglects the documentation associated with Variables (e.g. the questions that have to be asked and instructions on how to execute tests) and focuses on functional descriptions. In functional terms, a Variable explores a Domain that usually corresponds to or refines the Domain explored by the corresponding instrument. Depending on whether this Domain coincides with the Instrument’s Domain or it relates to other similar entities , one distinguishes between a Main Variable and a Secondary Variable, respectively. Furthermore, a Variable aims at measuring a dimension or property of these Domain entities, which we conceptualize as a Quality . The explored Domain and the measured Quality constitute the functional information attached to a Variable.Expanded Disability Status Scale (EDSS) neurologic instrument measures the subject’s neurologic state on a scale that hasForMinimumScaleItem: “0.0: Normal neurologic exam” and hasForMaximumScaleItem: “10.0: Death due to MS”. It is important to note that for a given Quality, a great number of Subjects share the same value as a measurement result.IQ Variable separated into 13 age-dependent groups. Variables are then categorized as Gender-Dependent Variables, Age-Dependent Variables and Cultural-Skill-Dependent Variables. Normative data are often used to quote individual Scores obtained by Subjects. In such a case, Raw Scores are converted to Corrected Scores and Standard Scores by using charts and tables provided with the Instrument.A Variable Assessment action isAProperPartOf an Instrument-based Assessment action. These actions share several properties: they have the same Agent and concern the same Subject. The Variable Assessment actions link scores (as results of measurements) to the measured Variables. Depending on the nature of the explored Domain, Qualities may have as value i) a Number or a Scalar Quale (a Number plus a Unit of Measure) – the corresponding Variable is called a “Numerical Variable”, or ii) coded items of a Scale – the corresponding Variable is called “Coded Variable” see Fig. . NumericThe objective of this section is to illustrate the use of the above-described core ontology to define specific ontologies of instruments through concept specialization. In the previous sections, we described our generic conceptualization of instruments and highlighted the latter’s common structure. In the present section, we show how this core ontology is used to model the MMS , the EDSS and the CDR , We introduce the instruments’ respective general structures and decompose them into sub-instruments and variables. The specific instruments and instrument variables are defined as subclasses of the generic classes of Instruments and Instrument variables. These classes model the common properties of the corresponding instrument and variable instances used at different healthcare institutions. Alternatively, we could have chosen to model these entities as instances and not as classes. However, our ontology was primarily intended for use as a common reference ontology, in order to integrate score data from different neuroimaging centers and obtained from assessment instruments that may slightly differ from one site to another. Modeling the common properties of these instruments as classes is appropriate and provides some flexibility in the definition of local instrument instances.A neuropsychological check-up is based on the observation and application of objective Tests for grading cognitive functions. A neuropsychological examination is structured by the list of the cognitive functions to be tested, e.g. executive function, memory, language, attention, arithmetic, logical reasoning, global cognitive efficiency, movements and visuospatial functions – each of which is explored by one or several Neuropsychological Instruments. Some of the latter may be composed of several Sub-Instruments, each of which is specifically designed to explore a particular cognitive function.The examination performed by a Neuropsychologist as an Agent generates both qualitative and quantitative Scores. The MMS is probably the most widely used neuropsychological instrument in dementia assessment , since it primarily relies on the subject’s actual performance .Hence, the EDSS is both a Test-Instrument and a Neuroclinical Instrument that mainly measures disability in walking and motor control  was developed at the Memory and Aging Project at Washington University School of Medicine in 1979 for the evaluation of staging severity of dementia. The CDR is obtained through semi-structured interviews of patients  and dementia is rated in 6 domains of functioning: memory, orientation, judgment and problem solving, community affairs, home and hobbies, and personal care; each of which is explored by a Sub-instrument . The global CDR score is computed using the Washington University online algorithm.NVA#60 hasForResult a Coded Score equal to “mild dementia”.The instance CDR-Pitié-Salpêtrière Hospital represents a specific CDR instrument used at Pitié-Salpêtrière Hospital . In this case, the A white rectangle represents a domain ontology concept; a gray one represents an instance.We shall first discuss the methodology used to build the ontology and then position our work within the field of ontological engineering in general and the engineering of biomedical ontologies in particular (§5.1). Lastly, we shall focus on our results, the ontology of instruments used in neurosciences, its current content, future extensions and connections with services (reasoning) supported by the model (§5.2).The “multi-abstraction-layer” and “multicomponent” approach adopted here is generally advocated for the design of large, multi-domain ontologies  initiative has federated a large group of researchers around the Basic Formal Ontology (BFO) and the reference ontology of relations  and regions of values  as abstract entities with no spatiotemporal location (Abstracts). In keeping with the notion of a Conceptually, formalization facilitates future ontology extensions, ontology reuse and inter-ontology interoperability (such DOLCE and BFO). However, only dissemination into several domain ontology applications (such as those proposed in this paper) can provide us with feedback on the strengths and weaknesses of our approach.As we saw in Section 4, OntoNeuroLOG covers a wide range of instruments - from tests to questionnaires. Along with the ontology’s scope in terms of domains covered, another important aspect relates to its functional scope (i.e. the kinds of reasoning that it enables). The latter is related to the point of view adopted and the level of detail considered when modeling the instruments.Since our current objective is to share scores within a federation of research centers, we combined a structural description of instruments with a representation of the words used to name the variables and items of scales. Scores are shared through the definition of standard instruments to which locally administered instruments conform to a varying degree. In this respect, it is important to note that today’s ontology representation languages fail to account correctly for our knowledge of instruments. As we have seen, OntoNeuroLOG’s classes represent standard instruments with a standard terminology, whereas a local instrument is conceptualized as an instance of one of these classes. This forces the descriptions of the local instrument and acquired scores to be logically consistent with the description of a class of standard instrument. As a consequence, it is not possible to represent variations of a local instrument with respect to a standard instrument . Indeed, Hoehndorf et al. have shown that it is impossible to correctly represent default knowledge in classes  with which a term is associated , the classes of entities to which these terms refer are generally not conceptualized in the literature. Here, we faced two challenges: firstly, as underlined by  finding instruments that explore a given function or by comparing instrument definitions that change over time (White and Hauan http://www.cognitiveatlas.org/).Again, these aspects show that our instrument ontology is not set in stone and will evolve, with (for example) the development of “cognitive” ontologies  initiative is aimed at harmonizing information provided in the context of Parkinson’s disease.One can also note the recent work on standardization undertaken by the US National Institute of Neurological Disorders and Stroke; the Common Data Elements  reflects a broad, well-understood, clinical state of the art. Moreover, the output of this acquired expertise (in the form of documents describing instruments and variables) matched the clinical procedures applied in three other French university medical centers  that participated in the NeuroLOG project. The fact that about 70 % of the tests incorporated into OntoNeuroLOG were used in all four institutions justifies our on-going efforts to standardize neuropsychological and behavioral assessments.cortical thickness and neuropsychological markers such as memory impairment or severe dementia, and the retrieval of the associated scores from a battery of tests.Secondly, our ontology may be extended to the representation of imaging data and ancillary, behavioral, neuropsychological and cognitive data. It provides a coherent semantic space and a knowledge repository for structuring and designing a new generation of databases and associated services in neurosciences. OntoNeuroLOG may facilitate automatic reasoning and knowledge extraction from appropriately designed and structured databases. An example of a query that can be expressed using our structured ontological framework is the selection of instruments that measure variables related to memory dysfunction, the retrieval of subjects with imaging markers such as Our ontology’s target application is the management of large data repositories in neurology and psychiatry – fields of medicine that are being completely transformed by the recent introduction of multimodal imaging. We consider that the scheme class/instance proposed here offers ontology builders the flexibility needed to seamlessly introduce notions that are currently difficult to formalize . We hypothesize that the development of the brain function ontology backed by some researchers . OWL and Ontospec  files can be downloaded from http://neurolog.unice.fr/ontoneurolog/v3.0/. Information about NeuroLOG project (ANR-06-TLOG-024) can be found on the wiki site at neurolog.i3s.unice.fr/.The ontology ) is available through the NCBO BioPortal ontologies (


A Natural History of Human Thinking. After offering an overview of the book, the paper focusses on one particular part of Tomasello’s proposal on the evolution of uniquely human thinking and raises two points of criticism against it. One of them concerns his notion of thinking. The other pertains to empirical findings on egocentric biases in communication.The paper briefly summarises and critiques Tomasello’s  A Natura There is evidence that a number of non-human animals, ranging from corvids, domestic pigs, and dolphins to great apes, are capable of high-level thinking that is in many ways familiar from that in our own species , humans and at least some other animals also solve some problems and make some decisions by thinking  the ability to cognitively represent experiences to oneself ‘off-line’; (2) the ability to simulate or make inferences transforming these representations causally, intentionally and/or logically; and (3) the ability to self-monitor and evaluate how these simulated experiences might lead to specific behavioural outcomes” : 4.Turning from thinking in general to human thinking, in particular, Tomasello holds that with respect to (1) to (3), unlike other animals, “only humans” are able to (i) cognitively represent and conceptualise identical situations or entities under “differing, possibly conflicting social perspectives (leading ultimately to a notion of ‘objectivity’)”, (ii) “make socially recursive and self-reflective inferences about others’ or their own intentional states”, and (iii) “self-monitor and evaluate their own thinking with respect to the normative perspectives and standards (‘reasons’) of others or the group” (ibid).A Natural History of Human Thinking is to offer an evolutionary explanation of how objective-reflective-normative thinking could emerge from the kind of thinking that humans share with non-human animals.Tomasello calls the uniquely human thinking characterised by (i)-(iii) “objective-reflective-normative thinking” (ibid). His aim in Tomasello calls the thinking that we share with non-human animals “individual intentionality” : 4. IndiTomasello mentions a number of studies that show that, e.g. great apes display individual intentionality. They are able to use cognitive representations of their physical surrounding for causal inferences, represent another agent’s intentional states, and employ the representation to make inferences pertaining to how the individual will act given the mental state she is in. Great apes also monitor their own cognition: based on their certainty about what they know, they assess their chances of success at a task and make decisions accordingly. Great ape thinking, which Tomasello takes to correspond to the thinking in our last non-human ancestors from 5 to 6 million years ago, is hence already relatively sophisticated.It is, however, only geared toward the satisfaction of the animal’s own individualistic needs when it is competing with group mates for valued resources, Tomasello writes. He holds that great apes’ individual intentionality is only self-focussed “cognition for competition” of typically lone-acting creatures : 31.A Natural History of Human Thinking, uniquely human thinking evolved from this self-focussed, individual intentionality as an adaptation for “dealing with problems of social coordination, specifically, problems presented by individuals’ attempts to collaborate and communicate with others” . Tomasello write that while humans’ great ape ancestors lived, just as contemporary great apes, mostly individualistic and competitive lives in which individual intentionality served them just fine, early humans could no longer survive without collaborating with each other in dyadic units when out foraging. The result was a species-unique selection for and evolution of skills and motivations to engage in cooperative activities, which relied on a “dual-level structure” consisting of “joint goals” i.e. goals that both interactants shared and knew they shared with each other—and “joint attention” i.e. both interactants were attending to the same thing and knew they both did—forming a “joint intentionality” of the moment  by the tree.To further strengthen conformity and facilitate collaborations within the group, early humans’ iconic gestures became substituted with linguistic conventions, which, unlike early humans’ gestures, supported arbitrary connections between signs and referents allowing for abstract conceptualisations, Tomasello writes. Since the linguistic conventions were passed on to the next generation, the children of the group didn’t have to reinvent conceptualisations but inherited from their social environment various different ways of classifying the world for themselves and others. They learned to view the same situation and entity simultaneously under different guises, e.g. as an antelope by the tree, as an animal by the tree, as food by the tree, etc. This knowledge, accumulated over time in the social environment via reliable teaching and learning mechanisms, introduced In addition, to be a good partner in collaborations, cooperative argumentation, and shared decision-making, which was vital for survival, individuals now also often had to make explicit in language their own attitudes toward particular contents (e.g. whether they were certain or doubtful about a proposition) and the reasons for their claims. To ensure the intelligibility and rationality of those linguistic acts and reasons, modern humans needed to simulate in advance the cultural group’s normative judgments of the intelligibility and rationality of the communicative acts and reasons in order to align them with the group’s standards.collective rather than merely second-personal, joint intentionality. They led to the evolution of reflective, ‘objective’, and normative, i.e. uniquely human thinking, Tomasello writes.In their self-reflection and self-monitoring, humans now referred to the normative perspective of all users of the linguistic conventions. For each of them took it that to be a member of the group, one must behave as the group as a whole does, i.e. follow the norms to which all are committed, or else be ostracised. Modern humans thus referred in their thinking and action planning to the “agent-neutral”, “‘objective’ perspective engendered” by their “cultural world” that then “justified personal judgments of true and false, right and wrong” : 115. ThHe ends the main discussion in his book by emphasising that skills of shared intentionality, e.g. the ability to engage in joint attention and form joint goals, are not innate but biological adaptations that come into being during ontogeny as the individual uses them to collaborate and communicate with others. This means that without social interactions during childhood, and without collectively created and transmitted cultural environments, including adults and all their cultural equipment (e.g. language), joint and collective intentionality won’t develop. As a result, uniquely human thinking won’t emerge either, Tomasello concludes.A Natural History of Human Thinking is clearly written and a rewarding reading for anyone interested in the evolution of human cognition. The book fills an important gap in the literature by offering an empirically and theoretically well-supported account of the evolution of a very specific aspect of human cognition, i.e. objective-reflective-normative thinking, and its link to uniquely human cooperation.The central argument of Tomasello’s book that uniquely human thinking evolved from individual intentionality in two steps that crucially involved a human-unique form of cooperation is illuminating and plausible. Overall While I’m largely sympathetic to Tomasello’s shared intentionality proposal, I have reservations about some of the details. I will focus only on his story about the evolution of one particular component of “objective-reflective-normative thinking”, namely subjects’ “socially recursive and self-reflective inferences about others’ or their own intentional states” : 4. I wiIt is a common view that reading other people’s minds and engaging in socially recursive thinking evolved in competitive social worlds for Machiavellian purposes, i.e. for the purpose of or for guarding against deception and manipulation .How are they able to know this? Tomasello argues that in the successful performance “in the object choice task […] the recipient [of the message] infers that the communicator Suppose that early humans were indeed, as Tomasello suggests, forced to cooperatively communicate. If subjects need to engage in socially recursive thinking in order to cooperatively communicate (e.g. in the object-choice task), then Tomasello’s proposal that such thinking evolved in early humans for enabling cooperative communication seems plausible.intends that she know” that the sought-after object is in the bucket (There is, however, reason to be sceptical about the claim that socially recursive thinking is required for this purpose. For instance, Tomasello holds that in the object-choice task, in order to grasp the communicated message, the recipient needs to infer that the communicator intends that she know that the sought-after object is in the bucket. Since the recipient of the message in the developmental psychology study that Tomasello cites is a 12-months-old infant : 52, in e bucket : 57.p requires the possession of some concept of knowledge because the propositional content of the intention explicitly refers to knowledge. Yet, there is no evidence that children acquire the concept of knowledge before the concept of belief (Butterfill This proposal lacks psychological plausibility, however. An understanding of the intention that S knows that Recent studies involving the violation-of-expectation paradigm and gaze tracking do indicate that infants as young as 7–15 months are able to register other subjects’ false beliefs (Onishi and Baillargeon implicit, i.e. automatic and unconscious in nature (see, e.g. Low and Perner explicit representations of other’s mental states, i.e. representations that figure in subject-controlled and conscious processing (Pacherie But, on the basis of further experimental results, it is widely accepted that this early understanding of mental states is at best Pacherie .Since that is so, it is fair to say that the 12-months-olds in the object-choice task also don’t engage in explicit socially recursive thinking. If they don’t do so, however, then, against Tomasello’s claim, such thinking isn’t required for cooperative communication. For, as he grants, these infants do engage in cooperative communication in, e.g. the object-choice task.Indeed, suppose that the child involved in the task makes the default assumption that in general an adult subject S will help her achieve her goals. When she is searching for the hidden object, and sees S point to one of the buckets, she will then infer from S’s behaviour that the object she is currently looking for is in the pointed-to bucket. To draw this inference, the child might simply treat S as a mindless machine that has the function to assist her in her projects and point her to the location of objects that she is looking for. That is, the child doesn’t need to represent, explicitly or implicitly, any mental states, let alone engage in socially recursive thinking in order to find what she is looking for. Similarly, if S makes the default assumption that making eye contact with the child and then pointing to an object will help her find the object, then S will be able to successfully communicate to her where the object is without any kind of meta-representational processing. Neither the infant nor S needs to engage in such processing to cooperatively communicate.A Natural History of Human Thinking, for the socially recursive thinking whose evolutionary origin he wishes to explain requires explicit representations of mental states. It requires explicit representations because, as mentioned above, for Tomasello, instances of “thinking”, including socially recursive thinking, are “system 2 processes” (3Furthermore, even if subjects had to start, e.g. implicit socially recursive thinking in order to cooperatively communicate, this still wouldn’t help Tomasello with his project in ocesses”  4. And socesses”  dual-sysocesses” : 4, explFinally, since Tomasello’s avowed focus is on system 2, i.e. explicit thinking, his proposal that socially recursive thinking evolved because it is required for cooperative communication becomes also questionable from a phenomenological point of view. For it is often noted in the literature on social cognition that if the inferences involved in producing mental state attributions were “explicit, they should show up in our experience”, but “they rarely do” (Gallagher and Hutto must think […] about their communicative partner thinking […] about their thinking [emphasis added]” (4There is no reason to believe that things were any different in early humans. That is, early humans too will presumably have been able to engage in cooperative communication without explicit, conscious meta-representational processing. But if that is so, then Tomasello’s claim that “human cooperative communication is evolutionarily new” in that individuals “ added]” : 59, whe added]” : 4, is fThere is another reason for being sceptical about Tomasello’s proposal even if we ignore the distinction between implicit and explicit thinking. It relates to a particular kind of bias in communication. I will say a bit more about the bias first before returning to Tomasello’s view.A number of studies show that in communication interactants tend to exhibit an “egocentric bias”: they have the tendency to take their own perspective to be automatically shared by the other (see, e.g. Nickerson For example, Savitsky et al.  investigSimilarly, in a second study, subjects who tried to convey particular “meanings with ambiguous phrases overestimated their success more when communicating with a friend or spouse than with strangers” (Savitsky et al. decrease in interactions with cooperative people with whom one is familiar and interdependent, e.g. spouses and friends, rather than strangers. In these situations, subjects seem to take their own perspective to be automatically shared by the other, and there is a trend away from perspective taking.These findingsPrima facie, this is puzzling, for an egocentric bias threatens cooperative communication and increases the potential for miscommunication. Why do subjects nonetheless exhibit such a bias especially when interacting with close others?The following proposal seems plausible. When interactants share the same environment and jointly attend to the same thing, what is accessible and salient to the communicator will usually be equally accessible and salient to the recipient. As a result, in these situations, an egocentric approach will support successful communication without requiring communicators and recipients to model each other’s perspective or mental states (Pickering and Garrod Does the recipient’s subsequent adjustment to the perspective of the communicator rely on representing his perspective?could directly compute each other’s perspective, in cooperative groups, they both will receive plenty of feedback from each other on their performance. This will allow them to update their semantic representations on the basis of individual successes or failures to convey and comprehend messages without having to compute each other’s perspectives and knowledge states themselves. Social feedback mechanisms thus allow the interactants to ‘off-load’ cognitive work, i.e. computations pertaining to each other’s perspective, onto their social environment (Young It is well known that simultaneously forming and entertaining distinct mental models is difficult (see, e.g. Johnson-Laird nt Young .There is evidence that such an externalisation of computations does indeed occur. Studies show, for instance, that listeners often ask speakers to clarify the reference of a term despite the fact that if they adopted the speaker’s perspective, they would find that their mutual knowledge uniquely defines the referent (Keysar et al. Note that once the referent has been fixed interactively, and a precedent has been set, the subsequent use and comprehension of the communicative act won’t require mutual perspective taking or socially recursive thinking either. For interactants may then on each occasion refer back to the precedent.Empirical work supports this view. Studies show, for instance, that listeners tend to interpret a referential expression according to naming precedents set by a previous speaker even when they are aware that the current speaker was not in fact present at the time when the precedents were established (Barr and Keysar More generally, given the way Tomasello characterises early humans’ social life, one would expect that particularly the kind of early humans that he envisages externalised computations about each other’s mental states and exploited the feedback mechanism involved in their interactions. For, as noted, he holds that early humans lived in “small” groups and were “interdependent with one another in an especially urgent way” : 137. FuNow, in social interactions in which participants are interdependent, mutually assume that the other is cooperative, and mutually make an effort to ensure communicative success, communicators will evidently refrain from ambiguous and deceptive communicative acts. Furthermore, they will aim to make information transmission as efficient as possible, because this will, given their interdependence, benefit both interactants. Since perspective taking and thinking about thinking are computationally complex and cognitively effortful processes for both parties (Apperly et al. Unlike Tomasello’s view, this proposal manages to accommodate the data on a stronger egocentrism in cooperative communication with close others. For, assuming that Tomasello is right about his characterisation of early humans’ social environments, then due to the interdependence of early humans and the small size of the groups in which they lived, early human communicators and recipients will have received copious feedback from each other on their performance. These aspects of early humans’ social environments will have allowed early humans to be more egocentric and assume by default that close others share their own perspective. Since an egocentric bias will for them also have made their cognitive processing in cooperative communication with close others computationally more economical and tractable, it seems likely that this is why the bias evolved and is still present in contemporary humans.enabling cooperative communication. It is more probable that the early humans that he considers evolved the disposition to anchor their interpretation of each other’s communicative acts onto their own egocentric perspective7In sum, then, the preceding points suggest that cooperative communication doesn’t necessarily require simulating what the other is thinking about one’s own thinking. They cast doubts on Tomasello’s proposal that socially recursive thinking evolved in groups of highly interdependent and cooperative individuals for But why then did socially recursive thinking evolve? While this isn’t the place for a detailed answer, the early development of meta-representational capacities in infants, who aren’t typically confronted with uncooperative interactants, suggests that these capacities, including socially recursive thinking, evolved not so much for enabling cooperative communication, as Tomasello suggest, but rather for allowing infants to deal with another pressing problem they face, namely social learning.8Social learning frequently requires that the learner “understand that a performance is stylised, that a crucial step has been slowed down, exaggerated, or repeated to make it more overt” Sterelny : 146. ToA Natural History of Human Thinking makes a plausible case for the view that the apparent uniqueness of our thinking is ultimately grounded in our species-specific dispositions and abilities to engage in collaboration and cooperative communication with each other. His overall argument would have benefitted if attention had been paid to the distinction between explicit and implicit thinking, and if the data on egocentric biases in communication had been considered. Having said that, Tomasello’s ideas on what makes human thought unique and what explains its origin are intriguing and likely to shape future debates on theses issues.9Tomasello’s new book


With her sexual configurations theory (SCT), van Anders  wants toI agree with van Anders that the conventional conceptualization of sexual orientation has a number of shortcomings. Indeed, why would the sex of our desired partners be the prime organizing feature of our sexuality? What is the role of partners’ genderedness or of other major person characteristics? “Biological sex” is not as clear-cut a category to justify its monopoly position in sexual orientation theory in the first place. Obviously, reliance on (difference or similarity between) discrete binary categories ill-caters for those who do not fit them, such as intersex and trans people. Moreover, Kinsey scores are extremely crude. And they are ill-catering for asexuality and inconsiderate of solo sexual experiences. Besides, “the score” assumes stability where we know dynamic fluidity exists. And indeed, the empirical differences in scores on the various domains of sexual orientation  add to the confusion of what we are exactly referring to when talking about “sexual orientation.”Because of all these problems, van Anders proposes SCT, aimed to better “address the complexities of actual people’s sexualities” and she wants to do so in an inclusive, norm free, and non-discriminatory way. She claims SCTs usefulness for self-knowledge and sexual minorities’ empowerment, as well as for neuroendocrinological, social, and health-related research methodologies and clinical practice. I gladly take the opportunity to share why I feel she has come a long way in reaching those goals while at the same time not fully fulfilling her ambitious promises. First, a short description of the SCT is in order.The key premise of the SCT is that sexual orientation diversity is fundamentally multidimensional. Gender, partner number, and the eroticism/nurturance distinction are added to “biological sex” as prime dimensions of one’s sexual preference. The parameter eroticism/nurturance mixes with partners’ gender/sex and partner number to allow for variability of combinations. In addition, the sexual configuration may comprise a (any?) further number of parameters (“parameter n”) such as age of the preferred partner(s), preference for consent, and/or physical violence and/or forms of kink.The assembly or notation of one’s sexual configuration implies scores on each dimension or parameter. The total mapping of scores on the various parameters is one’s configuration. There are two main strands in one’s sexual configuration, one relating to partnered and one to solitary sexuality. Unfortunately, van Anders limits herself to the first strand only in her article. Parameters gender/sex, partner number, and eroticism/nurturance are most comprehensively described.The parameter gender/sex deals with someone’s orientation to male and/or female sexes and/or genders. In contrast to Kinsey’s one-dimensional line, van Anders introduces a widening/narrowing spiraling circle. Actually, she introduces three of them: one for attraction guided by partners’ sex, one by partners’ gender, and one by a combination of both. On each of these spiraling circles, attraction (or behavior/status) can vary in terms of binarity, specificity, and strength. A non-binary gender/sex attraction concerns, for example, people who challenge the gender/sex binary or exist outside of it . Together with attraction to cis men or women and/or traditional femininity/masculinity, these options are positioned at the specific side of the circle. Non-specifically, “pan”-oriented individuals lean towards any gender and/or sex. When one’s gender/sex orientation is less strong , partners’ gender/sex is of less importance compared to, for instance, other characteristics such as power, humor, servitude, just to name a few .The parameter partner number deals with preference for  zero, one, two, or more partners. This parameter allows for asexual, monogamous, bisexual, and polyamorous orientations (or statuses). Again, the possible variation in terms of binarity, specificity, and strength can be scored. A binary orientation refers to a distinct preference for either one or more partners while someone with a non-specific orientation could not care less about their number. Finally, orientations can vary according to preference for eroticism versus nurturance, a distinction which may again differ in terms of binarity, specificity, and strength. When multiply oriented, one can be erotically interested in some but nurturantly in other partner(s). Whereas the concept sociosexuality refers to a general liking of having erotic sex with multiple partners, the SCT permits all possible combinations. The SCT is also sensitive to, for instance, “Gray-A” by allowing for scoring the strength and thus degree of asexuality instead of assuming a distinct either-or.Scores on all these dimensions together form one’s sexual configuration, which is a complex of different, interconnected but distinct orientations, of “multiple multifaceted facets” of one’s sexuality. A sexual configuration is clearly much more than a numbered dot on a line. It is a multidimensional conceptual space squiggly marked out between assembled scores on the various parameters that I visually imagine standing there like spiraling cones in what van Anders calls the Sexual Configuration Landscape, which I picture like an undulating blanket tied up between a potentially infinite number of parameter stalagmites.First and foremost, I feel van Anders must be lauded for a clever, creative, geometrically cunning, and inspiring intellectual exercise. She has no doubt managed to tackle some of the problems with conventional conceptualizations of sexual orientation. Notably, the introduction of non-binary positions and attractions makes the theory fully useable for and inclusive of categories of “real people” otherwise left out and considered difficult to locate. Granting gender a conceptual space next to biological sex has done away with objectionable bio-essentialism. And the introduction of multiple parameters in combination with the possibility to vary on them in terms of specificity and strength has hugely expanded the possible number and subtleties of orientations and given enormous depth to our thinking about diversity. With its openness also to punishable, paraphilic, and “grey” attractions, it is inclusive beyond what any theory on sexual diversity that I am aware of has ever achieved. The well-sharpened, highly sensitive diversity glasses that van Anders puts on are undeniably conducive to doing justice to the complexity and diversity of our lived realities.As such, the attentive value of the SCT is high. In accordance with van Anders’ claim, I can see its usefulness as a tool for self-investigation and self-knowledge. I can see its emancipatory value as well as its clinical importance. I tend to see limitations to its empirical usefulness, however.N = 1 or N > 1 studies, may provide theoretical and empirical insights and may certainly have the attentive, awareness raising, and emancipatory value already referred to. And maybe some quantitative measurements may provide individual and group scores on separate aspects of (separate parameters of) sexual configurations. But I am lost as soon as I try to think about overall classifications of sexual configurations. The complexity and uniqueness of each configuration simply forbids it. “Not all configurations are as complex,” van Anders puts forward and, of course, she is right. In quite a number of configurations, dimensions may sooner coincide than branch off; the possible complexity and subtlety is wasted on those. But I have difficulty seeing how configurations that fully exploit the possibilities of being multifaceted and detailed can yet again be classified in meaningful categories of sexual identities. van Anders describes a number of identities in SCT terms. She notes, for instance, that specific configurations in a specific context and in intersectional relation to other personal factors may be experienced as identities, such as wink, bear, or stud. Indeed, those and many other identities may be well characterized in SCT terminology. But as soon as they are being used as a category of configurations, as a classification, they detract from what I feel is SCT’s main strength and gain, namely its “let a thousand flowers bloom” principle, its pontifical opening of a wide-ranging fan of possible configurations and identities based on multiple descriptive dimensions. What the SCT, in my opinion, shows best are the many nuanced colors in the rainbow; reduction to a couple of primary ones is a step backwards.I am not fully convinced by how van Anders envisions the ways in which the SCT can make the complexity and diversity of our lived realities empirically visible. Clearly, qualitative descriptions, in The fact remains that the relation between one’s assembled configuration and one’s lived identity is not straightforward. Every dimension added to the SCT, or every parameter stalagmite added to the configuration landscape, makes it harder to identify the landscape as a singular identity, a coherently, classifiable lived experience. Moreover, as was the case with thinking in terms of a singular orientation, the distinction and possible deviation between attractions (or orientations), behaviors (or statuses), and self-identifications remains an issue. van Anders proposes different notations when demarcating the different aspects in one’s Sexual Configuration Landscape, like a-dots for attractions and s-dots for statuses. Well, that does not make me too happy.Other problems that the SCT aimed to solve were not essentially solved either. Although solitary sexuality has been given principle space in the sexual configuration, it remains distinct from partnered sexuality and the ways solitary sexuality may affect one’s overall sexual configuration remain largely unexplored. Likewise, van Anders acknowledges the possible temporality and fluidity of sexual configurations, but does not do much more to incorporate that notion in one’s overall configuration than was done in singular orientation theory. Luckily, some problems remain to be solved.With van Anders’ introduction of SCT, our thinking about sexual diversity has gained substantial and irreversible progress. SCT offers a sophisticated tool that is implementable towards increasing understanding, normalization, communication, and capacity building in relation to sexual orientation/configuration. SCT provides an open and future-proof vision adaptable to attractions lived by new generations beyond our imagination right now. What we now need to conceptualize and investigate are the conditions under which such a colorful configurations diversity may also be societally supported. What are the consequences for legal and educational systems? What does it mean for sexual minorities’ self-organization and emancipatory movements? How to find a proper balance between specificities and generalities in health care and social work? How to counter conservative or even reactionary powers stepping up their efforts to reduce our intimate lives to the monogamous heterosexual variant? Although important, such questions do not refrain from the relevance of the leap forward van Anders has presented us with. Let us start implementing!


We would like to draw the attention of the readers to the inappropriate use of term “cytotoxic” as a substitute for “antineoplastic”. This can be noticed in numerous scientific articles, especially those reporting the anticancer properties of certain chemical compounds. For example, there are published studies reporting the anticancer activity of certain drugs/chemicals and the authors have assessed the anticancer activities of some novel drugs against certain target cancers. These investigations have repeatedly involved the term “cytotoxic” instead of “antineoplastic”. For instance, recently a report has been published in DARU by Vosough et al.  about thLiterally cytotoxic refers to “toxic to living cells” while, antineoplastic means inhibiting or preventing the development and spread of neoplasms. For drugs that control or kill only neoplastic cells, the proper term that could describe this inherent activity of drugs is known as antineoplastic or anticancer activity. Moreover, the physiology of a normal cell is entirely dissimilar to that of cancerous cells or neoplasms, having an excessive quantity of free radicals and subsequent oxidative stress ,6. Cytothttp://www.nlm.nih.gov/mesh/MBrowser.html does not suggest the term cytotoxic as a substitute for antineoplastic, but the opposite could easily be seen. Furthermore, MeSH is a very comprehensive controlled scientific terminology helping in proper indexing of the scientific article and books.At the end, we are of the opinion that great care must be exercised while using the term cytotoxicity as an alternative to antineoplastic activity, particularly mentioning the activity of anticancer agents. Also, the National Library of Medicine–Medical Subject Headings (MeSH)