A proposal of bioinspired motor-system cognitive architecture focused on feed-forward-control movements

The objective of this article is to present a conceptual motor-system cognitive architecture inspired in the human nervous system, and a cognitive architecture focused on the voluntary movement controlled by feed-forward. The article first focuses on describing the brain cortex areas that make up the motor system, presenting the supplementary motor area (SMA), premotor cortex and primary cortex, the tasks that these cortices do, and how they work together. Then, a cognitive architecture based on the information presented is shown. The areas in a computational level (functions, and algorithms used) are then described. Finally, a case study is presented, where the cognitive architecture proposed is used to execute a voluntary-movement-by-feed-forward-control task.     

A cognitive architecture for inner speech

A cognitive architecture for inner speech is presented. It is based on the Standard Model of Mind, integrated with modules for self-talking. Briefly, the working memory of the proposed architecture includes the phonological loop as a component which manages the exchanging information between the phonological store and the articulatory control system. The inner dialogue is modeled as a loop where the phonological store hears the inner voice produced by the hidden articulator process. A central executive module drives the whole system, and contributes to the generation of conscious thoughts by retrieving information from long-term memory. The surface form of thoughts thus emerges by the phonological loop. Once a conscious thought is elicited by inner speech, the perception of new context takes place and then repeating the cognitive loop. A preliminary formalization of some of the described processes by event calculus, and early results of their implementation on the humanoid robot Pepper by SoftBank Robotics are discussed.     

Declarative working memory: A bio-inspired cognitive architecture proposal

Memory is considered one of the most important functions since it allows us to code, store and retrieve knowledge. These qualities make it an indispensable function for a virtual creature. In general, memory can be classified based on the durability of the stored data in working memory and long-term memory. Working memory refers to the capacity to maintain temporarily a limited amount of information in mind, which can then be used to support various abilities, including learning, reasoning, planning and decision-making. Unlike short-term memory, working memory is not only a storage site, but it is also a framework of interacting processes that involve the temporary storage and manipulation of information in the service of performing complex cognitive activities. Declarative memory is a type of long-term memory related with the storage of facts and events. This research focuses on the development of a cognitive architecture for the type of working memory that maintains and manipulates declarative information. The construction of the model was grounded in theoretical evidence taken from cognitive sciences such as neuroscience and psychology, which gave us the components and their processes. The model was evaluated through a case study that covers the encoding, storing, and retrieval stages. Our hypothesis is that a virtual creature endowed with our working memory model will provide faster access to the information needed for the ongoing task. Therefore, it improves the planning and decision-making processes.     

A neural cognitive architecture

It is difficult to study the mind, but cognitive architectures are one tool. As the mind emerges from the behaviour of the brain, neuropsychological methods are another method to study the mind, though a rather indirect method. A cognitive architecture that is implemented in spiking neurons is a method of studying the mind that can use neuropsychological evidence directly. A neural cognitive architecture, based on rule based systems and associative memory, can be readily implemented, and would provide a good bridge between standard cognitive architectures, such as Soar, and neuropsychology. This architecture could be implemented in spiking neurons, and made available via the Human Brain Project, which provides a good collaborative environment. The architecture could be readily extended to use spiking neurons for subsystems, such as spatial reasoning, and could evolve over time toward a complete architecture. The theory behind this architecture could evolve over time. Simplifying assumptions, made explicit, such as those behind the rule based system, could gradually be replaced by more neuropsychologically accurate behaviour. The overall task of collaborative architecture development would be eased by direct evidence of the actual neural cognitive architectures in human brains. While the initial architecture is biologically inspired, the ultimate goal is a biological cognitive architecture.     

Multilayer cognitive architecture for UAV control

Extensive use of unmanned aerial vehicles (UAVs) in recent years has induced the rapid growth of research areas related to UAV production. Among these, the design of control systems capable of automating a wide range of UAV activities is one of the most actively explored and evolving. Currently, researchers and developers are interested in designing control systems that can be referred to as intelligent, e.g. the systems which are suited to solve such tasks as planning, goal prioritization, coalition formation, etc. and thus guarantee high levels of UAV autonomy. One of the principal problems in intelligent control system design is tying together various methods and models traditionally used in robotics and aimed at solving such tasks as dynamics modeling, control signal generation, location and mapping, path planning, etc. with the methods of behavior modeling and planning which are thoroughly studied in cognitive science. Our work is aimed at solving this problem. We propose layered architecture—STRL (strategic, tactical, reactive, layered)—of the control system that automates the behavior generation using a cognitive approach while taking into account complex dynamics and kinematics of the control object (UAV). We use a special type of knowledge representation—sign world model—that is based on the psychological activity theory to describe individual behavior planning and coalition formation processes. We also propose path planning methodology which serves as the mediator between the high-level cognitive activities and the reactive control signals generation. To generate these signals we use a state-dependent Riccati equation and specific method for solving it. We believe that utilization of the proposed architecture will broaden the spectrum of tasks which can be solved by the UAV’s coalition automatically, as well as raise the autonomy level of each individual member of that coalition.     

Reflections on dynamics,adaptation and control: A cognitive architecture for mental models

In this paper, an overview of the wide variety of occurrences of mental models in the literature is discussed. They are classified according to two dimensions obtaining four categories of them: static-dynamic and world-mental, where static refers to mental models for static world states or for static mental states and dynamic refers to mental models for world processes or for mental processes. In addition, distinctions are made for what can be done by mental models: they can, for example, be (1) used for internal simulation, they can be (2) adapted, and these processes can be (3) controlled. This leads to a global three-level cognitive architecture covering these three ways of handling mental models. It is discussed that in this cognitive architecture reflection principles play an important role to define the interactions between the different levels.     

The cognitive architecture for chaining of two mental operations

A simple view, which dates back to Turing, proposes that complex cognitive operations are composed of serially arranged elementary operations, each passing intermediate results to the next. However, whether and how such serial processing is achieved with a brain composed of massively parallel processors, remains an open question. Here, we study the cognitive architecture for chained operations with an elementary arithmetic algorithm: we required participants to add (or subtract) two to a digit, and then compare the result with five. In four experiments, we probed the internal implementation of this task with chronometric analysis, the cued-response method, the priming method, and a subliminal forced-choice procedure. We found evidence for an approximately sequential processing, with an important qualification: the second operation in the algorithm appears to start before completion of the first operation. Furthermore, initially the second operation takes as input the stimulus number rather than the output of the first operation. Thus, operations that should be processed serially are in fact executed partially in parallel. Furthermore, although each elementary operation can proceed subliminally, their chaining does not occur in the absence of conscious perception. Overall, the results suggest that chaining is slow, effortful, imperfect (resulting partly in parallel rather than serial execution) and dependent on conscious control.     

Human symbol manipulation within an integrated cognitive architecture

This article describes the Adaptive Control of Thought–Rational (ACT–R) cognitive architecture (Anderson et al., 2004; Anderson & Lebiere, 1998) and its detailed application to the learning of algebraic symbol manipulation. The theory is applied to modeling the data from a study by Qin, Anderson, Silk, Stenger, & Carter (2004) in which children learn to solve linear equations and perfect their skills over a 6-day period. Functional MRI data show that: (a) a motor region tracks the output of equation solutions, (b) a prefrontal region tracks the retrieval of declarative information, (c) a parietal region tracks the transformation of mental representations of the equation, (d) an anterior cingulate region tracks the setting of goal information to control the information flow, and (e) a caudate region tracks the firing of productions in the ACT–R model. The article concludes with an architectural comparison of the competence children display in this task and the competence that monkeys have shown in tasks that require manipulations of sequences of elements.     

A cognitively enhanced collaborative control architecture for an intelligent wheelchair: Formalization,implementation and evaluation

For people with mobility impairment, powered wheelchairs are able to extend independent transportation. However, most users find it difficult to operate the powered wheelchairs effectively. This can be due to variety of physical or cognitive impairments. Herein lies the motivation of developing intelligent wheelchairs that provide the user, assistance in control and navigation as and when required, supporting retention of residual skills. For better Human-Robot Interaction, such intelligent wheelchairs need to be cognitively enhanced. This paper propose a Cognitive Collaborative Architecture (CCA) for an intelligent wheelchair which is designed to assist the user as a team member. Whenever user finds it difficult to drive or control the wheelchair, CCA transfers control to the robotic agent which continues the human navigation strategy providing ‘assistance-as-required’.     

A computational cognitive framework of spatial memory in brains and robots

Computational cognitive models of spatial memory often neglect difficulties posed by the real world, such as sensory noise, uncertainty, and high spatial complexity. On the other hand, robotics is unconcerned with understanding biological cognition. Here, we describe a computational framework for robotic architectures aiming to function in realistic environments, as well as to be cognitively plausible.We motivate and describe several mechanisms towards achieving this despite the sensory noise and spatial complexity inherent in the physical world. We tackle error accumulation during path integration by means of Bayesian localization, and loop closing with sequential gradient descent. Finally, we outline a method for structuring spatial representations using metric learning and clustering. Crucially, unlike the algorithms of traditional robotics, we show that these mechanisms can be implemented in neuronal or cognitive models.We briefly outline a concrete implementation of the proposed framework as part of the LIDA cognitive architecture, and argue that this kind of probabilistic framework is well-suited for use in cognitive robotic architectures aiming to combine spatial functionality and psychological plausibility.     

A cognitive architecture for modeling emotion dynamics: Intensity estimation from physiological signals

Current approaches to emotion recognition do not address the fact that emotions are dynamic processes. This work concerns itself with the development of a cognitive architecture for modeling the dynamics of emotions with specific focus on a gray-box model for dynamic emotion intensity estimation that can incorporate findings from appraisal models, specifically Scherer’s Component Process Model. It is based on Dynamic Field Theory which allows the combination of theoretical knowledge with data-driven experimental approaches. A user study is conducted applying the proposed model to estimate intensity of negative emotions from physiological signals. Results show significant improvements of the proposed model to common methodology and baselines. The flexible cognitive architecture opens a wide field of experiments and directions to deepen the understanding of emotion processes as a whole.     

Socially emotional brain-inspired cognitive architecture framework for artificial intelligence

Artificial Intelligence of the next generation needs to interact with users socially, convincing them in its ability to understand human minds, including emotions. For this to happen, an artificial emotional intelligence is needed, capable of adequate, believable behavior in social emotional interactions. Building on previous developments, the present work extends the general framework of emotional Biologically Inspired Cognitive Architecture (eBICA: Samsonovich, 2013, 2018), endowing it with fluents describing, in addition to appraisals, somatic markers, feelings, emotions, moods, emotional reactions and biases. Key building blocks that integrate them are moral schemas and semantic maps. The model describes interaction of three factors: plans and commitments, moral and ethical values, and somatic comfort. Learning in this framework includes self-organization of semantic maps that in turn may provide guidance for active humanlike learning. Implications for empirical studies and practical applications are discussed together with the expected impact.     

Models of dependence and independence: A two-dimensional architecture of dual processing

This theoretical note proposes a two-dimensional cognitive architecture for dual-process theories of reasoning and decision making. Evans (2007b Evans, J. St. B. T. 2007b. On the resolution of conflict in dual process theories of reasoning. Thinking and Reasoning, 13: 321–339. [Taylor & Francis Online], [Web of Science ®] , [Google Scholar], 2008a Evans, J. St. B. T. 2008a. Dual-processing accounts of reasoning, judgment, and social cognition. Annual Review of Psychology, 59: 255–278. [Taylor & Francis Online], [Web of Science ®] , [Google Scholar], 2009 Evans, J. St. B. T. and Frankish, K. 2009. In two minds: Dual processes and beyond, Oxford, , UK: Oxford University Press. [Crossref] , [Google Scholar]) distinguishes between two types of dual-processing models: parallel-competitive, in which both types of processes operate in parallel, and default-interventionist, in which heuristic processes precede the analytic processes. I suggest that this temporal dimension should be enhanced with a functional distinction between interactionist architecture, in which either type of process influences the content and valence of the other, and independent architecture, in which they do not. Override architecture is a special case of the latter, which postulates statistical interaction, but no interaction of valence and content. I show that this added dimensional distinction casts doubt on two assumptions of statistical modelling that Evans makes: independence and linearity. However, Evans' (2007b Evans, J. St. B. T. 2007b. On the resolution of conflict in dual process theories of reasoning. Thinking and Reasoning, 13: 321–339. [Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) point, that statistical modelling is underspecified vis-à-vis the verbal theory, is given further support. The functional dimension is crucial to interpreting the statistical model, as well as to theoretical understanding of the cognitive architecture and its educational applications.     

睡眠限制对认知功能的影响及其潜在作用机制

睡眠限制已然成为现代社会人们普遍面临的问题, 其对个体身心机能的影响备受研究者关注。众多研究表明, 睡眠限制会对注意功能、执行功能和长时记忆等不同认知领域的心理加工产生差异化影响, 且影响程度与任务类型、睡眠限制的严重程度、年龄和性别等因素相关。研究者们提出了4种主要的作用假说：唤醒假说、注意控制假说、警觉性假说以及前额皮层易感性假说。未来研究需要从关注个体间差异、使用动脉自旋标记灌注功能磁共振成像技术以及重视轻度睡眠限制的影响等角度进行深化和扩展。     

Grammatical language impairment and the specificity of cognitive domains: relations between auditory and language abilities

Grammatical-specific language impairment (G-SLI) in children, arguably, provides evidence for the existence of a specialised grammatical sub-system in the brain, necessary for normal language development. Some researchers challenge this, claiming that domain-general, low-level auditory deficits, particular to rapid processing, cause phonological deficits and thereby SLI. We investigate this possibility by testing the auditory discrimination abilities of G-SLI children for speech and non-speech sounds, at varying presentation rates, and controlling for the effects of age and language on performance. For non-speech formant transitions, 69% of the G-SLI children showed normal auditory processing, whereas for the same acoustic information in speech, only 31% did so. For rapidly presented tones, 46% of the G-SLI children performed normally. Auditory performance with speech and non-speech sounds differentiated the G-SLI children from their age-matched controls, whereas speed of processing did not. The G-SLI children evinced no relationship between their auditory and phonological/grammatical abilities. We found no consistent evidence that a deficit in processing rapid acoustic information causes or maintains G-SLI. The findings, from at least those G-SLI children who do not exhibit any auditory deficits, provide further evidence supporting the existence of a primary domain-specific deficit underlying G-SLI.     

The impact of demographics and nutritional status on cognitive functioning in an Iranian adults sample

This study investigated the impact of demographic variables and nutritional status on adult cognitive functioning using structural equation modeling. Demographic variables that were considered were height, weight and gender, whilst nutritional status was measured on the Nutrition Assessment Inventory (NAI). Cognitive functions, such as executive cognitive functions, cognitive flexibility, cognitive ability and cognitive vulnerability were measured using the Amsterdam Executive Function Inventory (AEFI), the Cognitive Flexibility Scale (CFS), the Cognitive Ability Questionnaire (CAQ), and the Dysfunctional Attitude Scale Form A-Revised (DAS-A-R) respectively. Findings indicated that ethnicity and weight variables contribute to 8.8% of the nutritional status variations observed. A SEM analysis showed that nutritional status has an impact on 13% on the measured cognitive abilities of adults. The effects of “healthy nutrition”, “use of complementary nutritients”, “coping with high fat foods”, and “high fat food assumption” subscales of the nutrition scale were found to play a role in cognitive ability. This study shows a fitted SEM for the predictive roles of ethnicity, weight and nutritional status on the cognitive ability in adults.     

A multi-modal approach to cognitive training and assistance in minimally invasive surgery

Minimally-invasive surgery (MIS) offers many benefits to patients, but is considerably more difficult to learn and perform than is open surgery. One main reason for the observed difficulty is attributable to the visuo-spatial challenges that arise in MIS, taxing the surgeons’ cognitive skills. In this contribution, we present a new approach that combines training and assistance as well as the visual and the auditory modality to help surgeons to overcome these challenges. To achieve this, our approach assumes two main components: An adaptive, individualized training component as well as a component that conveys spatial information through sound. The training component (a) specifically targets the visuo-spatial processes crucial for successful MIS performance and (b) trains surgeons in the use of the sound component. The second component is an auditory display based on a psychoacoustic sonification, which reduces and avoids some of the commonly experienced MIS challenges. Implementations of both components are described and their integration is discussed. Our approach and both of its components go beyond the current state of the art in important ways. The training component has been explicitly designed to target MIS-specific visuo-spatial skills and to allow for adaptive testing, promoting individualized learning. The auditory display is conveying spatial information in 3-D space. Our approach is the first that encompasses both training for improved mastery and reduction of cognitive challenges in MIS. This promises better tailoring of surgical skills and assistance to the needs and the capabilities of the surgeons and, thus, ultimately, increased patient safety and health.     

Auditory speed tasks as potential candidates for the study of cognitive ageing

Speed of information processing is an important cognitive ability. It facilitates the efficient operation of higher order cognitive functions, such as reasoning, and is implicated in various models of cognitive decline. The present study considers the potential benefits of expanding the measurement of processing speed to include the auditory modality. It examines the reliability and factorial structure of a variety of auditory and visual speed tasks in a sample of N = 138 older adults aged between 51 and 82 years. Our findings demonstrate that auditory measures can be used to assess processing speed as indexed by existing widely used tests of this ability. Moreover, the inclusion of auditory tasks significantly increases the relationship between processing speed and general cognitive ability. This novel research provides strong evidence of the suitability of auditory speed tasks for the study of cognitive function in older people, and demonstrates the importance of expanding cognitive measurement to include alternate modalities.     

A comparison of metacognitions in patients with hallucinations,delusions, panic disorder,and non-patient controls

This study tested the hypothesis that metacognitions are a general vulnerability factor for psychological disorder. It was predicted that patients with psychosis (hallucinations or delusions), and patients with panic disorder would score higher than non-patients on measures of metacognition. Moreover, it was hypothesised that patients showing most dysregulation of thinking (voice-hearers) would endorse significantly higher metacognition scores than individuals in the other groups. The Meta-Cognitions Questionnaire (MCQ: ) was administered to patients who met DSM-IV criteria for schizophrenia spectrum disorders with auditory hallucinations, patients who met DSM-IV criteria for schizophrenia spectrum disorders with persecutory delusions, patients who met DSM-IV criteria for panic disorder and non-patients. The results showed that psychotic patients who experience auditory hallucinations tended to exhibit higher levels of dysfunctional metacognitive beliefs than other patient groups, scoring significantly higher than at least two of the three control groups on positive beliefs about worry, negative beliefs about uncontrollability and danger, cognitive confidence and negative beliefs including superstition, punishment and responsibility. It was also found that the metacognitive beliefs of patients with persecutory delusions and panic patients were often similar to each other, and elevated in comparison to non-patients, suggesting that such beliefs are generic vulnerability factors. The theoretical and clinical implications of these findings are discussed.     

Reconsidering therapeutic action: Loewald, cognitive neuroscience and the integration of memory's duality

Both Loewald's relational theory of memory and the Self-Memory System (SMS) of cognitive neuroscience describe a dual memory system, one system that is experience-near sensory-perceptual, and the other, symbolic and conceptual. In contrast to perspectives that locate therapeutic action in either altering implicit procedural memories or interpreting explicit historical content, we argue that psychological health emerges from effective integration of both memory systems, achieved through a combination of transference dynamics and analytic insight. We support this position by elaborating four key assumptions of the loewaldian and SMS perspectives, followed by application to a clinical example. We highlight the power of certain integrative autobiographical memories called 'self-defining memories' in assisting an understanding of transference dynamics and providing metaphoric touchstones to guide subsequent treatment.