Human Cognition Research Articles

Intelligent Head-bot, towards the Development of an AI Based Cognitive Platform

A cognitive humanoid head is an AI enabled head-bot platform that resembles human's cognitive abilities, such as perception, thinking, learning, and decision-making. The platform is able to interact with human through natural language processing and recognize individuals, thus allowing seamless communication between two parties. No such cognitive platform has been introduced in Bangladesh, thus creating an open field to contribute to the field of Machine Intelligence. This study aims to develop an AI based humanoid head (head-bot) capable of imitating a range of expressions, recognizing individuals, and interacts with visitors through general conversation. The head-bot skeleton is developed using a number of hexagonal blocks of PVC sheet to mimic a human-head-like structure where LCD, camera, microphones, and speaker are mounted. Two separate Machine Learning models are designed for face detection and recognitions, and voice enabled chat-bot implementation. The head-bot platform incorporates 2-DoF neck movements for various head gestures and face tracking. The Artificial Neural Network models are tested with accuracy of 95.05%, and 99.0%, for face detection and recognitions, and speech recognitions and response generation, respectively. According to the overall results and system performances, it seems that the proposed system has a number of good potentials for real life applications such as entertainment, guidance, conversations, interactive receptionists, personal companion, medical assistance, and so on.

The peptide Acein promotes dopamine secretion through clec-126 to extend the lifespan of elderly C. elegans.

Dopamine plays a crucial role in regulating brain activity and movement and modulating human behavior, cognition and mood. Regulating dopamine signaling may improve cognitive abilities and physical functions during aging. Acein, a nonapeptide of sequence H-Pro-Pro-Thr-Thr-Thr-Lys-Phe-Ala-Ala-OH is able to stimulate dopamine secretion in the brain. By using genetic editing and lifespan investigation in C. elegans, we showed that the lack of the C-type lectin domain-containing protein clec-126 significantly suppressed the aging phenotype and prolonged lifespan, while overexpression of clec-126 promoted aging-related phenotypes and accelerated the aging process. We examined the aging phenotype of C. elegans and showed that Acein could induce a decrease in clec-126 expression, prolonging the lifespan of aged C. elegans. The mechanism proceeds through the Acein-induced stimulation of dopamine secretion that ameliorates motor function decline and extends the healthy lifespan of aged C. elegans. In addition, we also observed an increase in brood number. Our study has shown that Acein regulates dopamine secretion and has good antiaging activity by decreasing clec-126 expression.

Proposal of a Hesitant Fuzzy Linguistic TOPSIS model for Supplier Sustainability Evaluation

Objective: The literature presents several multi-criteria models to support the evaluation of supplier sustainability. However, most of them deals with the environmental, social and economic dimensions in a compensatory way, and none allow the use of linguistic expressions. In order to fill these gaps, this study proposes a decision-making model, based on the Hesitant Fuzzy Linguistic (HFL) TOPSIS method, to support the supplier sustainability evaluation. Method: It can be classified as quantitative research based on modeling and simulation. The research stages encompass bibliographical research, computational modeling, pilot application in a company and analysis of results. The implementation of four computational models based on HFL-TOPSIS was done using Microsoft Excel. Results and conclusion: Results of the pilot application indicated that the model is capable of providing consistent results which are easily interpretable by the decision maker. In the application in question, economic criteria received greater weight, which reflects the priorities of the company in question. The evaluation of six suppliers by a decision maker made it possible to categorize them in a three-dimensional matrix. Research Implications: The proposed model provides support for the elaboration of supplier development programs. Another benefit is related to modeling sustainability dimensions in a non-compensatory way. Thus, if a supplier achieves high performance in one dimension, this does not compensate for a possible low performance in another dimension. Originality: In contrast to the previous approaches, It supports modeling preferences in a way closer to human cognition. It also deals with situations in which there is hesitation in choosing linguistic terms.

Oxytocin modulates neural activity during early perceptual salience attribution

Leading hypotheses of oxytocin’s (OT) role in human cognition posit that it enhances salience attribution. However, whether OT exerts its effects predominantly in social (vs non-social) contexts remains debatable, and the time-course of intranasal OT’s effects’ on salience attribution processing is still unknown. We used the social Salience Attribution Task modified (sSAT) in a double-blind, placebo-controlled intranasal OT (inOT) administration, between-subjects design, with 54 male participants, to test existing theories of OT’s role in cognition. Namely, we aimed to test whether inOT would differently affect salience attribution processing of social stimuli (expressing fearfulness) and non-social stimuli (fruits) made relevant via monetary reinforcement, and its neural processing time-course. During electroencephalography (EEG) recording, participants made speeded responses to emotional social (fearful faces) and non-emotional non-social (fruits) stimuli - which were matched for task-relevant motivational salience through their (color-dependent) probability of monetary reinforcement. InOT affected early (rather than late, P3b and LPP) EEG components, increasing N170 amplitude (p = .041) and P2b latency (p .001; albeit not of P1), regardless of stimuli’s (emotional) socialness or reinforcement probability. Fear-related socialness affected salience attribution processing EEG (p .05) across time (N170, P2b and P3b), being later modulated by reinforcement probability (LPP). Our data suggest that OT’s effects on neural activity during early perception, may exist irrespective of fear-related social- or reward-contexts. This partially supports the tri-phasic model of OT (which posits OT enhances salience attribution in an early perception stage regardless of socialness), and not the social salience nor the general approach-withdrawal hypotheses of OT, for early salience processing event-related potentials.

RHYTHMS: Real-time Data-driven Human-machine Synchronization for Proactive Ergonomic Risk Mitigation in the Context of Industry 4.0 and Beyond

Human-machine work system (HMWS) represents a composite system that integrates machine precision and strength with human cognitive abilities, flexibility, and adaptability, aiming to achieve enhanced performance in various tasks aligned with a common goal, which is getting smarter in the era of Industry 4.0 (I4.0) and has received extensive attention from academia and industry. However, the lack of real-time information sharing during HMWS implementation and operation, coupled with uncertainties stemming from human instability and the complexities introduced by smart networking environments in the context of I4.0, poses challenges to the synchronous coordination of this distributed human-centric manufacturing system. Failure in synchronization not only compromises overall system integrity, leading to unrealistic decision-making and potential harm to human health but also goes against the principles of Industry 5.0 (I5.0), which proposes placing human well-being at the center of the production process for human-centric smart manufacturing in the future. In this context, this research presents real-time data-driven hyper objects orchestrating for the human-machine synchronization (RHYTHMS) based on a service-oriented human-to-machine architecture (SOH2M) and a model reference adaptive fuzzy control for real-time information sharing and synchronous coordination of the smart HMWS. Based on these, a real-life assembly case is carried out by a full-scale HMWS prototype to quantitatively analyze the benefits of the proposed approach in proactive ergonomic risk mitigation (PERM), contributing to the human-centric value-oriented I5.0 era.

L’ordine giuridico dell’algoritmo: la funzione regolatrice del diritto e la funzione ordinatrice dell’algoritmo

Humans have historically developed tools, both tangible and intangible, to impose order, mitigate risks, and align actions with collective values. This article explores the parallel roles of legal norms and algorithms in establishing regularities that may be beneficial to human cognition, shielding it from boundless unpredictability. With an emphasis on the intertwining of rational and emotional facets of human cognition, we delve into the shared ordering functions of law and AI algorithms. The article highlights the challenges, biases, and dilemmas surrounding AI and its regulation. We conclude by advocating for a more structured political approach to AI governance, emphasizing the importance of delineating roles for AI to ensure certain domains remain exclusively within human purview.

The Impact of Free and Added Sugars on Cognitive Function: A Systematic Review and Meta-Analysis.

A relationship between excessive sugar consumption and cognitive function has been described in animal models, but the specific effects of sugars in humans remains unclear. This systematic review and meta-analysis aimed to evaluate the current knowledge, research characteristics, and quality of evidence of studies investigating the impacts of free and added sugars on human cognition in healthy participants. The review identified 77 studies (65 experimental trials, n = 3831; 9 cross-sectional studies, n = 11,456; and 3 cohort studies, n = 2059). All cohort studies and eight of the nine cross-sectional studies found significant positive correlations between added sugar consumption and risk of cognitive impairment. Four studies identified reduced risk of cognitive impairment associated with natural fructose-containing foods. The majority of randomised control trials assessed short-term glucose facilitation effects on cognitive outcomes. The results from these studies suggest the need for a tightly regulated blood glucose level, dependent on individualised physiological factors, for optimal cognitive function. A meta-analysis of a subset of studies that assessed the impact of glucose on recall found improvements in immediate free recall compared to controls (p = 0.002). The findings highlight the potentially detrimental effect of excessive, long-term, or prenatal added sugar consumption on cognitive function. Further research is needed to examine the specific effects of free and added sugars on cognitive function.

Understanding the impact of augmented reality product presentation on diagnosticity, cognitive load, and product sales

Augmented reality (AR) enhances consumers’ sensory responses to online product presentations, providing a more immersive experience. In online marketplaces, the utilization of various sensory modalities for product representation proves valuable for consumers’ evaluations. To investigate the impact of AR interfaces on human cognition, we developed a mobile AR app and conducted an experiment. Subjects tested the app, equipped with AR capabilities, alongside traditional two-dimensional (2D) representations for various product types. Our findings reveal that, in comparison to conventional 2D presentations, AR affordances significantly enhance consumers’ perceived product diagnosticity. Notably, this effect is more pronounced for technology products. Additionally, our research indicates that AR interfaces may contribute to an increased perceived cognitive load. In a second study, we conducted a natural experiment using AR-enabled Amazon products to explore the influence of AR interfaces on purchase decisions. For technology products, we observed a substantial increase in product sales when utilizing AR for online presentations. This research makes a valuable contribution to the mobile commerce literature, offering insights to retailers about the efficacy of AR interfaces in the realm of mobile shopping.

From Artificial Intelligence and Bayesian Statistics to Neuroanatomy: Connections, Analogies, and Applications

This study examines the interaction between artificial intelligence (AI), Bayesian statistics, and various key brain structures, such as the hippocampus, amygdala, and thalamic nuclei. The goal is to explore how Bayesian inference can contribute to the development of AI systems that simulate and optimize essential aspects of human cognition, such as decision-making, attention, learning, and memory. By analyzing the functions of these structures within the framework of Bayesian statistics, possible avenues are identified for improving the adaptability and efficiency of AI systems in problem-solving and decision-making. Additionally, the relevance of Brodmann areas in the context of AI and Bayesian statistics is considered. The knowledge gained from this study can provide a solid foundation for the design of increasingly advanced and human-centric AI systems, facilitating more effective and understandable interaction between humans and AI technologies.

Do we all synch alike? Brain-body-environment interactions in ASD.

Autism Spectrum Disorder (ASD) is characterized by rigidity of routines and restricted interests, and atypical social communication and interaction. Recent evidence for altered synchronization of neuro-oscillatory brain activity with regularities in the environment and of altered peripheral nervous system function in ASD present promising novel directions for studying pathophysiology and its relationship to ASD clinical phenotype. Human cognition and action are significantly influenced by physiological rhythmic processes that are generated by both the central nervous system (CNS) and the autonomic nervous system (ANS). Normally, perception occurs in a dynamic context, where brain oscillations and autonomic signals synchronize with external events to optimally receive temporally predictable rhythmic information, leading to improved performance. The recent findings on the time-sensitive coupling between the brain and the periphery in effective perception and successful social interactions in typically developed highlight studying the interactions within the brain-body-environment triad as a critical direction in the study of ASD. Here we offer a novel perspective of autism as a case where the temporal dynamics of brain-body-environment coupling is impaired. We present evidence from the literature to support the idea that in autism the nervous system fails to operate in an adaptive manner to synchronize with temporally predictable events in the environment to optimize perception and behavior. This framework could potentially lead to novel biomarkers of hallmark deficits in ASD such as cognitive rigidity and altered social interaction.

Exploring expressions for cardinal directions in Tshiluba

This paper presents the outcomes of a pilot study that explores expressions for cardinal directions in Tshiluba, a Bantu language primarily spoken in the Democratic Republic of the Congo. Language data were collected from a native Tshiluba speaker using three elicitation methods and an online dictionary. The results reveal several potential nomenclatural strategies and conceptual sources that Tshiluba uses to linguistically encode cardinal directions, including references to body parts, geographical and environmental landmarks and features, and celestial bodies and events. Meanwhile, a comprehensive exploration of the inherent characteristics of these Tshiluba cardinal direction expressions remains a subject of further investigation. The paper also includes reflections and suggestions regarding research methodologies on this topic. This paper contributes to cross–linguistic exploration and documentation of cardinal direction expressions, both within and beyond the Bantu language family. It also encourages further research on spatial language as a whole, which is a pursuit of great importance in advancing our understanding of human spatial cognition and our interactions with the external world.

Evaluation of a headphones-fitted EEG system for the recording of auditory evoked potentials and mental workload assessment

Advancements in portable neuroimaging technologies open up new opportunities to gain insight into the neural dynamics and cognitive processes underlying day-to-day behaviors. In this study, we evaluated the relevance of a headphone- mounted electroencephalogram (EEG) system for monitoring mental workload. The participants (N = 12) were instructed to pay attention to auditory alarms presented sporadically while performing the Multi-Attribute Task Battery (MATB) whose difficulty was staged across three conditions to manipulate mental workload. The P300 Event-Related Potentials (ERP) elicited by the presentation of auditory alarms were used as probes of attentional resources available. The amplitude and latency of P300 ERPs were compared across experimental conditions. Our findings indicate that the P300 ERP component can be captured using a headphone-mounted EEG system. Moreover, neural responses to alarm could be used to classify mental workload with high accuracy (over 80%) at a single-trial level. Our analyses indicated that the signal-to-noise ratio acquired by the sponge-based sensors remained stable throughout the recordings. These results highlight the potential of portable neuroimaging technology for the development of neuroassistive applications while underscoring the current limitations and challenges associated with the integration of EEG sensors in everyday-life wearable technologies. Overall, our study contributes to the growing body of research exploring the feasibility and validity of wearable neuroimaging technologies for the study of human cognition and behavior in real-world settings.

The giant leap to humankind

Penny (2009) urges that biologists stress more strongly the biological continuity between great apes and humans. Besides stressing genetic similarities, he suggests that great apes also share psychological capacities, including language and tool use. I argue that he underestimates the psychological differences. There is no evidence that great apes have anything approaching human language, or human technological capacity. A main ingredient of human cognition is recursion, which lifted communication to true combinatorial language and simple tool use to advanced combinatorial technology. Recursion may also explain the combinatorial structure of human memory, imagination, and theory of mind. Part of the key, as Penny recognises, may lie in the trajectory of human brain growth, but there is still much to understand in how micro-tweaking of the genome achieved such dramatic differences between ape and human.

Difficulties in Assessing the Economic Burden of Alzheimer's Disease

Background. Age-related changes associated with the decrease in health and autonomy drastically increase the cost of medical care, maintenance and treatment. Late detection of ilnesses is the root cause of escalating the economic weight from age-related diseases, causing a surge in costs for the recovery, treatment and care of those needing outside assistance. One of the age-associated diseases is Alzheimer's disease. Alzheimer's disease is one of the many manifestations of age-related dementia, accompanied by a violation of human cognitive abilities. This cluster of diseases does not affect other systems (cardiovascular, musculoskeletal, digestive), and they can operate normally. An important effect of this disease for society is the impossibility of conducting a full-fledged work activity, as memory, attention, etc. are disturbed. That is, with absolutely normally functioning body systems, a person cannot perform the simplest operations. Another important feature is the lack of an effective way to treat this disease. The pathogenesis is so complex that today there is no method of treatment aimed at all links. Also of great importance is the timeliness of detection of this disease. Due to the fact that recently there were test systems and express diagnostics for the early detection of Alzheimer's disease, it became possible to start treatment earlier, which increased the chances of recovery and reduced treatment costs in case of diagnosing moderate and severe Alzheimer's disease gravity. Aim. Revealing the difficulties of assessing the economic burden of Alzheimer's Disease. Materials and methods. To identify the difficulties of assessing the economic burden, free sources, publications on Alzheimer's disease, data from clinical guidelines, the standard for providing medical care to elderly and senile patients with cognitive disorders, information on maximum selling prices registered and included in the State Register of Vital and Essential Drugs Prices, statistical data, compulsory health insurance tariffs. Results. The main problematic issues of the difficulty of assessing the economic burden of Alzheimer's disease are identified. Conclusion. Diseases of the nervous system are of particular importance for the health of the patient, since disorders affecting this system do not allow the patient to fully and fully fulfill their labor duties. In this regard, the development of a method for assessing the cost-effectiveness of Alzheimer's disease, as one of the most common disorders of cognitive functions, is an extremely important social task aimed at optimizing the treatment process, early detection and effective treatment aimed at recovery.

Why large language models are poor theories of human linguistic cognition: A reply to Piantadosi

In a recent manuscript entitled “Modern language models refute Chomsky’s approach to language”, Steven Piantadosi proposes that large language models such as GPT-3 can serve as serious theories of human linguistic cognition. In fact, he maintains that these models are significantly better linguistic theories than proposals emerging from within generative linguistics. The present note explains why this claim is wrong.

An energy costly architecture of neuromodulators for human brain evolution and cognition

In comparison to other species, the human brain exhibits one of the highest energy demands relative to body metabolism. It remains unclear whether this heightened energy demand uniformly supports an enlarged brain or if specific signaling mechanisms necessitate greater energy. We hypothesized that the regional distribution of energy demands will reveal signaling strategies that have contributed to human cognitive development. We measured the energy distribution within the brain functional connectome using multimodal brain imaging and found that signaling pathways in evolutionarily expanded regions have up to 67% higher energetic costs than those in sensory-motor regions. Additionally, histology, transcriptomic data, and molecular imaging independently reveal an up-regulation of signaling at G-protein-coupled receptors in energy-demanding regions. Our findings indicate that neuromodulator activity is predominantly involved in cognitive functions, such as reading or memory processing. This study suggests that an up-regulation of neuromodulator activity, alongside increased brain size, is a crucial aspect of human brain evolution.

Non-weird (psycho)linguistic endeavors: theoretical and metacognitive research with the Karajá of central Brazil

Cognitive psychology and psycholinguistics have historically been dominated by research conducted within Western, Educated, Industrialized, Rich, and Democratic (WEIRD) societies, resulting in a disproportionate representation of this demographic in scholarly investigations. In this article, we report basic and applied research investigating order of constituents and morphological representation and processing conducted with speakers of Karajá, a non-european language of Central Brazil. The basic research findings contribute novel insights about the Karajá language, challenging certain purported language universals while corroborating others, thereby enriching the broader understanding of human cognition. The applied research explores methodological avenues to foreground indigenous voices and perspectives into the investigation process, acknowledging the potential drawbacks of employing WEIRD analytical categories when exploring non-WEIRD languages. We invite speakers of the language to the center of the discussion in metacognitive activities in which speakers use their insights to formulate hypotheses and create a theory for the grammar of the language. In line with the discussions in Maia (2022) in which eye tracking data was used at the Middle school and University levels, in these Karajá sessions, we also used qualitative eye tracking data as an aid to help Karajá language teachers to “go meta”, as put by Mahdavi (2014). We conclude by stressing that if we are to take seriously the importance of non-WEIRD science to the WEIRD world, there ought to be an increasing recentering of “participants” to more protagonist roles in research.

Digital Environmental Humanities: Scholarship and Activism in India

The advent of digital age impacted a massive transformation in the academia and dissemination of information and communication and also how human cognition takes place and such changes will only accelerate. Digital Humanities is an interdisciplinary field of inquiry that uses the methodologies of digital technological innovations to study humanities. Digital environmental humanities is a branch of digital humanities that deals with the intersections of digital arena and environmental concerns This article intends study the position of digital environmental humanities in Indian environmentalism. It also attempts to place on the Indian context of the field and trace the scholarship and activism of digital environmental humanities in India.

Cross-cultural differences in visual object and background processing in the infant brain

Abstract Human visual cognition differs profoundly between cultures. A key finding is that visual processing is tuned toward focal elements of a visual scene in Western cultures (US and Europe) and toward the background in Eastern cultures (Asia). Although some evidence for cultural differences exists for young children, to date, the ontogenetic origins of cultural differences in human visual cognition have not been unveiled. This study explores early cross-cultural differences in human visual processing, by tracking the neural signatures for object versus background elements of a visual scene in the electroencephalogram (EEG) of 12-month-old infants, in Vienna (Austria; a Western culture; n = 35) and Kyoto (Japan; an Eastern culture; n = 36). Specifically, we separated neural signatures by presenting object and background at different stimulation frequencies (5.67 and 8.5 Hz). Results show that human visual processing is different between cultures from early on. We found that infants from Vienna showed a higher object signal, in contrast to infants from Kyoto, who showed an accentuated background signal. This early emergence of cultural differences in human vision may be explained in part by early social experiences: In a separate interaction phase, mothers from Vienna pointed out object (versus background) elements more often than mothers from Kyoto. To conclude, with a cross-cultural developmental neuroscience approach, we reveal that cross-cultural differences in visual processing of object and background are already present in the first year after birth, which is much earlier than previously thought.

Sequence representation as an early step in the evolution of language.

Human language is unique in its compositional, open-ended, and sequential form, and its evolution is often solely explained by advantages of communication. However, it has proven challenging to identify an evolutionary trajectory from a world without language to a world with language, especially while at the same time explaining why such an advantageous phenomenon has not evolved in other animals. Decoding sequential information is necessary for language, making domain-general sequence representation a tentative basic requirement for the evolution of language and other uniquely human phenomena. Here, using formal evolutionary analyses of the utility of sequence representation we show that sequence representation is exceedingly costly and that current memory systems found in animals may prevent abilities necessary for language to emerge. For sequence representation to evolve, flexibility allowing for ignoring irrelevant information is necessary. Furthermore, an abundance of useful sequential information and extensive learning opportunities are required, two conditions that were likely fulfilled early in human evolution. Our results provide a novel, logically plausible trajectory for the evolution of uniquely human cognition and language, and support the hypothesis that human culture is rooted in sequential representational and processing abilities.