Human Sensory System Research Articles

Human Oral Sensory Systems and Swallowing

Numerous oral sensations contribute to the flavor experienced from foods. Texture is sensed throughout the mouth by nerve endings in the oral epithelium. Chemesthetic sensations, including irritation, spiciness, and chemical burn or cooling, are sensed by these same nerves. Tastes are sensed by taste buds, primarily on the tongue, which transduce information through the gustatory nerves. Even after placing food in the mouth, odor is still experienced through retronasal olfaction, the air that passes through the rear of the oral cavity into the nasal passages. All of these sensations combine to give an overall experience of flavor. In individuals with dysphagia, these oral sensory systems can be used to improve swallowing function. Texture is the most common current approach, but the other oral sensations, particularly chemesthesis, may also hold potential for making sensory modified foods for dysphagia management. However, modifying any of these sensory properties also alters the overall food flavor, which can lead to decreased liking of the food.

Optimal control and analysis of stabilometric tests with step disturbances of human sensory systems

Several optimal control problems are considered for a human motion model in the case of stabilometric tests when the posture of a person changes under a step disturbance. Such a situation is observed in the case of a galvanic vestibular stimulation or a vibration stimulation of the proprioceptors of shin muscles. Stabilometric tests with visual step disturbance are widespread in Russia. A characteristic feature of center of pressure (COP) trajectories for these tests is the presence of swings and overshoots. The test results are compared with the solutions of optimal control problems devoted to the repositioning of an inverted pendulum by a coupling torque. A speed-of-response problem and an optimal stabilization problem with a quadratic quality criterion are considered. The solutions to these optimum problems are compared with the results of stabilometric tests, which allows one to state a hypothesis on the sources of the above effects.

The Human Olfactory System: Cortical Brain Mapping Using fMRI

Background:: Functional magnetic resonance imaging (fMRI) is a non-invasive and convenient method of mapping brain activity associated with the human sensory systems. Among these systems there is a lack of data from olfactory studies, which could be attributed to technical difficulties in odor delivery during scanning. The current study took advantage of an olfactometer to evaluate brain activity during the odor-smelling process. Objectives:: This study aimed to investigate the brain regions of the human olfactory system via fMRI brain imaging. A speculative survey was used to highlight the differences between studies conducted in healthy populations using olfactory tasks, as well as conducting literature survey in terms of the technical principles applying through these tasks in fMRI studies. Subjects and Methods:: A functional map of the olfactory system that used a block design, alternating between odor and non-odor phases, was examined in 15 healthy volunteers. The general linear model was used to identify statistically significant voxels that showed activation during the activation blocks. Results:: Primary and secondary olfactory regions, including the piriformis, insula, amygdala, parahippocampal gyrus, caudate nucleus, inferior frontal gyrus, middle frontal gyrus, superior temporal gyrus, and cerebellum, demonstrated significant activation in response to odor stimulation. Conclusion:: Activation of the aforementioned brain areas, and the pattern of activation, is largely in accordance with previous published olfactory studies carried out in healthy individuals.

An Ultrasensitive, Selective, Multiplexed Superbioelectronic Nose That Mimics the Human Sense of Smell.

Human sensory-mimicking systems, such as electronic brains, tongues, skin, and ears, have been promoted for use in improving social welfare. However, no significant achievements have been made in mimicking the human nose due to the complexity of olfactory sensory neurons. Combinational coding of human olfactory receptors (hORs) is essential for odorant discrimination in mixtures, and the development of hOR-combined multiplexed systems has progressed slowly. Here, we report the first demonstration of an artificial multiplexed superbioelectronic nose (MSB-nose) that mimics the human olfactory sensory system, leading to high-performance odorant discriminatory ability in mixtures. Specifically, portable MSB-noses were constructed using highly uniform graphene micropatterns (GMs) that were conjugated with two different hORs, which were employed as transducers in a liquid-ion gated field-effect transistor (FET). Field-induced signals from the MSB-nose were monitored and provided high sensitivity and selectivity toward target odorants (minimum detectable level: 0.1 fM). More importantly, the potential of the MSB-nose as a tool to encode hOR combinations was demonstrated using principal component analysis.

Hybrid fabrication process of additive manufacturing and direct writing for a 4×4 mm matrix flexible tactile sensor

Various machines require data from their external environments for safety and/or accuracy. In this respect, many sensors that mimic the human sensory system have been investigated. Among these, tactile sensors may be useful for obtaining data on the roughness of, and external forces acting upon, an object. Several tactile sensors have been developed; however, these are typically fabricated via a series of complex processes, and hence are unsuitable for volume manufacturing. In this paper, we report a fabrication process for a 4×4 mm matrix flexible sensor element using layered manufacturing and direct-write technology. A composite composed of photocurable resin and Multi-walled carbon nanotubes (MWCNTs) was used as the sensing material. The MWCNTs were mixed with the photocurable resin using ultrasonic dispersion, and the liquid mixture exhibited excellent piezoresistive properties following curing using ultraviolet light. The used photocurable resin is flexible and elastic after curing. Therefore, the composite material can be bent and deformed. To use this composite material with the flexible sensor, dispensing characteristics were examined using direct-write technology. For the acquisition of sensor data, a commercial pin-header was inserted and photocurable resin was filled up to the height of pin-header and cured. Then, the composite material was dispensed onto the pin-header as a sensing material. Using this process, a flexible sensor with piezoresistive properties was formed.

Multisensory integration using dynamical Bayesian networks.

Multisensory integration using dynamical Bayesian networks.

Conscious Brain-to-Brain Communication in Humans Using Non-Invasive Technologies

Human sensory and motor systems provide the natural means for the exchange of information between individuals, and, hence, the basis for human civilization. The recent development of brain-computer interfaces (BCI) has provided an important element for the creation of brain-to-brain communication systems, and precise brain stimulation techniques are now available for the realization of non-invasive computer-brain interfaces (CBI). These technologies, BCI and CBI, can be combined to realize the vision of non-invasive, computer-mediated brain-to-brain (B2B) communication between subjects (hyperinteraction). Here we demonstrate the conscious transmission of information between human brains through the intact scalp and without intervention of motor or peripheral sensory systems. Pseudo-random binary streams encoding words were transmitted between the minds of emitter and receiver subjects separated by great distances, representing the realization of the first human brain-to-brain interface. In a series of experiments, we established internet-mediated B2B communication by combining a BCI based on voluntary motor imagery-controlled electroencephalographic (EEG) changes with a CBI inducing the conscious perception of phosphenes (light flashes) through neuronavigated, robotized transcranial magnetic stimulation (TMS), with special care taken to block sensory (tactile, visual or auditory) cues. Our results provide a critical proof-of-principle demonstration for the development of conscious B2B communication technologies. More fully developed, related implementations will open new research venues in cognitive, social and clinical neuroscience and the scientific study of consciousness. We envision that hyperinteraction technologies will eventually have a profound impact on the social structure of our civilization and raise important ethical issues.

Gestalt principles in multimodal data representation.

Data visualization is a powerful tool to communicate data in a clear, digestible format through graphical means. To be effective, however, form and function need to work in tandem, filtering layers of noise to reveal the key aspects of the analyzed data. Indeed, this could prove to be sufficient in discovering already known patterns. Still, the search for undiscovered patterns would require the full dataset to be presented as a whole, which bears the risk of sensory overload. Human sensory systems function as a systemic unit in relation to one another, dynamically sampling the signals around us to give a concise scene analysis. To decipher a complex, multidimensional dataset, a representational system that is able to reproduce the layers of information through different stimulations would be required. This article explores the possibilities of using multimodal data representation as a method to communicate multidimensional data, guided by the principles of Gestalt psychology. Point Cloud, an artwork that implements such explorations through the visualization and sonification of lightning data is presented as an application of this research. The Web extra can be found at http://youtu.be/pQtxsvgv80E.

Neurobiological foundations of neurologic music therapy: rhythmic entrainment and the motor system.

Entrainment is defined by a temporal locking process in which one system’s motion or signal frequency entrains the frequency of another system. This process is a universal phenomenon that can be observed in physical (e.g., pendulum clocks) and biological systems (e.g., fire flies). However, entrainment can also be observed between human sensory and motor systems. The function of rhythmic entrainment in rehabilitative training and learning was established for the first time by Thaut and colleagues in several research studies in the early 1990s. It was shown that the inherent periodicity of auditory rhythmic patterns could entrain movement patterns in patients with movement disorders (see for a review: Thaut et al., 1999). Physiological, kinematic, and behavioral movement analysis showed very quickly that entrainment cues not only changed the timing of movement but also improved spatial and force parameters. Mathematical models have shown that anticipatory rhythmic templates as critical time constraints can result in the complete specification of the dynamics of a movement over the entire movement cycle, thereby optimizing motor planning and execution. Furthermore, temporal rhythmic entrainment has been successfully extended into applications in cognitive rehabilitation and speech and language rehabilitation, and thus become one of the major neurological mechanisms linking music and rhythm to brain rehabilitation. These findings provided a scientific basis for the development of neurologic music therapy.

A data-driven framework for archiving and exploring social media data

Social media data are available and accumulated at the extra-byte level every day. As social media applications are widely deployed in various platforms from personal computers to mobile devices, they are becoming a natural extension to human sensory system. The synthesis of social media with human intelligence has the potential to be the intelligent sensor network of unprecedented scale and capacity. However, it also poses several grand challenges to archive and retrieve information from massive social media data. One of these challenges is how to archive, retrieve and mine such massive unstructured data set efficiently to support real-time emergency response. To explore potential solutions, this paper utilizes parallel computing methods to harvest social media data sets, using Twitter as an example, and to store, index, query and analyse them. Within this framework, a Not Only SQL database (DB), MongoDB, is used to store data as document entries rather than relational tables. To retrieve information from the massive data sets efficiently, several strategies are used: (1) data are archived in the MongoDB across multiple collections with each collection containing a subset of the accumulated data, (2) parallel computing is applied to query and process data from each collection and (3) data are duplicated across multiple servers to support massive concurrent access of the data sets. This study has also tested the performance of spatiotemporal query, concurrent user requests and sentiment analysis over multiple DB servers, and performance benchmark results showed that the proposed approach could provide a solution for processing massive social media data with more than 40% performance improvement. A proof-of-concept prototype implements the design to harvest, process and analyse tweets.

Conscious brain-to-brain communication in humans using non-invasive technologies.

Human sensory and motor systems provide the natural means for the exchange of information between individuals, and, hence, the basis for human civilization. The recent development of brain-computer interfaces (BCI) has provided an important element for the creation of brain-to-brain communication systems, and precise brain stimulation techniques are now available for the realization of non-invasive computer-brain interfaces (CBI). These technologies, BCI and CBI, can be combined to realize the vision of non-invasive, computer-mediated brain-to-brain (B2B) communication between subjects (hyperinteraction). Here we demonstrate the conscious transmission of information between human brains through the intact scalp and without intervention of motor or peripheral sensory systems. Pseudo-random binary streams encoding words were transmitted between the minds of emitter and receiver subjects separated by great distances, representing the realization of the first human brain-to-brain interface. In a series of experiments, we established internet-mediated B2B communication by combining a BCI based on voluntary motor imagery-controlled electroencephalographic (EEG) changes with a CBI inducing the conscious perception of phosphenes (light flashes) through neuronavigated, robotized transcranial magnetic stimulation (TMS), with special care taken to block sensory (tactile, visual or auditory) cues. Our results provide a critical proof-of-principle demonstration for the development of conscious B2B communication technologies. More fully developed, related implementations will open new research venues in cognitive, social and clinical neuroscience and the scientific study of consciousness. We envision that hyperinteraction technologies will eventually have a profound impact on the social structure of our civilization and raise important ethical issues.

Logarithmic and power law input-output relations in sensory systems with fold-change detection.

Two central biophysical laws describe sensory responses to input signals. One is a logarithmic relationship between input and output, and the other is a power law relationship. These laws are sometimes called the Weber-Fechner law and the Stevens power law, respectively. The two laws are found in a wide variety of human sensory systems including hearing, vision, taste, and weight perception; they also occur in the responses of cells to stimuli. However the mechanistic origin of these laws is not fully understood. To address this, we consider a class of biological circuits exhibiting a property called fold-change detection (FCD). In these circuits the response dynamics depend only on the relative change in input signal and not its absolute level, a property which applies to many physiological and cellular sensory systems. We show analytically that by changing a single parameter in the FCD circuits, both logarithmic and power-law relationships emerge; these laws are modified versions of the Weber-Fechner and Stevens laws. The parameter that determines which law is found is the steepness (effective Hill coefficient) of the effect of the internal variable on the output. This finding applies to major circuit architectures found in biological systems, including the incoherent feed-forward loop and nonlinear integral feedback loops. Therefore, if one measures the response to different fold changes in input signal and observes a logarithmic or power law, the present theory can be used to rule out certain FCD mechanisms, and to predict their cooperativity parameter. We demonstrate this approach using data from eukaryotic chemotaxis signaling.

Tongue-Supported Human-Computer Interaction systems: a review.

The tongue can substitute human sensory systems and has been used as a medium of input to help impaired patients communicate with the world. Innovative techniques have been employed to realize tongue movement, sense its position and exploit tongue dexterity, in order to achieve Tongue Supported Human Computer Interaction (TSHCI). This paper examines various approaches of using tongue dexterousness in TSHCI systems and introduces two infrared signal supported minimally-invasive TSHCI systems developed at Curtin University. Methods of sensing tongue movement and position are especially discussed and depending on the employed methods, TSHCI systems are categorized as either invasive or minimally-invasive. A set of system usability criteria is proposed to help build more effective TSHCI systems in future.

Addition of visual noise boosts evoked potential-based brain-computer interface.

Although noise has a proven beneficial role in brain functions, there have not been any attempts on the dedication of stochastic resonance effect in neural engineering applications, especially in researches of brain-computer interfaces (BCIs). In our study, a steady-state motion visual evoked potential (SSMVEP)-based BCI with periodic visual stimulation plus moderate spatiotemporal noise can achieve better offline and online performance due to enhancement of periodic components in brain responses, which was accompanied by suppression of high harmonics. Offline results behaved with a bell-shaped resonance-like functionality and 7–36% online performance improvements can be achieved when identical visual noise was adopted for different stimulation frequencies. Using neural encoding modeling, these phenomena can be explained as noise-induced input-output synchronization in human sensory systems which commonly possess a low-pass property. Our work demonstrated that noise could boost BCIs in addressing human needs.

The human sensory system as a collection of specialized fuzzifiers: A conceptual framework to inspire new artificial intelligent systems computing with words

The Human Sensory System consists of seven distinct elements: the visual, olfactory, gustatory, auditory, superficial somatosensory, inner somatosensory along with vestibular, and thermosensory systems. Each of them is provided with a specialized sets of receptor cells and is able to perceive a stimulus of specific modality. The power to finely discriminate different stimuli of the same modality derives from the properties of the receptor cells which play like fuzzy sets. A stimulus belongs to the receptor fuzzy sets at different degrees. The information of stimuli is encoded in fuzzy information, i.e. in values of membership functions. Due to the structural constraints of sensory systems and the neural noise, human perception is fuzzy-granular and a process of Bayesian probabilistic inference. A link between the Bayes theory of perception and fuzzy sensory information is established in this work. The ideas presented herein will inspire the design of new Artificial Sensory Systems having the purpose of solving Pattern Recognition problems.

Mechanical life: expression of artificial life shown in kinetic art

The use of various media as well as development of technique led to much attention to artistic expression of artificial life. In particular, development of motor to which high technique is applied, application of sensor which plays a role like a human sensory system as well as research on new type of system to which objet is combined that reacts to external environment contribute to artistic creation. In addition, application of characteristics that lives have enabled classification as mechanical life unlike simple mechanical system. Existing kinetic art produced artworks considering only movement as important concept. However, application of research which simulates process of life by using computer or other media helped express mechanical life. This study analyzes kinetic artworks which were created based on theories on artificial life. This study covers artistic value of articial life in kinetic art by making mechanical life that can expand communication with spectators.

The Human Machine at the Aboagora Symposium

Aboagora 2013 discussed the complex relationships between man and machine, where not only may the human being itself be viewed as a corporeal machine, but it is also possible to interpret the machine as an extension of the human sensory system. After three days of lectures and workshops about the multifaceted relationship between man and the machine, the ontological dividing line between humans and machines was open to question. For example, while the human body can be defined as the ultimate machine – an assemblage of forces, actions and mechanisms ranging from the optics of the eye to the processes of cognition – the boundaries between man and machine may be blurred as technological devices are used as integral parts of the human body. Where do we draw the line between man and machine in such situations? The Aboagora symposium on 'The Human Machine' raised important questions about the ontological qualities and delineations of various entities.

Inference management, trust and obfuscation principles for quality of information in emerging pervasive environments

The emergence of large scale, distributed, sensor-enabled, machine-to-machine pervasive applications necessitates engaging with providers of information on demand to collect the information, of varying quality levels, to be used to infer about the state of the world and decide actions in response. In these highly fluid operational environments, involving information providers and consumers of various degrees of trust and intentions, information transformation, such as obfuscation, is used to manage the inferences that could be made to protect providers from misuses of the information they share, while still providing benefits to their information consumers. In this paper, we develop the initial principles for relating to inference management and the role that trust and obfuscation plays in it within the context of this emerging breed of applications. We start by extending the definitions of trust and obfuscation into this emerging application space. We, then, highlight their role as we move from the tightly-coupled to loosely-coupled sensory-inference systems and describe how quality, value and risk of information relate in collaborative and adversarial systems. Next, we discuss quality distortion illustrated through a human activity recognition sensory system. We then present a system architecture to support an inference firewall capability in a publish/subscribe system for sensory information and conclude with a discussion and closing remarks.

Spectral data reveal unexpected cryptic colour polymorphism in female sailfin silverside fish from ancient Lake Matano

Persistent colour polymorphisms can result from natural and/or sexual selection, and may occur in males, females, or both sexes. Contrary to conspicuous patterns frequently observed in courtship colouration, differences in cryptic colouration are not always perceived by the human sensory system. In sexually dimorphic sailfin silversides fishes, males show conspicuous colour polymorphisms whereas females appear monomorphic and cryptic. We measured the spectral composition of body, fin and peduncle colouration in male and female Telmatherina antoniae ‘small’, a sailfin silverside species endemic to ancient Lake Matano, and found evidence for a colour polymorphism in both sexes. The three colour morphs distinguished by spectral data correspond to those commonly reported for males, and are also present in the visually (to a human eye) cryptic females. Females show hue value patterns similar to those present in males, but differ from males substantially in chroma and brightness. This is, to the best of our knowledge, the first example of a cryptic colour polymorphism in fishes; however, its significance for the mating system remains unknown. The present finding highlights the need for incorporating female spectral data into analyses of colour patterns, and suggests that colour analyses should include cryptic sexes.

Formal Models and Cognitive Mechanisms of the Human Sensory System

The human sensory system is a perfect natural real-time distributed system. It transforms physical and chemical stimuli of the external environment into electronic neural signals by specialized sensory receptors. This paper presents a comprehensive framework of the human sensory system as well as its cognitive and theoretical foundations. A set of primary and perceptual sensory and neural receptors is formally modeled and analyzed. Sensory neural interfaces and interactions to the central and peripheral nervous systems of the brain and associated memories are systematically described. This work is a part of a strategic project towards the development of cognitive computers and cognitive robots.