Stimulus Information Research Articles

청취-작문 융합형 수업 모델 연구: 정보처리이론을 바탕으로

The human information processing center “memory” is defined as the process of encoding – storage – retrieval of external stimuli (information). Considering that all learning begins with memories, the teaching-learning design should present an efficient methodology without biasing the learner’s cognitive process step by step. Based on this information processing theory, this study systematically considered the following three aspects: First, an efficient teaching-learning model is designed by focusing on the input (listening) and output (writing) of the second foreign language on the premise of facilitating communication, which is the goal of language learning. Second, we will try to implement the structuring and systematization of knowledge, which is the ultimate goal of learning, through language learning. Lastly, in applying this to actual classes, based on the constructivism epistemology, the REACT model (Crawford, 2001) - Relating, Experiencing, Applying, Cooperating, Transferring - is borrowed, through which the lecture is conducted. The survey was also conducted for analyzing students’ perceptions of the learning methodology and got meaningful results from students’ lecture evaluations.

Current situation and prospect of researches on regularities and mechanisms of acupuncture-moxibustion in alleviating chronic inflammatory response

The inflammatory response plays an important role in the onset, development and prognosis of inflammatory diseases and a variety of chronic diseases. Long-term uncontrolled inflammatory response may lead to dysfunction or loss of organ tissue function. Clinical practice and evidence-based medicine suggest that acupuncture can effectively alleviate the inflammatory status of various inflammatory diseases and chronic diseases. Stimulation of acupoints related to internal organs and target organs can initiate neuromodulation by modulating the microenvironment of acupoints. After integration of acupuncture stimulus information in the central nervous system, neurotransmitters, hormones, etc. are released and ultimately act on immune cells through neuro-endocrine-immune pathways, such as the vagus-mediated cholinergic anti-inflammatory pathway, vagus nerve-adrenal medullary-dopamine pathway, somatic sympathetic nerve pathway, and hypothalamic-pituitary-adrenal axis, etc. Ultimately, the intracellular signaling pathways and polarization balance of monocytes/macrophages and T cell subsets are regulated and the immune homeo-stasis of target organs of the body realizes. Therefore, we proposed that the anti-inflammatory action of acupuncture may be one of the universal therapeutic strategies for multiple diseases, and a powerful interpretation of acupuncture in regulating the balance of yin and yang. The elucidation of its anti-inflammatory action rules and mechanism may better realize the clinical transformation of acupuncture and moxibustion precision treatment.

Distinct early and late neural mechanisms regulate feature-specific sensory adaptation in the human visual system

A canonical feature of sensory systems is that they adapt to prolonged or repeated inputs, suggesting the brain encodes the temporal context in which stimuli are embedded. Sensory adaptation has been observed in the central nervous systems of many animal species, using techniques sensitive to a broad range of spatiotemporal scales of neural activity. Two competing models have been proposed to account for the phenomenon. One assumes that adaptation reflects reduced neuronal sensitivity to sensory inputs over time (the "fatigue" account); the other posits that adaptation arises due to increased neuronal selectivity (the "sharpening" account). To adjudicate between these accounts, we exploited the well-known "tilt aftereffect", which reflects adaptation to orientation information in visual stimuli. We recorded whole-brain activity with millisecond precision from human observers as they viewed oriented gratings before and after adaptation, and used inverted encoding modeling to characterize feature-specific neural responses. We found that both fatigue and sharpening mechanisms contribute to the tilt aftereffect, but that they operate at different points in the sensory processing cascade to produce qualitatively distinct outcomes. Specifically, fatigue operates during the initial stages of processing, consistent with tonic inhibition of feedforward responses, whereas sharpening occurs ~200 ms later, consistent with feedback or local recurrent activity. Our findings reconcile two major accounts of sensory adaptation, and reveal how this canonical process optimizes the detection of change in sensory inputs through efficient neural coding.

Hierarchical differences in the encoding of sound and choice in the subcortical auditory system.

Detection of sounds is a fundamental function of the auditory system. Although studies of auditory cortex have gained substantial insight into detection performance using behaving animals, previous subcortical studies have mostly taken place under anesthesia, in passively listening animals, or have not measured performance at threshold. These limitations preclude direct comparisons between neuronal responses and behavior. To address this, we simultaneously measured auditory detection performance and single-unit activity in the inferior colliculus (IC) and cochlear nucleus (CN) in macaques. The spontaneous activity and response variability of CN neurons were higher than those observed for IC neurons. Signal detection theoretic methods revealed that the magnitude of responses of IC neurons provided more reliable estimates of psychometric threshold and slope compared with the responses of single CN neurons. However, pooling small populations of CN neurons provided reliable estimates of psychometric threshold and slope, suggesting sufficient information in CN population activity. Trial-by-trial correlations between spike count and behavioral response emerged 50-75 ms after sound onset for most IC neurons, but for few neurons in the CN. These results highlight hierarchical differences between neurometric-psychometric correlations in CN and IC and have important implications for how subcortical information could be decoded.NEW & NOTEWORTHY The cerebral cortex is widely recognized to play a role in sensory processing and decision-making. Accounts of the neural basis of auditory perception and its dysfunction are based on this idea. However, significantly less attention has been paid to midbrain and brainstem structures in this regard. Here, we find that subcortical auditory neurons represent stimulus information sufficient for detection and predict behavioral choice on a trial-by-trial basis.

Skin properties and afferent density in the deterioration of tactile spatial acuity with age.

Tactile sensitivity is affected by age, as shown by the deterioration of spatial acuity assessed with the two-point discrimination task. This is assumed to be partly a result of age-related changes of the peripheral somatosensory system. In particular, in the elderly, the density of mechanoreceptive afferents decreases with age and the skin tends to become drier, less elastic and less stiff. To assess to what degree mechanoreceptor density, skin hydration, elasticity and stiffness can account for the deterioration of tactile spatial sensitivity observed in the elderly, several approaches were combined, including psychophysics, measurements of finger properties, modelling and simulation of the response of first-order tactile neurons. Psychophysics confirmed that the Elderly group has lower tactile acuity than the Young group. Correlation and commonality analysis showed that age was the most important factor in explaining decreases in behavioural performance. Biological elasticity, hydration and finger pad area were also involved. These results were consistent with the outcome of simulations showing that lower afferent density and lower Young's modulus (i.e. lower stiffness) negatively affected the tactile encoding of stimulus information. Simulations revealed that these changes resulted in a lower build-up of task-relevant stimulus information. Importantly, the reduction in discrimination performance with age in the simulation was less than that observed in the psychophysical testing, indicating that there are additional peripheral as well as central factors responsible for age-related changes in tactile discrimination. KEY POINTS: Ageing effects on tactile perception involve the deterioration of spatial sensitivity, although the contribution of central and peripheral factors is not clear. We combined psychophysics, measurements of finger properties, modelling and simulation of the response of first-order tactile neurons to investigate to what extent skin elasticity, stiffness, hydration, finger pad area and afferent density can account for the lower spatial sensitivity observed in the elderly. Correlation and commonality analysis revealed that age was the most important factor to predict behavioural performance. Skin biological elasticity, hydration and finger pad area contributed to a lesser extent. The simulation of first-order tactile neuron responses indicated that reduction in afferent density plays a major role in the deterioration of tactile spatial acuity. Simulations also showed that lower skin stiffness and lower afferent density affect the build-up of stimulus information and the response of SA1 (i.e. type 1 slowly adapting fibres) and RA1 (i.e. type 1 rapidly adapting fibres) afferent fibres.

Geometries in sound: an investigation of embodied cognition in contemporary art music

This paper examines how listeners hear contemporary art music practices such as post-spectralism, glitch-electronica, contemporary classical and electroacoustic music. The sound configurations of this music evoke sensorial qualities and mental imagery as abstract geometries. These result from tonotopic information of acoustic stimuli organised according to Gestalt and kinaesthetic patterns. The study, employing listening surveys, suggests that our aural experience involves an embodied connection to the world. This paper proposes that contemporary art music facilitates an engagement with our experiential knowledge, minimising semantic interpretation and factual listening. Overall, it offers new insights into perceptual approaches to contemporary art music.

A Spiking Neural Network with Adaptive Graph Convolution and LSTM for EEG-Based Brain-Computer Interfaces.

Electroencephalography (EEG) signals classification is essential for the brain-computer interface (BCI). Recently, energy-efficient spiking neural networks (SNNs) have shown great potential in EEG analysis due to their ability to capture the complex dynamic properties of biological neurons while also processing stimulus information through precisely timed spike trains. However, most existing methods do not effectively mine the specific spatial topology of EEG channels and temporal dependencies of the encoded EEG spikes. Moreover, most are designed for specific BCI tasks and lack some generality. Hence, this study presents a novel SNN model with the customized spike-based adaptive graph convolution and long short-term memory (LSTM), termed SGLNet, for EEG-based BCIs. Specifically, we first adopt a learnable spike encoder to convert the raw EEG signals into spike trains. Then, we tailor the concepts of the multi-head adaptive graph convolution to SNN so that it can make good use of the intrinsic spatial topology information among distinct EEG channels. Finally, we design the spike-based LSTM units to further capture the temporal dependencies of the spikes. We evaluate our proposed model on two publicly available datasets from two representative fields of BCI, notably emotion recognition, and motor imagery decoding. The empirical evaluations demonstrate that SGLNet consistently outperforms existing state-of-the-art EEG classification algorithms. This work provides a new perspective for exploring high-performance SNNs for future BCIs with rich spatiotemporal dynamics.

Attentional adjustment in priming tasks: control strategies depend on context

Goal-directed behavior is assumed to require processes of attentional biasing to counter unwanted action tendencies elicited by distracting stimulus information. This is particularly so if stimulus categories that define the target and the distractor frequently reverse, requiring participants to respond to previously ignored stimulus categories and vice versa. In the current study, we investigated control strategies under such conditions. Specifically, we assessed trial-to-trial modulation of distractor-interference (i.e., congruency sequence effect, CSE) in a temporal flanker task associated with repetition versus alternation of the assignment of stimulus category (i.e., digits, letters) to targets and distractors (i.e., the character presented second or first, respectively) under conditions of a long SOA of 1000 ms (Experiment 1A) and 1200 ms (Experiment 1B). Whereas previous research, using a shorter SOA, suggested temporal-order control (i.e., the occurrence of a CSE in both repetition and—albeit less pronounced—alternation trials), lengthening the distractor-target SOA resulted in a CSE confined to repetition trials, suggesting strong or exclusive reliance on stimulus categories for attentional control (Experiment 1A and B). Adding a redundant stimulus feature (i.e., color), discriminating targets and distractors, eliminated the difference of CSE patterns in repetition and alternation trials (Experiment 2). Together, our results suggest that the strength of concurrently applied control strategies or the choice of a particular control strategy depend on contextual factors.

Neurophysiological evidence against attentional suppression as the source of the same-location cost in spatial cueing.

Spatial cues that mismatch the colour of a subsequent target have been shown to slow responses to targets that share their location. The source of this 'same location cost' (SLC) is currently unknown. Two potential sources are attentional signal suppression and object-file updating. Here, we tested a direct prediction of the suppression account using data from a spatial-cueing study in which we recorded brain activity using electroencephalography (EEG), and focusing on the event-related PD component, which is thought to index attentional signal suppression. Correlating PD amplitude with SLC magnitude, we tested the prediction that if attentional signal suppression is the source of the SLC, then the SLC should be positively correlated with PD amplitude. Across 48 participants, SLC and PD magnitudes were negatively correlated, in direct contradiction to a suppression account of the SLC. These results are compatible with an object-file updating account of the SLC in which updating is facilitated by reactive suppression of the to-be-updated stimulus information.

Pressure‐Temperature Dual‐Parameter Flexible Sensors Based on Conformal Printing of Conducting Polymer PEDOT:PSS on Microstructured Substrate

AbstractFlexible sensors play an important role in collecting stimuli information and sending them to a central processing unit or cloud for analysis and decision‐making. As much information is needed to be collected, the fabrication of multiparameter flexible sensors is becoming increasingly urgent. To this end, conducting polymer‐based composites have been proven as promising materials for developing pressure‐temperature dual‐parameter sensors. However, fabrication of ideal dual‐parameter sensors with fully decoupled pressure‐temperature readings, good sensitivity, and a simple preparation process remain challenges. Here, a strategy of fabricating a pressure‐temperature dual‐parameter sensor based on conformal printing of conducting polymer poly(3,4‐ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) on the surface of microstructured polydimethylsiloxane (PDMS) substrate is demonstrated. It is found that secondary doped PEDOT:PSS provides temperature‐independent conductivity. Combined with the sea‐island microstructured PDMS substrate, a screen‐printed flexible sensor demonstrates fully decoupled pressure‐temperature reading ability, competitive sensitivity, and good stability. The excellent sensing properties of the devices, with a maximum pressure sensitivity of 134.25 kPa−1 and linear response region over 300 kPa as well as highly sensitive temperature sensing for finger touch, together with their unique advantages of low‐cost and large‐area fabrication, make the printed flexible dual‐parameter sensors promising applications in electric‐skin (e‐skin), human‐machine interaction, and robotics.

Developments in Transcranial Magnetic Stimulation to Study Human Cognition.

Developments in Transcranial Magnetic Stimulation to Study Human Cognition.

Get Stoke(s)d! Introduction to the Special Focus.

Get Stoke(s)d! Introduction to the Special Focus.

A corticostriatal projection for sound-evoked and anticipatory motor behavior following temporal expectation.

The ability to form predictions based on recent sensory experience is essential for behavioral adaptation to our ever-changing environment. Predictive encoding represented by neuronal activity has been observed in sensory cortex, but how this neuronal activity is transformed into anticipatory motor behavior remains unclear. Fiber photometry to investigate a corticostriatal projection from the auditory cortex to the posterior striatum during an auditory paradigm in mice, and pharmacological experiments in a task that induces a temporal expectation of upcoming sensory stimuli. We find that the auditory corticostriatal projection relays both sound-evoked stimulus information as well as predictive signals in relation to stimulus timing following rhythmic auditory stimulation. Pharmacological experiments suggest that this projection is required for the initiation of both sound-evoked and anticipatory licking behavior in an auditory associative-learning behavioral task, but not for the general recognition of presented auditory stimuli. This auditory corticostriatal projection carries predictive signals, and the posterior striatum is critical to the anticipatory stimulus-driven motor behavior.

Evidence for independent representational contents in inhibitory control subprocesses associated with frontoparietal cortices.

Inhibitory control processes have intensively been studied in cognitive science for the past decades. Even though the neural dynamics underlying these processes are increasingly better understood, a critical open question is how the representational dynamics of the inhibitory control processes are modulated when engaging in response inhibition in a relatively automatic or a controlled mode. Against the background of an overarching theory of perception-action integration, we combine temporal and spatial EEG signal decomposition methods with multivariate pattern analysis and source localization to obtain fine-grained insights into the neural dynamics of the representational content of response inhibition. For this purpose, we used a sample of N= 40 healthy adult participants. The behavioural data suggest that response inhibition was better in a more controlled than a more automated response execution mode. Regarding neural dynamics, effects of response inhibition modes relied on a concomitant coding of stimulus-related information and rules of how stimulus information is related to the appropriate motor programme. Crucially, these fractions of information, which are encoded at the same time in the neurophysiological signal, are based on two independent spatial neurophysiological activity patterns, also showing differences in the temporal stability of the representational content. Source localizations revealed that the precuneus and inferior parietal cortex regions are more relevant than prefrontal areas for the representation of stimulus-response selection codes. We provide a blueprint how a concatenation of EEG signal analysis methods, capturing distinct aspects of neural dynamics, can be connected to cognitive science theory on the importance of representations in action control.

Relationship between Economic Stimulus Programme and Information Communication Technology Integration in Selected Public Secondary Schools in Kenya

Relationship between Economic Stimulus Programme and Information Communication Technology Integration in Selected Public Secondary Schools in Kenya

Decreased Modulation of Population Correlations in Auditory Cortex Is Associated with Decreased Auditory Detection Performance in Old Mice.

Age-related hearing loss (presbycusis) affects one-third of the world's population. One hallmark of presbycusis is difficulty hearing in noisy environments. Presbycusis can be separated into two components: the aging ear and the aging brain. To date, the role of the aging brain in presbycusis is not well understood. Activity in the primary auditory cortex (A1) during a behavioral task is because of a combination of responses representing the acoustic stimuli, attentional gain, and behavioral choice. Disruptions in any of these aspects can lead to decreased auditory processing. To investigate how these distinct components are disrupted in aging, we performed in vivo 2-photon Ca2+ imaging in both male and female mice (Thy1-GCaMP6s × CBA/CaJ mice) that retain peripheral hearing into old age. We imaged A1 neurons of young adult (2-6 months) and old mice (16-24 months) during a tone detection task in broadband noise. While young mice performed well, old mice performed worse at low signal-to-noise ratios. Calcium imaging showed that old animals have increased prestimulus activity, reduced attentional gain, and increased noise correlations. Increased correlations in old animals exist regardless of cell tuning and behavioral outcome, and these correlated networks exist over a much larger portion of cortical space. Neural decoding techniques suggest that this prestimulus activity is predictive of old animals making early responses. Together, our results suggest a model in which old animals have higher and more correlated prestimulus activity and cannot fully suppress this activity, leading to the decreased representation of targets among distracting stimuli.SIGNIFICANCE STATEMENT Aging inhibits the ability to hear clearly in noisy environments. We show that the aging auditory cortex is unable to fully suppress its responses to background noise. During an auditory behavior, fewer neurons were suppressed in the old relative to young animals, which leads to higher prestimulus activity and more false alarms. We show that this excess activity additionally leads to increased correlations between neurons, reducing the amount of relevant stimulus information in the auditory cortex. Future work identifying the lost circuits that are responsible for proper background suppression could provide new targets for therapeutic strategies to preserve auditory processing ability into old age.

Category learning in a recurrent neural network with reinforcement learning.

It is known that humans and animals can learn and utilize category information quickly and efficiently to adapt to changing environments, and several brain areas are involved in learning and encoding category information. However, it is unclear that how the brain system learns and forms categorical representations from the view of neural circuits. In order to investigate this issue from the network level, we combine a recurrent neural network with reinforcement learning to construct a deep reinforcement learning model to demonstrate how the category is learned and represented in the network. The model consists of a policy network and a value network. The policy network is responsible for updating the policy to choose actions, while the value network is responsible for evaluating the action to predict rewards. The agent learns dynamically through the information interaction between the policy network and the value network. This model was trained to learn six stimulus-stimulus associative chains in a sequential paired-association task that was learned by the monkey. The simulated results demonstrated that our model was able to learn the stimulus-stimulus associative chains, and successfully reproduced the similar behavior of the monkey performing the same task. Two types of neurons were found in this model: one type primarily encoded identity information about individual stimuli; the other type mainly encoded category information of associated stimuli in one chain. The two types of activity-patterns were also observed in the primate prefrontal cortex after the monkey learned the same task. Furthermore, the ability of these two types of neurons to encode stimulus or category information was enhanced during this model was learning the task. Our results suggest that the neurons in the recurrent neural network have the ability to form categorical representations through deep reinforcement learning during learning stimulus-stimulus associations. It might provide a new approach for understanding neuronal mechanisms underlying how the prefrontal cortex learns and encodes category information.

Decoding Visual fMRI Stimuli from Human Brain Based on Graph Convolutional Neural Network

Brain decoding is to predict the external stimulus information from the collected brain response activities, and visual information is one of the most important sources of external stimulus information. Decoding functional magnetic resonance imaging (fMRI) based on visual stimulation is helpful in understanding the working mechanism of the brain visual function regions. Traditional brain decoding algorithms cannot accurately extract stimuli features from fMRI. To address these shortcomings, this paper proposed a brain decoding algorithm based on a graph convolution network (GCN). Firstly, 11 regions of interest (ROI) were selected according to the human brain visual function regions, which can avoid the noise interference of the non-visual regions of the human brain; then, a deep three-dimensional convolution neural network was specially designed to extract the features of these 11 regions; next, the GCN was used to extract the functional correlation features between the different human brain visual regions. Furthermore, to avoid the problem of gradient disappearance when there were too many layers of graph convolutional neural network, the residual connections were adopted in our algorithm, which helped to integrate different levels of features in order to improve the accuracy of the proposed GCN. The proposed algorithm was tested on the public dataset, and the recognition accuracy reached 98.67%. Compared with the other state-of-the-art algorithms, the proposed algorithm performed the best.

Processing directional information in stimuli inhibits the spatial association of luminance levels.

Previous studies have found that the spatial-numerical association of the response codes (SNARC) effect automatically occurred when processing both numbers and non-symbolic magnitudes. However, this conclusion was challenged by several recent studies that found no SNARC effect when processing non-symbolic magnitudes with a directional cue. In the present study, we hypothesized that automatic spatial association of non-symbolic magnitudes would be inhibited by directional cues; thus, we utilized left and right arrow stimuli with different luminance levels to systematically investigate the spatial association of luminance. To ensure that participants could effectively discriminate the luminance stimuli, we first replicated the SNARC effect in Experiment 1, by presenting rectangles with different luminance levels. Then, arrows with the same luminance levels as the rectangles were randomly presented to participants on the centre of a screen; participants completed direction classification (Experiment 2), colour classification (Experiment 3), or luminance classification (Experiment 4) tasks with these arrow stimuli. We found that (1) the SNARC effect was present when processing rectangles with different luminance levels (Experiment 1); however, (2) the Simon-like effect rather than the spatial association of luminance was observed when processing arrows with different luminance levels in the luminance-irrelevant classification tasks (Experiments 2 and 3) and the luminance-relevant classification task (Experiment 4). These results indicate that processing of a directional cue inhibited the spatial association of luminance in both luminance-relevant and luminance-irrelevant classification tasks.

Enhancing allocation of visual attention with emotional cues presented in two sensory modalities

BackgroundResponses to a visual target stimulus in an exogenous spatial cueing paradigm are usually faster if cue and target occur in the same rather than in different locations (i.e., valid vs. invalid), although perceptual conditions for cue and target processing are otherwise equivalent. This cueing validity effect can be increased by adding emotional (task-unrelated) content to the cue. In contrast, adding a secondary non-emotional sensory modality to the cue (bimodal), has not consistently yielded increased cueing effects in previous studies. Here, we examined the interplay of bimodally presented cue content (i.e., emotional vs. neutral), by using combined visual-auditory cues. Specifically, the current ERP-study investigated whether bimodal presentation of fear-related content amplifies deployment of spatial attention to the cued location.ResultsA behavioral cueing validity effect occurred selectively in trials in which both aspects of the cue (i.e., face and voice) were related to fear. Likewise, the posterior contra-ipsilateral P1-activity in valid trials was significantly larger when both cues were fear-related than in all other cue conditions. Although the P3a component appeared uniformly increased in invalidly cued trials, regardless of cue content, a positive LPC deflection, starting about 450 ms after target onset, was, again, maximal for the validity contrast in trials associated with bimodal presentation of fear-related cues.ConclusionsSimultaneous presentation of fear-related stimulus information in the visual and auditory modality appears to increase sustained visual attention (impairing disengagement of attention from the cued location) and to affect relatively late stages of target processing.