The article presents and discusses an ongoing fellowship project entitled ‘Space for Interference’, conducted under the Norwegian Programme for Research Fellowships in the Arts. Two concrete site-specific art projects produced under Space for Interference serve as a point of departure for an investigation into methods of interference and the forms of address that artists use when intervening in other specialized fields in society. The institutions that provide the site for an art project have different social functions. We ask what may (...) be their motivation for allowing artists access to their physical environments, apparatuses, procedures, systems and discourses. The fact that the artists’ projects in these contexts function as a means of self-observation for the institutions seems obvious. Nevertheless, we seek to investigate the various economic and political factors that allow these institutions to include potentially critical activities, which aim to modify or transgress their systems, and thereby displaying how they are malleable and mobile bodies. One assertion we make is that by doing so the involved institutions prove to be modern, self-critical and flexible, thus complying with political requirements to adapt to the rapidly changing environments of the information and communication age. The perspective from systems theory in the Luhmannian tradition has proved useful since it shows how the issues of art may also be the problems of science, business, politics and the law in the complex and decentered social universe of today. The issues of contingency, insecurity, paradox and autoreflexivity, surplus meanings and the complexity and decentering of the subject are at the heart of contemporary art. Systems theory provides a way to link such practices theoretically with scientific discourse and with the advanced problem solving and criticality of other social domains, like politics, business and the media industries. (shrink)

The quality and quantity of training data are crucial to the performance of a deep-learning-based brain-computer interface system. However, it is not practical to record EEG data over several long calibration sessions. A promising time- and cost-efficient solution is artificial data generation or data augmentation. Here, we proposed a DA method for the motor imagery EEG signal called brain-area-recombination. For the BAR, each sample was first separated into two ones by left/right brain channels, and the artificial samples were generated by (...) recombining the half-samples. We then designed two schemas corresponding to the single- and multi-subject scenarios. Extensive experiments using the classifier of EEGnet were conducted on two public datasets under various training set sizes. In both schemas, the BAR method can make the EEGnet have a better performance of classification. To make a comparative investigation, we selected two common DA methods, and the BAR method beat them. Further, using the proposed BAR for augmentation, EEGnet achieved up to 8.3% improvement than a typical decoding algorithm CSP-SVM, note that both the models were trained on the augmented dataset. This study shows that BAR usage can significantly improve the classification ability of deep learning to MI-EEG signals. To a certain extent, it may promote the development of deep learning technology in the field of BCI. (shrink)

The purpose of the article is to shed light on how experiences of sensory perceptions in the domains of vision, smell, taste, and touch are recast into text and discourse in the genre of wine reviews. Because of the alleged paucity of sensory vocabularies, in particular in the olfactory domain, it is of particular interest to investigate what resources language has to offer in order to describe those experiences. We show that the main resources are, on the one hand, words (...) evoking properties that are applicable cross-modally and properties of objects that range over more than one domain, and on the other, vivid imagery that compares the characteristics of the wine with people, buildings, animals, and the hustle and bustle of market places and other events. The second goal is to account for the construals of the meanings of the expressions used in the recontextualization into written discourse in the light of their apparent flexibility across the descriptions of the sensory experiences. In contrast to a large body of the literature on sensory meanings in language, we argue that the descriptors of properties such as sharp, soft, lemon, and cherry used to describe a wine's qualities across the sensory domains are not polysemous synesthetic metaphors, but monosemous synesthetic metonymizations, more precisely zone activations. With regard to the imagery used, the construals represented cover both similes, metaphorizations and metonymizations proper. (shrink)

Molecular vibrations and quantum tunneling may link ligand binding to the function of pharmacological receptors. The well‐established lock‐and‐key model explains a ligand's binding and recognition by a receptor; however, a general mechanism by which receptors translate binding into activation, inactivation, or modulation remains elusive. The Vibration Theory of Olfaction was proposed in the 1930s to explain this subset of receptor‐mediated phenomena by correlating odorant molecular vibrations to smell, but a mechanism was lacking. In the 1990s, inelastic electron tunneling was proposed (...) as a plausible mechanism for translating molecular vibration to odorant physiology. More recently, studies of ligands’ vibrational spectra and the use of deuterated ligand analogs have provided helpful information to study this admittedly controversial hypothesis in metabotropic receptors other than olfactory receptors. In the present work, based in part on published experiments from our laboratory using planarians as an experimental organism, I will present a rationale and possible experimental approach for extending this idea to ligand‐gated ion channels. (shrink)

A set of images can be considered as meaningfully different for an observer if they can be distinguished phenomenally from one another. Each phenomenal difference must be supported by some neurophysiological differences. Differentiation analysis aims to quantify neurophysiological differentiation evoked by a given set of stimuli to assess its meaningfulness to the individual observer. As a proof of concept using high-density EEG, we show increased neurophysiological differentiation for a set of natural, meaningfully different images in contrast to another set of (...) artificially generated, meaninglessly different images in nine participants. Stimulus-evoked neurophysiological differentiation (over 257 channels, 800 ms) was systematically greater for meaningful vs. meaningless stimulus categories both at the group level and for individual subjects. Spatial breakdown showed a central-posterior peak of differentiation, consistent with the visual nature of the stimulus sets. Temporal breakdown revealed an early peak of differentiation around 110 ms, prominent in the central-posterior region; and a later, longer-lasting peak at 300–500 ms that was spatially more distributed. The early peak of differentiation was not accompanied by changes in mean ERP amplitude, whereas the later peak was associated with a higher amplitude ERP for meaningful images. An ERP component similar to visual-awareness-negativity occurred during the nadir of differentiation across all image types. Control stimulus sets and further analysis indicate that changes in neurophysiological differentiation between meaningful and meaningless stimulus sets could not be accounted for by spatial properties of the stimuli or by stimulus novelty and predictability. (shrink)

Loving-Kindness Meditation (LKM) is an efficient mental practice with a long history that has recently attracted interest in the fields of neuroscience, medicine and education. However, the neural characters and underlying mechanisms have not yet been fully illustrated, which has hindered its practical usefulness. This study aimed to investigate LKM from varied aspects and interactions between the brain, the heart, and psychological measurements. A Buddhist monk practitioner was recruited to complete one 10-min LKM practice, in between two 10-min resting tasks (...) (pre- and post-resting) per experimental run. Two sets of single-channel wearable EEG devices were used to collect EEG data (placed at Fz and Pz) and heart rate simultaneously. A self-report evaluation was conducted to repeatedly record the comprehensive performance of mind and body in each session. EEG data were preprossessed and analyzed by EEGlab. Further statistics were made by SPSS. Spectrum analysis showed a significant increase of theta power (Fz: t = −3.356; p = 0.002; Pz: t = −5.199; p < 0.001) and decrease of heart rate between pre- and post-resting tasks (t = 4.092, p < 0.001). The analysis showed a negative correlation between theta power and heart rate (Fz: r = −0.681, p < 0.001; Pz: r = −0.384, p = 0.008), and a positive correlation between theta power and the self-designed report score (Fz: r = 0.601, p < 0.001). These findings suggest that LKM is accompanied by significant neurophysiological changes, mainly an increase in slower frequencies, such as theta, and a decrease in heart rate. More importantly, subjective psychological assessments were also correlated with objective neurophysiological measurements in a long-term meditator participant. During LKM meditation, this connection was stronger. The results of this case report have promising implications for LKM practice in daily life. (shrink)

In special application scenarios, such as portable anesthesia depth monitoring, portable emotional state recognition and portable sleep monitoring, electroencephalogram (EEG) signal acquisition equipment is required to be convenient and easy to use. It is difficult to remove electrooculogram (EOG) artifacts when the number of EEG acquisition channels is small, especially when the number of observed signals is less than that of the source signals, and the overcomplete problem will arise. The independent component analysis (ICA) algorithm commonly used for artifact removal (...) requires the number of basis vectors to be smaller than the dimension of the input data due to a set of standard orthonormal bases learned during the convergence process, so it cannot be used to solve the overcomplete problem. The empirical mode decomposition method decomposes the signal into several independent intrinsic mode functions so that the number of observed signals is more than that of the source signals, solving the overcomplete problem. However, when using this method to solve overcompleteness, the modal aliasing problem will arise, which is caused by abnormal events such as sharp signals, impulse interference, and noise. Aiming at the above problems, we propose a novel EEG artifact removal method based on discrete wavelet transform, complete empirical mode decomposition for adaptive noise (CEEMDAN) and ICA in this paper. First, the input signals are transformed by discrete wavelet (DWT), and then CEEMDAN is used to solve the overcomplete and mode aliasing problems, meeting the a priori conditions of the ICA algorithm. Finally, the components belonging to EOG artifacts are removed according to the sample entropy value of each independent component. Experiments show that this method can effectively remove EOG artifacts while solving the overcomplete and modal aliasing problems. (shrink)

Depression is a common mental health illness worldwide that affects our quality of life and ability to work. Although prior research has used EEG signals to increase the accuracy to identify depression, the rates of underdiagnosis remain high, and novel methods are required to identify depression. In this study, we built a model based on single-channel, dry-electrode EEG sensor technology to detect state depression, which measures the intensity of depressive feelings and cognitions at a particular time. To test the (...) accuracy of our model, we compared the results of our model with other commonly used methods for depression diagnosis, including the PHQ-9, Hamilton Depression Rating Scale, and House-Tree-Person drawing test, in three different studies. In study 1, we compared the results of our model with PHQ-9 in a sample of 158 senior high students. The results showed that the consistency rate of the two methods was 61.4%. In study 2, the results of our model were compared with HAM-D among 71 adults. We found that the consistency rate of state-depression identification by the two methods was 63.38% when a HAM-D score above 7 was considered depression, while the consistency rate increased to 83.10% when subjects showed at least one depressive symptom. In study 3, 68 adults participated in the study, and the results revealed that the consistency rate of our model and HTP drawing test was 91.2%. The results showed that our model is an effective means to identify state depression. Our study demonstrates that using our model, people with state depression could be identified in a timely manner and receive interventions or treatments, which may be helpful for the early detection of depression. (shrink)

Natural fluctuations in sustained attention can lead to attentional failures in everyday tasks and even dangerous incidences. These fluctuations depend on personal factors, as well as task characteristics. So far, our understanding of sustained attention is partly due to the common usage of laboratory setups and tasks, and the complex interplay between behavior and brain activity. The focus of the current study was thus to test the feasibility of applying a single-channel wireless EEG to monitor patterns of sustained attention (...) during a set of ecological tasks. An EEG marker of attention (BEI—Brain Engagement Index) was continuously recorded from 42 healthy volunteers during auditory and visual tasks from the Test of Everyday Attention (TEA) and Trail Making Test (TMT). We found a descending pattern of both performance and BEI in the auditory tasks as task complexity increases, while the increase in performance and decrease in BEI on the visual task. In addition, patterns of BEI in the complex tasks were used to detect outliers and the optimal range of attention through exploratory models. The current study supports the feasibility of combined electrophysiological and neurocognitive investigation of sustained attention in ecological tasks yielding unique insights on patterns of sustained attention as a function of task modality and task complexity. (shrink)

Tracking emotional responses as they unfold has been one of the hallmarks of applied neuroscience and related disciplines, but recent studies suggest that automatic tracking of facial expressions have low validation. In this study, we focused on the direct measurement of facial muscles involved in expressions such as smiling. We used single-channel surface electromyography to evaluate the muscular activity from the Zygomaticus Major face muscle while participants watched music videos. Participants were then tasked with rating each video with regard (...) to their thoughts and responses to each of them, including their judgment of emotional tone, personal preference and rating of whether the video displayed strength and impression. Using a minimal recording setup, we employed three ways to characterize muscular activity associated with spontaneous smiles. The total time spent smiling, the average duration of smiles, and instances of high valence. Our results demonstrate that Valence was the emotional dimension that was most related to the Zygomaticus activity. Here, the ZygoNum had higher discriminatory power than ZygoLen for Valence quantification. An additional investigation using fractal properties of sEMG time series confirmed previous studies of the Facial Action Coding System documenting a smoother contraction of facial muscles for enjoyment smiles. Further analysis using ZygoTrace responses over time to the video events discerned “high valence” stimuli with a 76% accuracy. Additional validation of this approach came against previous findings on valence detection using features derived from a single channel EEG setup. We discuss these results in light of both the recent replication problems of facial expression measures, and in relation to the need for methods to reliably assess emotional responses in more challenging conditions, such as Virtual Reality, in which facial expressions are often covered by the equipment used. (shrink)

Increasing behavioural evidence suggests that expert video game players (VGPs) show enhanced visual attention and visuospatial abilities, but what underlies these enhancements remains unclear. We administered the Poffenberger paradigm with concurrent electroencephalogram (EEG) recording to assess occipital N1 latencies and interhemispheric transfer time (IHTT) in expert VGPs. Participants comprised 15 right-handed male expert VGPs and 16 non-VGP controls matched for age, handedness, IQ and years of education. Expert VGPs began playing before age 10, had a minimum 8 years experience, and (...) maintained playtime of at least 20 hours per week over the last 6 months. Non-VGPs had little-to-no game play experience (maximum 1.5 years). Participants responded to checkerboard stimuli presented to the left and right visual fields while 128-channel EEG was recorded. Expert VGPs responded significantly more quickly than non-VGPs. Expert VGPs also had significantly earlier occipital N1s in direct visual pathways (the hemisphere contralateral to the visual field in which the stimulus was presented). IHTT was calculated by comparing the latencies of occipital N1 components between hemispheres. No significant between-group differences in electrophysiological estimates of IHTT were found. Shorter N1 latencies may enable expert VGPs to discriminate attended visual stimuli significantly earlier than non-VGPs and contribute to faster responding in visual tasks. As successful video-game play requires precise, time pressured, bimanual motor movements in response to complex visual stimuli, which in this sample began during early childhood, these differences may reflect the experience and training involved during the development of video-game expertise, but training studies are needed to test this prediction. (shrink)

Over recent years, brain-computer interface (BCI) has emerged as an alternative communication system between the human brain and an output device. Deciphered intents, after detecting electrical signals from the human scalp, are translated into control commands used to operate external devices, computer displays and virtual objects in the real-time. BCI provides an augmentative communication by creating a muscle-free channel between the brain and the output devices, primarily for subjects having neuromotor disorders, or trauma to nervous system, notably spinal cord (...) injuries (SCI), and subjects with unaffected sensorimotor functions but disarticulated or amputated residual limbs. This review identifies the potentials of electroencephalography (EEG) based BCI applications for locomotion and mobility rehabilitation. Patients could benefit from its advancements such as wearable lower-limb (LL) exoskeletons, orthosis, prosthesis, wheelchairs, and assistive-robot devices. The EEG communication signals employed by the aforementioned applications that also provide feasibility for future development in the field are sensorimotor rhythms (SMR), event-related potentials (ERP) and visual evoked potentials (VEP). The review is an effort to progress the development of user’s mental task related to LL for BCI reliability and confidence measures. As a novel contribution, the reviewed BCI control paradigms for wearable LL and assistive-robots are presented by a general control framework fitting in hierarchical layers. It reflects informatic interactions, between the user, the BCI operator, the shared controller, the robotic device and the environment. Each sub layer of the BCI operator is discussed in detail, highlighting the feature extraction, classification and execution methods employed by the various systems. All applications’ key features and their interaction with the environment are reviewed for the EEG-based activity mode recognition, and presented in form of a table. It is suggested to structure EEG-BCI controlled LL assistive devices within the presented framework, for future generation of intent-basedmultifunctional controllers. Despite the development of controllers, for BCI-based wearable or assistive devices that can seamlessly integrate user intent, practical challenges associated with such systems exist and have been discerned, which can be constructive for future developments in the field. (shrink)

Car driving is considered a very complex activity, consisting of different concomitant tasks and subtasks, thus it is crucial to understand the impact of different factors, such as road complexity, traffic, dashboard devices, and external events on the driver’s behavior and performance. For this reason, in particular situations the cognitive demand experienced by the driver could be very high, inducing an excessive experienced mental workload and consequently an increasing of error commission probability. In this regard, it has been demonstrated that (...) human error is the main cause of the 57 % of road accidents and a contributing factor in most of them. In this study, 20 young subjects were involved in a real driving experiment, performed under different traffic conditions (rush hour and not) and along different road types (main and secondary streets). Moreover, during the driving tasks different specific events, in particular a pedestrian crossing the road and a car entering the traffic flow just ahead of the experimental subject, were acted. A Workload Index based on the Electroencephalographic (EEG), i.e. brain activity, of the drivers has been employed to investigate the impact of the different factors on the driver’s workload. Eye-Tracking technology and subjective measures were also employed in order to have a comprehensive overview of the driver’s perceived workload and to investigate the different insights obtainable from the employed methodologies. The employment of such EEG-based Workload index confirmed the significant impact of both traffic and road types on the drivers’ behavior (increasing their workload), with the advantage of being under real settings. Also, it allowed to highlight the increased workload related to external events while driving, in particular with a significant effect during those situations when the traffic was low. Finally, the comparison between methodologies revealed the higher sensitivity of neurophysiological measures with respect to Eye-Tracking and subjective ones. In conclusion, such an EEG-based Workload index would allow to assess objectively the mental workload experienced by the driver, standing out as a powerful tool for research aimed to investigate drivers’ behavior and providing additional and complementary insights with respect to traditional methodologies employed within road safety research. (shrink)

Recent advances in mobile electroencephalogram (EEG) systems, featuring non-prep dry electrodes and wireless telemetry, have urged the needs of mobile brain-computer interfaces (BCIs) for applications in our daily life. Since the brain may behave differently while people are actively situated in ecologically-valid environments versus highly-controlled laboratory environments, it remains unclear how well the current laboratory-oriented BCI demonstrations can be translated into operational BCIs for users with naturalistic movements. Understanding inherent links between natural human behaviors and brain activities is the key (...) to ensuring the applicability and stability of mobile BCIs. This study aims to assess the quality of steady-state visual-evoked potentials (SSVEPs), which is one of promising channels for functioning BCI systems, recorded using a mobile EEG system under challenging recording conditions, e.g., walking. To systemati-cally explore the effects of walking locomotion on the SSVEPs, this study instructed subjects to stand or walk on a treadmill running at speeds of 1, 2, and 3 mile (s) per hour (MPH) while con-currently perceiving visual flickers (11 and 12 Hz). Empirical results of this study showed that the SSVEP amplitude tended to deteriorate when subjects switched from standing to walking. Such SSVEP suppression could be attributed to the walking locomotion, leading to distinctly deteriorated SSVEP detectability from standing (84.87±13.55%) to walking (1 MPH: 83.03±13.24%, 2 MPH: 79.47±13.53%, and 3 MPH: 75.26±17.89%). These findings not only demonstrated the applicability and limitations of SSVEPs recorded from freely behaving humans in realistic environments, but also provide useful methods and techniques for boosting the translation of the BCI technology from laboratory demonstrations to practical applications. (shrink)

Repeatedly performing a submaximal motor task for a prolonged period of time leads to muscle fatigue comprising a central and peripheral component, which demands a gradually increasing effort. However, the brain contribution to the enhancement of effort to cope with progressing fatigue lacks a complete understanding. The intermittent motor tasks closely resemble many activities of daily living, thus remaining physiologically relevant to study fatigue. The scope of this study is therefore to investigate the EEG-based brain activation patterns in healthy subjects (...) performing IMT until self-perceived exhaustion. Fourteen participants repeated elbow flexion contractions at 40% maximum voluntary contraction by following visual cues displayed on an oscilloscope screen until subjective exhaustion. Each contraction lasted ≈5 s with a 2-s rest between trials. The force, EEG, and surface EMG data were simultaneously collected. After preprocessing, we selected a subset of trials at the beginning, middle, and end of the study session representing brain activities germane to mild, moderate, and severe fatigue conditions, respectively, to compare and contrast the changes in the EEG time-frequency characteristics across the conditions. The outcome of channel- and source-level TF analyses reveals that the theta, alpha, and beta power spectral densities vary in proportion to fatigue levels in cortical motor areas. We observed a statistically significant change in the band-specific spectral power in relation to the graded fatigue from both the steady- and post-contraction EEG data. The findings would enhance our understanding on the etiology and physiology of voluntary motor-action-related fatigue and provide pointers to counteract the perception of muscle weakness and lack of motor endurance associated with ADL. The study outcome would help rationalize why certain patients experience exacerbated fatigue while carrying out mundane tasks, evaluate how clinical conditions such as neurological disorders and cancer treatment alter neural mechanisms underlying fatigue in future studies, and develop therapeutic strategies for restoring the patients' ability to participate in ADL by mitigating the central and muscle fatigue. (shrink)

The role of EEG in confirming the clinical diagnosis of isolated brain death has undergone evolutionary changes since the original recommendations concerning its use. Accumulated evidence now supports that approach that the EEG can be used not only as a confirmatory test for brain death, but one which considerably facilitates making the diagnosis. Using the EEG, brain death can often be identified with absolute certainty within just a few, rather than the previously recommended 24 or more hours after a known (...) precipitating event. Guidelines to this effect have now been established. (shrink)

Previous research has shown that language comprehenders resolve reference quickly and incrementally, but not much is known about the neural processes and representations that are involved. Studies of visual short-term memory suggest that access to the representation of an item from a previously seen display is associated with a negative evoked potential at posterior electrodes contralateral to the spatial location of that item in the display. In this paper we demonstrate that resolving the reference of a noun phrase in a (...) recently seen visual display is associated with an event-related potential that is analogous to this effect. Our design was adapted from the visual world paradigm: in each trial, participants saw a display containing three simple objects, followed by a question about the objects, such as Was the pink fish next to a boat?, presented word by word. Questions differed in whether the color adjective allowed the reader to identify the referent of the noun phrase or not (i.e., whether one or more objects of the named color were present). Consistent with our hypothesis, we observed that reference resolution by the adjective was associated with a negative evoked potential at posterior electrodes contralateral to spatial location of the referent, starting approximately 333 ms after the onset of the adjective. The fact that the laterality of the effect depended upon the location of the referent within the display suggests that reference resolution in visual domains involves, at some level, a modality-specific representation. In addition, the effect gives us an estimate of the time course of processing from perception of the written word to the point at which its meaning is brought into correspondence with the referential domain. (shrink)

One potentially ethically relevant feature of an utterance is that utterance's influence on the likelihoods that our future discourses wind up with one Stalnakerian ‘common ground’ or body of shared information rather than another. Such likelihoods matter ethically, so the ways our utterances influence them can matter ethically, despite the fact that such influences are often unintended, and often hard to see. By offering a relatively neutral descriptive framework that can enhance our collective sensitivity to and discussion of ethically, socially, (...) and politically important features of language use, this paper contributes to the ethics of language use. It discusses ways in which utterances can influence the likelihoods of future common grounds by deploying one system of categorization rather than another, and argues that language’s effects on the evolution of discourse can affect the paths to and probabilities of different sorts of consensus. (shrink)

Traditional rehabilitation strategies become difficult in the chronic phase stage of stroke prognosis. Brain–computer interface combined with external devices may improve motor function in chronic stroke patients, but it lacks comprehensive assessments of neurological changes regarding functional rehabilitation. This study aimed to comprehensively and quantitatively investigate the changes in brain activity induced by BCI–FES training in patients with chronic stroke. We analyzed the EEG of two groups of patients with chronic stroke, one group received functional electrical stimulation rehabilitation training and (...) the other group received BCI combined with FES training. We constructed functional networks in both groups of patients based on direct directed transfer function and assessed the changes in brain activity using graph theory analysis. The results of this study can be summarized as follows: after rehabilitation training, the Fugl–Meyer assessment scale score was significantly improved in the BCI–FES group, and there was no significant difference in the FES group. Both the global and local graph theory measures of the brain network of patients with chronic stroke in the BCI–FES group were improved after rehabilitation training. The node strength in the contralesional hemisphere and central region of patients in the BCI–FES group was significantly higher than that in the FES group after the intervention, and a significant increase in the node strength of C4 in the contralesional sensorimotor cortex region could be observed in the BCI–FES group. These results suggest that BCI–FES rehabilitation training can induce clinically significant improvements in motor function of patients with chronic stroke. It can improve the functional integration and functional separation of brain networks and boost compensatory activity in the contralesional hemisphere to a certain extent. The findings of our study may provide new insights into understanding the plastic changes of brain activity in patients with chronic stroke induced by BCI–FES rehabilitation training. (shrink)

Current research in molecular epidemiology uses biomarkers to model the different disease phases from environmental exposure, to early clinical changes, to development of disease. The hope is to get a better understanding of the causal impact of a number of pollutants and chemicals on several diseases, including cancer and allergies. In a recent paper Russo and Williamson address the question of what evidential elements enter the conceptualisation and modelling stages of this type of biomarkers research. Recent research in causality has (...) examined Ned Hall’s distinction between two concepts of causality: production and dependence. In another recent paper, Illari examined the relatively under-explored production approach to causality, arguing that at least one job of an account of causal production is to illuminate our inferential practices concerning causal linking. Illari argued that an informational account solves existing problems with traditional accounts. This paper follows up this previous work by investigating the nature of the causal links established in biomarkers research. We argue that traditional accounts of productive causality are unable to provide a sensible account of the nature of the causal link in biomarkers research, while an informational account is very promising. (shrink)

This article provides an overview of recent developments in solving the timing problem (discreteness vs. continuity) in cognitive neuroscience. Both theoretical and empirical studies have been considered, with an emphasis on the framework of Operational Architectonics (OA) of brain functioning (Fingelkurts and Fingelkurts, 2001, 2005). This framework explores the temporal structure of information flow and interarea interactions within the network of functional neuronal populations by examining topographic sharp transition processes in the scalp EEG, on the millisecond scale. We conclude, based (...) on the OA framework, that brain functioning is best conceptualized in terms of continuity-discreteness unity which is also the characteristic property of cognition. At the end we emphasize where one might productively proceed for the future research. (shrink)

We recast parts of decision theory in terms of channel theory concentrating on qualitative issues. Channel theory allows one to move between model theoretic and language theoretic notions as is necessary for an adequate covering. Doing so clarifies decision theory and presents the opportunity to investigate alternative formulations. As an example, we take some of Savage’s notions of decision theory and recast them within channel theory. In place of probabilities, we use a particular logic of preference. We (...) introduce a logic for describing actions separate from the logic of preference over actions. The structures introduced by channel theory that represent the decision problems can be seen to be an abstract framework. This frame-work is very accommodating to changing the nature of the decision problems to handle different aspects or theories about decision making. (shrink)

An increasing number of studies indicate that changes in cytosolic free Ca2+ ([Ca2+]c) mediate specific types of signal transduction in plant cells. Modulation of [Ca2+]c is likely to be achieved through changes in the activity of Ca2+ channels, which catalyse passive influx of Ca2+ to the cytosol from extracellular and intracellular compartments. Voltage‐sensitive Ca2+ channels have been detected in the plasma membranes of algae, where they control membrane electrical properties and cell turgor. These channels are sensitive to 1,4‐dihydropyridines, which in (...) animal cells specifically affect one class of voltage‐regulated plasma membrane Ca2+ channel. Ca2+‐permeable channels with different pharmacological properties have been found in the plasma membrane of higher plants. Recent evidence suggests the existence of two discrete classes of Ca2+ channel co‐resident in the vacuolar membrane (tonoplast) of higher plants. The first is gated by inositol 1,4,5‐trisphosphate, and bears a number of similarities to its animal counterpart which is located in the endoplasmic reticulum (ER). The second tonoplast Ca2+ channel is voltage‐operated. However, the specific roles of these tonoplast channels in signal transduction have yet to be elucidated. (shrink)

The identification of additional subunits of the cGMP-gated cation channel suggests exciting questions about their regulatory roles and about structure/functional relationships. How do the different subunits interact? How is the complex assembled into the plasma membrane? Divalent cations have been implicated in the regulation of adaptation. One often overlooked cation is magnesium. Could this ion play a role in phototransduction?

With the development of wireless technology, two basic wireless network models that are commonly used, known as infrastructure and wireless ad hoc networks, have been developed. In the literature, it has been observed that channel contention is one of the main reasons for packet drop in WANETs. To handle this problem, this paper presents a routing protocol named CCBR. CCBR tries to determine a least contended path between the endpoints to increase packet delivery ratio and to reduce packet delay (...) and normalized routing overhead. Moreover, throughout the active data section, each intermediate node computes its channel contention value. If an intermediate node detects an increase in channel contention, it notifies the source node. Then the source node determines another least contended route for transmission. The advantages of CCBR are verified in our NS2-based performance study, and the results show that CCBR outperforms ad hoc on-demand distance vector in terms of packet delivery ratio, end-to-end delay, and routing overhead by 4% to 9%. (shrink)

We tested the hypothesis that perception of an alternative image in ambiguous figures would be manifest as high-frequency (gamma) components that become synchronized over multiple scalp sites as a ''cognitive binding'' process occurs. For 171 combinations of data from 19 electrodes, obtained from 17 subjects and 10 replicate stimuli, we calculated the difference in correlation between the response to first seeing an ambiguous figure and when the alternative percept for that figure became consciously realized (cognitively bound). Numerous statistically significant correlation (...) differences occurred in all frequency bands tested with ambiguous-figure stimulation, but not in two kinds of control data (a reaction-time test to sound stimuli and a no-task, mind-wandering test). Statistically significant correlation changes were widespread, involving frontal, parietal, central, and occipital regions of both hemispheres. Correlation changes were evident at each of five frequency bands, ranging up to 62.5 Hz. Most of the statistically significant correlation changes were not between adjacent sites but between sites relatively distant, both ipsilateral and contralateral. Typically, these correlation changes occurred in more than one frequency band. These results suggest that cognitive binding is a distinct mental state that is reliably induced by ambiguous-figure perception tasks. Coherent oscillations at multiple frequencies may reflect the mechanism by which such binding occurs. Moreover, different coherent frequencies may mediate different components of the total cognitive-binding process. (shrink)

The use of cross-media and transmedia-based art installation has generated new ways for the audience to appreciate, understand and experience art. Transmedia, the integration of multiple media forms to augment a single narrative, has not only been largely used in commercial films, but has also been used by artists to communicate their message more effectively. In this article, we explore some remarkable multi-channel video installations and transmedia artworks to highlight how this technology has shaped new uses of technology as (...) a new medium to express artistic concepts. We discuss one artwork, an experimental collaboration between artists and scientists, entitled Reefs on the Edge, which communicates valuable information about climate change to a general audience. (shrink)

The notion of that information is relative to a context is important in many different ways. The idea that the context is small — that is, not necessarily a consistent and complete possible world — plays a role not only in situation theory, but it is also an enlightening perspective from which to view other areas, such as modal logics, relevant logics, categorial grammar and much more. In this article we will consider these areas, and focus then on one further (...) question: How can we account for information about one thing giving us information about something else? This is a question addressed by channel theory. We will look at channel theory and then see how the issues of information flow and conditionality play a role in each of the different domains we have examined. (shrink)

The cyclic GMP-gated channel responds to changes in free intracellular cGMP, and as a result, it plays a central role in the phototransduction process in rod and cone photoreceptor cells. Recent biochemical, immunochemical, and molecular biology studies indicate that this channel consists of a complex of two distinct subunits and one or more associated proteins. Primary structural analysis indicates that the a and (3 subunits contain a cGMP-binding domain, an even number of membrane-spanning segments, a voltage sensor motif (...) and a pore region. The latter two features are found in voltage-gated channels and suggest that these two classes of channels have evolved from the same ancestral channel protein. A working model for the membrane topography of the channel subunits is proposed based on immunogold labeling studies and sequence analysis. Recent studies also indicate that calmodulin binds to the 240 kDa protein of the channel complex and modulates the sensitivity of the channel for cGMP in a Ca2+-dependent manner. The molecular properties of the channel complex and the possible role of Ca2+-calmodulin modulation of the channel during photoactivation and photorecovery are discussed in relation to the current mechanism of phototransduction in photoreceptor cells. (shrink)

This article constructs a static model of information acquisition when the agent does not know exactly what pieces of information he is missing. A representation of preferences over information channels and menus of lotteries is shown by adapting the model of unforeseen contingencies by Dekel et al. (Econometrica 69:891–934, 2001; Econometrica 75:591–600, 2007), which is an extension of Kreps (Econometrica 47:565–576, 1979; Economic analysis of markets and games: essays in honor of Frank Hahn, 1992). Also, characterisation of informativeness of an (...) information channel analogous to the one by Blackwell (Ann Math Stud 24:265–272, 1953) is examined in conjunction with the preference for flexibility by applying the structure of Shapley value. (shrink)

Neonatal brain monitoring in the neonatal intensive care units (NICU) requires a continuous review of the spontaneous cortical activity, i.e., the electroencephalograph (EEG) background activity. This needs development of bedside methods for an automated assessment of the EEG background activity. In this paper, we present development of the key components of a neonatal EEG background classifier, starting from the visual background scoring to classifier design, and finally to possible bedside visualization of the classifier results. A dataset with 13,200 5-minute EEG (...) epochs (8–16 channels) from 27 infants with birth asphyxia was used for classifier training after scoring by two independent experts. We tested three classifier designs based on 98 computational features, and their performance was assessed with respect to scoring system, pre- and post-processing of labels and outputs, choice of channels, and visualization in monitor displays. The optimal solution achieved an overall classification accuracy of 97% with a range across subjects of 81–100%. We identified a set of 23 features that make the classifier highly robust to the choice of channels and missing data due to artefact rejection. Our results showed that an automated bedside classifier of EEG background is achievable, and we publish the full classifier algorithm to allow further clinical replication and validation studies. (shrink)

Substance use disorders (SUDs) constitute a growing global health crisis, yet many limitations and challenges exist in SUD treatment research, including the lack of objective brain-based markers for tracking treatment outcomes. Electroencephalography (EEG) is a neurophysiological technique for measuring brain activity, and although much is known about EEG activity in acute and chronic substance use, knowledge regarding EEG in relation to abstinence and treatment outcomes is sparse. We performed a scoping review of longitudinal and pre-post treatment EEG studies that explored (...) putative changes in brain function associated with abstinence and/or treatment in individuals with SUD. Following PRISMA guidelines, we identified studies published between January 2000 and March 2022 from online databases. Search keywords included EEG, addictive substances (e.g., alcohol, cocaine, methamphetamine), and treatment related terms (e.g., abstinence, relapse). Selected studies used EEG at least at one time point as a predictor of abstinence or other treatment-related outcomes; or examined pre- vs. post-SUD intervention (brain stimulation, pharmacological, behavioral) EEG effects. Studies were also rated on the risk of bias and quality using validated instruments. Forty-four studies met the inclusion criteria. More consistent findings included lower oddball P3 and higher resting beta at baseline predicting negative outcomes, and abstinence-mediated longitudinal decrease in cue-elicited P3 amplitude and resting beta power. Other findings included abstinence or treatment-related changes in late positive potential (LPP) and N2 amplitudes, as well as in delta and theta power. Existing studies were heterogeneous and limited in terms of specific substances of interest, brief times for follow-ups, and inconsistent or sparse results. Encouragingly, in this limited but maturing literature, many studies demonstrated partial associations of EEG markers with abstinence, treatment outcomes, or pre-post treatment-effects. Studies were generally of good quality in terms of risk of bias. More EEG studies are warranted to better understand abstinence- or treatment-mediated neural changes or to predict SUD treatment outcomes. Future research can benefit from prospective large-sample cohorts and the use of standardized methods such as task batteries. EEG markers elucidating the temporal dynamics of changes in brain function related to abstinence and/or treatment may enable evidence-based planning for more effective and targeted treatments, potentially pre-empting relapse or minimizing negative lifespan effects of SUD. (shrink)

In spite of their striking differences with real-life perception, films are perceived and understood without effort. Cognitive film theory attributes this to the system of continuity editing, a system of editing guidelines outlining the effect of different cuts and edits on spectators. A major principle in this framework is the 180° rule, a rule recommendation that, to avoid spectators’ attention to the editing, two edited shots of the same event or action should not be filmed from angles differing in a (...) way that expectations of spatial continuity are strongly violated. In the present study, we used high-density EEG to explore the neural underpinnings of this rule. In particular, our analysis shows that cuts and edits in general elicit early ERP component indicating the registration of syntactic violations as known from language, music, and action processing. However, continuity edits and cuts-across the line differ from each other regarding later components likely to be indicating the differences in spatial remapping as well as in the degree of conscious awareness of one's own perception. Interestingly, a time–frequency analysis of the occipital alpha rhythm did not support the hypothesis that such differences in processing routes are mainly linked to visual attention. On the contrary, our study found specific modulations of the central mu rhythm ERD as an indicator of sensorimotor activity, suggesting that sensorimotor networks might play an important role. We think that these findings shed new light on current discussions about the role of attention and embodied perception in film perception and should be considered when explaining spectators’ different experience of different kinds of cuts. (shrink)

Transcranial Photobiomodulation has demonstrated its ability to alter electrophysiological activity in the human brain. However, it is unclear how tPBM modulates brain electroencephalogram networks and is related to human cognition. In this study, we recorded 64-channel EEG from 44 healthy humans before, during, and after 8-min, right-forehead, 1,064-nm tPBM or sham stimulation with an irradiance of 257 mW/cm2. In data processing, a novel methodology by combining group singular value decomposition with the exact low-resolution brain electromagnetic tomography was implemented and (...) performed on the 64-channel noise-free EEG time series. The gSVD+eLORETA algorithm produced 11 gSVD-derived principal components projected in the 2D sensor and 3D source domain/space. These 11 PCs took more than 70% weight of the entire EEG signals and were justified as 11 EEG brain networks. Finally, baseline-normalized power changes of each EEG brain network in each EEG frequency band were quantified during the first 4-min, second 4-min, and post tPBM/sham periods, followed by comparisons of frequency-specific power changes between tPBM and sham conditions. Our results showed that tPBM-induced increases in alpha powers occurred at default mode network, executive control network, frontal parietal network and lateral visual network. Moreover, the ability to decompose EEG signals into individual, independent brain networks facilitated to better visualize significant decreases in gamma power by tPBM. Many similarities were found between the cortical locations of SVD-revealed EEG networks and fMRI-identified resting-state networks. This consistency may shed light on mechanistic associations between tPBM-modulated brain networks and improved cognition outcomes. (shrink)

In a number of membrane-bound viruses, ion channels are formed by integral membrane proteins. These channel proteins include M2 from influenza A, NB from influenza B, and, possibly, Vpu from HIV-1. M2 is important in facilitating uncoating of the influenza A viral genome and is the target of amantadine, an anti-influenza drug. The biological roles of NB and Vpu are less certain. In all cases, the protein contains a single transmembrane α-helix close to its N-terminus. Channels can be formed (...) by homo-oligomerization of these proteins, yielding bundles of transmembrane helices that span the membrane and surround a central ion-permeable pore. Molecular modeling may be used to integrate and interpret available experimental data concerning the structure of such transmembrane pores. This has proved successful for the M2 channel domain, where two independently derived models are in agreement with one another, and with solid-state nuclear magnetic resonance (NMR) data. Simulations based on channel models may yield insights into possible ion conduction and selectivity mechanisms. BioEssays 20:992–1000, 1998. © 1998 John Wiley & Sons, Inc. (shrink)

A general conceptual framework for large-scale neocortical dynamics based on data from many laboratories is applied to a variety of experimental designs, spatial scales, and brain states. Partly distinct, but interacting local processes (e.g., neural networks) arise from functional segregation. Global processes arise from functional integration and can facilitate (top down) synchronous activity in remote cell groups that function simultaneously at several different spatial scales. Simultaneous local processes may help drive (bottom up) macroscopic global dynamics observed with electroencephalography (EEG) or (...) magnetoencephalography (MEG). A local/global dynamic theory that is consistent with EEG data and the proposed conceptual framework is outlined. This theory is neutral about properties of neural networks embedded in macroscopic fields, but its global component makes several qualitative and semiquantitative predictions about EEG measures of traveling and standing wave phenomena. A more general “metatheory” suggests what large-scale quantitative theories of neocortical dynamics may be like when more accurate treatment of local and nonlinear effects is achieved. The theory describes the dynamics of excitatory and inhibitory synaptic action fields. EEG and MEG provide large-scale estimates of modulation of these synaptic fields around background levels. Brain states are determined by neuromodulatory control parameters. Purely local states are dominated by local feedback gains and rise and decay times of postsynaptic potentials. Dominant local frequencies vary with brain region. Other states are purely global, with moderate to high coherence over large distances. Multiple global mode frequencies arise from a combination of delays in corticocortical axons and neocortical boundary conditions. Global frequencies are identical in all cortical regions, but most states involve dynamic interactions between local networks and the global system. EEG frequencies may involve a “matching” of local resonant frequencies with one or more of the many, closely spaced global frequencies. Key Words: binding problem; cell assemblies; coherence; EEG; limit cycles; neocortical dynamics; pacemakers; phase locking; spatial scale; standing waves; synchronization. Footnotes1 The relationship between the synaptic action fields proposed in the target article and cell assemblies is clarified with Figure R1 (p. 416) of the Response. (This figure was not available to Commentators. (shrink)

Rationale: High-frequency oscillations in intracranial EEG are used to delineate the epileptogenic zone during presurgical diagnostic assessment in patients with epilepsy. HFOs are historically divided into ripples, fast ripples, and their co-occurrence. In a previous study, we had validated the rate of FRandRs during deep sleep to predict seizure outcome. Here, we ask whether epileptic FRandRs might be confounded by physiological FRandRs that are unrelated to epilepsy.Methods: We recorded iEEG in the medial temporal lobe MTL in 17 patients while they (...) performed cognitive tasks. The three cognitive tasks addressed verbal working memory, visual working memory, and emotional processing. In our previous studies, these tasks activated the MTL. We re-analyzed the data of these studies with the automated detector that focuses on the co-occurrence of ripples and FRs.Results: For each task, we identified those channels in which the HFO rate was modulated during the task condition compared to the control condition. However, the number of these channels did not exceed the chance level. Interestingly, even during wakefulness, the HFO rate was higher for channels within the seizure onset zone than for channels outside the SOZ.Conclusion: Our prospective definition of an epileptic HFO, the FRandR, is not confounded by physiological HFOs that might be elicited by our cognitive tasks. This is reassuring for the clinical use of FRandR as a biomarker of the EZ. (shrink)

Advances in intracranial electroencephalography and neurophysiology have enabled the study of previously inaccessible brain regions with high fidelity temporal and spatial resolution. Studies of iEEG have revealed a rich neural code subserving healthy brain function and which fails in disease states. Machine learning, a form of artificial intelligence, is a modern tool that may be able to better decode complex neural signals and enhance interpretation of these data. To date, a number of publications have applied ML to iEEG, but clinician (...) awareness of these techniques and their relevance to neurosurgery, has been limited. The present work presents a review of existing applications of ML techniques in iEEG data, discusses the relative merits and limitations of the various approaches, and examines potential avenues for clinical translation in neurosurgery. One-hundred-seven articles examining artificial intelligence applications to iEEG were identified from 3 databases. Clinical applications of ML from these articles were categorized into 4 domains: i) seizure analysis, ii) motor tasks, iii) cognitive assessment, and iv) sleep staging. The review revealed that supervised algorithms were most commonly used across studies and often leveraged publicly available timeseries datasets. We conclude with recommendations for future work and potential clinical applications. (shrink)

Establishing the basic knowledge, methodology, and technology for a framework for the continuous decoding of hand/arm movement intention was the aim of the ERC-funded project “Feel Your Reach”. In this work, we review the studies and methods we performed and implemented in the last 6 years, which build the basis for enabling severely paralyzed people to non-invasively control a robotic arm in real-time from electroencephalogram. In detail, we investigated goal-directed movement detection, decoding of executed and attempted movement trajectories, grasping correlates, (...) error processing, and kinesthetic feedback. Although we have tested some of our approaches already with the target populations, we still need to transfer the “Feel Your Reach” framework to people with cervical spinal cord injury and evaluate the decoders’ performance while participants attempt to perform upper-limb movements. While on the one hand, we made major progress towards this ambitious goal, we also critically discuss current limitations. (shrink)

In a number of membrane-bound viruses, ion channels are formed by integral membrane proteins. These channel proteins include M2 from influenza A, NB from influenza B, and, possibly, Vpu from HIV-1. M2 is important in facilitating uncoating of the influenza A viral genome and is the target of amantadine, an anti-influenza drug. The biological roles of NB and Vpu are less certain. In all cases, the protein contains a single transmembrane α-helix close to its N-terminus. Channels can be formed (...) by homo-oligomerization of these proteins, yielding bundles of transmembrane helices that span the membrane and surround a central ion-permeable pore. Molecular modeling may be used to integrate and interpret available experimental data concerning the structure of such transmembrane pores. This has proved successful for the M2 channel domain, where two independently derived models are in agreement with one another, and with solid-state nuclear magnetic resonance (NMR) data. Simulations based on channel models may yield insights into possible ion conduction and selectivity mechanisms. BioEssays 20:992–1000, 1998. © 1998 John Wiley & Sons, Inc. (shrink)

Recent advances in neuroscience indicate that analysis of bio-signals such as rest state electroencephalogram and eye-tracking data can provide more reliable evaluation of children autism spectrum disorder than traditional methods of behavior measurement relying on scales do. However, the effectiveness of the new approaches still lags behind the increasing requirement in clinical or educational practices as the “bio-marker” information carried by the bio-signal of a single-modality is likely insufficient or distorted. This study proposes an approach to joint analysis of EEG (...) and eye-tracking for children ASD evaluation. The approach focuses on deep fusion of the features in two modalities as no explicit correlations between the original bio-signals are available, which also limits the performance of existing methods along this direction. First, the synchronization measures, information entropy, and time-frequency features of the multi-channel EEG are derived. Then a random forest applies to the eye-tracking recordings of the same subjects to single out the most significant features. A graph convolutional network model then naturally fuses the two group of features to differentiate the children with ASD from the typically developed subjects. Experiments have been carried out on the two types of the bio-signals collected from 42 children. The results indicate that the proposed approach can achieve an accuracy of 95% in ASD detection, and strong correlations exist between the two bio-signals collected even asynchronously, in particular the EEG synchronization against the face related/joint attentions in terms of covariance. (shrink)

With the aim of giving a naturalistic foundation to the notion of mental representation, Fred Dretske (1981;1988) has put forward and developed the idea that the relation between a representation and its intentional content is grounded on an informational relation. In this explanatory model, mental representations are conceived of as states of organisms which a learning process has selected to play a functional role: a necessary condition for fulfilling this role is that the organism or some proper part of it (...) (presumably situated in the brain) is a natural indicator of the occurrence of a determinate type of event in the environment of the organism (or in the organism but outside of the proper part serving as the indicator). A state of the organism is a natural indicator of a type of event if and only if it carries information about the occurrence of that type of event. Jerry Fodor (1987) has devised and followed another strategy which consists in considering the relation between a mental representation and its intentional object as a relation of lawful, or nomic, dependence. A representational state of an organism has an objective content in virtue of the existence of a relation of nomic dependence between this state - presumably a property of the brain of the organism - and some objective property in the world. This dependence also creates a regular correlation between the occurrences of representational states of a certain type and the states of affairs whose type is their representational content. Both approaches encounter indeterminacy problems: for each, there exist situations in which the explanatory model chosen - information flow or nomic dependence - does not succeed in selecting, purely on the basis of the constraints characteristic of that model, one out of several potential contents for a given representational state. In such cases, that state is related to more than one type of events in accordance with the informational or nomic constraints imposed by those theories. In what follows, I examine an attempt by Pierre Jacob (1997) to solve two problems of indeterminacy threatening the informational theory of mental representation. According to Jacob, one of these problems can be solved with the help of the distinction between the source which is the target of the information and the channel over which the information is transmitted, whereas the solution to the other problem requires the introduction of the concept of function. I shall begin with a consideration of the distinction, with respect to a situation of information transmission, between the source and the channel. I argue that both the source and the channel, and thus the information transmitted, depend not only on the external situation which characterises the source, the channel and the receiving organism, but also on the previous knowledge and the informational needs of the receiver. I then try to show that this relativity of information undermines the solution Jacob proposes to one of the problems of indeterminacy of representational content. Finally, I examine the possibility considered by Dretske and Jacob to solve this 'problem of the reference class' due to the mentioned relativity of information, by grounding the flow of information on lawful dependence instead of statistical dependence. I shall propose two arguments showing first that these two groundings are not equivalent and second that nomic dependence is inappropriate as a grounding for information flow. I conclude by suggesting that the problem of the reference class can be solved within the framework of the informational approach, on the condition of enriching it with functional considerations. (shrink)

It was meaningful to predict the customers' decision-making behavior in the field of market. However, due to individual differences and complex, non-linear natures of the electroencephalogram signals, it was hard to classify the EEG signals and to predict customers' decisions by using traditional classification methods. To solve the aforementioned problems, a recurrent t-distributed stochastic neighbor embedding neural network was proposed in current study to classify the EEG signals in the designed brand extension paradigm and to predict the participants' decisions. The (...) recurrent t-SNE neural network contained two steps. In the first step, t-SNE algorithm was performed to extract features from EEG signals. Second, a recurrent neural network with long short-term memory layer, fully connected layer, and SoftMax layer was established to train the features, classify the EEG signals, as well as predict the cognitive performance. The proposed network could give a good prediction with accuracy around 87%. Its superior in prediction accuracy as compared to a recurrent principal component analysis network, a recurrent independent component correlation algorithm [independent component analysis ] network, a t-SNE support vector machine network, a t-SNE back propagation neural network, a deep LSTM neural network, and a convolutional neural network were also demonstrated. Moreover, the performance of the proposed network with different activated channels were also investigated and compared. The results showed that the proposed network could make a relatively good prediction with only 16 channels. The proposed network would become a potentially useful tool to help a company in making marketing decisions and to help uncover the neural mechanisms behind individuals' decision-making behavior with low cost and high efficiency. (shrink)