Following Cass Sunstein's popular treatment of the concept, echo chambers are often defined as environments which exclude contrary opinions through omission. C. Thi Nguyen contests the popular usage and defines echo chambers in terms of in-group trust and out-group distrust. In this paper, I argue for a more comprehensive treatment. While both exclusion by omission and out-group distrust help sustain echo chambers, neither defines the phenomenon. I develop a social network model of echo chambers which focuses on the role of (...) belief-reinforcing echoes. First, I argue that the model allows us to incorporate Nguyen's main point about distrust without construing other commentators as deeply mistaken about the nature of echo chambers. Second, I use the model to develop an account of collaborative resistance and use it to clarify the role echo chambers play in spreading misinformation. (shrink)

Following Cass Sunstein's popular treatment of the concept, echo chambers are often defined as environments which exclude contrary opinions through omission. C. Thi Nguyen contests the popular usage and defines echo chambers in terms of in-group trust and out-group distrust. In this paper, I argue for a more comprehensive treatment. While both exclusion by omission and out-group distrust help sustain echo chambers, neither defines the phenomenon. I develop a social network model of echo chambers which focuses on the role of (...) belief-reinforcing echoes. First, I argue that the model allows us to incorporate Nguyen's main point about distrust without construing other commentators as deeply mistaken about the nature of echo chambers. Second, I use the model to develop an account of collaborative resistance and use it to clarify the role echo chambers play in spreading misinformation. (shrink)

Introduction: Motherese, or emotional infant directed speech, is the specific form of speech used by parents to address their infants. The prosody of IDS has affective properties, expresses caregiver involvement, is a marker of caregiver-infant interaction quality. IDS prosodic characteristics can be detected with automatic analysis. We aimed to explore whether pregnant women “speak” to their unborn baby, whether they use motherese while speaking and whether anxio-depressive or obstetrical status impacts speaking to the fetus.Participants and Methods: We conducted an observational (...) study of pregnant women with gestational ages from 26 to 38 weeks. Women were recruited in a university hospital department of obstetrics. Thirty-five women agreed to participate in the study, and 26 audio records were exploitable. We collected obstetrical and sociodemographic data, pregnancy outcomes, anxiety and depressive status using the Covy and Raskin Scales, and life events using the Sensations During Pregnancy and Life Event Questionnaire. Each participant was left alone with an audio recorder with a recommendation to feel free to speak to her fetus as she would have done at home. The recording was stopped after 3 min. Audio recordings were analyzed by two methods: psycholinguist experts' annotation and computational objective automatic analyses.Results: Most mothers reported speaking to their fetuses. We found a correlation between maternal first perceptions of fetal movements and the start of mother's speaking to fetus. Motherese prosody was detected with both annotation and automatic analysis with a significant correlation between the two methods. In this exploratory study, motherese use was not associated with maternal anxiodepressive or obstetrical status. However, the more future mothers were depressed, the less they spoke with their fetuses during the recording.Conclusion: Fetal directed speech can be detected during pregnancy, and it contains a period of prosody that shares the same characteristics of motherese that can be described as prenatal motherese or emotional fetal-directed speech. This means that pregnant women start using motherese much earlier than expected. FDS seems to be correlated with maternal first perceptions of fetal movements and depression scores. However, more research is needed to confirm these exploratory results. (shrink)

It is a matter of fact that Europe is facing more and more crucial challenges regarding health and social care due to the demographic change and the current economic context. The recent COVID-19 pandemic has stressed this situation even further, thus highlighting the need for taking action. Active and Assisted Living technologies come as a viable approach to help facing these challenges, thanks to the high potential they have in enabling remote care and support. Broadly speaking, AAL can be referred (...) to as the use of innovative and advanced Information and Communication Technologies to create supportive, inclusive and empowering applications and environments that enable older, impaired or frail people to live independently and stay active longer in society. AAL capitalizes on the growing pervasiveness and effectiveness of sensing and computing facilities to supply the persons in need with smart assistance, by responding to their necessities of autonomy, independence, comfort, security and safety. The application scenarios addressed by AAL are complex, due to the inherent heterogeneity of the end-user population, their living arrangements, and their physical conditions or impairment. Despite aiming at diverse goals, AAL systems should share some common characteristics. They are designed to provide support in daily life in an invisible, unobtrusive and user-friendly manner. Moreover, they are conceived to be intelligent, to be able to learn and adapt to the requirements and requests of the assisted people, and to synchronise with their specific needs. Nevertheless, to ensure the uptake of AAL in society, potential users must be willing to use AAL applications and to integrate them in their daily environments and lives. In this respect, video- and audio-based AAL applications have several advantages, in terms of unobtrusiveness and information richness. Indeed, cameras and microphones are far less obtrusive with respect to the hindrance other wearable sensors may cause to one’s activities. In addition, a single camera placed in a room can record most of the activities performed in the room, thus replacing many other non-visual sensors. Currently, video-based applications are effective in recognising and monitoring the activities, the movements, and the overall conditions of the assisted individuals as well as to assess their vital parameters. Similarly, audio sensors have the potential to become one of the most important modalities for interaction with AAL systems, as they can have a large range of sensing, do not require physical presence at a particular location and are physically intangible. Moreover, relevant information about individuals’ activities and health status can derive from processing audio signals. Nevertheless, as the other side of the coin, cameras and microphones are often perceived as the most intrusive technologies from the viewpoint of the privacy of the monitored individuals. This is due to the richness of the information these technologies convey and the intimate setting where they may be deployed. Solutions able to ensure privacy preservation by context and by design, as well as to ensure high legal and ethical standards are in high demand. After the review of the current state of play and the discussion in GoodBrother, we may claim that the first solutions in this direction are starting to appear in the literature. A multidisciplinary debate among experts and stakeholders is paving the way towards AAL ensuring ergonomics, usability, acceptance and privacy preservation. The DIANA, PAAL, and VisuAAL projects are examples of this fresh approach. This report provides the reader with a review of the most recent advances in audio- and video-based monitoring technologies for AAL. It has been drafted as a collective effort of WG3 to supply an introduction to AAL, its evolution over time and its main functional and technological underpinnings. In this respect, the report contributes to the field with the outline of a new generation of ethical-aware AAL technologies and a proposal for a novel comprehensive taxonomy of AAL systems and applications. Moreover, the report allows non-technical readers to gather an overview of the main components of an AAL system and how these function and interact with the end-users. The report illustrates the state of the art of the most successful AAL applications and functions based on audio and video data, namely lifelogging and self-monitoring, remote monitoring of vital signs, emotional state recognition, food intake monitoring, activity and behaviour recognition, activity and personal assistance, gesture recognition, fall detection and prevention, mobility assessment and frailty recognition, and cognitive and motor rehabilitation. For these application scenarios, the report illustrates the state of play in terms of scientific advances, available products and research project. The open challenges are also highlighted. The report ends with an overview of the challenges, the hindrances and the opportunities posed by the uptake in real world settings of AAL technologies. In this respect, the report illustrates the current procedural and technological approaches to cope with acceptability, usability and trust in the AAL technology, by surveying strategies and approaches to co-design, to privacy preservation in video and audio data, to transparency and explainability in data processing, and to data transmission and communication. User acceptance and ethical considerations are also debated. Finally, the potentials coming from the silver economy are overviewed. (shrink)

Paramedics encounter ethical dilemmas at work, and while previous research has improved ethics education and practice, more can be learned from the lived experience of paramedics facing ethical challenges. This paper explores the lived experience of two paramedics, one with five years’ experience, the other twenty, presented with comparable cases. The participants, who were interviewed in a broader qualitative study exploring practical wisdom, were asked to select a case involving ethical decision-making from their own practice experience. Semi-structured interviews employed the (...) five-step Critical Decision Method as a framework to explore various aspects of the decision-making process. The two cases were identified as exemplars of prominent themes suitable for discussion. The findings highlighted several factors that influence paramedic ethical decision-making, including practical wisdom, communication and teamwork, clinical support, and education. This case comparison identifies a greater need to focus education on the fostering of practical wisdom, and the development of non-technical skills such as communication and teamwork, supported by interprofessional education endeavours. Furthermore, greater access to support for paramedics must be available to further evolve practical wisdom. The combination of improved education and support will likely cater for the full spectrum of ethical challenges faced by paramedics in their work. (shrink)

This study examines the practices of Equine Assisted Therapy and Learning in Australia. Among Equine Assisted Therapy and Equine Assisted Learning centers there is a large degree of variation in practice worldwide. The current study outlines a range of practices in two states in Australia whereeatandealhave arisen and evolved from models developed elsewhere. The philosophical foundations, training and certification processes followed along with the types and training of horses involved are compared across facilities. The findings of the study illustrated the (...) large variation ineatandealin current practice in Australia. The results suggested that if the practices ofeatandealare to move out of the “fringe” of mental health and learning professional practice and into the mainstream, their theoretical underpinnings, certification and licensure procedures, and methodology of practice must become more clearly defined. (shrink)

During the COVID-19 pandemic, questions have been raised about the impact of face masks on communication in classroom settings. However, it is unclear to what extent visual obstruction of the speaker’s mouth or changes to the acoustic signal lead to speech processing difficulties, and whether these effects can be mitigated by semantic predictability, i.e., the availability of contextual information. The present study investigated the acoustic and visual effects of face masks on speech intelligibility and processing speed under (...) varying semantic predictability. Twenty-six children and twenty-six adults performed an internet-based cued shadowing task, in which they had to repeat aloud the last word of sentences presented in audio-visual format. The results showed that children and adults made more mistakes and responded more slowly when listening to face mask speech compared to speech produced without a face mask. Adults were only significantly affected by face mask speech when both the acoustic and the visual signal were degraded. While acoustic mask effects were similar for children, removal of visual speech cues through the face mask affected children to a lesser degree. However, high semantic predictability reduced audio-visual mask effects, leading to full compensation of the acoustically degraded mask speech in the adult group. Even though children did not fully compensate for face mask speech with high semantic predictability, overall, they still profited from semantic cues in all conditions. Therefore, in classroom settings, strategies that increase contextual information such as building on students’ prior knowledge, using keywords, and providing visual aids, are likely to help overcome any adverse face mask effects. (shrink)

Technological advances over the past 50 years or so have resulted in the development of a succession of hardware and software systems intended to improve the quality and effectiveness of Western music instrument pedagogy during classroom instruction or individual study. These systems have aimed to provide evaluation or visualization of single or combined technical aspects by analyzing performance data collected in real time or offline. The number of such educational technologies shows an ever-increasing trend over time, aided by the wide (...) diffusion and availability of mobile devices. However, we believe there are unrealized opportunities for modern technologies to help music students in their technical development and assist them during their practice sessions in between visits to their teachers. The ubiquity of PCs and mobile devices with built-in microphones, speakers, and cameras has inspired the development of media technologies in support of music pedagogy. They offer an attractive potential for implementing audio signal processing algorithms addressing different technical skills of the performer, providing real-time feedback, collecting data over time, and applying statistical models. Despite this potential, most available software for music instrument pedagogy remains very limited in functionality. This study provides a survey of music edTech software available, together with the methods of use, addressed technical skills, commonalities, and limitations. Results show that most current software is based on the metronome and tuner, with only a few systems that have limited abilities to follow a performance in real-time and compare it to a given score to monitor correctness of notes, intonation, and rhythm. The survey also highlights a high and under-exploited potential regarding the monitoring of other more specific technical skills, which are more instrument-dependent, but no less important, such as the control of dynamic range and clarity of the attack. This article ends with a discussion of possible directions for future development of technologies to support the practice of music students at different levels, with some consideration for the corresponding signal processing methods that can be utilized or that need advancement. By helping students to more efficiently achieve a high level of proficiency of their instruments with assistive technologies, we hope to minimize stress and afford better enjoyment of the music performance experience for all. (shrink)

Four sequential, sub-processes are identified as the fundamental steps in the processing of signals by big-brained animals. These are, Detection of the signal, its Representation in correlated sensory brain structure, the Interpretation of the signal in another part of the brain and the Expression of the receiver’s response. We label this four-step spatiotemporal process DRIE. We support the view that when the context within which such signals are produced and received is relatively constant, the DRIE process can (...) be ultimately assimilated into the genome, with the Interpretation sub-phase is markedly decreased in duration as speed and efficiency are maximized. With frequent repetition and learning, an analogous result can be attained epigenetically as exemplified in human word and text recognition, allowing tasks critical to primate social function to be accomplished with rapidity and accuracy. (shrink)

Low frequency oscillation is an important attribute of human brain activity, and the amplitude of low frequency fluctuation is an effective method to reflect the characteristics of low frequency oscillation, which has been widely used in the treatment of brain diseases and other fields. However, due to the low accuracy of the current analysis methods for low frequency signal extraction of ALFF, we propose the Fourier-based synchrosqueezing transform, which is often used in the field of signal processing (...) to extract the ALFF of the low frequency power spectrum of the whole-time dimension. The low frequency characteristics of the extracted signal are compared with those of FSST and fast Fourier transform through the resting-state data. It is clear that the signal extracted by FSST has more low frequency characteristics, which is significantly different from FFT. (shrink)

In this modern world, a massive amount of data is processed and broadcasted daily. This includes the use of high energy, massive use of memory space, and increased power use. In a few applications, for example, image processing, signal processing, and possession of data signals, etc., the signals included can be viewed as light in a few spaces. The compressive sensing theory could be an appropriate contender to manage these limitations. “Compressive Sensing theory” preserves extremely helpful while (...) signals are sparse or compressible. It very well may be utilized to recoup light or compressive signals with less estimation than customary strategies. Two issues must be addressed by CS: plan of the estimation framework and advancement of a proficient sparse recovery calculation. The essential intention of this work expects to audit a few ideas and utilizations of compressive sensing and to give an overview of the most significant sparse recovery calculations from every class. The exhibition of acquisition and reconstruction strategies is examined regarding the Compression Ratio, Reconstruction Accuracy, Mean Square Error, and so on. (shrink)

With the technological evolutionary advent, a vision-based approach presents the remote measuring approach for the analysis of vibration. The structure vibration test and model parameter identification in the detection of the structure of the bridge evaluation occupies the important position. The bridge structure to operate safely and reliably is ensured, according to the geological data of qixiashan lead-zinc mine and engineering actual situation, with the aid of international mining software Surpac. To build the 3D visualization model of the application of (...) visualization in mine production are discussed. The results show that the final solid model of -425 stope can accurately display the spatial form of each layer of stope through rotation, amplification and movement. The proposed system is effectually able to perform cutting, volume calculation and roaming in any direction, which has certain guiding significance for mine production management. An accuracy value of 98.75%, the sensitivity of 99%, specificity of 99.64% and PPV of 99.89% are achieved using the proposed 3D modelling and visualization algorithm for vibration signal processing and management. (shrink)

Threshold- and signal-detection-based models have dominated theorizing about recognition memory. Building upon these theoretical frameworks, we have argued for a dual-process model in which conscious recollection and familiarity contribute to memory performance. In the current paper we assessed several memory models by examining the effects of levels of processing and the number of presentations on recognition memory receiver operating characteristics . In general, when the ROCs were plotted in probability space they exhibited an inverted U shape; however, when (...) they were plotted inzspace they exhibited a U shape. An examination of the ROCs showed that the dual-process model could account for the observed ROCs, but that models based solely on either threshold or signal-detection processes failed to provide a sufficient account of the data. Furthermore, an examination of subjects' introspective reports using the remember/know procedure showed that subjects were aware of recollection and familiarity and were able to consistently report on their occurrence. The remember/know data were used to accurately predict the shapes of the ROCs, and estimates of recollection and familiarity derived from the ROC data mirrored the subjective reports of these processes. (shrink)

When multiple individuals interact in a conversation or as part of a large crowd, emergent structures and dynamics arise that are behavioral properties of the interacting group rather than of any individual member of that group. Recent work using traditional signal processing techniques and machine learning has demonstrated that global acoustic data recorded from a crowd at a basketball game can be used to classify emergent crowd behavior in terms of the crowd's purported emotional state. We propose that (...) the description of crowd behavior from such global acoustic data could benefit from nonlinear analysis methods derived from dynamical systems theory. Such methods have been used in recent research applying nonlinear methods to audio data extracted from music and group musical interactions. In this work, we used nonlinear analyses to extract features that are relevant to the behavioral interactions that underlie acoustic signals produced by a crowd attending a sporting event. We propose that recurrence dynamics measured from these audio signals via recurrence quantification analysis (RQA) reflect information about the behavioral dynamics of the crowd itself. We analyze these dynamics from acoustic signals recorded from crowds attending basketball games, and that were manually labeled according to the crowds' emotional state across six categories: angry noise, applause, cheer, distraction noise, positive chant, and negative chant. We show that RQA measures are useful to differentiate the emergent acoustic behavioral dynamics between these categories, and can provide insight into the recurrence patterns that underlie crowd interactions. (shrink)

In the process of communication between people, everyone will have emotions, and different emotions will have different effects on communication. With the help of external performance information accompanied by emotional expression, such as emotional speech signals or facial expressions, people can easily communicate with each other and understand each other. Emotion recognition is an important network of affective computers and research centers for signal processing, pattern detection, artificial intelligence, and human-computer interaction. Emotions convey important information in human communication (...) and communication. Since the end of the last century, people have started the research on emotion recognition, especially how to correctly judge the emotion type has invested a lot of time and energy. In this paper, multi-modal emotion recognition is introduced to recognize facial expressions and speech, and conduct research on adaptive higher education management. Language and expression are the most direct ways for people to express their emotions. After obtaining the framework of the dual-modal emotion recognition system, the BOW model is used to identify the characteristic movement of local areas or key points. The recognition rates of emotion recognition for 1,000 audios of anger, disgust, fear, happiness, sadness and surprise are: 97.3, 83.75, 64.87, 89.87, 84.12, and 86.68%, respectively. (shrink)

The common neurotrophin receptor (p75NTR) regulates various functions in the developing and adult nervous system. Cell survival, cell death, axonal and growth cone retraction, and regulation of the cell cycle can be regulated by p75NTR‐mediated signals following activation by either mature or pro‐neurotrophins and in combination with various co‐receptors, including Trk receptors and sortilin. Here, we review the known functions of p75NTR by cell type, receptor‐ligand combination, and whether regulated intra‐membrane proteolysis of p75NTR is required for signalling. We highlight that (...) the generation of the intracellular domain fragment of p75NTR is associated with many of the receptor functions, regardless of its ligand and co‐receptor interactions. (shrink)

This article argues that errors in audio data processing should be examined to explore and expose the underlying components that enable linguistic communication and cross-cultural understanding. Examples of errors in the transcription of a Mexican social network’s conversations are analyzed to demonstrate the potential of such data in the development of sociocognitive language-processing theories. It is suggested that researchers working with audio-recorded data should expand the scope of what is considered useful data for the sake of (...) both methodological reflexivity and identifying the underlying cognitive processes enabling linguistic understanding. (shrink)

The redundant-signals paradigm (RSP) is designed to investigate response behavior in perceptual tasks in which response-relevant targets are defined by either one or two features, or modalities. The common finding is that responses are speeded for redundantly compared to singly defined targets. This redundant-signals effect (RSE) can be accounted for by race models if the response times do not violate the race model inequality (RMI). When there are violations of the RMI, race models are effectively excluded as a viable account (...) of the RSE. The common alternative is provided by co-activation accounts, which assume that redundant target signals are integrated at some processing stage. However, ‘co-activation’ has mostly been only indirectly inferred and the accounts have only rarely been explicitly modeled; if they were modeled, the RSE has typically been assumed to have a decisional locus. Yet, there are also indications in the literature that the RSE might originate, at least in part, at a non-decisional or motor stage. In the present study, using a distribution analysis of sequential-sampling models (ex-Wald and Ratcliff Diffusion model), the locus of the RSE was investigated for two bimodal (audio-visual) detection tasks that strongly violated the RMI, indicative of substantial co-activation. Three model variants assuming different loci of the RSE were fitted to the quantile reaction time proportions: a decision, a non-decision, and a combined variant both to vincentized group as well as individual data. The results suggest that for the two bimodal detection tasks, co-activation has a shared decisional and non-decisional locus. These findings point to the possibility that the mechanisms underlying the RSE depend on the specifics (task, stimulus, conditions, etc.) of the experimental paradigm. (shrink)

Noise will be inevitably mixed with music signals in the recording process. To improve the quality of music signals, it is necessary to reduce noise as much as possible. This article briefly introduces noise, the masking effect, and the spectral subtraction method for reducing noise in reverberant music. The spectral subtraction method was improved by the human ear masking effect to enhance its noise reduction performance. Simulation experiments were carried out on the traditional and improved spectral subtraction methods. The results (...) showed that the improved spectral subtraction method could reduce the noise in reverberant music more effectively; under an objective evaluation criterion, the signal-to-noise ratio, the de-reverberated music signal processed by the improved spectral subtraction method had a higher signal-to-noise ratio; under a subjective evaluation criterion, mean opinion score, the de-reverberated music signal processed by the improved spectral subtraction method also had a better evaluation. (shrink)

The common neurotrophin receptor (p75NTR) regulates various functions in the developing and adult nervous system. Cell survival, cell death, axonal and growth cone retraction, and regulation of the cell cycle can be regulated by p75NTR‐mediated signals following activation by either mature or pro‐neurotrophins and in combination with various co‐receptors, including Trk receptors and sortilin. Here, we review the known functions of p75NTR by cell type, receptor‐ligand combination, and whether regulated intra‐membrane proteolysis of p75NTR is required for signalling. We highlight that (...) the generation of the intracellular domain fragment of p75NTR is associated with many of the receptor functions, regardless of its ligand and co‐receptor interactions. (shrink)

Brian Skyrms offers a fascinating demonstration of how fundamental signals are to our world. He uses various scientific tools to investigate how meaning and communication develop. Signals operate in networks of senders and receivers at all levels of life, transmitting and processing information. That is how humans and animals think and interact.

C. S. Peirce defined the sign as a means to communicate a form or habit embodied in the object to the interpretant, thus constraining (through a sign) the behavior of an interpreter to a limited series of effects. This is part of the process of “semiotic scaffolding” in which sign relations interlock and reinforce one another, providing directionality to the process. In biological evolutionary studies canalization is defined as the adjustment of developmental pathways by natural selection to bring about a (...) uniform result despite genetic and environmental variations. Establishing parallelism between the two concepts allows the possibility of understanding how semiotic processes introduce information from the environment resulting in canalization (and assimilation), determining “fixed” pathways to elaborate signal repertoires for particular species adapted to particular environments sensed by particular organs. This kind of sign action can produce an “encapsulation” process of the sign meaning, further affecting the meaning-making process developing in the receiver, a process affecting signal usage by animals, constraining agency of biological systems’ behavior towards a definite sequence of events or signals and providing a certain orientation of the process (“semiotic canalization”). Therefore, we can also say that signs could potentially be built by senders (i.e. by the sign-vehicle) in a sort of pre-determined way and not extracted by the receiver from a “neutral” sender. Semiotic canalization is seen as a part of a more general process of scaffolding during development, acting mainly during some information exchanges between communicating subjects, providing adaptive responses to some standard communicative situations. (shrink)

Recent computational models of perception conceptualize auditory oddball responses as signatures of a learning process, in line with the influential view of the mismatch negativity as a prediction error signal. Novel MMN experimental paradigms have put an emphasis on neurophysiological effects of manipulating regularity and predictability in sound sequences. This raises the question of the contextual adaptation of the learning process itself, which on the computational side speaks to the mechanisms of gain-modulated prediction error. In this study using electrocorticographic (...) signals, we manipulated the predictability of oddball sound sequences with two objectives: Uncovering the computational process underlying trial-by-trial variations of the cortical responses. The fluctuations between trials, generally ignored by approaches based on averaged evoked responses, should reflect the learning involved. We used a general linear model and Bayesian Model Reduction to assess the respective contributions of experimental manipulations and learning mechanisms under probabilistic assumptions. To validate and expand on previous findings regarding the effect of changes in predictability using simultaneous EEG-MEG recordings. Our trial-by-trial analysis revealed only a few stimulus-responsive sensors but the measured effects appear to be consistent over subjects in both time and space. In time, they occur at the typical latency of the MMN. In space, we found a dissociation between time-independent effects in more anterior temporal locations and time-dependent effects in more posterior locations. However, we could not observe any clear and reliable effect of our manipulation of predictability modulation onto the above learning process. Overall, these findings clearly demonstrate the potential of trial-to-trial modeling to unravel perceptual learning processes and their neurophysiological counterparts. (shrink)

A novel method for ECG signal outlier processing based on autoencoder neural networks is presented in the article. Typically, heartbeats with serious waveform distortions are treated as outliers and are skipped from the authentication pipeline. The main idea of the paper is to correct these waveform distortions rather them in order to provide the system with better statistical base. During the experiments, the optimum autoencoder architecture was selected. An open Physionet ECGID database was used to verify the proposed (...) method. The results of the studies were compared with previous studies that considered the correction of anomalies based on a statistical approach. On the one hand, the autoencoder shows slightly lower accuracy than the statistical method, but it greatly simplifies the construction of biometric identification systems, since it does not require precise tuning of hyperparameters. (shrink)

Philosophical proponents of predictive processing cast the novelty of predictive models of perception in terms of differences in the functional role and information content of neural signals. However, they fail to provide constraints on how the crucial semantic mapping from signals to their informational contents is determined. Beyond a novel interpretative gloss on neural signals, they have little new to say about the causal structure of the system, or even what statistical information is carried by the signals. That means (...) that the predictive framework for perception can be relabeled in traditional, non-predictive terms, with no empirical consequences relevant to existing or future data. To the extent that neuroscientific research based on predictive processing is both innovative and productive, it will be due to the framework’s suggestive heuristic effects, or perhaps auxiliary empirical claims about implementation, rather than a difference in the information-processing structure that it describes. (shrink)