Confounding in studies on metacognition : a preliminary causal analysis framework

By definition, metacognitive processes may monitor or regulate various stages of first-order processing. By combining causal analysis with hypotheses expressed by other authors we derive the theoretical and methodological consequences of this special relation between metacognition and the underlying processes. In particular, we prove that because multiple processing stages may be monitored or regulated and because metacognition may form latent feedback loops, (1) without strong additional causal assumptions, typical measures of metacognitive monitoring or regulation are confounded; (2) without strong additional causal assumptions, typical methods of controlling for first-order task performance (i.e., calibration, staircase, including first-order task performance in a regression analysis, or analyzing correct and incorrect trials separately) not only do not deconfound measures of metacognition but may even introduce bias; (3) that the first two problems cannot be solved by using simple models of decision-making derived from Signal Detection Theory. We conclude the paper by advocating robust methods of discovering properties of latent mechanisms

Opisać świadomość na skali od zera do jeden. Perturbacyjny Indeks Złożoności jako naukowa próba pomiaru świadomości na poziomie indywidualnym

Describing consciousness on scale from zero to one. Perturbational Complexity Index as a scientific attempt on measuring consciousness on an individual levelScientific study of consciousness entered a new era with research focused on finding its neural correlates. The article depicts reasoning underlying this paradigm and controversies it arises using a novel tool designed to measure one’s level of consciousness by means of analyzing EEG signal. Perturbational Complexity Index, created by team led by Guilio Tononi, is used to present theoretical debate concerning the possibility of creating an objective consciousness measure. Stemming from reflections on mechanisms of loss of consciousness, authors of the index infer the informational nature of the phenomena, which is said to be demonstrated by experiments with participants under anesthesia, in deep sleep or suffering from disorders of consciousness. The extraordinary capability of the index to measure the level of consciousness on an individual level and its practical applications are discussed in context of possibility of experimental access to subjective experience

Describing consciousness on scale from zero to one : perturbational Complexity Index as a scientific attempt on measuring consciousness on an individual level

Scientific study of consciousness entered a new era with research focused on finding its neural correlates. The article depicts reasoning underlying this paradigm and controversies it arises using a novel tool designed to measure one’s level of consciousness by means of analyzing EEG signal. Perturbational Complexity Index, created by team led by Guilio Tononi, is used to present theoretical debate concerning the possibility of creating an objective consciousness measure. Stemming from reflections on mechanisms of loss of consciousness, authors of the index infer the informational nature of the phenomena, which is said to be demonstrated by experiments with participants under anesthesia, in deep sleep or suffering from disorders of consciousness. The extraordinary capability of the index to measure the level of consciousness on an individual level and its practical applications are discussed in context of possibility of experimental access to subjective experience

Transcranial magnetic stimulation-induced motor cortex activity influences visual awareness judgments

The influence of non-visual information on visual awareness judgments has recently gained substantial interest. Using single-pulse Transcranial Magnetic Stimulation (TMS), we investigate the potential contribution of evidence from the motor system to judgment of visual awareness. We hypothesized that TMS-induced activity in the primary motor cortex (M1) would increase reported visual awareness as compared to the control condition. Additionally, we investigated whether TMS-induced motor-evoked potential could measure accumulated evidence for stimulus perception. Following stimulus presentation and TMS, participants first rated their visual awareness verbally using the Perceptual Awareness Scale, after which they responded manually to a Gabor orientation identification task. Delivering TMS to M1 resulted in higher average awareness ratings as compared to the control condition when the hand with which participants responded was contralateral to the stimulated hemisphere (TMS-response-congruent trials). This effect was accompanied by longer Perceptual Awareness Scale response times, irrespective of the congruence between TMS and identification response. Moreover, longer identification response times were observed in TMS-response-congruent trials in the M1 condition as compared to the control condition. Additionally, the amplitudes of motor-evoked potentials were related to the awareness ratings when response congruence was taken into account. We argue that motor-evoked potential can serve as an indirect measure of evidence accumulated for stimulus perception and that longer Perceptual Awareness Scale response times and higher amplitudes of motor-evoked potentials in the M1 condition reflect integration of additional evidence with visual awareness judgment. In conclusion, we advocate that motor activity influences perceptual awareness judgments

Brain correlates of task-load and dementia elucidation with tensor machine learning using oddball BCI paradigm

Dementia in the elderly has recently become the most usual cause of cognitive decline. The proliferation of dementia cases in aging societies creates a remarkable economic as well as medical problems in many communities worldwide. A recently published report by The World Health Organization (WHO) estimates that about 47 million people are suffering from dementia-related neurocognitive declines worldwide. The number of dementia cases is predicted by 2050 to triple, which requires the creation of an AI-based technology application to support interventions with early screening for subsequent mental wellbeing checking as well as preservation with digital-pharma (the so-called beyond a pill) therapeutical approaches. We present an attempt and exploratory results of brain signal (EEG) classification to establish digital biomarkers for dementia stage elucidation. We discuss a comparison of various machine learning approaches for automatic event-related potentials (ERPs) classification of a high and low task-load sound stimulus recognition. These ERPs are similar to those in dementia. The proposed winning method using tensor-based machine learning in a deep fully connected neural network setting is a step forward to develop AI-based approaches for a subsequent application for subjective- and mild-cognitive impairment (SCI and MCI) diagnostics.Comment: In ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 8578-8582, May 201

Disorders of consciousness : clinical and ethical perspective

Disorders of consciousness are among the main consequences of severe brain injury. They are characterised by the disruption of the relationship between the quantitative (arousal, wakefulness) and the qualitative (awareness of the self and environment) aspects of consciousness. This includes conditions where a high level of arousal is not accompanied with retained awareness (and vice versa). An accurate diagnosis of patients with severe brain injuries who present with various forms of disorders of consciousness still poses a real clinical, scientific and ethical challenge. This paper describes those conditions as well as diagnostic criteria and behavioural tools commonly used for their discrimination. The authors discuss brain death, coma, vegetative state, minimally conscious state and locked-in syndrome. Ethical and prognostic issues associated with the diagnosis and treatment of such patients are also discussed. Moreover, a clear classification of disorders of consciousness is proposed, which is intended to eliminate some ambiguities in Polish nomenclature concerning this type of neurological disorders. Behavioural scales are standard clinical tools for bedside assessment of patients with disorders of consciousness. In this paper, we review several behavioural scales, and describe their diagnostic advantages and shortcomings. The JFK Coma Recovery Scale–Revised (CRS-R) appears to present high sensitivity and specificity of diagnosing disorders of consciousness. The use of scales, such as the CRS-R, along with neuroimaging approaches (which have been developing intensively in the recent years) may provide a way to obtain a complete and accurate diagnosis of disorders of consciousness. That is why translation of the CRS-R and its validation in Polish conditions might play an important role in the diagnosis of such patients in our country

The Confidence Database

Understanding how people rate their confidence is critical for the characterization of a wide range of perceptual, memory, motor and cognitive processes. To enable the continued exploration of these processes, we created a large database of confidence studies spanning a broad set of paradigms, participant populations and fields of study. The data from each study are structured in a common, easy-to-use format that can be easily imported and analysed using multiple software packages. Each dataset is accompanied by an explanation regarding the nature of the collected data. At the time of publication, the Confidence Database (which is available at https://osf.io/s46pr/) contained 145 datasets with data from more than 8,700 participants and almost 4 million trials. The database will remain open for new submissions indefinitely and is expected to continue to grow. Here we show the usefulness of this large collection of datasets in four different analyses that provide precise estimations of several foundational confidence-related effects

Estimation of effective cerebral connectivity with EEG somatosensory steady-state evoked potentials.

Wykonano badania pilotażowe, testujące metodę somatosensorycznych potencjałów stanu ustalonego (SSS-EP), jako użytecznego kryterium diagnostycznego do oceny poziomu pobudzenia korowego u pacjentów z zaburzeniami świadomości. Zgodnie z hipotezą przerwania efektywnej łączności korowej, funkcjonalna charakterystyka pracy kory mózgowej podczas braku świadomości jest wspólna dla pacjentów po ciężkim urazie mózgu, jak i osób pogrążonych we śnie. Dlatego też za model mózgu z przerwaną łącznością korową posłużyły osoby w stanie głębokiego snu (N2 i N3).Przebadano 32 zdrowych ochotników, z których 22 osoby wzięły udział w obu warunkach eksperymentalnych (snu i przytomności). Badanym podawano serie elektrycznych bodźców generujących doznania somatosensoryczne poniżej progu bólu. Zastosowano stymulację o częstotliwości nośnej 60Hz i 62,5Hz modulowaną prostokątnie przez częstotliwości 6Hz, 8Hz, 12Hz, 20Hz i 25Hz, poszukując odpowiedzi o najbardziej optymalnym stosunku sygnału do szumu. Zebrane dane EEG przekształcono do domeny częstotliwościowej, a następnie badano wpływ i interakcje pomiędzy zmiennymi niezależnymi (poziomu pobudzenia oraz dwóch zmiennych lokalizacyjnych – czynnika X i Y – kodujących położenie wyszczególnionych regionów) na parametr siły reakcji SS-EP.Zaobserwowano efekt zmniejszonej amplitudy w warunku głębokiego snu dla trzech częstotliwości modulujących (12Hz, 20Hz oraz 25Hz) oraz częściowe efekty lokalizacji dla wybranych częstotliwości. Uzyskane wyniki potwierdzają wystarczający potencjał różnicujący narzędzia, co zachęca do rozszerzenia testów o populację pacjentów z zaburzeniami świadomości.The present pilot study explored the somatosensory steady-state evoked potentials (SSS-EP) as a potential diagnostic measure of cortical connectivity in patients with disorders of consciousness. Following the hypothesis of breakdown of cortical connectivity appearing both in deep sleep and after traumatic loss of consciousness, healthy volunteers during their deep sleep phase were considered as a functional model of a brain with disordered consciousness.32 healthy volunteers were tested, of which 22 participated in both experimental conditions (high level of wakefulness and deep sleep). They were presented with series of electric somatosensory stimulation, with 60Hz and 62.5Hz carrier frequencies, box-car modulated. EEG data was analysed in the frequency domain. Level of cortical arousal and scalp location were treated as independent variables.The effects of reduced response strength in deep sleep were found for some frequencies (12Hz, 20Hz and 25Hz), just as partial localization effects. Acquired results encourage further development of the procedure and extending the sample group to clinical patients

How much consciousness is there in complexity

The notion of complexity receives currently significant amount of attention in neuroscience, mostly through the popularity of the Integrated Information Theory (IIT). It has proven successful in research centred on discriminating states of consciousness, while little theoretical and experimental effort was directed towards studying the content. In this paper, we argue that exploring the relation between complexity and conscious content is necessary to properly understand the importance of information-theoretic measures with consciousness. We outline how content can be experimentally operationalized and how rudimental testable hypotheses can be formulated without the necessity for inclusion of formalisms of IIT. This approach would not only allow for better understanding of aspects of consciousness captured by complexity, but could also facilitate comparisons of theories of consciousness