Alterations in The States and Contents of Consciousness: Empirical and Theoretical Aspects

The main purpose of the present doctoral thesis is to investigate subjective experiences and cognitive processes in four different types of altered states of consciousness: naturally occurring dreaming, cognitively induced hypnosis, pharmacologically induced sedation, and pathological psychosis. Both empirical and theoretical research is carried out, resulting in four empirical and four theoretical studies. The thesis begins with a review of the main concepts used in consciousness research, the most influential philosophical and neurobiological theories of subjective experience, the classification of altered states of consciousness, and the main empirical methods used to study consciousness alterations. Next, findings of the original studies are discussed, as follows. Phenomenal consciousness is found to be dissociable from responsiveness, as subjective experiences do occur in unresponsive states, including anaesthetic-induced sedation and natural sleep, as demonstrated by post-awakening subjective reports. Two new tools for the content analysis of subjective experiences and dreams are presented, focusing on the diversity, complexity and dynamics of phenomenal consciousness. In addition, a new experimental paradigm of serial awakenings from non-rapid eye movement sleep is introduced, which enables more rapid sampling of dream reports than has been available in previous studies. It is also suggested that lucid dreaming can be studied using transcranial brain stimulation techniques and systematic analysis of pre-lucid dreaming. For blind judges, dreams of psychotic patients appear to be indistinguishable from waking mentation reports collected from the same patients, which indicates a close resemblance of these states of mind. However, despite phenomenological similarities, dreaming should not be treated as a uniform research model of psychotic or intact consciousness. Contrary to this, there seems to be a multiplicity of routes of how different states of consciousness can be associated. For instance, seemingly identical time perception distortions in different alterations of consciousness may have diverse underlying causes for these distortions. It is also shown that altered states do not necessarily exhibit impaired cognitive processing compared to a baseline waking state of consciousness: a case study of time perception in a hypnotic virtuoso indicates a more consistent perceptual timing under hypnosis than in a waking state. The thesis ends with a brief discussion of the most promising new perspectives for the study of alterations of consciousness.Siirretty Doriast

14 challenges and their solutions for conducting social neuroscience and longitudinal EEG research with infants.

The use of electroencephalography (EEG) to study infant brain development is a growing trend. In addition to classical longitudinal designs that study the development of neural, cognitive and behavioural functions, new areas of EEG application are emerging, such as novel social neuroscience paradigms using dual infant-adult EEG recordings. However, most of the experimental designs, analysis methods, as well as EEG hardware were originally developed for single-person adult research. When applied to study infant development, adult-based solutions often pose unique problems that may go unrecognised. Here, we identify 14 challenges that infant EEG researchers may encounter when designing new experiments, collecting data, and conducting data analysis. Challenges related to the experimental design are: (1) small sample size and data attrition, and (2) varying arousal in younger infants. Challenges related to data acquisition are: (3) determining the optimal location for reference and ground electrodes, (4) control of impedance when testing with the high-density sponge electrode nets, (5) poor fit of standard EEG caps to the varying infant head shapes, and (6) ensuring a high degree of temporal synchronisation between amplifiers and recording devices during dual-EEG acquisition. Challenges related to the analysis of longitudinal and social neuroscience datasets are: (7) developmental changes in head anatomy, (8) prevalence and diversity of infant myogenic artefacts, (9) a lack of stereotypical topography of eye movements needed for the ICA-based data cleaning, (10) and relatively high inter-individual variability of EEG responses in younger cohorts. Additional challenges for the analysis of dual EEG data are: (11) developmental shifts in canonical EEG rhythms and difficulties in differentiating true inter-personal synchrony from spurious synchrony due to (12) common intrinsic properties of the signal and (13) shared external perturbation. Finally, (14) there is a lack of test-retest reliability studies of infant EEG. We describe each of these challenges and suggest possible solutions. While we focus specifically on the social neuroscience and longitudinal research, many of the issues we raise are relevant for all fields of infant EEG research.This research was funded by an ESRC Transforming Social Sciences collaboration grant (ES/N006461/1) to VL and SW, and by ESRC FRL Fellowship (ES/N017560/1) to SW

Emotional valence modulates the topology of the parent-infant inter-brain network.

Emotional communication between parents and children is crucial during early life, yet little is known about its neural underpinnings. Here, we adopt a dual connectivity approach to assess how positive and negative emotions modulate the interpersonal neural network between infants and their mothers during naturalistic interaction. Fifteen mothers were asked to model positive and negative emotions toward pairs of objects during social interaction with their infants (mean age 10.3 months) whilst the neural activity of both mothers and infants was concurrently measured using dual electroencephalography (EEG). Intra-brain and inter-brain network connectivity in the 6-9 Hz range (i.e. infant Alpha band) during maternal expression of positive and negative emotions was computed using directed (partial directed coherence, PDC) and non-directed (phase-locking value, PLV) connectivity metrics. Graph theoretical measures were used to quantify differences in network topology as a function of emotional valence. We found that inter-brain network indices (Density, Strength and Divisibility) consistently revealed strong effects of emotional valence on the parent-child neural network. Parents and children showed stronger integration of their neural processes during maternal demonstrations of positive than negative emotions. Further, directed inter-brain metrics (PDC) indicated that mother to infant directional influences were stronger during the expression of positive than negative emotional states. These results suggest that the parent-infant inter-brain network is modulated by the emotional quality and tone of dyadic social interactions, and that inter-brain graph metrics may be successfully applied to examine these changes in parent-infant inter-brain network topology.UK Economic and Social Research Council (ESRC) Transforming Social Sciences Grant ES/N006461/1 (to V.L. and S.W.), a Nanyang Technological University start-up Grant M4081585.SS0 (to V.L.), a Ministry of Education (Singapore) Tier 1 grant M4012105.SS0 (V.L.) and an ESRC Future Research Leaders Fellowship ES/N017560/1 (to S.W.)

Silent Expectations: Dynamic Causal Modeling of Cortical Prediction and Attention to Sounds That Weren't.

UNLABELLED: There is increasing evidence that human perception is realized by a hierarchy of neural processes in which predictions sent backward from higher levels result in prediction errors that are fed forward from lower levels, to update the current model of the environment. Moreover, the precision of prediction errors is thought to be modulated by attention. Much of this evidence comes from paradigms in which a stimulus differs from that predicted by the recent history of other stimuli (generating a so-called "mismatch response"). There is less evidence from situations where a prediction is not fulfilled by any sensory input (an "omission" response). This situation arguably provides a more direct measure of "top-down" predictions in the absence of confounding "bottom-up" input. We applied Dynamic Causal Modeling of evoked electromagnetic responses recorded by EEG and MEG to an auditory paradigm in which we factorially crossed the presence versus absence of "bottom-up" stimuli with the presence versus absence of "top-down" attention. Model comparison revealed that both mismatch and omission responses were mediated by increased forward and backward connections, differing primarily in the driving input. In both responses, modeling results suggested that the presence of attention selectively modulated backward "prediction" connections. Our results provide new model-driven evidence of the pure top-down prediction signal posited in theories of hierarchical perception, and highlight the role of attentional precision in strengthening this prediction. SIGNIFICANCE STATEMENT: Human auditory perception is thought to be realized by a network of neurons that maintain a model of and predict future stimuli. Much of the evidence for this comes from experiments where a stimulus unexpectedly differs from previous ones, which generates a well-known "mismatch response." But what happens when a stimulus is unexpectedly omitted altogether? By measuring the brain's electromagnetic activity, we show that it also generates an "omission response" that is contingent on the presence of attention. We model these responses computationally, revealing that mismatch and omission responses only differ in the location of inputs into the same underlying neuronal network. In both cases, we show that attention selectively strengthens the brain's prediction of the future.This work was supported by the UK Medical Research Council Programme [MC-A060-5PR10 to RH], in addition to grants from the Wellcome Trust [WT093811MA to TAB], the James S. McDonnell Foundation, and the Evelyn Trust [15/07 to SC].This is the final version of the article. It first appeared from the Society for Neuroscience via http://dx.doi.org/10.1523/JNEUROSCI.1125-16.201

EEG Frontal Alpha Asymmetry and Dream Affect: Alpha Oscillations over the Right Frontal Cortex during REM Sleep and Presleep Wakefulness Predict Angerin REM Sleep Dreams

Affective experiences are central not only to our waking life but also to rapid eye movement (REM) sleep dreams. Despite our increasing understanding of the neural correlates of dreaming, we know little about the neural correlates of dream affect. Frontal alpha asymmetry (FAA) is considered a marker of affective states and traits as well as affect regulation in the waking state. Here, we explored whether FAA during REM sleep and during evening resting wakefulness is related to affective experiences in REM sleep dreams. EEG recordings were obtained from 17 human participants (7men) who spent 2 nights in the sleep laboratory. Participants were awakened 5minafter the onset of every REM stage after which they provided a dream report and rated their dream affect. Two-minute preawakening EEG segments were analyzed. Additionally, 8 min of evening presleep and morning postsleep EEG were recorded during resting wakefulness. Mean spectral power in the alpha band (8 –13 Hz) and corresponding FAA were calculated over the frontal (F4-F3) sites. Results showed that FAA during REM sleep, and during evening resting wakefulness, predicted ratings of dream anger. This suggests that individuals with greater alpha power in the right frontal hemisphere may be less able to regulate (i.e., inhibit) strong affective states, such as anger, in dreams. Additionally, FAA was positively correlated across wakefulness and REM sleep. Together, these findings imply that FAA may serve as a neural correlate of affect regulation not only in the waking but also in the dreaming state.</p

A short note on the reliability of perceptual timing tasks as commonly used in research on developmental disorders.

OBJECTIVES: Perceptual timing tasks are frequently applied in research on developmental disorders, but information on their reliability is lacking in pediatric studies. We therefore aimed to assess the reliability of the four paradigms most frequently used, i.e., time discrimination, time estimation, time production, and time reproduction. METHODS: Based on the data from our recent longitudinal study by Marx et al. (Front Hum Neurosci 11:122, 2017), we estimated the internal consistency and test-retest reliability of these tasks in children with ADHD and typically developing children. Individual thresholds were used as dependent measures for the time discrimination task, whereas absolute error and accuracy coefficient scores were used for the other three tasks. RESULTS: Although less commonly used, the time estimation paradigm was the most robust measure of perceptual timing in terms of internal consistency and test-retest reliability in both ADHD and typically developing children, whereas the most frequently used paradigms showed poor internal consistency (time reproduction) and poor test-retest reliability (time discrimination). Compared to the absolute errors, accuracy coefficients showed almost exclusively higher internal consistency and test-retest reliability. CONCLUSIONS: Our findings call for more frequent use of the time estimation paradigm in studies of perceptual timing in ADHD. The time reproduction paradigm should be re-considered, avoiding pooling of a wide range of time intervals (2-48 s). The accuracy coefficient score is the more reliable and the more intuitive dependent variable and should be preferred in future timing research. To increase the reliability of the timing measurement, each experimental session should be performed twice, if possible

Toward the Understanding of Topographical and Spectral Signatures of Infant Movement Artifacts in Naturalistic EEG

Electroencephalography (EEG) is perhaps the most widely used brain-imaging technique for pediatric populations. However, EEG signals are prone to distortion by motion. Compared to adults, infants’ motion is both more frequent and less stereotypical yet motion effects on the infant EEG signal are largely undocumented. Here, we present a systematic assessment of naturalistic motion effects on the infant EEG signal. EEG recordings were performed with 14 infants (12 analyzed) who passively watched movies whilst spontaneously producing periods of bodily movement and rest. Each infant produced an average of 38.3 s (SD = 14.7 s) of rest and 18.8 s (SD = 17.9 s) of single motion segments for the final analysis. Five types of infant motions were analyzed: Jaw movements, and Limb movements of the Hand, Arm, Foot, and Leg. Significant movement-related distortions of the EEG signal were detected using cluster-based permutation analysis. This analysis revealed that, relative to resting state, infants’ Jaw and Arm movements produced significant increases in beta (∼15 Hz) power, particularly over peripheral sites. Jaw movements produced more anteriorly located effects than Arm movements, which were most pronounced over posterior parietal and occipital sites. The cluster analysis also revealed trends toward decreased power in the theta and alpha bands observed over central topographies for all motion types. However, given the very limited quantity of infant data in this study, caution is recommended in interpreting these findings before subsequent replications are conducted. Nonetheless, this work is an important first step to inform future development of methods for addressing EEG motion-related artifacts. This work also supports wider use of naturalistic paradigms in social and developmental neuroscience

Event timing in human vision : Modulating factors and independent functions

Essential for successful interaction with the environment is the human capacity to resolve events in time. Typical event timing paradigms are judgements of simultaneity (SJ) and of temporal order (TOJ). It remains unclear whether SJ and TOJ are based on the same underlying mechanism and whether there are fixed thresholds for resolution. The current study employed four visual event timing task versions: horizontal and vertical SJ and TOJ. Binary responses were analysed using multilevel binary regression modelling. Modulatory effects of potential explanatory variables on event timing perception were investigated: (1) Individual factors (sex and age), (2) temporal factors (SOA, trial number, order of experiment, order of stimuli orientation, time of day) and (3) spatial factors (left or right stimulus first, top or bottom stimulus first, horizontal vs. vertical orientation). The current study directly compares for the first time, performance on SJ and TOJ tasks using the same paradigm and presents evidence that a variety of factors and their interactions selectively modulate event timing functions in humans, explaining the variance found in previous studies. We conclude that SJ and TOJ are partially independent functions, because they are modulated differently by individual and contextual variables.Peer reviewe

Alertness fluctuations when performing a task modulate cortical evoked responses to transcranial magnetic stimulation.

Transcranial magnetic stimulation (TMS) has been widely used in human cognitive neuroscience to examine the causal role of distinct cortical areas in perceptual, cognitive and motor functions. However, it is widely acknowledged that the effects of focal cortical stimulation can vary substantially between participants and even from trial to trial within individuals. Recent work from resting state functional magnetic resonance imaging (fMRI) studies has suggested that spontaneous fluctuations in alertness over a testing session can modulate the neural dynamics of cortical processing, even when participants remain awake and responsive to the task at hand. Here we investigated the extent to which spontaneous fluctuations in alertness during wake-to-sleep transition can account for the variability in neurophysiological responses to TMS. We combined single-pulse TMS with neural recording via electroencephalography (EEG) to quantify changes in motor and cortical reactivity with fluctuating levels of alertness defined objectively on the basis of ongoing brain activity. We observed rapid, non-linear changes in TMS-evoked responses with decreasing levels of alertness, even while participants remained responsive in the behavioural task. Specifically, we found that the amplitude of motor evoked potentials peaked during periods of EEG flattening, whereas TMS-evoked potentials increased and remained stable during EEG flattening and the subsequent occurrence of theta ripples that indicate the onset of NREM stage 1 sleep. Our findings suggest a rapid and complex reorganization of active neural networks in response to spontaneous fluctuations of alertness over relatively short periods of behavioural testing during wake-to-sleep transition