Unconscious multisensory integration: behavioral and neural evidence from subliminal stimuli

Introduction

The prevailing theories of consciousness consider the integration of different sensory stimuli as a key component for this phenomenon to rise on the brain level. Despite many theories and models have been proposed for multisensory integration between supraliminal stimuli (e.g., the optimal integration model), we do not know if multisensory integration occurs also for subliminal stimuli and what psychophysical mechanisms it follows.

Methods

To investigate this, subjects were exposed to visual (Virtual Reality) and/or haptic stimuli (Electro-Cutaneous Stimulation) above or below their perceptual threshold. They had to discriminate, in a two-Alternative Forced Choice Task, the intensity of unimodal and/or bimodal stimuli. They were then asked to discriminate the sensory modality while recording their EEG responses.

Results

We found evidence of multisensory integration for supraliminal condition, following the classical optimal model. Importantly, even for subliminal trials participant's performances in the bimodal condition were significantly more accurate when discriminating the intensity of the stimulation. Moreover, significant differences emerged between unimodal and bimodal activity templates in parieto-temporal areas known for their integrative role.

Discussion

These converging evidences - even if preliminary and needing confirmation from the collection of further data - suggest that subliminal multimodal stimuli can be integrated, thus filling a meaningful gap in the debate about the relationship between consciousness and multisensory integration.

Mutual interaction between visual homeostatic plasticity and sleep in adult humans

Sleep and plasticity are highly interrelated, as sleep slow oscillations and sleep spindles are associated with consolidation of Hebbian-based processes. However, in adult humans, visual cortical plasticity is mainly sustained by homeostatic mechanisms, for which the role of sleep is still largely unknown. Here, we demonstrate that non-REM sleep stabilizes homeostatic plasticity of ocular dominance induced in adult humans by short-term monocular deprivation: the counterintuitive and otherwise transient boost of the deprived eye was preserved at the morning awakening (>6 hr after deprivation). Subjects exhibiting a stronger boost of the deprived eye after sleep had increased sleep spindle density in frontopolar electrodes, suggesting the involvement of distributed processes. Crucially, the individual susceptibility to visual homeostatic plasticity soon after deprivation correlated with the changes in sleep slow oscillations and spindle power in occipital sites, consistent with a modulation in early occipital visual cortex.

Sleep slow oscillations favour local cortical plasticity underlying the consolidation of reinforced procedural learning in human sleep

We investigated changes of slow-wave activity and sleep slow oscillations in the night following procedural learning boosted by reinforcement learning, and how these changes correlate with behavioural output. In the Task session, participants had to reach a visual target adapting cursor's movements to compensate an angular deviation introduced experimentally, while in the Control session no deviation was applied. The task was repeated at 13:00 hours, 17:00 hours and 23:00 hours before sleep, and at 08:00 hours after sleep. The deviation angle was set at 15° (13:00 hours and 17:00 hours) and increased to 45° (reinforcement) at 23:00 hours and 08:00 hours. Both for Task and Control nights, high-density electroencephalogram sleep recordings were carried out (23:30-19:30 hours). The Task night as compared with the Control night showed increases of: (a) slow-wave activity (absolute power) over the whole scalp; (b) slow-wave activity (relative power) in left centro-parietal areas; (c) sleep slow oscillations rate in sensorimotor and premotor areas; (d) amplitude of pre-down and up states in premotor regions, left sensorimotor and right parietal regions; (e) sigma crowning the up state in right parietal regions. After Task night, we found an improvement of task performance showing correlations with sleep slow oscillations rate in right premotor, sensorimotor and parietal regions. These findings suggest a key role of sleep slow oscillations in procedural memories consolidation. The diverse components of sleep slow oscillations selectively reflect the network activations related to the reinforced learning of a procedural visuomotor task. Indeed, areas specifically involved in the task stand out as those with a significant association between sleep slow oscillations rate and overnight improvement in task performance.

Functional determinants of enhanced and depressed interareal information flow in nonrapid eye movement sleep between neuronal ensembles in rat cortex and hippocampus

Compared with wakefulness, neuronal activity during nonrapid eye movement (NREM) sleep is characterized by a decreased ability to integrate information, but also by the reemergence of task-related information patterns. To investigate the mechanisms underlying these seemingly opposing phenomena, we measured directed information flow by computing transfer entropy between neuronal spiking activity in three cortical regions and the hippocampus of rats across brain states. State-dependent information flow was jointly determined by the anatomical distance between neurons and by their functional specialization. We distinguished two regimes, operating at short and long time scales, respectively. From wakefulness to NREM sleep, transfer entropy at short time scales increased for interareal connections between neurons showing behavioral task correlates. Conversely, transfer entropy at long time scales became stronger between nontask modulated neurons and weaker between task-modulated neurons. These results may explain how, during NREM sleep, a global interareal disconnection is compatible with highly specific task-related information transfer.

Inefficient stimulus processing at encoding affects formation of high-order general representation: A study on cross-modal word-stem completion task

Priming is an implicit memory effect in which previous exposure to one stimulus influences the response to another stimulus. The main characteristic of priming is that it occurs without awareness. Priming takes place also when the physical attributes of previously studied and test stimuli do not match; in fact, it greatly refers to a general stimulus representation activated at encoding independently of the sensory modality engaged. Our aim was to evaluate whether, in a cross-modal word-stem completion task, negative priming scores could depend on inefficient word processing at study and therefore on an altered stimulus representation. Words were presented in the auditory modality, and word-stems to be completed in the visual modality. At study, we recorded auditory ERPs, and compared the P300 (attention/memory) and N400 (meaning processing) of individuals with positive and negative priming. Besides classical averaging-based ERPs analysis, we used an ICA-based method (ErpICASSO) to separate the potentials related to different processes contributing to ERPs. Classical analysis yielded significant difference between the two waves across the whole scalp. ErpICASSO allowed separating the novelty-related P3a and the top-down control-related P3b sub-components of P300. Specifically, in the component C3, the positive deflection identifiable as P3b, was significantly greater in the positive than in the negative priming group, while the late negative deflection corresponding to the parietal N400, was reduced in the positive priming group. In conclusion, inadequacy of specific processes at encoding, such as attention and/or meaning retrieval, could generate weak semantic representations, making words less accessible in subsequent implicit retrieval.

Looking for a precursor of spontaneous Sleep Slow Oscillations in human sleep: The role of the sigma activity

Sleep Slow Oscillations (SSOs), paradigmatic EEG markers of cortical bistability (alternation between cellular downstates and upstates), and sleep spindles, paradigmatic EEG markers of thalamic rhythm, are two hallmarks of sleeping brain. Selective thalamic lesions are reportedly associated to reductions of spindle activity and its spectrum ~14 Hz (sigma), and to alterations of SSO features. This apparent, parallel behavior suggests that thalamo-cortical entrainment favors cortical bistability. Here we investigate temporally-causal associations between thalamic sigma activity and shape, topology, and dynamics of SSOs. We recorded sleep EEG and studied whether spatio-temporal variability of SSO amplitude, negative slope (synchronization in downstate falling) and detection rate are driven by cortical-sigma-activity expression (12-18Hz), in 3 consecutive 1s-EEG-epochs preceding each SSO event (Baselines). We analyzed: (i) spatial variability, comparing maps of baseline sigma power and of SSO features, averaged over the first sleep cycle; (ii) event-by-event shape variability, computing for each electrode correlations between baseline sigma power and amplitude/slope of related SSOs; (iii) event-by-event spreading variability, comparing baseline sigma power in electrodes showing an SSO event with the homologous ones, spared by the event. The scalp distribution of baseline sigma power mirrored those of SSO amplitude and slope; event-by-event variability in baseline sigma power was associated with that in SSO amplitude in fronto-central areas; within each SSO event, electrodes involved in cortical bistability presented higher baseline sigma activity than those free of SSO. In conclusion, spatio-temporal variability of thalamocortical entrainment, measured by background sigma activity, is a reliable estimate of the cortical proneness to bistability.

Brain responses to emotional stimuli during breath holding and hypoxia: an approach based on the independent component analysis

Voluntary breath holding represents a physiological model of hypoxia. It consists of two phases of oxygen saturation dynamics: an initial slow decrease (normoxic phase) followed by a rapid drop (hypoxic phase) during which transitory neurological symptoms as well as slight impairment of integrated cerebral functions, such as emotional processing, can occur. This study investigated how breath holding affects emotional processing. To this aim we characterized the modulation of event-related potentials (ERPs) evoked by emotional-laden pictures as a function of breath holding time course. We recorded ERPs during free breathing and breath holding performed in air by elite apnea divers. We modeled brain responses during free breathing with four independent components distributed over different brain areas derived by an approach based on the independent component analysis (ICASSO). We described ERP changes during breath holding by estimating amplitude scaling and time shifting of the same components (component adaptation analysis). Component 1 included the main EEG features of emotional processing, had a posterior localization and did not change during breath holding; component 2, localized over temporo-frontal regions, was present only in unpleasant stimuli responses and decreased during breath holding, with no differences between breath holding phases; component 3, localized on the fronto-central midline regions, showed phase-independent breath holding decreases; component 4, quite widespread but with frontal prevalence, decreased in parallel with the hypoxic trend. The spatial localization of these components was compatible with a set of processing modules that affects the automatic and intentional controls of attention. The reduction of unpleasant-related ERP components suggests that the evaluation of aversive and/or possibly dangerous situations might be altered during breath holding.

Detection and removal of ocular artifacts from EEG signals for an automated REM sleep analysis

Rapid eye movements (REMs) are a prominent feature of REM sleep, and their distribution and time density over the night represent important physiological and clinical parameters. At the same time, REMs produce substantial distortions on the electroencephalographic (EEG) signals, which strongly affect the significance of normal REM sleep quantitative study. In this work a new procedure for a complete and automated analysis of REM sleep is proposed, which includes both a REMs detection algorithm and an ocular artifact removal system. The two steps, based respectively on Wavelet Transform and adaptive filtering, are fully integrated and their performance is evaluated using REM simulated signals. Thanks to the integration with the detection algorithm, the proposed artifact removal system shows an enhanced accuracy in the recovering of the true EEG signal, compared to a system based on the adaptive filtering only. Finally the artifact removal system is applied to physiological data and an estimation of the actual distortion induced by REMs on EEG signals is supplied.

Automated detection of sleep EEG slow waves based on matching pursuit using a restricted dictionary

In this paper, an original method to detect sleep slow waves (SSW) in electroencephalogram (EEG) recordings is proposed. This method takes advantage of a Matching Pursuit algorithm using a dictionary reduced to Gabor functions reproducing the main targeted waveform characteristics. By describing the EEG signals in terms of SSW properties, the corresponding algorithm is able to identify waveforms based on the largest matching coefficients. The implemented algorithm was tested on a database of whole night sleep EEG recordings collected in 9 young healthy subjects where SSW have been visually scored by an expert. Besides being fully automated and much faster than visual scoring analysis, the results obtained to the proposed method were in excellent agreement with the expert with 98% of correct detections and a 77% concordance in event time position and duration. These results were superior from those of the classical method both in terms of sensibility and precision.

Thalamic contribution to Sleep Slow Oscillation features in humans: a single case cross sectional EEG study in Fatal Familial Insomnia

OBJECTIVE

Studying the thalamic role in the cortical expression of the Sleep Slow Oscillation (SSO) in humans by comparing SSO features in a case of Fatal Familial Insomnia (FFI) and a group of controls.

METHODS

We characterize SSOs in a 51-year-old male with FFI carrying the D178N mutation and the methionine/methionine homozygosity at the polymorphic 129 codon of the PRNP gene and in eight gender and age-matched healthy controls. Polysomnographic (21 EEG electrodes, two consecutive nights) and volumetric- (Diffusion tensor imaging Magnetic Resonance Imaging DTI MRI) evaluations were carried out for the patient in the middle course of the disease (five months after the onset of insomnia; disease duration: 10 months). We measured a set of features describing each SSO event: the wave shape, the event-origin location, the number and the location of all waves belonging to the event, and the grouping of spindle activity as a function of the SSO phase.

RESULTS

We found that the FFI individual showed a marked reduction of SSO event rate and wave morphological alterations as well as a significant reduction in grouping spindle activity, especially in frontal areas. These alterations paralleled DTI changes in the thalamus and the cingulate cortex.

CONCLUSIONS

This work gives a quantitative picture of spontaneous SSO activity during the NREM sleep of a FFI individual. The results suggest that a thalamic neurodegeneration specifically alters the cortical expression of the SSO. This characterization also provides indications about cortico-thalamic interplays in SSO activity in humans.