What are the limits of unconscious language processing? Can language circuits process simple grammatical constructions unconsciously and integrate the meaning of several unseen words? Using behavioural priming and electroencephalography (EEG), we studied a specific rule-based linguistic operation traditionally thought to require conscious cognitive control: the negation of valence. In a masked priming paradigm, two masked words were successively (Experiment 1) or simultaneously presented (Experiment 2), a modifier (‘not’/‘very’) and an adjective (e.g. ‘good’/‘bad’), followed by a visible target noun (e.g. ‘peace’/‘murder’). Subjects indicated whether the target noun had a positive or negative valence. The combination of these three words could either be contextually consistent (e.g. ‘very bad - murder’) or inconsistent (e.g. ‘not bad - murder’). EEG recordings revealed that grammatical negations could unfold partly unconsciously, as reflected in similar occipito-parietal N400 effects for conscious and unconscious three-word sequences forming inconsistent combinations. However, only conscious word sequences elicited P600 effects, later in time. Overall, these results suggest that multiple unconscious words can be rapidly integrated and that an unconscious negation can automatically ‘flip the sign’ of an unconscious adjective. These findings not only extend the limits of subliminal combinatorial language processes, but also highlight how consciousness modulates the grammatical integration of multiple words.

In the neuropsychological case series approach, tasks are administered that tap different cognitive domains, and differences within rather than across individuals are the basis for theorising; each individual is effectively their own control. This approach is a mainstay of cognitive neuropsychology, and is particularly suited to the study of populations with heterogeneous deficits. However it has very rarely been applied to the study of cognitive differences in autism spectrum disorder (ASD). Here, we investigate whether this approach can yield information beyond that given by the typical group study method, when applied to an ASD population. Twenty-one high-functioning adult ASD participants and 22 IQ, age, and gender-matched control participants were administered a large battery of neuropsychological tests that would represent a typical neuropsychological assessment for neurological patients in the United Kingdom. The data were analysed using both group and single-case study methods. The group analysis revealed a limited number of deficits, principally on tests with a large executive function component, with no impairment in more routine abilities such as basic attending, language and perception. Single-case study analysis proved more fruitful revealing evidence of considerable variation in abilities both between and within ASD participants. Both sub-normal and supra-normal performance were observed, with the most defining feature of the ASD group being this variability. We conclude that the use of group-level analysis alone in the study of cognitive deficits in ASD risks missing cognitive characteristics that may be vitally important both theoretically and clinically, and even may be misleading because of averaging artifact.

Perceptual decisions seem to be made automatically and almost instantly. Constructing a unitary subjective conscious experience takes more time. For example, when trying to avoid a collision with a car on a foggy road you brake or steer away in a reflex, before realizing you were in a near accident. This subjective aspect of object recognition has been given little attention. We used metacognition (assessed with confidence ratings) to measure subjective experience during object detection and object categorization for degraded and masked objects, while objective performance was matched. Metacognition was equal for degraded and masked objects, but categorization led to higher metacognition than did detection. This effect turned out to be driven by a difference in metacognition for correct rejection trials, which seemed to be caused by an asymmetry of the distractor stimulus: It does not contain object-related information in the detection task, whereas it does contain such information in the categorization task. Strikingly, this asymmetry selectively impacted metacognitive ability when objective performance was matched. This finding reveals a fundamental difference in how humans reflect versus act on information: When matching the amount of information required to perform two tasks at some objective level of accuracy (acting), metacognitive ability (reflecting) is still better in tasks that rely on positive evidence (categorization) than in tasks that rely more strongly on an absence of evidence (detection).

Several electrophysiological studies have provided evidence for the frontal asymmetry of emotion. In this model the motivation to approach is lateralized to the left, whereas the motivation to avoidance is lateralized to the right hemisphere. The aim of the present experiment was to seek evidence for this model by relating electrophysiological and phenomenological indices of frontal asymmetry to a direct measure of cortical excitability. Frontal asymmetrical resting states of the electroencephalogram and motivational tendencies indexed by the Carver and White questionnaire were compared with neural excitability of the left and right primary motor cortex as assessed by transcranial magnetic stimulation in 24 young healthy right-handed volunteers. In agreement with the model of frontal asymmetry, predominant left over right frontal cortical excitability was associated with enhanced emotional approach relative to emotional avoidance. Moreover, the asymmetries of brain excitability and approach-avoidance motivational predispositions were both reflected by frontal beta (13-30 Hz) electroencephalogram asymmetries. In conclusion, the currently demonstrated interconnections between cortical excitability, electrophysiological activity, and self-reported emotional tendencies for approach or avoidance support the frontal asymmetry of emotion model and provide novel insights into its biological underpinnings.

To create subjective experience, our brain must translate physical stimulus input by incorporating prior knowledge and expectations. For example, we perceive color and not wavelength information, and this in part depends on our past experience with colored objects ( Hansen et al. 2006; Mitterer and de Ruiter 2008). Here, we investigated the influence of object knowledge on the neural substrates underlying subjective color vision. In a functional magnetic resonance imaging experiment, human subjects viewed a color that lay midway between red and green (ambiguous with respect to its distance from red and green) presented on either typical red (e.g., tomato), typical green (e.g., clover), or semantically meaningless (nonsense) objects. Using decoding techniques, we could predict whether subjects viewed the ambiguous color on typical red or typical green objects based on the neural response of veridical red and green. This shift of neural response for the ambiguous color did not occur for nonsense objects. The modulation of neural responses was observed in visual areas (V3, V4, VO1, lateral occipital complex) involved in color and object processing, as well as frontal areas. This demonstrates that object memory influences wavelength information relatively early in the human visual system to produce subjective color vision.

Multi-voxel pattern analyses have proved successful in ‘decoding’ mental states from fMRI data, but have not been used to examine brain differences associated with atypical populations. We investigated a group of 16 (14 males) high-functioning participants with autism spectrum disorder (ASD) and 16 non-autistic control participants (12 males) performing two tasks (spatial/verbal) previously shown to activate medial rostral prefrontal cortex (mrPFC). Each task manipulated: (i) attention towards perceptual versus self-generated information and (ii) reflection on another person's mental state (‘mentalizing'versus ‘non-mentalizing’) in a 2 × 2 design. Behavioral performance and group-level fMRI results were similar between groups. However, multi-voxel similarity analyses revealed strong differences. In control participants, the spatial distribution of activity generalized significantly between task contexts (spatial/verbal) when examining the same function (attention/mentalizing) but not when comparing different functions. This pattern was disrupted in the ASD group, indicating abnormal functional specialization within mrPFC, and demonstrating the applicability of multi-voxel pattern analysis to investigations of atypical populations.

It has been proposed that visual attention and consciousness are separate [Koch, C., & Tsuchiya, N. Attention and consciousness: Two distinct brain processes. Trends in Cognitive Sciences, 11, 16-22, 2007] and possibly even orthogonal processes [Lamme, V. A. F. Why visual attention and awareness are different. Trends in Cognitive Sciences, 7, 12-18, 2003]. Attention and consciousness converge when conscious visual percepts are attended and hence become available for conscious report. In such a view, a lack of reportability can have two causes: the absence of attention or the absence of a conscious percept. This raises an important question in the field of perceptual learning. It is known that learning can occur in the absence of reportability [Gutnisky, D. A., Hansen, B. J., Iliescu, B. F., & Dragoi, V. Attention alters visual plasticity during exposure-based learning. Current Biology, 19, 555-560, 2009; Seitz, A. R., Kim, D., & Watanabe, T. Rewards evoke learning of unconsciously processed visual stimuli in adult humans. Neuron, 61, 700-707, 2009; Seitz, A. R., & Watanabe, T. Is subliminal learning really passive? Nature, 422, 36, 2003; Watanabe, T., Náñez, J. E., & Sasaki, Y. Perceptual learning without perception. Nature, 413, 844-848, 2001], but it is unclear which of the two ingredients-consciousness or attention-is not necessary for learning. We presented textured figure-ground stimuli and manipulated reportability either by masking (which only interferes with consciousness) or with an inattention paradigm (which only interferes with attention). During the second session (24 hr later), learning was assessed neurally and behaviorally, via differences in figure-ground ERPs and via a detection task. Behavioral and neural learning effects were found for stimuli presented in the inattention paradigm and not for masked stimuli. Interestingly, the behavioral learning effect only became apparent when performance feedback was given on the task to measure learning, suggesting that the memory trace that is formed during inattention is latent until accessed. The results suggest that learning requires consciousness, and not attention, and further strengthen the idea that consciousness is separate from attention.

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