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Perceptual grouping and visual attention are two mechanisms that help to segregate visual input into meaningful objects. Here we report how perceptual grouping, which affects perceived numerosity, is reduced when visual attention is engaged in a concurrent visual task. We asked participants to judge the numerosity of clouds of dot-pairs connected by thin lines, known to cause underestimation of numerosity, while simultaneously performing a color conjunction task. Diverting attention to the concomitant visual distractor significantly reduced the grouping-induced numerosity biases. Moreover, while the magnitude of the illusion under free viewing covaried strongly with AQ-defined autistic traits, under conditions of divided attention the relationship was much reduced. These results suggest that divided attention modulates the perceptual grouping of elements by connectedness and that it is independent of the perceptual style of participants.

It has recently been suggested that dyslexia may manifest as a deficit in the neural synchrony underlying language-based codes (Goswami, 2011), such that the phonological deficits apparent in dyslexia occur as a consequence of poor synchronisation of oscillatory brain signals to the sounds of language. There is compelling evidence to support this suggestion, and it provides an intriguing new development in understanding the aetiology of dyslexia. It is undeniable that dyslexia is associated with poor phonological coding, however, reading is also a visual task, and dyslexia has also been associated with poor visual coding, particularly visuo-spatial sensitivity. It has been hypothesized for some time that specific frequency oscillations underlie visual perception. Although little research has been done looking specifically at dyslexia and cortical frequency oscillations, it is possible to draw on converging evidence from visual tasks to speculate that similar deficits could occur in temporal frequency oscillations in the visual domain in dyslexia. Thus, here the plausibility of a visual correlate of the Temporal Sampling Framework is considered, leading to specific hypotheses and predictions for future research. A common underlying neural mechanism in dyslexia, may subsume qualitatively different manifestations of reading difficulty, which is consistent with the heterogeneity of the disorder, and may open the door for a new generation of exciting research.

In a previous study we reported on a non-invasive functional diffusion tensor imaging (fDTI) method to measure neuronal signals directly from subtle changes in fractional anisotropy along white matter tracts. We hypothesized that these fractional anisotropy changes relate to morphological changes of glial cells induced by axonal activity. In the present study we set out to replicate the results of the previous study with an improved fDTI scan acquisition scheme. A group of twelve healthy human participants were scanned on a 3 Tesla MRI scanner. Activation was revealed in the contralateral thalamo-cortical tract and optic radiations during tactile and visual stimulation, respectively. Mean percent signal change in FA was 3.47% for the tactile task and 3.79% for the visual task, while for the MD the mean percent signal change was only -0.10 and -0.09%. The results support the notion of different response functions for tactile and visual stimuli. With this study we successfully replicated our previous findings using the same types of stimuli but on a different group of healthy participants and at different field-strength. The successful replication of our first fDTI results suggests that the non-invasive fDTI method is robust enough to study the functional neural networks in the human brain within a practically feasible time period.

The manipulation of attention can produce mismatch negativity-like components that are not necessarily connected to the unintentional sensory registration of the violation of probability-based regularity. For clinical purposes, attentional bias should be quantified because it can vary substantially among subjects and can decrease the specificity of the examination. This experiment targets the role of attention in the generation of visual mismatch negativity (vMMN). The visual regularity was generated by a sequence of two radial motions while subjects focused on visual tasks in the central part of the display. Attentional load was systematically varied and had three levels, no-load, easy, and difficult. Rare, deviant, and frequent standard motions were presented with a 10/60 ratio in oddball sequences. Data from 12 subjects was recorded from 64 channels and processed. vMMN was identified within the interval of 142-198 ms. The mean amplitude was evaluated during the aforementioned interval in the parietal and fronto-central regions. A general linear model for repeated measures was applied to the mean amplitude with a three-factor design and showed a significant difference [F (1, 11) = 17.40, p = 0.002] between standard and deviant stimuli and between regions [F (1, 11) = 8.40, p = 0.01]; however, no significant effect of the task [F (2, 22) = 1.26, p = 0.30] was observed. The unintentional detection of irregularity during the processing of the visual motion was independent of the attentional load associated with handling the central visual task. The experiment did not demonstrate an effect of attentional load manipulation on mismatch negativity (MMN) induced by the motion-sequence, which supports the clinical utility of this examination. However, used stimulation paradigm should be further optimized to generate mismatch negativity that is stable enough to be usable not only for group comparisons but also for a single subject assessment.

We investigated how the brain integrates motivational and attentional signals by using a neuroimaging paradigm that provided separate estimates for transient cue- and target-related signals, in addition to sustained block-related responses. Participants performed a Posner-type task in which an endogenous cue predicted target location on 70% of trials, while motivation was manipulated by varying magnitude and valence of a cash incentive linked to task performance. Our findings revealed increased detection performance (d’) as a function of incentive value. In parallel, brain signals revealed that increases in absolute incentive magnitude led to cue- and target-specific response modulations that were independent of sustained state effects across visual cortex, fronto-parietal regions, and subcortical regions. Interestingly, state-like effects of incentive were observed in several of these brain regions, too, suggesting that both transient and sustained fMRI signals may contribute to task performance. For both cue and block periods, the effects of administering incentives were correlated with individual trait measures of reward sensitivity. Taken together, our findings support the notion that motivation improves behavioral performance in a demanding attention task by enhancing evoked responses across a distributed set of anatomical sites, many of which have been previously implicated in attentional processing. However, the effect of motivation was not simply additive as the impact of absolute incentive was greater during invalid than valid trials in several brain regions, possibly because motivation had a larger effect on reorienting than orienting attentional mechanisms at these sites.