Control of Visual Selection during Visual Search in the Human Brain

How do we find a target object in a cluttered visual scene? Targets carrying unique salient features can be found in parallel without directing attention, whereas targets defined by feature conjunctions or non-salient features need to be scrutinized in a serial attentional process in order to be identified. In this article, we review a series of experiments in which we used fMRI to probe the neural basis of this active search process in the human brain. In all experiments, we compared the fMRI signal between a difficult and an easy visual search (each performed without eye movements) in order to isolate neural activity reflecting the search process from other components such as stimulus responses and movement-related activity. The difficult search was either a conjunction search or a hard feature search and compared with an easy feature search, matched in visual stimulation and motor requirements. During both, the conjunction search and the hard feature search the frontal eye fields (FEF) and three parietal regions located in the intraparietal sulcus (IPS) were differentially activated: the anterior and posterior part of the intraparietal sulcus (AIPS, PIPS) as well as the junction of the intraparietal with the transverse occipital sulcus (IPTO). Only in PIPS, the modulation strength was most indistinguishable between conjunction and hard feature search. In a further experiment we showed that AIPS and IPTO are involved in visual conjunction search even in the absence of distractors; by contrast, the involvement of PIPS seems to depend on the presence of distractors. Taken together, these findings from these experiments demonstrate that all four key nodes of the human ’frontoparietal attention network’ are generally engaged in the covert selection process of visual search. But they also suggest that these areas play differential roles, perhaps reflecting different sub-processes in active search. We conclude by discussing a number of such sub-processes, such as the direction of spatial attention, visual feature binding, and the active suppression of distractors

Inhibitory non-invasive brain stimulation to homologous language regions as an adjunct to speech and language therapy in post-stroke aphasia: a meta-analysis.

Chronic communication impairment is common after stroke, and conventional speech and language therapy (SLT) strategies have limited effectiveness in post-stroke aphasia. Neurorehabilitation with non-invasive brain stimulation techniques (NIBS)-particularly repetitive transcranial magnetic stimulation (rTMS) or transcranial direct current stimulation (tDCS)-may enhance the effects of SLT in selected patients. Applying inhibitory NIBS to specific homologous language regions may induce neural reorganization and reduce interhemispheric competition. This mini review highlights randomized controlled trials (RCTs) and randomized cross-over trials using low-frequency rTMS or cathodal tDCS over the non-lesioned non-language dominant hemisphere and performs an exploratory meta-analysis of those trials considered combinable. Using a random-effects model, a meta-analysis of nine eligible trials involving 215 participants showed a significant mean effect size of 0.51 (95% CI = 0.24-0.79) for the main outcome "accuracy of naming" in language assessment. No heterogeneity was observed (I (2) = 0%). More multicenter RCTs with larger populations and homogenous intervention protocols are required to confirm these and the longer-term effects

Long-Lasting Enhancement of Visual Perception with Repetitive Noninvasive Transcranial Direct Current Stimulation

Understanding processes performed by an intact visual cortex as the basis for developing methods that enhance or restore visual perception is of great interest to both researchers and medical practitioners. Here, we explore whether contrast sensitivity, a main function of the primary visual cortex (V1), can be improved in healthy subjects by repetitive, noninvasive anodal transcranial direct current stimulation (tDCS). Contrast perception was measured via threshold perimetry directly before and after intervention (tDCS or sham stimulation) on each day over 5 consecutive days (24 subjects, double- blind study). tDCS improved contrast sensitivity from the second day onwards, with significant effects lasting 24 h. After the last stimulation on day 5, the anodal group showed a significantly greater improvement in contrast perception than the sham group (23 vs. 5%). We found significant long-term effects in only the central 2–4° of the visual field 4 weeks after the last stimulation. We suspect a combination of two factors contributes to these lasting effects. First, the V1 area that represents the central retina was located closer to the polarization electrode, resulting in higher current density. Second, the central visual field is represented by a larger cortical area relative to the peripheral visual field (cortical magnification). This is the first study showing that tDCS over V1 enhances contrast perception in healthy subjects for several weeks. This study contributes to the investigation of the causal relationship between the external modulation of neuronal membrane potential and behavior (in our case, visual perception). Because the vast majority of human studies only show temporary effects after single tDCS sessions targeting the visual system, our study underpins the potential for lasting effects of repetitive tDCS-induced modulation of neuronal excitability

Long-Term Effects of Serial Anodal tDCS on Motion Perception in Subjects with Occipital Stroke Measured in the Unaffected Visual Hemifield

Transcranial direct current stimulation (tDCS) is a novel neuromodulatory tool that has seen early transition to clinical trials, although the high variability of these findings necessitates further studies in clincally-relevant populations. The majority of evidence into effects of repeated tDCS is based on research in the human motor system, but it is unclear whether the long-term effects of serial tDCS are motor-specific or transferable to other brain areas. This study aimed to examine whether serial anodal tDCS over the visual cortex can exogenously induce long-term neuroplastic changes in the visual cortex. However, when the visual cortex is affected by a cortical lesion, up-regulated endogenous neuroplastic adaptation processes may alter the susceptibility to tDCS. To this end, motion perception was investigated in the unaffected hemifield of subjects with unilateral visual cortex lesions. Twelve subjects with occipital ischaemic lesions participated in a within-subject, sham-controlled, double-blind study. MRI-registered sham or anodal tDCS (1.5 mA, 20 minutes) was applied on five consecutive days over the visual cortex. Motion perception was tested before and after stimulation sessions and at 14- and 28-day follow-up. After a 16-day interval an identical study block with the other stimulation condition (anodal or sham tDCS) followed. Serial anodal tDCS over the visual cortex resulted in an improvement in motion perception, a function attributed to MT/V5. This effect was still measurable at 14- and 28-day follow-up measurements. Thus, this may represent evidence for long-term tDCS-induced plasticity and has implications for the design of studies examining the time course of tDCS effects in both the visual and motor systems

Independent external validation of a stroke recurrence score in patients with embolic stroke of undetermined source

Abstract Background Embolic stroke of undetermined source (ESUS) accounts for a substantial proportion of ischaemic strokes. A stroke recurrence score has been shown to predict the risk of recurrent stroke in patients with ESUS based on a combination of clinical and imaging features. This study aimed to externally validate the performance of the ESUS recurrence score using data from a randomized controlled trial. Methods The validation dataset consisted of eligible stroke patients with available magnetic resonance imaging (MRI) data enrolled in the PreDAFIS sub-study of the MonDAFIS study. The score was calculated using three variables: age (1 point per decade after 35 years), presence of white matter hyperintensities (2 points), and multiterritorial ischaemic stroke (3 points). Patients were assigned to risk groups as described in the original publication. The model was evaluated using standard discrimination and calibration methods. Results Of the 1054 patients, 241 (22.9%) were classified as ESUS. Owing to insufficient MRI quality, three patients were excluded, leaving 238 patients (median age 65.5 years [IQR 20.75], 39% female) for analysis. Of these, 30 (13%) patients experienced recurrent ischaemic stroke or transient ischemic attack (TIA) during a follow-up period of 383 patient-years, corresponding to an incidence rate of 7.8 per 100 patient-years (95% CI 5.3–11.2). Patients with an ESUS recurrence score value of ≥ 7 had a 2.46 (hazard ratio (HR), 95% CI 1.02–5.93) times higher risk of stroke recurrence than patients with a score of 0–4. The cumulative probability of stroke recurrence in the low-(0–4), intermediate-(5–6), and high-risk group (≥ 7) was 9%, 13%, and 23%, respectively (log-rank test, χ2 = 4.2, p = 0.1). Conclusions This external validation of a published scoring system supports a threshold of ≥ 7 for identifying ESUS patients at high-risk of stroke recurrence. However, further adjustments may be required to improve the model’s performance in independent cohorts. The use of risk scores may be helpful in guiding extended diagnostics and further trials on secondary prevention in patients with ESUS. Trial registration: Clinical Trials, NCT02204267. Registered 30 July 2014, https://clinicaltrials.gov/ct2/show/NCT02204267

Dynamic Spatial Coding within the Dorsal Frontoparietal Network during a Visual Search Task

To what extent are the left and right visual hemifields spatially coded in the dorsal frontoparietal attention network? In many experiments with neglect patients, the left hemisphere shows a contralateral hemifield preference, whereas the right hemisphere represents both hemifields. This pattern of spatial coding is often used to explain the right-hemispheric dominance of lesions causing hemispatial neglect. However, pathophysiological mechanisms of hemispatial neglect are controversial because recent experiments on healthy subjects produced conflicting results regarding the spatial coding of visual hemifields. We used an fMRI paradigm that allowed us to distinguish two attentional subprocesses during a visual search task. Either within the left or right hemifield subjects first attended to stationary locations (spatial orienting) and then shifted their attentional focus to search for a target line. Dynamic changes in spatial coding of the left and right hemifields were observed within subregions of the dorsal front-parietal network: During stationary spatial orienting, we found the well-known spatial pattern described above, with a bilateral hemifield representation in the right hemisphere and a contralateral preference in the left hemisphere. However, during search, the right hemisphere had a contralateral preference and the left hemisphere equally represented both hemifields. This finding leads to novel perspectives regarding models of visuospatial attention and hemispatial neglect

Dynamic Spatial Coding within the Dorsal Frontoparietal Network during a Visual Search Task

To what extent are the left and right visual hemifields spatially coded in the dorsal frontoparietal attention network? In many experiments with neglect patients, the left hemisphere shows a contralateral hemifield preference, whereas the right hemisphere represents both hemifields. This pattern of spatial coding is often used to explain the right-hemispheric dominance of lesions causing hemispatial neglect. However, pathophysiological mechanisms of hemispatial neglect are controversial because recent experiments on healthy subjects produced conflicting results regarding the spatial coding of visual hemifields. We used an fMRI paradigm that allowed us to distinguish two attentional subprocesses during a visual search task. Either within the left or right hemifield subjects first attended to stationary locations (spatial orienting) and then shifted their attentional focus to search for a target line. Dynamic changes in spatial coding of the left and right hemifields were observed within subregions of the dorsal front-parietal network: During stationary spatial orienting, we found the wellknown spatial pattern described above, with a bilateral hemifield representation in the right hemisphere and a contralateral preference in the left hemisphere. However, during search, the right hemisphere had a contralateral preference and the left hemisphere equally represented both hemifields. This finding leads to novel perspectives regarding models of visuospatia

Contralateral preference of activated voxels during easy and difficult search conditions.

<p>Contralateral preference visualized by t-tests for all voxels activated by easy search and difficult search conditions (p<0.005, RFX, cluster threshold: 50 mm²). The color convention and the significance level for hemifield preference are described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0003167#pone-0003167-g002" target="_blank">Fig. 2</a>. (a) Histograms with t-values for all activated voxels within predefined ROIs of the dorsal FPN. The range of t-values represented by each bar is 1.13. The significance level (p<0.05) for contralateral preference to the left (−) or right (+) is indicated by black lines on the x-axis of each histogram. As in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0003167#pone-0003167-g002" target="_blank">Figure 2</a>, the percentage of voxels with a significant contralateral preference for the left or right hemifield is given on the appropriate side of the histograms. (b) Dorsal posterior view of the flattened left and right hemisphere with representation of t-values on the surface. (c) Histograms with t-values for all activated voxels within control ROIs MC (motor cortex) and VO (visual occipital). T: mean t-value of activated voxels; STD: standard deviation of t-values; Yellow dotted lines: predefined anatomical ROIs.</p