The existence of facial aftereffects suggests that shape-selective mechanisms at the higher stages visual object coding — similarly to early processing low-level features are adaptively recalibrated. Our goal was uncover ERP correlates adaptation and test whether it is also involved in human body parts. We found prolonged female hands faces biased judgements about subsequently presented hand stimuli: they were perceived more masculine than control conditions. showed these size orientation...

Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, application convolutional networks has been proposed only very recently and remained largely unexplored. In this paper we describe a neural architecture for functional connectome classification called connectome-convolutional (CCNN). Our results on simulated datasets publicly available dataset amnestic mild cognitive...

Previously several functional magnetic resonance imaging (fMRI) studies point toward the role of perceptual expectations in determining adaptation or repetition suppression (RS) humans. These showed that probability repetitions faces within a block influences magnitude face-related areas human brain (Summerfield et al., 2008). However, current macaque single-cell/local field potential (LFP) recording study using objects as stimuli found no evidence for modulation neural response by inferior...

Traditional resting-state network concept is based on calculating linear dependence of spontaneous low frequency fluctuations the BOLD signals different brain areas, which assumes temporally stable zero-lag synchrony across regions. However, growing amount experimental findings suggest that functional connectivity exhibits dynamic changes and a complex time-lag structure, cannot be captured by static correlation analysis. Here we propose new approach applying Dynamic Time Warping distance to...

Abstract Magnetic Resonance Imaging (MRI) provides a unique opportunity to investigate neural changes in healthy and clinical conditions. Its large inherent susceptibility motion, however, often confounds the measurement. Approaches assessing, correcting, or preventing motion corruption of MRI measurements are under active development, such efforts can greatly benefit from carefully controlled datasets. We present dataset structural brain images collected 148 adults which includes both...

THE cellular, and subcellular distribution of the mGluR5a metabotropic glutamate receptor was studied in spinal cord rat using an antibody raised against a mGluR5a-specific carboxy-terminal peptide. Strong mGluR5a-immunoreactivity (mGluR5a-ir) found laminae I-II dorsal horn, which gradually decreased towards deeper layers. At electron microscopical level, mGluR5a-ir present exclusively neuronal somata, dendrites. Immunometal labelling revealed that is concentrated at periphery postsynaptic...

It has been proposed that perceptual decision making involves a task-difficulty component, which detects uncertainty and guides allocation of attentional resources. is thought to take place immediately after the early extraction sensory information specifically reflected in positive component event related potentials, peaking at ∼220 ms stimulus onset. However, previous research, neural processes associated with monitoring overall task difficulty were confounded by those increased processing...

Head motion artifacts in magnetic resonance imaging (MRI) are an important confounding factor concerning brain research as well clinical practice. For this reason, several machine learning-based methods have been developed for the automatic quality control of structural MRI scans. Deep learning offers a promising solution to problem, however, given its data-hungry nature and scarcity expert-annotated datasets, advantage over traditional identifying motion-corrupted scans is yet be...

While there is strong evidence for the central role of human MT+/V5 in motion processing, its involvement adaptation still subject debate. We used transcranial direct current stimulation (tDCS) to test whether part neural network involved long-term adaptation-induced after-effect humans. It was found that both cathodal and anodal over resulted a significant reduction perceived duration, but had no effect on performance luminance-change-detection task determine attentional load during...

The equivalent notions of neuroanatomy and the cellular neural network (CNN) model are discussed with a view toward studying visual system. Various mainly subcortical phenomena studied simple effects like directional sensitivity length tuning modeled. A more accurate retina has been developed, taking into account some amacrine cells. It is shown that standard errors occurring in models retinal illusions can be eliminated by using including delays. Lateral geniculate nucleus (LGN) without...

Increased fMRI food cue reactivity in obesity, i.e. higher responses to high- vs. low-calorie images, is a promising marker of the dysregulated brain reward system underlying enhanced susceptibility obesogenic environmental cues. Recently, it has also been shown that weight loss interventions might affect and there close association between alteration outcome intervention. Here we tested whether could be used as diet-induced early changes neural processing striatum are predictive To this end...

Abstract Pre‐embedding immunogold histochemistry was combined with Phaseolus vulgaris leucoagglutinin anterograde tract tracing in order to analyse the relationship between subcellular localization of mGluR1a metabotropic glutamate receptors and distribution corticothalamic synapses dorsal lateral geniculate nucleus (dLGN) posterior (LP) rat. The injection tracer into area 17 labelled two types terminals: (i) small boutons constituting majority fibres which form asymmetrical both dLGN LP;...

Reading is a unique human ability that plays pivotal role in the development and functioning of our modern society. However, its neural basis remains poorly understood since previous research was focused on reading words with fixed gaze. Here we developed methodological framework for single-trial analysis fixation onset-related EEG activity (FOREA) enabled us to investigate visual information processing during natural reading. To reveal effect skills orthographic reading, measured how...

We investigated the representation of objects' position at higher, shape-selective stages visual processing by testing position-specificity behavioural and neural effects facial adaptation. Here, we show that after-effects evoked adaptation to both upright upside-down faces are significantly larger when adaptor test presented on same retinal than they displayed in different hemifields. Our event-related potential recordings revealed measured amplitude N170 component over hemisphere was...

Slow-wave sleep (SWS) is essential for restorative neural processes, and its decline associated with both healthy pathological ageing. Building on previous rodent research, this longitudinal study identified a significant association between nucleus accumbens (NAcc) volume SWS duration in cognitively unimpaired older adults, whilst no link was observed NAcc N2 or rapid eye movement (REM) percentage. Our findings support the involvement of ageing-related modulation thus suggest as potential...

Deep learning is gaining importance in the prediction of cognitive states and brain pathology based on neuroimaging data. Including multiple hidden layers artificial neural networks enables unprecedented predictive power; however, proper training deep requires thousands exemplars. Collecting this amount data not feasible typical experiments. A handy solution to problem, which has largely fallen outside scope applications neuroimaging, repurpose that have already been trained large datasets...

In recent years, deep learning (DL) has become more widespread in the fields of cognitive and clinical neuroimaging. Using neural network models to process neuroimaging data is an efficient method classify brain disorders identify individuals who are at increased risk age-related decline neurodegenerative disease. Here we investigated, for first time, whether structural imaging DL can be used predicting a physical trait that significant relevance—the body mass index (BMI) individual. We show...

Abstract Due to their robustness and speed, recently developed deep learning-based methods have the potential provide a faster hence more scalable alternative conventional neuroimaging analysis pipelines in terms of whole-brain segmentation based on magnetic resonance (MR) images. These were also shown higher test–retest reliability, raising possibility that they could exhibit superior head motion tolerance. We investigated this by comparing effect motion-induced artifacts structural MR...

Abstract Cortical feedback is the largest extraretinal projection to lateral geniculate nucleus. This input thought modulate transfer of visual information in a state‐dependent manner. The quantitative distribution and synaptology axon terminals arising from different cortical areas still an unsolved question. To address this problem, synaptic termination pattern corticogeniculate axons 17 18 entering nucleus cat was examined. Phaseolus vulgaris leucoagglutinin anterograde tract tracing...