Cross-species real-time detection of trends in pupil size fluctuation.

Pupillometry is a popular method because pupil size is easily measured and sensitive to central neural activity linked to behavior, cognition, emotion, and perception. Currently, there is no method for online monitoring phases of pupil size fluctuation. We introduce rtPupilPhase-an open-source software that automatically detects trends in pupil size in real time.

Visual imagery vividness correlates with afterimage conscious perception.

Afterimages are illusory, visual conscious perceptions. A widely accepted theory is that afterimages are caused by retinal signaling that continues after the physical disappearance of a light stimulus. However, afterimages have been reported without preceding visual, sensory stimulation (e.

In-Scanner Thoughts shape Resting-state Functional Connectivity: how participants "rest" matters.

Resting-state fMRI (rs-fMRI) scans-namely those lacking experimentally-controlled stimuli or cognitive demands-are often used to identify aberrant patterns of functional connectivity (FC) in clinical populations. To minimize interpretational uncertainty, researchers control for across-cohort disparities in age, gender, co-morbidities, and head motion. Yet, studies rarely, if ever, consider the possibility that systematic differences in inner experience (i.

A Unifying Model for Discordant and Concordant Results in Human Neuroimaging Studies of Facial Viewpoint Selectivity.

Recognizing faces regardless of their viewpoint is critical for social interactions. Traditional theories hold that view-selective early visual representations gradually become tolerant to viewpoint changes along the ventral visual hierarchy. Newer theories, based on single-neuron monkey electrophysiological recordings, suggest a three-stage architecture including an intermediate face-selective patch abruptly achieving invariance to mirror-symmetric face views.

Cross-species real time detection of trends in pupil size fluctuation.

Pupillometry is a popular method because pupil size is easily measured, sensitive to central neural activity, and associated with behavior, cognition, emotion, and perception. Currently, there is no method for online monitoring phases of pupil size fluctuation. We introduce - an open source software that automatically detects trends in pupil size in real time, enabling novel implementations of real time pupillometry towards achieving numerous research and translational goals.

Visual imagery vividness correlates with afterimage conscious perception.

Afterimages are illusory, visual conscious perceptions. A widely accepted theory is that afterimages are caused by retinal signaling that continues after the physical disappearance of a light stimulus. However, afterimages have been reported without preceding visual, sensory stimulation (e.

Whole-brain multivariate hemodynamic deconvolution for functional MRI with stability selection.

Conventionally, analysis of functional MRI (fMRI) data relies on available information about the experimental paradigm to establish hypothesized models of brain activity. However, this information can be inaccurate, incomplete or unavailable in multiple scenarios such as resting-state, naturalistic paradigms or clinical conditions. In these cases, blind estimates of neuronal-related activity can be obtained with paradigm-free analysis methods such as hemodynamic deconvolution.

Manifold learning for fMRI time-varying functional connectivity.

Whole-brain functional connectivity () measured with functional MRI (fMRI) evolves over time in meaningful ways at temporal scales going from years (e.g., development) to seconds [e.

Cortex-wide neural dynamics predict behavioral states and provide a neural basis for resting-state dynamic functional connectivity.

Although resting-state functional magnetic resonance imaging (fMRI) studies have observed dynamically changing brain-wide networks of correlated activity, fMRI's dependence on hemodynamic signals makes results challenging to interpret. Meanwhile, emerging techniques for real-time recording of large populations of neurons have revealed compelling fluctuations in neuronal activity across the brain that are obscured by traditional trial averaging. To reconcile these observations, we use wide-field optical mapping to simultaneously record pan-cortical neuronal and hemodynamic activity in awake, spontaneously behaving mice.

Highlight results, don't hide them: Enhance interpretation, reduce biases and improve reproducibility.

Most neuroimaging studies display results that represent only a tiny fraction of the collected data. While it is conventional to present "only the significant results" to the reader, here we suggest that this practice has several negative consequences for both reproducibility and understanding. This practice hides away most of the results of the dataset and leads to problems of selection bias and irreproducibility, both of which have been recognized as major issues in neuroimaging studies recently.

The art and science of using quality control to understand and improve fMRI data.

Designing and executing a good quality control (QC) process is vital to robust and reproducible science and is often taught through hands on training. As FMRI research trends toward studies with larger sample sizes and highly automated processing pipelines, the people who analyze data are often distinct from those who collect and preprocess the data. While there are good reasons for this trend, it also means that important information about how data were acquired, and their quality, may be missed by those working at later stages of these workflows.

A unifying model for discordant and concordant results in human neuroimaging studies of facial viewpoint selectivity.

Our ability to recognize faces regardless of viewpoint is a key property of the primate visual system. Traditional theories hold that facial viewpoint is represented by view-selective mechanisms at early visual processing stages and that representations become increasingly tolerant to viewpoint changes in higher-level visual areas. Newer theories, based on single-neuron monkey electrophysiological recordings, suggest an additional intermediate processing stage invariant to mirror-symmetric face views.

Manifold Learning for fMRI time-varying FC.

Whole-brain functional connectivity ( ) measured with functional MRI (fMRI) evolve over time in meaningful ways at temporal scales going from years (e.g., development) to seconds (e.

Distribution of M1 and M2 macrophages in cerebral granulomas caused by Encephalitozoon cuniculi.

Encephalitozoon cuniculi spores cause severe granulomatous inflammation in the brain where mononuclear cells and macrophages infiltrate. Here, we orally infected New Zealand white rabbits with 1 × 10E. cuniculi viable spores to study the recruitment and localization of macrophages in brain granulomas.

The challenge of BWAs: Unknown unknowns in feature space and variance.

The recent paper by Marek et al. has shown that, to capture brain-wide associations using fMRI and MRI measures, thousands of individuals are required. These results can be potentially misunderstood to imply that MRI or fMRI lack sensitivity or specificity.

Traveling and standing waves in the brain.

Studying the natural wanderings of the living brain is extremely challenging. Bolt et al. describe a new framework to consider the brain’s intrinsic activity based on the geophysical concepts of standing and traveling waves.

Ultra-slow fMRI fluctuations in the fourth ventricle as a marker of drowsiness.

Wakefulness levels modulate estimates of functional connectivity (FC), and, if unaccounted for, can become a substantial confound in resting-state fMRI. Unfortunately, wakefulness is rarely monitored due to the need for additional concurrent recordings (e.g.

How to Interpret Resting-State fMRI: Ask Your Participants.

Resting-state fMRI (rsfMRI) reveals brain dynamics in a task-unconstrained environment as subjects let their minds wander freely. Consequently, resting subjects navigate a rich space of cognitive and perceptual states (i.e.

Theta-burst TMS to the posterior superior temporal sulcus decreases resting-state fMRI connectivity across the face processing network.

Humans process faces by using a network of face-selective regions distributed across the brain. Neuropsychological patient studies demonstrate that focal damage to nodes in this network can impair face recognition, but such patients are rare. We approximated the effects of damage to the face network in neurologically normal human participants by using theta burst transcranial magnetic stimulation (TBS).

Language lateralization from task-based and resting state functional MRI in patients with epilepsy.

We compared resting state (RS) functional connectivity and task-based fMRI to lateralize language dominance in 30 epilepsy patients (mean age = 33; SD = 11; 12 female), a measure used for presurgical planning. Language laterality index (LI) was calculated from task fMRI in frontal, temporal, and frontal + temporal regional masks using LI bootstrap method from SPM12. RS language LI was assessed using two novel methods of calculating RS language LI from bilateral Broca's area seed based connectivity maps across regional masks and multiple thresholds (p < .

Imaging the spontaneous flow of thought: Distinct periods of cognition contribute to dynamic functional connectivity during rest.

Brain functional connectivity (FC) changes have been measured across seconds using fMRI. This is true for both rest and task scenarios. Moreover, it is well accepted that task engagement alters FC, and that dynamic estimates of FC during and before task events can help predict their nature and performance.

A deconvolution algorithm for multi-echo functional MRI: Multi-echo Sparse Paradigm Free Mapping.

This work introduces a novel algorithm for deconvolution of the BOLD signal in multi-echo fMRI data: Multi-echo Sparse Paradigm Free Mapping (ME-SPFM). Assuming a linear dependence of the BOLD percent signal change on the echo time (TE) and using sparsity-promoting regularized least squares estimation, ME-SPFM yields voxelwise time-varying estimates of the changes in the apparent transverse relaxation (ΔR) without prior knowledge of the timings of individual BOLD events. Our results in multi-echo fMRI data collected during a multi-task event-related paradigm at 3 Tesla demonstrate that the maps of R changes obtained with ME-SPFM at the times of the stimulus trials show high spatial and temporal concordance with the activation maps and BOLD signals obtained with standard model-based analysis.

Visual temporal frequency preference shows a distinct cortical architecture using fMRI.

Studies of visual temporal frequency preference typically examine frequencies under 20 Hz and measure local activity to evaluate the sensitivity of different cortical areas to variations in temporal frequencies. Most of these studies have not attempted to map preferred temporal frequency within and across visual areas, nor have they explored in detail, stimuli at gamma frequency, which recent research suggests may have potential clinical utility. In this study, we address this gap by using functional magnetic resonance imaging (fMRI) to measure response to flickering visual stimuli varying in frequency from 1 to 40 Hz.