Online self-evaluation of fMRI-based neurofeedback performance.

This study explores the subjective evaluation of supplementary motor area (SMA) regulation performance in a real-time functional magnetic resonance imaging neurofeedback (fMRI-NF) task. In fMRI-NF, people learn how to self-regulate their brain activity by performing mental actions to achieve a certain target level (TL) of blood-oxygen-level-dependent (BOLD) activation. Here, we studied two types of self-evaluation: performance predictions and perceived confidence in the prediction judgement.

Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation.

Neurofeedback (NF) is endogenous neuromodulation of circumscribed brain circuitry. While its use of real-time brain activity in a closed-loop system is similar to brain-computer interfaces, instead of controlling an external device like the latter, the goal of NF is to change a targeted brain function. In this special issue on NF, we present current and future methods for extracting and manipulating neural function, how these methods may reveal new insights about brain function, applications, and rarely discussed ethical considerations of guiding and interpreting the brain activity of others.

Semantic fMRI neurofeedback of emotions: from basic principles to clinical applications.

During fMRI neurofeedback participants learn to self-regulate activity in relevant brain areas and networks based on ongoing feedback extracted from measured responses in those regions. This closed-loop approach has been successfully applied to reduce symptoms in mood disorders such as depression by showing participants a thermometer-like display indicating the strength of activity in emotion-related brain areas. The hitherto employed conventional neurofeedback is, however, 'blind' with respect to emotional content, i.

Laminar CBV and BOLD response-characteristics over time and space in the human primary somatosensory cortex at 7T.

Uncovering the cortical representation of the body has been at the core of human brain mapping for decades, with special attention given to the digits. In the last decade, advances in functional magnetic resonance imaging (fMRI) technologies have opened the possibility of noninvasively unraveling the 3rd dimension of digit representations in humans along cortical layers. In laminar fMRI it is common to combine the use of the highly sensitive blood oxygen level dependent (BOLD) contrast with cerebral blood volume sensitive measurements, like vascular space occupancy (VASO), that are more specific to the underlying neuronal populations.

Convolutional neural networks develop major organizational principles of early visual cortex when enhanced with retinal sampling.

Primate visual cortex exhibits key organizational principles: cortical magnification, eccentricity-dependent receptive field size and spatial frequency tuning as well as radial bias. We provide compelling evidence that these principles arise from the interplay of the non-uniform distribution of retinal ganglion cells, and a quasi-uniform convergence rate from the retina to the cortex. We show that convolutional neural networks outfitted with a retinal sampling layer, which resamples images according to retinal ganglion cell density, develop these organizational principles.

An integrative, multiscale view on neural theories of consciousness.

How is conscious experience related to material brain processes? A variety of theories aiming to answer this age-old question have emerged from the recent surge in consciousness research, and some are now hotly debated. Although most researchers have so far focused on the development and validation of their preferred theory in relative isolation, this article, written by a group of scientists representing different theories, takes an alternative approach. Noting that various theories often try to explain different aspects or mechanistic levels of consciousness, we argue that the theories do not necessarily contradict each other.

Characterisation of laminar and vascular spatiotemporal dynamics of CBV and BOLD signals using VASO and ME-GRE at 7T in humans.

Interpretation of cortical laminar functional magnetic resonance imaging (fMRI) activity requires detailed knowledge of the spatiotemporal haemodynamic response across vascular compartments due to the well-known vascular biases (e.g. the draining veins).

AngoraPy: A Python toolkit for modeling anthropomorphic goal-driven sensorimotor systems.

Goal-driven deep learning increasingly supplements classical modeling approaches in computational neuroscience. The strength of deep neural networks as models of the brain lies in their ability to autonomously learn the connectivity required to solve complex and ecologically valid tasks, obviating the need for hand-engineered or hypothesis-driven connectivity patterns. Consequently, goal-driven models can generate hypotheses about the neurocomputations underlying cortical processing that are grounded in macro- and mesoscopic anatomical properties of the network's biological counterpart.

Early visual experience refines the retinotopic organization within and across visual cortical regions.

Early visual areas are retinotopically organized in human and non-human primates. Population receptive field (pRF) size increases with eccentricity and from lower- to higher-level visual areas. Furthermore, the cortical magnification factor (CMF), a measure of how much cortical space is devoted to each degree of visual angle, is typically larger for foveal as opposed to peripheral regions of the visual field.

No threat: Emotion regulation neurofeedback for police special forces recruits.

Police officers of the Special Forces are confronted with highly demanding situations in terms of stress, high tension and threats to their lives. Their tasks are specifically high-risk operations, such as arrests of armed suspects and anti-terror interventions. Improving the emotion regulation skills of police officers might be a vital investment, supporting them to stay calm and focused.

Layer-fMRI VASO with short stimuli and event-related designs at 7 T.

Layers and columns are the dominant processing units in the human (neo)cortex at the mesoscopic scale. While the blood oxygenation dependent (BOLD) signal has a high detection sensitivity, it is biased towards unwanted signals from large draining veins at the cortical surface. The additional fMRI contrast of vascular space occupancy (VASO) has the potential to augment the neuroscientific interpretability of layer-fMRI results by means of capturing complementary information of locally specific changes in cerebral blood volume (CBV).

Imaging the columnar functional organization of human area MT+ to axis-of-motion stimuli using VASO at 7 Tesla.

Cortical columns of direction-selective neurons in the motion sensitive area (MT) have been successfully established as a microscopic feature of the neocortex in animals. The same property has been investigated at mesoscale (<1 mm) in the homologous brain area (hMT+, V5) in living humans by using ultra-high field functional magnetic resonance imaging (fMRI). Despite the reproducibility of the selective response to axis-of-motion stimuli, clear quantitative evidence for the columnar organization of hMT+ is still lacking.

Talking with hands and feet: Selective somatosensory attention and fMRI enable robust and convenient brain-based communication.

In brain-based communication, voluntarily modulated brain signals (instead of motor output) are utilized to interact with the outside world. The possibility to circumvent the motor system constitutes an important alternative option for severely paralyzed. Most communication brain-computer interface (BCI) paradigms require intact visual capabilities and impose a high cognitive load, but for some patients, these requirements are not given.

Ultra-High Field Imaging of Human Visual Cognition.

Functional magnetic resonance imaging (fMRI), the key methodology for mapping the functions of the human brain in a noninvasive manner, is limited by low temporal and spatial resolution. Recent advances in ultra-high field (UHF) fMRI provide a mesoscopic (i.e.

Magnetic resonance imaging at 9.4 T: the Maastricht journey.

The 9.4 T scanner in Maastricht is a whole-body magnet with head gradients and parallel RF transmit capability. At the time of the design, it was conceptualized to be one of the best fMRI scanners in the world, but it has also been used for anatomical and diffusion imaging.

A vision of 14 T MR for fundamental and clinical science.

Objective: We outline our vision for a 14 Tesla MR system. This comprises a novel whole-body magnet design utilizing high temperature superconductor; a console and associated electronic equipment; an optimized radiofrequency coil setup for proton measurement in the brain, which also has a local shim capability; and a high-performance gradient set.

Research Fields: The 14 Tesla system can be considered a 'mesocope': a device capable of measuring on biologically relevant scales.

Mesoscopic in vivo human T dataset acquired using quantitative MRI at 7 Tesla.

Mesoscopic (0.1-0.5 mm) interrogation of the living human brain is critical for advancing neuroscience and bridging the resolution gap with animal models.

Improved correspondence of fMRI visual field localizer data after cortex-based macroanatomical alignment.

Studying the visual system with fMRI often requires using localizer paradigms to define regions of interest (ROIs). However, the considerable interindividual variability of the cerebral cortex represents a crucial confound for group-level analyses. Cortex-based alignment (CBA) techniques reliably reduce interindividual macroanatomical variability.

Self-modulation of motor cortex activity after stroke: a randomized controlled trial.

Real-time functional MRI neurofeedback allows individuals to self-modulate their ongoing brain activity. This may be a useful tool in clinical disorders that are associated with altered brain activity patterns. Motor impairment after stroke has previously been associated with decreased laterality of motor cortex activity.

Semantic fMRI neurofeedback: a multi-subject study at 3 tesla.

Real-time functional magnetic resonance imaging neurofeedback (rt-fMRI-NF) is a non-invasive procedure allowing the self-regulation of brain functions via enhanced self-control of fMRI based neural activation. In semantic rt-fMRI-NF, an estimated relation between multivariate fMRI activation patterns and abstract mental states is exploited for a multi-dimensional feedback stimulus via real-time representational similarity analysis (rt-RSA). Here, we assessed the performances of this framework in a multi-subject multi-session study on a 3 T MRI clinical scanner.

Linking Brain Structure, Activity, and Cognitive Function through Computation.

Understanding the human brain is a "Grand Challenge" for 21st century research. Computational approaches enable large and complex datasets to be addressed efficiently, supported by artificial neural networks, modeling and simulation. Dynamic generative multiscale models, which enable the investigation of causation across scales and are guided by principles and theories of brain function, are instrumental for linking brain structure and function.

See, Hear, or Feel - to Speak: A Versatile Multiple-Choice Functional Near-Infrared Spectroscopy-Brain-Computer Interface Feasible With Visual, Auditory, or Tactile Instructions.

Severely motor-disabled patients, such as those suffering from the so-called "locked-in" syndrome, cannot communicate naturally. They may benefit from brain-computer interfaces (BCIs) exploiting brain signals for communication and therewith circumventing the muscular system. One BCI technique that has gained attention recently is functional near-infrared spectroscopy (fNIRS).