Impaired Face Discrimination in Acquired Prosopagnosia Is Associated with Abnormal Response to Individual Faces in the Right Middle Fusiform Gyrus

The middle fusiform gyrus (MFG) and the inferior occipital gyrus (IOG) are activated by both detection and identification of faces. Paradoxically, patients with acquired prosopagnosia following lesions to either of these regions in the right hemisphere cannot identify faces, but can still detect faces. Here we acquired functional magnetic resonance imaging (fMRI) data during face processing in a patient presenting a specific deficit in individual face recognition, following lesions encompassing the right IOG. Using an adaptation paradigm we show that the fMRI signal in the rMFG of the patient, while being larger in response to faces as compared to objects, does not differ between conditions presenting identical and distinct faces, in contrast to the larger response to distinct faces observed in controls. These results suggest that individual discrimination of faces critically depends on the integrity of both the rMFG and the rIOG, which may interact through re-entrant cortical connections in the normal brai

Time-resolved searchlight analysis of imagined visual motion using 7T ultra-high field fMRI: Data on interindividual differences

AbstractInterindividual differences play a crucial role in research on mental imagery. The inherently private nature of imagery does not allow for the same experimental control that is possible in perception research. Even when there are precise instructions subjects will differ in their particular imagery strategy and, hence, show different brain activations. Here, we show results of a time-resolved searchlight analysis for 12 individual subjects who perform a visual motion imagery task. The data show the spatial and temporal extent of brain areas and time windows that allow for a successful decoding of the direction of imagined motion out of four options. Accuracy maps for six different time windows are shown for every individual subject and are made freely available on NeuroVault. These data accompany the findings in the publication “Decoding the direction of imagined visual motion using 7T ultra-high field fMRI” (Emmerling et al., 2016) [1]

Control freaks: Towards optimal selection of control conditions for fMRI neurofeedback studies

fMRI Neurofeedback research employs many different control conditions. Currently, there is no consensus as to which control condition is best, and the answer depends on what aspects of the neurofeedback-training design one is trying to control for. These aspects can range from determining whether participants can learn to control brain activity via neurofeedback to determining whether there are clinically significant effects of the neurofeedback intervention. Lack of consensus over criteria for control conditions has hampered the design and interpretation of studies employing neurofeedback protocols. This paper presents an overview of the most commonly employed control conditions currently used in neurofeedback studies and discusses their advantages and disadvantages. Control conditions covered include no control, treatment-as-usual, bidirectional-regulation control, feedback of an alternative brain signal, sham feedback, and mental-rehearsal control. We conclude that the selection of the control condition(s) should be determined by the specific research goal of the study and best procedures that effectively control for relevant confounding factor

Real-Time Self-Regulation of Emotion Networks in Patients with Depression

Many patients show no or incomplete responses to current pharmacological or psychological therapies for depression. Here we explored the feasibility of a new brain self-regulation technique that integrates psychological and neurobiological approaches through neurofeedback with functional magnetic resonance imaging (fMRI). In a proof-of-concept study, eight patients with depression learned to upregulate brain areas involved in the generation of positive emotions (such as the ventrolateral prefrontal cortex (VLPFC) and insula) during four neurofeedback sessions. Their clinical symptoms, as assessed with the 17-item Hamilton Rating Scale for Depression (HDRS), improved significantly. A control group that underwent a training procedure with the same cognitive strategies but without neurofeedback did not improve clinically. Randomised blinded clinical trials are now needed to exclude possible placebo effects and to determine whether fMRI-based neurofeedback might become a useful adjunct to current therapies for depression

Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist)

Neurofeedback has begun to attract the attention and scrutiny of the scientific and medical mainstream. Here, neurofeedback researchers present a consensus-derived checklist that aims to improve the reporting and experimental design standards in the field.</p

Selective auditory attention within naturalistic scenes modulates reactivity to speech sounds

Rapid recognition and categorization of sounds are essential for humans and animals alike, both for understanding and reacting to our surroundings and for daily communication and social interaction. For humans, perception of speech sounds is of crucial importance. In real life, this task is complicated by the presence of a multitude of meaningful non-speech sounds. The present behavioural, magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) study was set out to address how attention to speech versus attention to natural non-speech sounds within complex auditory scenes influences cortical processing. The stimuli were superimpositions of spoken words and environmental sounds, with parametric variation of the speech-to-environmental sound intensity ratio. The participants' task was to detect a repetition in either the speech or the environmental sound. We found that specifically when participants attended to speech within the superimposed stimuli, higher speech-to-environmental sound ratios resulted in shorter sustained MEG responses and stronger BOLD fMRI signals especially in the left supratemporal auditory cortex and in improved behavioural performance. No such effects of speech-to-environmental sound ratio were observed when participants attended to the environmental sound part within the exact same stimuli. These findings suggest stronger saliency of speech compared with other meaningful sounds during processing of natural auditory scenes, likely linked to speech-specific top-down and bottom-up mechanisms activated during speech perception that are needed for tracking speech in real-life-like auditory environments.Peer reviewe

Another kind of 'BOLD Response': answering multiple-choice questions via online decoded single-trial brain signals.

The term 'locked-in'syndrome (LIS) describes a medical condition in which persons concerned are severely paralyzed and at the same time fully conscious and awake. The resulting anarthria makes it impossible for these patients to naturally communicate, which results in diagnostic as well as serious practical and ethical problems. Therefore, developing alternative, muscle-independent communication means is of prime importance. Such communication means can be realized via brain-computer interfaces (BCIs) circumventing the muscular system by using brain signals associated with preserved cognitive, sensory, and emotional brain functions. Primarily, BCIs based on electrophysiological measures have been developed and applied with remarkable success. Recently, also blood flow-based neuroimaging methods, such as functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS), have been explored in this context. After reviewing recent literature on the development of especially hemodynamically based BCIs, we introduce a highly reliable and easy-to-apply communication procedure that enables untrained participants to motor-independently and relatively effortlessly answer multiple-choice questions based on intentionally generated single-trial fMRI signals that can be decoded online. Our technique takes advantage of the participants' capability to voluntarily influence certain spatio-temporal aspects of the blood oxygenation level-dependent (BOLD) signal: source location (by using different mental tasks), signal onset and offset. We show that healthy participants are capable of hemodynamically encoding at least four distinct information units on a single-trial level without extensive pretraining and with little effort. Moreover, real-time data analysis based on simple multi-filter correlations allows for automated answer decoding with a high accuracy (94.9%) demonstrating the robustness of the presented method. Following our 'proof of concept', the next step will involve clinical trials with LIS patients, undertaken in close collaboration with their relatives and caretakers in order to elaborate individually tailored communication protocols. As our procedure can be easily transferred to MRI-equipped clinical sites, it may constitute a simple and effective possibility for online detection of residual consciousness and for LIS patients to communicate basic thoughts and needs in case no other alternative communication means are available (yet)--especially in the acute phase of the LIS. Future research may focus on further increasing the efficiency and accuracy of fMRI-based BCIs by implementing sophisticated data analysis methods (e.g., multivariate and independent component analysis) and neurofeedback training techniques. Finally, the presented BCI approach could be transferred to portable fNIRS systems as only this would enable hemodynamically based communication in daily life situations

fMRI neurofeedback facilitates anxiety regulation in females with spider phobia

BACKGROUND: Spider phobics show an exaggerated fear response when encountering spiders. This fear response is aggravated by negative and irrational beliefs about the feared object. Cognitive reappraisal can target these beliefs, and therefore has a fear regulating effect. The presented study investigated if neurofeedback derived from functional magnetic resonance imaging (fMRI) would facilitate anxiety regulation by cognitive reappraisal, using spider phobia as a model of anxiety disorders. Feedback was provided based on activation in left dorsolateral prefrontal cortex and right insula, as indicators of engagement and regulation success, respectively. METHODS: Eighteen female spider phobics participated in a randomized, controlled, single-blinded study. All participants completed a training session in the MRI scanner. Participants assigned to the neurofeedback condition were instructed to shape their regulatory strategy based on the provided feedback. Participants assigned to the control condition were asked to adapt their strategy intuitively. RESULTS: Neurofeedback participants exhibited lower anxiety levels than the control group at the end of the training. In addition, only neurofeedback participants achieved down-regulation of insula activation levels by cognitive reappraisal. Group differences became more pronounced over time, supporting learning as a mechanism behind this effect. Importantly, within the neurofeedback group, achieved changes in insula activation levels during training predicted long-term anxiety reduction. CONCLUSIONS: The conducted study provides first evidence that fMRI neurofeedback has a facilitating effect on anxiety regulation in spider phobia

Automated selection of brain regions for real-time fMRI brain-computer interfaces

Objective. Brain-computer interfaces (BCIs) implemented with real-time functional magnetic resonance imaging (rt-fMRI) use fMRI time-courses from predefined regions of interest (ROIs). To reach best performances, localizer experiments and on-site expert supervision are required for ROI definition. To automate this step, we developed two unsupervised computational techniques based on the general linear model (GLM) and independent component analysis (ICA) of rt-fMRI data, and compared their performances on a communication BCI. Approach. 3 T fMRI data of six volunteers were re-analyzed in simulated real-time. During a localizer run, participants performed three mental tasks following visual cues. During two communication runs, a letter-spelling display guided the subjects to freely encode letters by performing one of the mental tasks with a specific timing. GLM- and ICA-based procedures were used to decode each letter, respectively using compact ROIs and whole-brain distributed spatio-temporal patterns of fMRI activity, automatically defined from subject-specific or group-level maps. Main results. Letter-decoding performances were comparable to supervised methods. In combination with a similarity-based criterion, GLM- and ICA-based approaches successfully decoded more than 80% (average) of the letters. Subject-specific maps yielded optimal performances. Significance. Automated solutions for ROI selection may help accelerating the translation of rt-fMRI BCIs from research to clinical applications

Topographic Somatosensory Imagery for Real-Time fMRI Brain-Computer Interfacing

Real-time functional magnetic resonance imaging (fMRI) is a promising non-invasive method for brain-computer interfaces (BCIs). BCIs translate brain activity into signals that allow communication with the outside world. Visual and motor imagery are often used as information-encoding strategies, but can be challenging if not grounded in recent experience in these modalities, e.g., in patients with locked-in-syndrome (LIS). In contrast, somatosensory imagery might constitute a more suitable information-encoding strategy as the somatosensory function is often very robust. Somatosensory imagery has been shown to activate the somatotopic cortex, but it has been unclear so far whether it can be reliably detected on a single-trial level and successfully classified according to specific somatosensory imagery content. Using ultra-high field 7-T fMRI, we show reliable and high-accuracy single-trial decoding of left-foot (LF) vs. right-hand (RH) somatosensory imagery. Correspondingly, higher decoding accuracies were associated with greater spatial separation of hand and foot decoding-weight patterns in the primary somatosensory cortex (S1). Exploiting these novel neuroscientific insights, we developed—and provide a proof of concept for—basic BCI communication by showing that binary (yes/no) answers encoded by somatosensory imagery can be decoded with high accuracy in simulated real-time (in 7 subjects) as well as in real-time (1 subject). This study demonstrates that body part-specific somatosensory imagery differentially activates somatosensory cortex in a topographically specific manner; evidence which was surprisingly still lacking in the literature. It also offers proof of concept for a novel somatosensory imagery-based fMRI-BCI control strategy, with particularly high potential for visually and motor-impaired patients. The strategy could also be transferred to lower MRI field strengths and to mobile functional near-infrared spectroscopy. Finally, given that communication BCIs provide the BCI user with a form of feedback based on their brain signals and can thus be considered as a specific form of neurofeedback, and that repeated use of a BCI has been shown to enhance underlying representations, we expect that the current BCI could also offer an interesting new approach for somatosensory rehabilitation training in the context of stroke and phantom limb pain