Two decades ago, the introduction of functional near-infrared spectroscopy (fNIRS) into the field of neuroscience created new opportunities for investigating neural processes within the human ...cerebral cortex. Since then, fNIRS has been increasingly used to conduct functional activation studies in different neuropsychiatric disorders, most prominently schizophrenic illnesses, affective disorders and developmental syndromes, such as attention-deficit/hyperactivity disorder as well as normal and pathological aging. This review article provides a comprehensive overview of state of the art fNIRS research in psychiatry covering a wide range of applications, including studies on the phenomenological characterization of psychiatric disorders, descriptions of life-time developmental aspects, treatment effects, and genetic influences on neuroimaging data. Finally, methodological shortcomings as well as current research perspectives and promising future applications of fNIRS in psychiatry are discussed. We conclude that fNIRS is a valid addition to the range of neuroscientific methods available to assess neural mechanisms underlying neuropsychiatric disorders. Future research should particularly focus on expanding the presently used activation paradigms and cortical regions of interest, while additionally fostering technical and methodological advances particularly concerning the identification and removal of extracranial influences on fNIRS data as well as systematic artifact correction. Eventually, fNIRS might be a useful tool in practical psychiatric settings involving both diagnostics and the complementary treatment of psychological disorders using, for example, neurofeedback applications.
•We provide a comprehensive review of state of the art fNIRS research in psychiatry.•So far, fNIRS studies in psychiatry have focused on phenomenological descriptions.•Future fNIRS applications concerning diagnostics and treatment are proposed.•Technical advances are still needed, particularly concerning artifact removal.•NIRS is a valid addition to neuroimaging devices used in psychiatric research.
Transcranial direct current stimulation (tDCS) to the dorsolateral prefrontal cortex (dlPFC) can modulate working memory (WM) performance. However, evidence regarding the enhancement of WM training, ...its sustainability and transferability is ambiguous. Since WM functioning appears to be lateralized in respect to stimulus characteristics, this study examined the difference between task-congruent (spatial-right, verbal-left), task-incongruent (spatial-left, verbal-right) and sham tDCS in regards to the efficacy of WM training. In a randomized, sham-controlled experiment, 71 healthy adults trained on a spatial or verbal adaptive n-back task. After a baseline session, anodal or sham tDCS (1 mA) to the right or left dlPFC was applied during the next three training sessions. Sustainability of training gains and near-transfer (verbal or spatial 3-back task) were tested in a fourth training and a follow-up session. Compared to sham stimulation, we found a steeper learning curve when WM training was combined with task-congruent tDCS. This advantage was also present compared to task-incongruent tDCS. Moreover, these effects lasted for up to nine months and transferred to the respective untrained task. These long-lasting, transferable, task-specific effects demonstrate a behaviorally relevant and sustainable facilitation of neuroplastic processes by tDCS that could be harnessed for the treatment of disorders associated with deficient WM.
Functional near-infrared spectroscopy (fNIRS) is an established optical neuroimaging method for measuring functional hemodynamic responses to infer neural activation. However, the impact of ...individual anatomy on the sensitivity of fNIRS measuring hemodynamics within cortical gray matter is still unknown. By means of Monte Carlo simulations and structural MRI of 23 healthy subjects (mean age: 25.0±2.8 years), we characterized the individual distribution of tissue-specific NIR-light absorption underneath 24 prefrontal fNIRS channels. We, thereby, investigated the impact of scalp-cortex distance (SCD), frontal sinus volume as well as sulcal morphology on gray matter volumes (V(gray)) traversed by NIR-light, i.e. anatomy-dependent fNIRS sensitivity. The NIR-light absorption between optodes was distributed describing a rotational ellipsoid with a mean penetration depth of (23.6±0.7) mm considering the deepest 5% of light. Of the detected photon packages scalp and bone absorbed (96.4±9.7)% and V(gray) absorbed (3.1±1.8)% of the energy. The mean V(gray) volume (1.1±0.4) cm3 was negatively correlated (r=-.76) with the SCD and frontal sinus volume (r=-.57) and was reduced by 41.5% in subjects with relatively large compared to small frontal sinus. Head circumference was significantly positively correlated with the mean SCD (r=.46) and the traversed frontal sinus volume (r=.43). Sulcal morphology had no significant impact on V(gray). Our findings suggest to consider individual SCD and frontal sinus volume as anatomical factors impacting fNIRS sensitivity. Head circumference may represent a practical measure to partly control for these sources of error variance.
Neurofeedback (NF) is a form of behavioral therapy used to treat e.g. attention-deficit/hyperactivity disorder (ADHD). Briefly, subjects are fed-back a putatively dysfunctional parameter of their ...brain activity in real time and must learn to control it in a suggested direction. NF protocols for ADHD have been used in practice for decades, though no clear standards on NF design have been implemented. Furthermore, studies often present only data from the general outcome of the NF treatment and do not look at how exactly the NF paradigm affects brain functionality, or what exactly the NF is training. The current study is two-fold: firstly, we look at how the functional connectivity (FC) patterns within key networks associated with ADHD differ between rests, feedback trials, success and failure in a complete functional near-infrared spectroscopy-based NF experiment on adults with ADHD. Secondly, due to methodological concerns discovered during the analysis of our data, we address important considerations in the design of NF that are often ignored in protocols being used widely in therapy and research today. In particular, we examine the common average reference and its impact on network activity as well as the importance of balancing the randomization in a design. Finally, we discuss how these methodological considerations may have influenced our FC results.
Research on face sensitivity is of particular relevance during the rapidly evolving Covid-19 pandemic leading to social isolation, but also calling for intact interaction and sharing. Humans possess ...high sensitivity even to a coarse face scheme, seeing faces in non-face images where real faces do not exist. The advantage of non-face images is that single components do not trigger face processing. Here by implementing a novel set of Face-n-Thing images, we examined (i) how face tuning alters with changing display orientation, and (ii) whether it is affected by observers' gender. Young females and males were presented with a set of Face-n-Thing images either with canonical upright orientation or inverted 180° in the image plane. Face impression was substantially impeded by display inversion. Furthermore, whereas with upright display orientation, no gender differences were found, with inversion, Face-n-Thing images elicited face impression in females significantly more often. The outcome sheds light on the origins of the face inversion effect in general. Moreover, the findings open a way for examination of face sensitivity and underwriting brain networks in neuropsychiatric conditions related to the current pandemic (such as depression and anxiety), most of which are gender/sex-specific.
Abstract
Reading bodies and faces is essential for efficient social interactions, though it may be thought-provoking for individuals with depression. Yet aberrations in the face sensitivity and ...underwriting neural circuits are not well understood, in particular, in male depression. Here, we use cutting-edge analyses of time course and dynamic topography of gamma oscillatory neuromagnetic cortical activity during administration of a task with Arcimboldo-like images. No difference in face tuning was found between individuals with depression and their neurotypical peers. Furthermore, this behavioral outcome nicely dovetails with magnetoencephalographic data: at early processing stages, the gamma oscillatory response to images resembling a face was rather similar in patients and controls. These bursts originated primarily from the right medioventral occipital cortex and lateral occipital cortex. At later processing stages, however, its topography altered remarkably in depression with profound engagement of the frontal circuits. Yet the primary difference in depressive individuals as compared with their neurotypical peers occurred over the left middle temporal cortices, a part of the social brain, engaged in feature integration and meaning retrieval. The outcome suggests compensatory recruitment of neural resources in male depression.
Major depression disorder (MDD) is characterized by cognitive control (CC) dysfunctions associated with increased attention toward negative information. The paced auditory serial addition task ...(PASAT) has been used as a targeted training of CC and studies show promising effects on depressive symptoms. However, neural mechanisms underlying its efficacy are still unclear. Based on previous findings of feedback-locked event-related potentials in healthy subjects, we investigated neural signatures during PASAT performance in 46 depressed patients. We found significantly larger amplitudes after negative than positive feedback for the P300 and late positive potential (LPP). However, this difference was not significant for the feedback-related negativity (FRN). Moreover, no associations of valence-specific ERPs and PASAT performance nor depressive symptoms were found. This indicates that depressed patients seem unable to use neural activation in late feedback processing stages (P300, LPP) to adapt accordingly. Moreover, lack of valence-specific neural reaction in early feedback processing stages (FRN) might point toward emotional indifference in depressed patients.
Trial registration number: NCT03518749 Date of registration: May 8, 2018.
Previous studies have consistently shown a pattern of prefrontal hypoactivation in depressed patients (DP); however, it remains unclear whether this neural correlate is a consequence or concomitant ...feature of depression and/or whether ruminative thinking might be underlying. Using a sample comprising 65 healthy controls (HC) and 77 DP, we investigated the behavioral and neural correlates in response to stress and their association with depressive symptomatology, trait and state rumination. Fitting repeated-measurement MANOVAs including 21 fNIRS-channels covering the bilateral Inferior Frontal Gyrus (IFG), Dorsolateral Prefrontal Cortex (DLPFC) and Somatosensory Association Cortex (SAC), we investigated the predictive value of diagnostic group (HC vs. DP) and state rumination. In DP, we observed significantly lower increases in cortical oxygenation under stress in channels of the right IFG and bilateral DLPFC. Participants reporting lower state rumination and no increases in state rumination under stress showed higher increases in cortical oxygenation compared to the other groups and in more channels compared to the analysis on diagnostic group. Re-running our fNIRS-analysis while correcting for performance resulted in time-dependent changes dependent on group (DP vs. HC) no longer yielding significance, however for the differentiation of state rumination groups.
Pattern recognition applied to whole-brain neuroimaging data, such as functional Magnetic Resonance Imaging (fMRI), has proved successful at discriminating psychiatric patients from healthy ...participants. However, predictive patterns obtained from whole-brain voxel-based features are difficult to interpret in terms of the underlying neurobiology. Many psychiatric disorders, such as depression and schizophrenia, are thought to be brain connectivity disorders. Therefore, pattern recognition based on network models might provide deeper insights and potentially more powerful predictions than whole-brain voxel-based approaches. Here, we build a novel sparse network-based discriminative modeling framework, based on Gaussian graphical models and L1-norm regularized linear Support Vector Machines (SVM). In addition, the proposed framework is optimized in terms of both predictive power and reproducibility/stability of the patterns. Our approach aims to provide better pattern interpretation than voxel-based whole-brain approaches by yielding stable brain connectivity patterns that underlie discriminative changes in brain function between the groups. We illustrate our technique by classifying patients with major depressive disorder (MDD) and healthy participants, in two (event- and block-related) fMRI datasets acquired while participants performed a gender discrimination and emotional task, respectively, during the visualization of emotional valent faces.
•Connectivity-based predictive models can potentially improve psychiatric diagnosis.•We present a novel sparse network-based discriminative model for fMRI data.•This model jointly optimizes predictive power and stability of the output patterns.•Aiming at better pattern interpretation than voxel-based/whole-brain models.•Model is applied to classify patients with major depression from two fMRI datasets.
Adaptive social behavior and mental well-being depend on not only recognizing emotional expressions but also, inferring the absence of emotion. While the neurobiology underwriting the perception of ...emotions is well studied, the mechanisms for detecting a lack of emotional content in social signals remain largely unknown. Here, using cutting-edge analyses of effective brain connectivity, we uncover the brain networks differentiating neutral and emotional body language. The data indicate greater activation of the right amygdala and midline cerebellar vermis to nonemotional as opposed to emotional body language. Most important, the effective connectivity between the amygdala and insula predicts people’s ability to recognize the absence of emotion. These conclusions extend substantially current concepts of emotion perception by suggesting engagement of limbic effective connectivity in recognizing the lack of emotion in body language reading. Furthermore, the outcome may advance the understanding of overly emotional interpretation of social signals in depression or schizophrenia by providing the missing link between body language reading and limbic pathways. The study thus opens an avenue for multidisciplinary research on social cognition and the underlying cerebrocerebellar networks, ranging from animal models to patients with neuropsychiatric conditions.
PDF
