NeuroImage

Shared neural representations of syntax during online dyadic communication Publication date: September 2019 Source: NeuroImage, Volume 198 Author(s): Wenda Liu, Holly P. Branigan, Lifen Zheng, Yuhang Long, Xialu Bai, Kanyu Li, Hui Zhao, Siyuan Zhou, Martin J. Pickering, Chunming Lu Abstract When people communicate, they come to see the world in a similar way to each other by aligning their mental representations at such levels as syntax. Syntax is an essential feature of human language that distinguishes humans from other non-human animals. However, whether and how communicators share neural representations of syntax is not well understood. Here we addressed this issue by measuring the brain activity of both communicators in a series of dyadic communication contexts, by using functional near-infrared spectroscopy (fNIRS)-based hyperscanning. Two communicators alternatively spoke sentences either with the same or with different syntactic structures. Results showed a significantly higher-level increase of interpersonal neural synchronization (INS) at right posterior superior temporal cortex when communicators produced the same syntactic structures as each other compared to when they produced different syntactic structures. These increases of INS correlated significantly with communication quality. Our findings provide initial evidence for shared neural representations of syntax between communicators.

Multimodal characterization of the human nucleus accumbens Publication date: September 2019 Source: NeuroImage, Volume 198 Author(s): Samuel CD. Cartmell, Qiyuan Tian, Brandon J. Thio, Christoph Leuze, Li Ye, Nolan R. Williams, Grant Yang, Gabriel Ben-Dor, Karl Deisseroth, Warren M. Grill, Jennifer A. McNab, Casey H. Halpern Abstract Dysregulation of the nucleus accumbens (NAc) is implicated in numerous neuropsychiatric disorders. Treatments targeting this area directly (e.g. deep brain stimulation) demonstrate variable efficacy, perhaps owing to non-specific targeting of a functionally heterogeneous nucleus. Here we provide support for this notion, first observing disparate behavioral effects in response to direct simulation of different locations within the NAc in a human patient. These observations motivate a segmentation of the NAc into subregions, which we produce from a diffusion-tractography based analysis of 245 young, unrelated healthy subjects. We further explore the mechanism of these stimulation-induced behavioral responses by identifying the most probable subset of axons activated using a patient-specific computational model. We validate our diffusion-based segmentation using evidence from several modalities, including MRI-based measures of function and microstructure, human post-mortem immunohistochemical staining, and cross-species comparison of cortical-NAc projections that are known to be conserved. Finally, we visualize the passage of individual axon bundles through one NAc subregion in a post-mortem human sample using CLARITY 3D histology corroborated by 7T tractography. Collectively, these findings extensively characterize human NAc subregions and provide insight into their structural and functional distinctions with implications for stereotactic treatments targeting this region.

The relation between brain signal complexity and task difficulty on an executive function task Publication date: September 2019 Source: NeuroImage, Volume 198 Author(s): John G. Grundy, Ryan M. Barker, John A.E. Anderson, Judith M. Shedden Abstract On a daily basis, we constantly deal with changing environmental cues and perceptual conflicts and as such, our brains must flexibly adapt to current demands in order to act appropriately. Brains become more efficient and are able to switch states more readily by increasing the complexity of their neural networks. However, it is unclear how brain signal complexity relates to behavior in young adults performing cognitively demanding executive function tasks. Here we used multiscale entropy analysis and multivariate statistics on EEG data while participants performed a bivalency effect task-switching paradigm to show that brain signal complexity in young adults increases as task demands increase, that increases in brain signal complexity are associated with both speed gains and losses depending on scalp location, and that more difficult tasks are associated with more circumscribed complexity across the scalp. Overall, these findings highlight a critical role for brain signal complexity in predicting behavior on an executive function task among young adults.

Group-level cortical and muscular connectivity during perturbations to walking and standing balance Publication date: September 2019 Source: NeuroImage, Volume 198 Author(s): Steven M. Peterson, Daniel P. Ferris Abstract Maintaining balance is a complex process requiring multisensory processing and coordinated muscle activation. Previous studies have indicated that the cortex is directly involved in balance control, but less information is known about cortical flow of signals for balance. We studied source-localized electrocortical effective connectivity dynamics of healthy young subjects (29 subjects: 14 male and 15 female) walking and standing with both visual and physical perturbations to their balance. The goal of this study was to quantify differences in group-level corticomuscular connectivity responses to sensorimotor perturbations during walking and standing. We hypothesized that perturbed visual input during balance would transiently decrease connectivity between occipital and parietal areas due to disruptive visual input during sensory processing. We also hypothesized that physical pull perturbations would increase cortical connections to central sensorimotor areas because of higher sensorimotor integration demands. Our findings show decreased occipito-parietal connectivity during visual rotations and widespread increases in connectivity during pull perturbations focused on central areas, as expected. We also found evidence for communication from cortex to muscles during perturbed balance. These results show that sensorimotor perturbations to balance alter cortical networks and can be quantified using effective connectivity estimation.

Change detection to tone pairs during the first year of life – Predictive longitudinal relationships for EEG-based source and time-frequency measures Publication date: September 2019 Source: NeuroImage, Volume 198 Author(s): Jarmo A. Hämäläinen, Silvia Ortiz-Mantilla, April Benasich Abstract Brain responses related to auditory processing show large changes throughout infancy and childhood with some evidence that the two hemispheres might mature at different rates. Differing rates of hemispheric maturation could be linked to the proposed functional specialization of the hemispheres in which the left auditory cortex engages in analysis of precise timing information whereas the right auditory cortex focuses on analysis of sound frequency. Here the auditory change detection process for rapidly presented tone-pairs was examined in a longitudinal sample of infants at the age of 6 and 12 months using EEG. The ERP response related to change detection of a frequency contrast, its estimated source strength in the auditory areas, as well as time-frequency indices showed developmental effects. ERP amplitudes, source strength, spectral power and inter-trial phase locking decreased across age. A differential lateralization pattern emerged between 6 and 12 months as shown by inter-trial phase locking at 2–3 Hz; specifically, a larger developmental change was observed in the right as compared to the left hemisphere. Predictive relationships for the change in source strength from 6 months to 12 months were found. Six-month predictors were source strength and phase locking values at low frequencies. The results show that the infant change detection response in rapidly presented tone pairs is mainly determined by low frequency power and phase-locking with a larger phase-locking response at 6 months predicting greater change at 12 months. The ability of the auditory system to respond systematically across stimuli is suggested as a marker of maturational change that leads to more automatic and fine-tuned cortical responses.

Enhancing neural efficiency of cognitive processing speed via training and neurostimulation: An fNIRS and TMS study Publication date: September 2019 Source: NeuroImage, Volume 198 Author(s): Adrian Curtin, Hasan Ayaz, Yingying Tang, Junfeng Sun, Jijun Wang, Shanbao Tong Abstract Speed of Processing (SoP) represents a fundamental limiting step in cognitive performance which may underlie General Intelligence. The measure of SoP is particularly sensitive to aging, neurological or cognitive diseases, and has become a benchmark for diagnosis, cognitive remediation, and enhancement. Neural efficiency of the Dorsolateral Prefrontal Cortex (DLPFC) is proposed to account for individual differences in SoP. However, the mechanisms by which DLPFC efficiency is shaped by training and whether it can be enhanced remain elusive. To address this, we monitored the brain activity of sixteen healthy participants using functional Near Infrared Spectroscopy (fNIRS) while practicing a common SoP task (Symbol Digit Substitution Task) across 4 sessions. Furthermore, in each session, participants received counterbalanced excitatory repetitive transcranial magnetic stimulation (rTMS) during mid-session breaks. Results indicate a significant involvement of the left-DLPFC in SoP, whose neural efficiency is consistently increased through task practice. Active neurostimulation, but not Sham, significantly enhanced the neural efficiency. These findings suggest a common mechanism by which neurostimulation may aid to accelerate learning.

Topological correction of infant white matter surfaces using anatomically constrained convolutional neural network Publication date: September 2019 Source: NeuroImage, Volume 198 Author(s): Liang Sun, Daoqiang Zhang, Chunfeng Lian, Li Wang, Zhengwang Wu, Wei Shao, Weili Lin, Dinggang Shen, Gang Li, UNC/UMN Baby Connectome Project Consortium Abstract Reconstruction of accurate cortical surfaces without topological errors (i.e., handles and holes) from infant brain MR images is very important in early brain development studies. However, infant brain MR images typically suffer extremely low tissue contrast and dynamic imaging appearance patterns. Thus, it is inevitable to have large amounts of topological errors in the segmented infant brain tissue images, which lead to inaccurately reconstructed cortical surfaces with topological errors. To address this issue, inspired by recent advances in deep learning, we propose an anatomically constrained network for topological correction on infant cortical surfaces. Specifically, in our method, we first locate regions of potential topological defects by leveraging a topology-preserving level set method. Then, we propose an anatomically constrained network to correct those candidate voxels in the located regions. Since infant cortical surfaces often contain large and complex handles or holes, it is difficult to completely correct all errors using one-shot correction. Therefore, we further enroll these two steps into an iterative framework to gradually correct large topological errors. To the best of our knowledge, this is the first work to introduce deep learning approach for topological correction of infant cortical surfaces. We compare our method with the state-of-the-art methods on both simulated topological errors and real topological errors in human infant brain MR images. Moreover, we also validate our method on the infant brain MR images of macaques. All experimental results show the superior performance of the proposed method. Graphical abstract

Empathy to emotional voices and the use of real-time fMRI to enhance activation of the anterior insula Publication date: September 2019 Source: NeuroImage, Volume 198 Author(s): Dana Kanel, Salim Al-Wasity, Kristian Stefanov, Frank E. Pollick Abstract The right anterior insula (AI), known to have a key role in the processing and understanding of social emotions, is activated during tasks that involve the act of empathising. Neurofeedback provides individuals with a visualisation of their own brain activity, enabling them to regulate and modify this activity. Following previous research investigating the ability of individuals to up-regulate right AI activity levels through neurofeedback, we investigated whether this could be similarly accomplished during an empathy task involving auditory stimuli of human positive and negative emotional expressions. Twenty participants, ten with feedback from right anterior insula and ten with feedback from a sham brain region, participated in two sessions that included sixteen neurofeedback runs and four transfer runs. Results showed that for the second session participants in the right AI neurofeedback group demonstrated better ability to up-regulate their right AI compared to the control group who received sham feedback. Examination of the relationship between individual participants' empathic traits and their ability to up-regulate right AI activity showed that participants low on empathic traits produced a greater increase in activation of right AI by the end of training. Moreover, the response to positively valenced audio stimuli was greater than for negatively valenced stimuli. These results have implications for therapeutic training of empathy in populations with limited empathic response.

Microelectrode array electrical impedance tomography for fast functional imaging in the thalamus Publication date: September 2019 Source: NeuroImage, Volume 198 Author(s): Danyi Zhu, Alistair McEwan, Calvin Eiber Abstract Electrical Impedance Tomography (EIT) has the potential to be able to observe functional tomographic images of neural activity in the brain at millisecond time-scales. Prior modelling and experimental work has shown that EIT is capable of imaging impedance changes from neural depolarisation in rat somatosensory cortex. Here, we investigate the feasibility of EIT for imaging impedance changes using a stereotaxically implanted microelectrode array in the thalamus. Microelectrode array EIT was simulated using an anatomically accurate marmoset brain model. Impedance imaging was validated and detectability estimated using physiological noise recorded from the marmoset visual thalamus. The results suggest that visual-input-driven impedance changes in visual subcortical bodies within 300 μm of the implanted array could be reliably reconstructed and localised, comparable to local field potential measurements. Furthermore, we demonstrated that microelectrode array EIT could reconstruct concurrent activity in multiple subcortical bodies simultaneously. Graphical abstract

Rhythmicity facilitates pitch discrimination: Differential roles of low and high frequency neural oscillations Publication date: September 2019 Source: NeuroImage, Volume 198 Author(s): Andrew Chang, Dan J. Bosnyak, Laurel J. Trainor Abstract Previous studies indicate that temporal predictability can enhance timing and intensity perception, but it is not known whether it also enhances pitch perception, despite pitch being a fundamental perceptual attribute of sound. Here we investigate this in the context of rhythmic regularity, a form of predictable temporal structure common in sound streams, including music and speech. It is known that neural oscillations in low (delta: 1–3 Hz) and high (beta: 15–25 Hz) frequency bands entrain to rhythms in phase and power, respectively, but it is not clear why both low and high frequency bands entrain to external rhythms, and whether they and their coupling serve different perceptual functions. Participants discriminated near-threshold pitch deviations (targets) embedded in either rhythmic (regular/isochronous) or arrhythmic (irregular/non-isochronous) tone sequences. Psychophysically, we found superior pitch discrimination performance for target tones in rhythmic compared to arrhythmic sequences. Electroencephalography recordings from auditory cortex showed that delta phase, beta power modulation, and delta-beta coupling were all modulated by rhythmic regularity. Importantly, trial-by-trial neural-behavioural correlational analyses showed that, prior to a target, the depth of U-shaped beta power modulation predicted pitch discrimination sensitivity whereas cross-frequency coupling strength predicted reaction time. These novel findings suggest that delta phase might reflect rhythmic temporal expectation, beta power temporal attention, and delta-beta coupling auditory-motor communication. Together, low and high frequency auditory neural oscillations reflect different perceptual functions that work in concert for tracking rhythmic regularity and proactively facilitate pitch perception.

Alexandros Sfakianakis
Anapafseos 5 . Agios Nikolaos
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alsfakia@gmail.com