From Motion to Emotion: Visual Pathways and Potential Interconnections.

The two visual pathway description of [Ungerleider, L. G., & Mishkin, M. Two cortical visual systems. In D. J. Dingle, M. A. Goodale, & R. J. W. Mansfield (Eds.), Analysis of visual behavior (pp. 549-586). Cambridge, MA: MIT, 1982] changed the course of late 20th century systems and cognitive neuroscience. Here, I try to reexamine our laboratory's work through the lens of the [Pitcher, D., & Ungerleider, L. G. Evidence for a third visual pathway specialized for social perception. Trends in Cognitive Sciences, 25, 100-110, 2021] new third visual pathway. I also briefly review the literature related to brain responses to static and dynamic visual displays, visual stimulation involving multiple individuals, and compare existing models of social information processing for the face and body. In this context, I examine how the posterior STS might generate unique social information relative to other brain regions that also respond to social stimuli. I discuss some of the existing challenges we face with assessing how information flow progresses between structures in the proposed functional pathways and how some stimulus types and experimental designs may have complicated our data interpretation and model generation. I also note a series of outstanding questions for the field. Finally, I examine the idea of a potential expansion of the third visual pathway, to include aspects of previously proposed "lateral" visual pathways. Doing this would yield a more general entity for processing motion/action (i.e., "[inter]action") that deals with interactions between people, as well as people and objects. In this framework, a brief discussion of potential hemispheric biases for function, and different forms of neuropsychological impairments created by focal lesions in the posterior brain is highlighted to help situate various brain regions into an expanded [inter]action pathway.

Neurodesk: an accessible, flexible and portable data analysis environment for reproducible neuroimaging.

Neuroimaging research requires purpose-built analysis software, which is challenging to install and may produce different results across computing environments. The community-oriented, open-source Neurodesk platform ( https://www.neurodesk.org/ ) harnesses a comprehensive and growing suite of neuroimaging software containers. Neurodesk includes a browser-accessible virtual desktop, command-line interface and computational notebook compatibility, allowing for accessible, flexible, portable and fully reproducible neuroimaging analysis on personal workstations, high-performance computers and the cloud.

Neurodesk: An accessible, flexible, and portable data analysis environment for reproducible neuroimaging.

Neuroimaging data analysis often requires purpose-built software, which can be challenging to install and may produce different results across computing environments. Beyond being a roadblock to neuroscientists, these issues of accessibility and portability can hamper the reproducibility of neuroimaging data analysis pipelines. Here, we introduce the Neurodesk platform, which harnesses software containers to support a comprehensive and growing suite of neuroimaging software (https://www.neurodesk.org/). Neurodesk includes a browser-accessible virtual desktop environment and a command line interface, mediating access to containerized neuroimaging software libraries on various computing platforms, including personal and high-performance computers, cloud computing and Jupyter Notebooks. This community-oriented, open-source platform enables a paradigm shift for neuroimaging data analysis, allowing for accessible, flexible, fully reproducible, and portable data analysis pipelines.

Advances in human intracranial electroencephalography research, guidelines and good practices.

Since the second-half of the twentieth century, intracranial electroencephalography (iEEG), including both electrocorticography (ECoG) and stereo-electroencephalography (sEEG), has provided an intimate view into the human brain. At the interface between fundamental research and the clinic, iEEG provides both high temporal resolution and high spatial specificity but comes with constraints, such as the individual's tailored sparsity of electrode sampling. Over the years, researchers in neuroscience developed their practices to make the most of the iEEG approach. Here we offer a critical review of iEEG research practices in a didactic framework for newcomers, as well addressing issues encountered by proficient researchers. The scope is threefold: (i) review common practices in iEEG research, (ii) suggest potential guidelines for working with iEEG data and answer frequently asked questions based on the most widespread practices, and (iii) based on current neurophysiological knowledge and methodologies, pave the way to good practice standards in iEEG research. The organization of this paper follows the steps of iEEG data processing. The first section contextualizes iEEG data collection. The second section focuses on localization of intracranial electrodes. The third section highlights the main pre-processing steps. The fourth section presents iEEG signal analysis methods. The fifth section discusses statistical approaches. The sixth section draws some unique perspectives on iEEG research. Finally, to ensure a consistent nomenclature throughout the manuscript and to align with other guidelines, e.g., Brain Imaging Data Structure (BIDS) and the OHBM Committee on Best Practices in Data Analysis and Sharing (COBIDAS), we provide a glossary to disambiguate terms related to iEEG research.

Good scientific practice in EEG and MEG research: Progress and perspectives.

Good scientific practice (GSP) refers to both explicit and implicit rules, recommendations, and guidelines that help scientists to produce work that is of the highest quality at any given time, and to efficiently share that work with the community for further scrutiny or utilization. For experimental research using magneto- and electroencephalography (MEEG), GSP includes specific standards and guidelines for technical competence, which are periodically updated and adapted to new findings. However, GSP also needs to be regularly revisited in a broader light. At the LiveMEEG 2020 conference, a reflection on GSP was fostered that included explicitly documented guidelines and technical advances, but also emphasized intangible GSP: a general awareness of personal, organizational, and societal realities and how they can influence MEEG research. This article provides an extensive report on most of the LiveMEEG contributions and new literature, with the additional aim to synthesize ongoing cultural changes in GSP. It first covers GSP with respect to cognitive biases and logical fallacies, pre-registration as a tool to avoid those and other early pitfalls, and a number of resources to enable collaborative and reproducible research as a general approach to minimize misconceptions. Second, it covers GSP with respect to data acquisition, analysis, reporting, and sharing, including new tools and frameworks to support collaborative work. Finally, GSP is considered in light of ethical implications of MEEG research and the resulting responsibility that scientists have to engage with societal challenges. Considering among other things the benefits of peer review and open access at all stages, the need to coordinate larger international projects, the complexity of MEEG subject matter, and today's prioritization of fairness, privacy, and the environment, we find that current GSP tends to favor collective and cooperative work, for both scientific and for societal reasons.

EEG measures for clinical research in major vascular cognitive impairment: recommendations by an expert panel.

Vascular contribution to cognitive impairment (VCI) and dementia is related to etiologies that may affect the neurophysiological mechanisms regulating brain arousal and generating electroencephalographic (EEG) activity. A multidisciplinary expert panel reviewed the clinical literature and reached consensus about the EEG measures consistently found as abnormal in VCI patients with dementia. As compared to cognitively unimpaired individuals, those VCI patients showed (1) smaller amplitude of resting state alpha (8-12 Hz) rhythms dominant in posterior regions; (2) widespread increases in amplitude of delta (< 4 Hz) and theta (4-8 Hz) rhythms; and (3) delayed N200/P300 peak latencies in averaged event-related potentials, especially during the detection of auditory rare target stimuli requiring participants' responses in "oddball" paradigms. The expert panel formulated the following recommendations: (1) the above EEG measures are not specific for VCI and should not be used for its diagnosis; (2) they may be considered as "neural synchronization" biomarkers to enlighten the relationships between features of the VCI-related cerebrovascular lesions and abnormalities in neurophysiological brain mechanisms; and (3) they may be tested in future clinical trials as prognostic biomarkers and endpoints of interventions aimed at normalizing background brain excitability and vigilance in wakefulness.

Statistical power: Implications for planning MEG studies.

Statistical power is key for robust, replicable science. Here, we systematically explored how numbers of trials and subjects affect statistical power in MEG sensor-level data. More specifically, we simulated "experiments" using the MEG resting-state dataset of the Human Connectome Project (HCP). We divided the data in two conditions, injected a dipolar source at a known anatomical location in the "signal condition", but not in the "noise condition", and detected significant differences at sensor level with classical paired t-tests across subjects, using amplitude, squared amplitude, and global field power (GFP) measures. Group-level detectability of these simulated effects varied drastically with anatomical origin. We thus examined in detail which spatial properties of the sources affected detectability, looking specifically at the distance from closest sensor and orientation of the source, and at the variability of these parameters across subjects. In line with previous single-subject studies, we found that the most detectable effects originate from source locations that are closest to the sensors and oriented tangentially with respect to the head surface. In addition, cross-subject variability in orientation also affected group-level detectability, boosting detection in regions where this variability was small and hindering detection in regions where it was large. Incidentally, we observed a considerable covariation of source position, orientation, and their cross-subject variability in individual brain anatomical space, making it difficult to assess the impact of each of these variables independently of one another. We thus also performed simulations where we controlled spatial properties independently of individual anatomy. These additional simulations confirmed the strong impact of distance and orientation and further showed that orientation variability across subjects affects detectability, whereas position variability does not. Importantly, our study indicates that strict unequivocal recommendations as to the ideal number of trials and subjects for any experiment cannot be realistically provided for neurophysiological studies and should be adapted according to the brain regions under study.

Differential effects of propofol and ketamine on critical brain dynamics.

Whether the brain operates at a critical "tipping" point is a long standing scientific question, with evidence from both cellular and systems-scale studies suggesting that the brain does sit in, or near, a critical regime. Neuroimaging studies of humans in altered states of consciousness have prompted the suggestion that maintenance of critical dynamics is necessary for the emergence of consciousness and complex cognition, and that reduced or disorganized consciousness may be associated with deviations from criticality. Unfortunately, many of the cellular-level studies reporting signs of criticality were performed in non-conscious systems (in vitro neuronal cultures) or unconscious animals (e.g. anaesthetized rats). Here we attempted to address this knowledge gap by exploring critical brain dynamics in invasive ECoG recordings from multiple sessions with a single macaque as the animal transitioned from consciousness to unconsciousness under different anaesthetics (ketamine and propofol). We use a previously-validated test of criticality: avalanche dynamics to assess the differences in brain dynamics between normal consciousness and both drug-states. Propofol and ketamine were selected due to their differential effects on consciousness (ketamine, but not propofol, is known to induce an unusual state known as "dissociative anaesthesia"). Our analyses indicate that propofol dramatically restricted the size and duration of avalanches, while ketamine allowed for more awake-like dynamics to persist. In addition, propofol, but not ketamine, triggered a large reduction in the complexity of brain dynamics. All states, however, showed some signs of persistent criticality when testing for exponent relations and universal shape-collapse. Further, maintenance of critical brain dynamics may be important for regulation and control of conscious awareness.

Issues and recommendations from the OHBM COBIDAS MEEG committee for reproducible EEG and MEG research.

The Organization for Human Brain Mapping (OHBM) has been active in advocating for the instantiation of best practices in neuroimaging data acquisition, analysis, reporting and sharing of both data and analysis code to deal with issues in science related to reproducibility and replicability. Here we summarize recommendations for such practices in magnetoencephalographic (MEG) and electroencephalographic (EEG) research, recently developed by the OHBM neuroimaging community known by the abbreviated name of COBIDAS MEEG. We discuss the rationale for the guidelines and their general content, which encompass many topics under active discussion in the field. We highlight future opportunities and challenges to maximizing the sharing and exploitation of MEG and EEG data, and we also discuss how this 'living' set of guidelines will evolve to continually address new developments in neurophysiological assessment methods and multimodal integration of neurophysiological data with other data types.

IFCN-endorsed practical guidelines for clinical magnetoencephalography (MEG).

Magnetoencephalography (MEG) records weak magnetic fields outside the human head and thereby provides millisecond-accurate information about neuronal currents supporting human brain function. MEG and electroencephalography (EEG) are closely related complementary methods and should be interpreted together whenever possible. This manuscript covers the basic physical and physiological principles of MEG and discusses the main aspects of state-of-the-art MEG data analysis. We provide guidelines for best practices of patient preparation, stimulus presentation, MEG data collection and analysis, as well as for MEG interpretation in routine clinical examinations. In 2017, about 200 whole-scalp MEG devices were in operation worldwide, many of them located in clinical environments. Yet, the established clinical indications for MEG examinations remain few, mainly restricted to the diagnostics of epilepsy and to preoperative functional evaluation of neurosurgical patients. We are confident that the extensive ongoing basic MEG research indicates potential for the evaluation of neurological and psychiatric syndromes, developmental disorders, and the integrity of cortical brain networks after stroke. Basic and clinical research is, thus, paving way for new clinical applications to be identified by an increasing number of practitioners of MEG.

A Review of Issues Related to Data Acquisition and Analysis in EEG/MEG Studies.

Electroencephalography (EEG) and magnetoencephalography (MEG) are non-invasive electrophysiological methods, which record electric potentials and magnetic fields due to electric currents in synchronously-active neurons. With MEG being more sensitive to neural activity from tangential currents and EEG being able to detect both radial and tangential sources, the two methods are complementary. Over the years, neurophysiological studies have changed considerably: high-density recordings are becoming de rigueur; there is interest in both spontaneous and evoked activity; and sophisticated artifact detection and removal methods are available. Improved head models for source estimation have also increased the precision of the current estimates, particularly for EEG and combined EEG/MEG. Because of their complementarity, more investigators are beginning to perform simultaneous EEG/MEG studies to gain more complete information about neural activity. Given the increase in methodological complexity in EEG/MEG, it is important to gather data that are of high quality and that are as artifact free as possible. Here, we discuss some issues in data acquisition and analysis of EEG and MEG data. Practical considerations for different types of EEG and MEG studies are also discussed.

Socio-emotionally significant experience and children's processing of irrelevant auditory stimuli.

Theory and research indicate considerable influence of socio-emotionally significant experiences on children's functioning and adaptation. In the current study, we examined neurophysiological correlates of children's allocation of information processing resources to socio-emotionally significant events, specifically, simulated marital interactions. We presented 9- to 11-year-old children (n=24; 11 females) with 15 videos of interactions between two actors posing as a married couple. Task-irrelevant brief auditory probes were presented during the videos, and event-related potentials (ERPs) elicited to the auditory probes were measured. As hypothesized, exposure to higher levels of interparental conflict was associated with smaller P1, P2, and N2 ERPs to the probes. This finding is consistent with the idea that children who had been exposed to more interparental conflict attended more to the videos and diverted fewer cognitive resources to processing the probes, thereby producing smaller ERPs to the probes. In addition, smaller N2s were associated with more child behavior problems, suggesting that allocating fewer processing resources to the probes was associated with more problem behavior. Results are discussed in terms of implications of socio-emotionally significant experiences for children's processing of interpersonal interactions.

Same Intervention-Different Reorganization: The Impact of Lesion Location on Training-Facilitated Somatosensory Recovery After Stroke.

BACKGROUND: The brain may reorganize to optimize stroke recovery. Yet relatively little is known about neural correlates of training-facilitated recovery, particularly after loss of body sensations. OBJECTIVE: Our aim was to characterize changes in brain activation following clinically effective touch discrimination training in stroke patients with somatosensory loss after lesions of primary/secondary somatosensory cortices or thalamic/capsular somatosensory regions using functional magnetic resonance imaging (fMRI). METHODS: Eleven stroke patients with somatosensory loss, 7 with lesions involving primary (S1) and/or secondary (S2) somatosensory cortex (4 male, 58.7 ± 13.3 years) and 4 with lesions primarily involving somatosensory thalamus and/or capsular/white matter regions (2 male, 58 ± 8.6 years) were studied. Clinical and MRI testing occurred at 6 months poststroke (preintervention), and following 15 sessions of clinically effective touch discrimination training (postintervention). RESULTS: Improved touch discrimination of a magnitude similar to previous clinical studies and approaching normal range was found. Patients with thalamic/capsular somatosensory lesions activated preintervention in left ipsilesional supramarginal gyrus, and postintervention in ipsilesional insula and supramarginal gyrus. In contrast, those with S1/S2 lesions did not show common activation preintervention, only deactivation in contralesional superior parietal lobe, including S1, and cingulate cortex postintervention. The S1/S2 group did, however, show significant change over time involving ipsilesional precuneus. This change was greater than for the thalamic/capsular group (P = .012; d = -2.43; CI = -0.67 to -3.76). CONCLUSION: Different patterns of change in activation are evident following touch discrimination training with thalamic/capsular lesions compared with S1/S2 cortical somatosensory lesions, despite common training and similar improvement.

On dissociating the neural time course of the processing of positive emotions.

Providing evidence for categorical theories of emotion mandates the inclusion of discrete emotion categories beyond the typical six "basic" emotions. Traditional neurophysiological investigations of emotion typically feature the six basic emotions with happiness as the lone positive exemplar. Here we studied how event-related potentials (ERPs) might differentiate between two positive emotional expressions: happiness and pride, and if so, at what time interval. Furthermore, given divergent findings in the ERP literature with respect to viewing emotional expressions, we explicitly examined how task type modulates neurophysiological responses when the same stimuli are viewed. While a continuous electroencephalogram (EEG) was recorded, 20 healthy participants completed two tasks: an implicit task where participants judged whether or not a face featured a brown spot (freckle), and an explicit task where they judged the face as portraying a "happy," "proud," or "neutral" expression. Behavioral performance exceeded 90% accuracy on both tasks. In the explicit task, participants responded faster and more accurately for Happy compared to Proud and Neutral expressions. Neurophysiologically, amplitudes for N170, VPP and P250 ERPs differentiated emotional from neutral expressions, but not from each other. In contrast, the late SPW component significantly differentiated Happy and Proud expressions from each other. Moreover, main effects of Task were found for the VPP, P250, LPP and SPW; additionally, Emotion X Task interactions were observed for P250 and SPW. Our data stress that task demands may magnify or diminish neural processing differences between emotion categories, which therefore cannot be disentangled with a single experimental paradigm. Additionally, some ERP differences may also reflect variations in categorization difficulty.

Something to sink your teeth into: The presence of teeth augments ERPs to mouth expressions.

If the whites of the sclera can impact neural processing of eye expressions (Hardee, Thompson, & Puce, 2008; Whalen et al., 1998), do seen teeth affect neural responses to mouth expressions? Twenty participants (10 females; ages 22-31) viewed avatar mouth images depicting grimaces, smiles and open mouth expressions that were presented with and without teeth. A continuous 256 channel electroencephalogram (EEG) was recorded while subjects completed two tasks: an implicit task evaluating stimulus color and an explicit task evaluating mouth expression valence. Event related potential (ERP) peak amplitudes and latencies and area under the curve (AUC) were measured in individual subject averaged ERPs. Statistical testing revealed a main effect of the presence of Teeth for P100, N170, and vertex positive potential (VPP) amplitudes and for slow positive wave (SPW) AUC. Task by teeth interactions occurred for P250 amplitude, underscoring how explicit task demands can influence neural processing. Arousal ratings co-varied with teeth presence, suggesting that low-level visual features such as teeth may drive the saliency of emotional expressions, and lie at the core of differences in neural processing to different emotional expressions.

Nodal centrality of functional network in the differentiation of schizophrenia.

A disturbance in the integration of information during mental processing has been implicated in schizophrenia, possibly due to faulty communication within and between brain regions. Graph theoretic measures allow quantification of functional brain networks. Functional networks are derived from correlations between time courses of brain regions. Group differences between SZ and control groups have been reported for functional network properties, but the potential of such measures to classify individual cases has been little explored. We tested whether the network measure of betweenness centrality could classify persons with schizophrenia and normal controls. Functional networks were constructed for 19 schizophrenic patients and 29 non-psychiatric controls based on resting state functional MRI scans. The betweenness centrality of each node, or fraction of shortest-paths that pass through it, was calculated in order to characterize the centrality of the different regions. The nodes with high betweenness centrality agreed well with hub nodes reported in previous studies of structural and functional networks. Using a linear support vector machine algorithm, the schizophrenia group was differentiated from non-psychiatric controls using the ten nodes with the highest betweenness centrality. The classification accuracy was around 80%, and stable against connectivity thresholding. Better performance was achieved when using the ranks as feature space as opposed to the actual values of betweenness centrality. Overall, our findings suggest that changes in functional hubs are associated with schizophrenia, reflecting a variation of the underlying functional network and neuronal communications. In addition, a specific network property, betweenness centrality, can classify persons with SZ with a high level of accuracy.