Inter-subject correlation of electroencephalographic and behavioural responses reflects time-varying engagement with natural music.

Musical engagement can be conceptualized through various activities, modes of listening and listener states. Recent research has reported that a state of focused engagement can be indexed by the inter-subject correlation (ISC) of audience responses to a shared naturalistic stimulus. While statistically significant ISC has been reported during music listening, we lack insight into the temporal dynamics of engagement over the course of musical works-such as those composed in the Western classical style-which involve the formulation of expectations that are realized or derailed at subsequent points of arrival. Here, we use the ISC of electroencephalographic (EEG) and continuous behavioural (CB) responses to investigate the time-varying dynamics of engagement with functional tonal music. From a sample of adult musicians who listened to a complete cello concerto movement, we found that ISC varied throughout the excerpt for both measures. In particular, significant EEG ISC was observed during periods of musical tension that built to climactic highpoints, while significant CB ISC corresponded more to declarative entrances and points of arrival. Moreover, we found that a control stimulus retaining envelope characteristics of the intact music, but little other temporal structure, also elicited significantly correlated EEG and CB responses, though to lesser extents than the original version. In sum, these findings shed light on the temporal dynamics of engagement during music listening and clarify specific aspects of musical engagement that may be indexed by each measure.

A statistical theory of optimal decision-making in sports betting.

The recent legalization of sports wagering in many regions of North America has renewed attention on the practice of sports betting. Although considerable effort has been previously devoted to the analysis of sportsbook odds setting and public betting trends, the principles governing optimal wagering have received less focus. Here the key decisions facing the sports bettor are cast in terms of the probability distribution of the outcome variable and the sportsbook's proposition. Knowledge of the median outcome is shown to be a sufficient condition for optimal prediction in a given match, but additional quantiles are necessary to optimally select the subset of matches to wager on (i.e., those in which one of the outcomes yields a positive expected profit). Upper and lower bounds on wagering accuracy are derived, and the conditions required for statistical estimators to attain the upper bound are provided. To relate the theory to a real-world betting market, an empirical analysis of over 5000 matches from the National Football League is conducted. It is found that the point spreads and totals proposed by sportsbooks capture 86% and 79% of the variability in the median outcome, respectively. The data suggests that, in most cases, a sportsbook bias of only a single point from the true median is sufficient to permit a positive expected profit. Collectively, these findings provide a statistical framework that may be utilized by the betting public to guide decision-making.

Computational modeling of posteroanterior lumbar traction by an automated massage bed: predicting intervertebral disc stresses and deformation.

Spinal traction is a physical intervention that provides constant or intermittent stretching axial force to the lumbar vertebrae to gradually distract spinal tissues into better alignment, reduce intervertebral disc (IVD) pressure, and manage lower back pain (LBP). However, such axial traction may change the normal lordotic curvature, and result in unwanted side effects and/or inefficient reduction of the IVD pressure. An alternative to axial traction has been recently tested, consisting of posteroanterior (PA) traction in supine posture, which was recently shown effective to increase the intervertebral space and lordotic angle using MRI. PA traction aims to maintain the lumbar lordosis curvature throughout the spinal traction therapy while reducing the intradiscal pressure. In this study, we developed finite element simulations of mechanical therapy produced by a commercial thermo-mechanical massage bed capable of spinal PA traction. The stress relief produced on the lumbar discs by the posteroanterior traction system was investigated on human subject models with different BMI (normal, overweight, moderate obese and extreme obese BMI cases). We predict typical traction levels lead to significant distraction stresses in the lumbar discs, thus producing a stress relief by reducing the compression stresses normally experienced by these tissues. Also, the stress relief experienced by the lumbar discs was effective in all BMI models, and it was found maximal in the normal BMI model. These results are consistent with prior observations of therapeutic benefits derived from spinal AP traction.

Computational Modeling of Deep Tissue Heating by an Automatic Thermal Massage Bed: Predicting the Effects on Circulation.

Automatic thermal and mechanical massage beds support self-managed treatment, including reduction of pain and stress, enhanced circulation, and improved mobility. As the devices become more sophisticated (increasing the degrees of freedom), it is essential to identify the settings that best target the desired tissue. To that end, we developed an MRI-derived model of the lower back and simulated the physiological effects of a commercial thermal-mechanical massage bed. Here we specifically estimated the tissue temperature and increased circulation under steady-state conditions for typical thermal actuator settings (i.e., 45-65°C). Energy transfer across nine tissues was simulated with finite element modeling (FEM) and the resulting heating was coupled to blood flow with an empirically-guided model of temperature-dependent circulation. Our findings indicate that thermal massage increases tissue temperature by 3-8°C and 1-3°C at depths of 2 and 3 cm, respectively. Importantly, due to the rapid (non-linear) increase of circulation with local temperature, this is expected to increase blood flow four-fold (4x) at depths occupied by deep tissue and muscle. These predictions are consistent with prior clinical observations of therapeutic benefits derived from spinal thermal massage.

Neuronal responses to focused ultrasound are gated by pre-stimulation brain rhythms.

BACKGROUND: Owing to its high spatial resolution and penetration depth, transcranial focused ultrasound stimulation (tFUS) is one of the most promising approaches to non-invasive neuromodulation. Identifying the impact of endogenous neural activity on neuromodulation outcome is critical to harnessing the potential of tFUS. OBJECTIVE: Here we sought to identify the relationship between pre-stimulation neural activity and the neuronal response to tFUS. METHODS: We applied 3 min of continuous-wave tFUS to the hippocampal region of the rat while recording local field potentials (LFP) and multi-unit activity (MUA) from the target. We also tested the application of tFUS but with an air gap separating the transducer and the skull, as well as active stimulation of the contralateral olfactory bulb. RESULTS: We observed a modest but significant increase in firing rate during hippocampal tFUS, but not during stimulation of the olfactory bulb or when an air gap was present. Importantly, the observed firing rate increase was significantly modulated by the power of baseline oscillations in the LFP, with low levels of delta (1-3 Hz) and high levels of theta (4-10 Hz) and gamma (30-250 Hz) power producing significantly larger firing rate increases. Firing rate increases were also amplified by a factor of 7× when stimulation was applied during periods of frequent sharp-wave ripple (SWR) activity. CONCLUSION: Our findings suggest that baseline brain rhythms may effectively "gate" the response to tFUS.

Inter-subject Correlation While Listening to Minimalist Music: A Study of Electrophysiological and Behavioral Responses to Steve Reich's Piano Phase.

Musical minimalism utilizes the temporal manipulation of restricted collections of rhythmic, melodic, and/or harmonic materials. One example, Steve Reich's Piano Phase, offers listeners readily audible formal structure with unpredictable events at the local level. For example, pattern recurrences may generate strong expectations which are violated by small temporal and pitch deviations. A hyper-detailed listening strategy prompted by these minute deviations stands in contrast to the type of listening engagement typically cultivated around functional tonal Western music. Recent research has suggested that the inter-subject correlation (ISC) of electroencephalographic (EEG) responses to natural audio-visual stimuli objectively indexes a state of "engagement," demonstrating the potential of this approach for analyzing music listening. But can ISCs capture engagement with minimalist music, which features less obvious expectation formation and has historically received a wide range of reactions? To approach this question, we collected EEG and continuous behavioral (CB) data while 30 adults listened to an excerpt from Steve Reich's Piano Phase, as well as three controlled manipulations and a popular-music remix of the work. Our analyses reveal that EEG and CB ISC are highest for the remix stimulus and lowest for our most repetitive manipulation, no statistical differences in overall EEG ISC between our most musically meaningful manipulations and Reich's original piece, and evidence that compositional features drove engagement in time-resolved ISC analyses. We also found that aesthetic evaluations corresponded well with overall EEG ISC. Finally we highlight co-occurrences between stimulus events and time-resolved EEG and CB ISC. We offer the CB paradigm as a useful analysis measure and note the value of minimalist compositions as a limit case for the neuroscientific study of music listening. Overall, our participants' neural, continuous behavioral, and question responses showed strong similarities that may help refine our understanding of the type of engagement indexed by ISC for musical stimuli.

Neural responses to natural visual motion are spatially selective across the visual field, with selectivity differing across brain areas and task.

It is well established that neural responses to visual stimuli are enhanced at select locations in the visual field. Although spatial selectivity and the effects of spatial attention are well understood for discrete tasks (e.g. visual cueing), little is known for naturalistic experience that involves continuous dynamic visual stimuli (e.g. driving). Here, we assess the strength of neural responses across the visual space during a kart-race game. Given the varying relevance of visual location in this task, we hypothesized that the strength of neural responses to movement will vary across the visual field, and it would differ between active play and passive viewing. To test this, we measure the correlation strength of scalp-evoked potentials with optical flow magnitude at individual locations on the screen. We find that neural responses are strongly correlated at task-relevant locations in visual space, extending beyond the focus of overt attention. Although the driver's gaze is directed upon the heading direction at the centre of the screen, neural responses were robust at the peripheral areas (e.g. roads and surrounding buildings). Importantly, neural responses to visual movement are broadly distributed across the scalp, with visual spatial selectivity differing across electrode locations. Moreover, during active gameplay, neural responses are enhanced at select locations in the visual space. Conventionally, spatial selectivity of neural response has been interpreted as an attentional gain mechanism. In the present study, the data suggest that different brain areas focus attention on different portions of the visual field that are task-relevant, beyond the focus of overt attention.

Visually evoked responses are enhanced when engaging in a video game.

While it is well known that vision guides movement, less appreciated is that the motor cortex also provides input to the visual system. Here, we asked whether neural processing of visual stimuli is acutely modulated during motor activity, hypothesizing that visual evoked responses are enhanced when engaged in a motor task that depends on the visual stimulus. To test this, we told participants that their brain activity was controlling a video game that was in fact the playback of a prerecorded game. The deception, which was effective in half of participants, aimed to engage the motor system while avoiding evoked responses related to actual movement or somatosensation. In other trials, subjects actively played the game with keyboard control or passively watched a playback. The strength of visually evoked responses was measured as the temporal correlation between the continuous stimulus and the evoked potentials on the scalp. We found reduced correlation during passive viewing, but no difference between active and sham play. Alpha-band (8-12 Hz) activity was reduced over central electrodes during sham play, indicating recruitment of motor cortex despite the absence of overt movement. To account for the potential increase of attention during gameplay, we conducted a second study with subjects counting screen items during viewing. We again found increased correlation during sham play, but no difference between counting and passive viewing. While we cannot fully rule out the involvement of attention, our findings do demonstrate an enhancement of visual evoked responses during active vision.

Natural music evokes correlated EEG responses reflecting temporal structure and beat.

The brain activity of multiple subjects has been shown to synchronize during salient moments of natural stimuli, suggesting that correlation of neural responses indexes a brain state operationally termed 'engagement'. While past electroencephalography (EEG) studies have considered both auditory and visual stimuli, the extent to which these results generalize to music-a temporally structured stimulus for which the brain has evolved specialized circuitry-is less understood. Here we investigated neural correlation during natural music listening by recording EEG responses from N=48 adult listeners as they heard real-world musical works, some of which were temporally disrupted through shuffling of short-term segments (measures), reversal, or randomization of phase spectra. We measured correlation between multiple neural responses (inter-subject correlation) and between neural responses and stimulus envelope fluctuations (stimulus-response correlation) in the time and frequency domains. Stimuli retaining basic musical features, such as rhythm and melody, elicited significantly higher behavioral ratings and neural correlation than did phase-scrambled controls. However, while unedited songs were self-reported as most pleasant, time-domain correlations were highest during measure-shuffled versions. Frequency-domain measures of correlation (coherence) peaked at frequencies related to the musical beat, although the magnitudes of these spectral peaks did not explain the observed temporal correlations. Our findings show that natural music evokes significant inter-subject and stimulus-response correlations, and suggest that the neural correlates of musical 'engagement' may be distinct from those of enjoyment.

Near-Infrared Light Increases Functional Connectivity with a Non-thermal Mechanism.

Although techniques for noninvasive brain stimulation are under intense investigation, an approach that has received limited attention is transcranial photobiomodulation (tPBM), the delivery of near-infrared light to the brain with a laser or light-emitting diode directed at the scalp. Here we employed functional magnetic resonance imaging to measure the blood-oxygenation-level-dependent signal in n = 20 healthy human participants while concurrently stimulating their right frontal pole with a near-infrared laser. Functional connectivity with the illuminated region increased by up to 15% during stimulation, with a quarter of all connections experiencing a significant increase. The time course of connectivity exhibited a sharp rise approximately 1 min after illumination onset. Brain-wide connectivity increases were also observed, with connections involving the stimulated hemisphere showing a significantly larger increase than those in the contralateral hemisphere. We subsequently employed magnetic resonance thermometry to measure brain temperature during tPBM (separate cohort, n = 20) and found no significant temperature differences between active and sham stimulation. Our findings suggest that near-infrared light synchronizes brain activity with a nonthermal mechanism, underscoring the promise of tPBM as a new technique for stimulating brain function.

Transcranial photobiomodulation with 1064-nm laser modulates brain electroencephalogram rhythms.

Noninvasive transcranial photobiomodulation (tPBM) with a 1064-nm laser has been reported to improve human performance on cognitive tasks as well as locally upregulate cerebral oxygen metabolism and hemodynamics. However, it is unknown whether 1064-nm tPBM also modulates electrophysiology, and specifically neural oscillations, in the human brain. The hypothesis guiding our study is that applying 1064-nm tPBM of the right prefrontal cortex enhances neurophysiological rhythms at specific frequency bands in the human brain under resting conditions. To test this hypothesis, we recorded the 64-channel scalp electroencephalogram (EEG) before, during, and after the application of 11 min of 4-cm-diameter tPBM (CW 1064-nm laser with 162 mW / cm 2 and 107 J / cm 2 ) to the right forehead of human subjects ( n = 20 ) using a within-subject, sham-controlled design. Time-resolved scalp topographies of EEG power at five frequency bands were computed to examine the tPBM-induced EEG power changes across the scalp. The results show time-dependent, significant increases of EEG spectral powers at the alpha (8 to 13 Hz) and beta (13 to 30 Hz) bands at broad scalp regions, exhibiting a front-to-back pattern. The findings provide the first sham-controlled topographic mapping that tPBM increases the strength of electrophysiological oscillations (alpha and beta bands) while also shedding light on the mechanisms of tPBM in the human brain.

Correlation of neural activity with behavioral kinematics reveals distinct sensory encoding and evidence accumulation processes during active tactile sensing.

Many real-world decisions rely on active sensing, a dynamic process for directing our sensors (e.g. eyes or fingers) across a stimulus to maximize information gain. Though ecologically pervasive, limited work has focused on identifying neural correlates of the active sensing process. In tactile perception, we often make decisions about an object/surface by actively exploring its shape/texture. Here we investigate the neural correlates of active tactile decision-making by simultaneously measuring electroencephalography (EEG) and finger kinematics while subjects interrogated a haptic surface to make perceptual judgments. Since sensorimotor behavior underlies decision formation in active sensing tasks, we hypothesized that the neural correlates of decision-related processes would be detectable by relating active sensing to neural activity. Novel brain-behavior correlation analysis revealed that three distinct EEG components, localizing to right-lateralized occipital cortex (LOC), middle frontal gyrus (MFG), and supplementary motor area (SMA), respectively, were coupled with active sensing as their activity significantly correlated with finger kinematics. To probe the functional role of these components, we fit their single-trial-couplings to decision-making performance using a hierarchical-drift-diffusion-model (HDDM), revealing that the LOC modulated the encoding of the tactile stimulus whereas the MFG predicted the rate of information integration towards a choice. Interestingly, the MFG disappeared from components uncovered from control subjects performing active sensing but not required to make perceptual decisions. By uncovering the neural correlates of distinct stimulus encoding and evidence accumulation processes, this study delineated, for the first time, the functional role of cortical areas in active tactile decision-making.

Extracting multidimensional stimulus-response correlations using hybrid encoding-decoding of neural activity.

In neuroscience, stimulus-response relationships have traditionally been analyzed using either encoding or decoding models. Here we propose a hybrid approach that decomposes neural activity into multiple components, each representing a portion of the stimulus. The technique is implemented via canonical correlation analysis (CCA) by temporally filtering the stimulus (encoding) and spatially filtering the neural responses (decoding) such that the resulting components are maximally correlated. In contrast to existing methods, this approach recovers multiple correlated stimulus-response pairs, and thus affords a richer, multidimensional analysis of neural representations. We first validated the technique's ability to recover multiple stimulus-driven components using electroencephalographic (EEG) data simulated with a finite element model of the head. We then applied the technique to real EEG responses to auditory and audiovisual narratives experienced identically across subjects, as well as uniquely experienced video game play. During narratives, both auditory and visual stimulus-response correlations (SRC) were modulated by attention and tracked inter-subject correlations. During video game play, SRC varied with game difficulty and the presence of a dual task. Interestingly, the strongest component extracted for visual and auditory features of film clips had nearly identical spatial distributions, suggesting that the predominant encephalographic response to naturalistic stimuli is supramodal. The diversity of these findings demonstrates the utility of measuring multidimensional SRC via hybrid encoding-decoding.

Optimal use of EEG recordings to target active brain areas with transcranial electrical stimulation.

To demonstrate causal relationships between brain and behavior, investigators would like to guide brain stimulation using measurements of neural activity. Particularly promising in this context are electroencephalography (EEG) and transcranial electrical stimulation (TES), as they are linked by a reciprocity principle which, despite being known for decades, has not led to a formalism for relating EEG recordings to optimal stimulation parameters. Here we derive a closed-form expression for the TES configuration that optimally stimulates (i.e., targets) the sources of recorded EEG, without making assumptions about source location or distribution. We also derive a duality between TES targeting and EEG source localization, and demonstrate that in cases where source localization fails, so does the proposed targeting. Numerical simulations with multiple head models confirm these theoretical predictions and quantify the achieved stimulation in terms of focality and intensity. We show that constraining the stimulation currents automatically selects optimal montages that involve only a few (4-7) electrodes, with only incremental loss in performance when targeting focal activations. The proposed technique allows brain scientists and clinicians to rationally target the sources of observed EEG and thus overcomes a major obstacle to the realization of individualized or closed-loop brain stimulation.

In-vivo measurements of human brain tissue conductivity using focal electrical current injection through intracerebral multicontact electrodes.

In-vivo measurements of human brain tissue conductivity at body temperature were conducted using focal electrical currents injected through intracerebral multicontact electrodes. A total of 1,421 measurements in 15 epileptic patients (age: 28 ± 10) using a radiofrequency generator (50 kHz current injection) were analyzed. Each contact pair was classified as being from healthy (gray matter, n = 696; white matter, n = 530) or pathological (epileptogenic zone, n = 195) tissue using neuroimaging analysis of the local tissue environment and intracerebral EEG recordings. Brain tissue conductivities were obtained using numerical simulations based on conductivity estimates that accounted for the current flow in the local brain volume around the contact pairs (a cube with a side length of 13 mm). Conductivity values were 0.26 S/m for gray matter and 0.17 S/m for white matter. Healthy gray and white matter had statistically different median impedances (P < 0.0001). White matter conductivity was found to be homogeneous as normality tests did not find evidence of multiple subgroups. Gray matter had lower conductivity in healthy tissue than in the epileptogenic zone (0.26 vs. 0.29 S/m; P = 0.012), even when the epileptogenic zone was not visible in the magnetic resonance image (MRI) (P = 0.005). The present in-vivo conductivity values could serve to create more accurate volume conduction models and could help to refine the identification of relevant intracerebral contacts, especially when located within the epileptogenic zone of an MRI-invisible lesion. Hum Brain Mapp 38:974-986, 2017. © 2016 Wiley Periodicals, Inc.

Cortical Components of Reaction-Time during Perceptual Decisions in Humans.

The mechanisms of perceptual decision-making are frequently studied through measurements of reaction time (RT). Classical sequential-sampling models (SSMs) of decision-making posit RT as the sum of non-overlapping sensory, evidence accumulation, and motor delays. In contrast, recent empirical evidence hints at a continuous-flow paradigm in which multiple motor plans evolve concurrently with the accumulation of sensory evidence. Here we employ a trial-to-trial reliability-based component analysis of encephalographic data acquired during a random-dot motion task to directly image continuous flow in the human brain. We identify three topographically distinct neural sources whose dynamics exhibit contemporaneous ramping to time-of-response, with the rate and duration of ramping discriminating fast and slow responses. Only one of these sources, a parietal component, exhibits dependence on strength-of-evidence. The remaining two components possess topographies consistent with origins in the motor system, and their covariation with RT overlaps in time with the evidence accumulation process. After fitting the behavioral data to a popular SSM, we find that the model decision variable is more closely matched to the combined activity of the three components than to their individual activity. Our results emphasize the role of motor variability in shaping RT distributions on perceptual decision tasks, suggesting that physiologically plausible computational accounts of perceptual decision-making must model the concurrent nature of evidence accumulation and motor planning.

Maximally reliable spatial filtering of steady state visual evoked potentials.

Due to their high signal-to-noise ratio (SNR) and robustness to artifacts, steady state visual evoked potentials (SSVEPs) are a popular technique for studying neural processing in the human visual system. SSVEPs are conventionally analyzed at individual electrodes or linear combinations of electrodes which maximize some variant of the SNR. Here we exploit the fundamental assumption of evoked responses--reproducibility across trials--to develop a technique that extracts a small number of high SNR, maximally reliable SSVEP components. This novel spatial filtering method operates on an array of Fourier coefficients and projects the data into a low-dimensional space in which the trial-to-trial spectral covariance is maximized. When applied to two sample data sets, the resulting technique recovers physiologically plausible components (i.e., the recovered topographies match the lead fields of the underlying sources) while drastically reducing the dimensionality of the data (i.e., more than 90% of the trial-to-trial reliability is captured in the first four components). Moreover, the proposed technique achieves a higher SNR than that of the single-best electrode or the Principal Components. We provide a freely-available MATLAB implementation of the proposed technique, herein termed "Reliable Components Analysis".

Audience preferences are predicted by temporal reliability of neural processing.

Naturalistic stimuli evoke highly reliable brain activity across viewers. Here we record neural activity from a group of naive individuals while viewing popular, previously-broadcast television content for which the broad audience response is characterized by social media activity and audience ratings. We find that the level of inter-subject correlation in the evoked encephalographic responses predicts the expressions of interest and preference among thousands. Surprisingly, ratings of the larger audience are predicted with greater accuracy than those of the individuals from whom the neural data is obtained. An additional functional magnetic resonance imaging study employing a separate sample of subjects shows that the level of neural reliability evoked by these stimuli covaries with the amount of blood-oxygenation-level-dependent (BOLD) activation in higher-order visual and auditory regions. Our findings suggest that stimuli which we judge favourably may be those to which our brains respond in a stereotypical manner shared by our peers.

Clinician accessible tools for GUI computational models of transcranial electrical stimulation: BONSAI and SPHERES.

Computational models of brain current flow during transcranial electrical stimulation (tES), including transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS), are increasingly used to understand and optimize clinical trials. We propose that broad dissemination requires a simple graphical user interface (GUI) software that allows users to explore and design montages in real-time, based on their own clinical/experimental experience and objectives. We introduce two complimentary open-source platforms for this purpose: BONSAI and SPHERES. BONSAI is a web (cloud) based application (available at neuralengr.com/bonsai) that can be accessed through any flash-supported browser interface. SPHERES (available at neuralengr.com/spheres) is a stand-alone GUI application that allow consideration of arbitrary montages on a concentric sphere model by leveraging an analytical solution. These open-source tES modeling platforms are designed go be upgraded and enhanced. Trade-offs between open-access approaches that balance ease of access, speed, and flexibility are discussed.

EEG precursors of detected and missed targets during free-viewing search.

When scanning a scene, the target of our search may be in plain sight and yet remain unperceived. Conversely, at other times the target may be perceived in the periphery prior to fixation. There is ample behavioral and neurophysiological evidence to suggest that in some constrained visual-search tasks, targets are detected prior to fixational eye movements. However, limited human data are available during unconstrained search to determine the time course of detection, the brain areas involved, and the neural correlates of failures to detect a foveated target. Here, we recorded and analyzed electroencephalographic (EEG) activity during free-viewing visual search, varying the task difficulty to compare neural signatures for detected and unreported ("missed") targets. When carefully controlled to remove eye-movement-related potentials, saccade-locked EEG shows that: (a) "Easy" targets may be detected as early as 150 ms prior to foveation, as indicated by a premotor potential associated with a button response; (b) object-discriminating occipital activity emerges during the saccade to target; and (c) success and failures to detect a target are accompanied by a modulation in alpha-band power over fronto-central areas as well as altered saccade dynamics. Taken together, these data suggest that target detection during free viewing can begin prior to and continue during a saccade, with failure or success in reporting a target possibly resulting from inhibition or activation of fronto-central processing areas associated with saccade control.