Noninvasive Neuromodulation Goes Deep.

Modulating deep regions of the brain with noninvasive technology has challenged researchers for decades. In a new study, Grossman et al. leverage the emergence of a slowly oscillating "beat" from intersecting high-frequency electric fields to stimulate deep brain regions, opening a frontier in the biophysics and technology of brain stimulation.

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.

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.

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.

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.

Inherent physiological artifacts in EEG during tDCS.

Online imaging and neuromodulation is invalid if stimulation distorts measurements beyond the point of accurate measurement. In theory, combining transcranial Direct Current Stimulation (tDCS) with electroencephalography (EEG) is compelling, as both use non-invasive electrodes and image-guided dose can be informed by the reciprocity principle. To distinguish real changes in EEG from stimulation artifacts, prior studies applied conventional signal processing techniques (e.g. high-pass filtering, ICA). Here, we address the assumptions underlying the suitability of these approaches. We distinguish physiological artifacts - defined as artifacts resulting from interactions between the stimulation induced voltage and the body and so inherent regardless of tDCS or EEG hardware performance - from methodology-related artifacts - arising from non-ideal experimental conditions or non-ideal stimulation and recording equipment performance. Critically, we identify inherent physiological artifacts which are present in all online EEG-tDCS: 1) cardiac distortion and 2) ocular motor distortion. In conjunction, non-inherent physiological artifacts which can be minimized in most experimental conditions include: 1) motion and 2) myogenic distortion. Artifact dynamics were analyzed for varying stimulation parameters (montage, polarity, current) and stimulation hardware. Together with concurrent physiological monitoring (ECG, respiration, ocular, EMG, head motion), and current flow modeling, each physiological artifact was explained by biological source-specific body impedance changes, leading to incremental changes in scalp DC voltage that are significantly larger than real neural signals. Because these artifacts modulate the DC voltage and scale with applied current, they are dose specific such that their contamination cannot be accounted for by conventional experimental controls (e.g. differing stimulation montage or current as a control). Moreover, because the EEG artifacts introduced by physiologic processes during tDCS are high dimensional (as indicated by Generalized Singular Value Decomposition- GSVD), non-stationary, and overlap highly with neurogenic frequencies, these artifacts cannot be easily removed with conventional signal processing techniques. Spatial filtering techniques (GSVD) suggest that the removal of physiological artifacts would significantly degrade signal integrity. Physiological artifacts, as defined here, would emerge only during tDCS, thus processing techniques typically applied to EEG in the absence of tDCS would not be suitable for artifact removal during tDCS. All concurrent EEG-tDCS must account for physiological artifacts that are a) present regardless of equipment used, and b) broadband and confound a broad range of experiments (e.g. oscillatory activity and event related potentials). Removal of these artifacts requires the recognition of their non-stationary, physiology-specific dynamics, and individualized nature. We present a broad taxonomy of artifacts (non/stimulation related), and suggest possible approaches and challenges to denoising online EEG-tDCS stimulation artifacts.

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.

Minimal Heating at the Skin Surface During Transcranial Direct Current Stimulation.

OBJECTIVE: To assess if transcranial direct current stimulation (tDCS) produces a temperature change at the skin surface, if any change is stimulation polarity (anode or cathode) specific, and the contribution of passive heating (joule heat) or blood flow on such change. MATERIAL AND METHODS: Temperature differences (ΔTs) in an agar phantom study and an in vivo study (forearm stimulation) including 20 volunteers with both experimental measures and finite element method (FEM) multiphysics prediction (current flow and bioheat) models of skin comprising three tissue layers (epidermis, dermis, and subcutaneous layer with blood perfusion) or of the phantom for active stimulation and control cases were compared. Temperature was measured during pre, post, and stimulation phases for both phantom and subject's forearms using thermocouples. RESULTS: In the phantom, ΔT under both anode and cathode, compared to control, was not significantly different and less than 0.1°C. Stimulation of subjects resulted in a gradual increase in temperature under both anode and cathode electrodes, compared to control (at t = 20 min: ΔTanode = 0.9°C, ΔTcathode = 1.1°C, ΔTcontrol = 0.05°C). The FEM phantom model predicted comparable maximum ΔT of 0.27°C and 0.28°C (at t = 20 min) for the control and anode/cathode cases, respectively. The FEM skin model predicted a maximum ΔT at t = 20 min of 0.98°C for control and 1.36°C under anode/cathode electrodes. CONCLUSIONS: Taken together, our results indicate a moderate and nonhazardous increase in temperature at the skin surface during 2 mA tDCS that is independent of polarity, and results from stimulation induced blood flow rather than joule heat.

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.

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".

Brief motivational intervention for heavy drinking mandated and voluntary freshmen: A 1-year follow-up assessment.

BACKGROUND: Alcohol abuse among freshmen university students is a major public health issue with associated costs to individuals and the society of substantial morbidity, high-risk negative behaviors (e.g., blackouts, rape, suicide, and violence), and mortality. This longitudinal study compared the effectiveness of a brief motivational intervention (MI) in decreasing alcohol consumption and related consequences among mandated students and voluntary students. Readiness to change drinking behaviors was compared between the groups. METHODS: Eligible participants (710 voluntary and 190 mandated, N = 900) received MI at baseline and again at 2 weeks with boosters at 3, 6, and 12 months. Repeated-measures analysis of variance was used to compare the two groups. RESULTS: Alcohol use and related consequences in both groups decreased significantly between baseline and 12 months. At baseline, a significantly larger percent of students from the mandated group than the voluntary group were in the action stage of change (52.1% vs. 27.5%), and a significantly smaller percentage of mandated students were in the precontemplation stage (p < .0001). DISCUSSION: MI effects were sustained over 12 months. Alcohol consumption and related consequences decreased significantly among the freshmen who were mandated to attend the program as well as among students who volunteered to participate in the study. The findings support the importance of advanced practice nurses conducting MI as an intervention with college students.

Is breakfast skipping associated with physical activity among U.S. adolescents? A cross-sectional study of adolescents aged 12-19 years, National Health and Nutrition Examination Survey (NHANES).

OBJECTIVE: To examine the association between breakfast skipping and physical activity among US adolescents aged 12-19 years. DESIGN: A cross-sectional study of nationally representative 2007-2008 National Health and Nutrition Examination Survey (NHANES) data. SETTING: Breakfast skipping was assessed by two 24 h dietary recalls. Physical activity was self-reported by participants and classified based on meeting national recommendations for physical activity for the appropriate age group. Multiple logistic regression analysis was used to model the association between breakfast skipping and physical activity while controlling for confounders. SUBJECTS: A total of 936 adolescents aged 12-19 years in the USA. RESULTS: After adjusting for family income, there was no association between breakfast skipping and meeting physical activity guidelines for age among adolescents aged 12-19 years (OR = 0.95, 95% CI 0.56, 1.32). CONCLUSIONS: Findings from the study differ from previous research findings on breakfast skipping and physical activity. Therefore, further research that uses large, nationally representative US samples and national recommended guidelines for physical activity is needed.

Comparison of prospective and retrospective measurements of frequency of sexual intercourse.

Measurements of sexual intercourse frequency are informative for research on pregnancy, contraception, and the transmission of sexually transmitted infections; however, efficiently collecting data on this sensitive topic is complex. The purpose of this study was to determine whether retrospective recall of sexual intercourse frequency was consistent with information obtained through the use of prospective daily diary methods corresponding to the same time period in a diverse sample of women. A total of 185 women participated in a longitudinal, prospective cohort study of oral contraceptive users and 98 of these women provided complete information on sexual intercourse frequency on diaries (prospective) and postcards (retrospective). Linear mixed models were used to test for variation in response within categories of demographic and other variables. The mean number of days women had sexual intercourse per week was 1.5 days using prospective diary information versus 2.0 days when using 3-month retrospective recall (p < 0.001). Mean differences for the various sociodemographic subgroups were positive for all groups indicating that women consistently reported a higher frequency of sexual intercourse on the retrospective postcards than they recorded on their prospective diaries; however, these mean differences did not vary significantly. If confirmed in other samples, the use of retrospective methods may be adequate to accurately collect data on sexual intercourse frequency-and may be preferable. Using only retrospective measurements could decrease study costs, the burden to participants, and have a higher response rate.

Personality Risk Factors and Readiness to Change in Mandated and Voluntary College Students Enrolled in an Alcohol Intervention Program.

This study compared personality risk factors and readiness to change drinking behavior among mandated and volunteer college students. The sample (N = 583) completed three measures of motivation to change and personality risk factors at baseline, 3 months, and 6 months between 2011 and 2012. Linear mixed models were used to determine an association of continuous outcome variable(s) with covariates over time. Participants in the action stage had lower impulsivity scores. Gender was significant, with females showing the highest anxiety and lowest sensation seeking. The findings indicate a number of future directions to advance innovative alcohol intervention and treatment programs on college campuses.

Cranial electrotherapy stimulation and transcranial pulsed current stimulation: a computer based high-resolution modeling study.

The field of non-invasive brain stimulation has developed significantly over the last two decades. Though two techniques of noninvasive brain stimulation--transcranial direct current stimulation (tDCS) and transcranial magnetic stimulation (TMS)--are becoming established tools for research in neuroscience and for some clinical applications, related techniques that also show some promising clinical results have not been developed at the same pace. One of these related techniques is cranial electrotherapy stimulation (CES), a class of transcranial pulsed current stimulation (tPCS). In order to understand further the mechanisms of CES, we aimed to model CES using a magnetic resonance imaging (MRI)-derived finite element head model including cortical and also subcortical structures. Cortical electric field (current density) peak intensities and distributions were analyzed. We evaluated different electrode configurations of CES including in-ear and over-ear montages. Our results confirm that significant amounts of current pass the skull and reach cortical and subcortical structures. In addition, depending on the montage, induced currents at subcortical areas, such as midbrain, pons, thalamus and hypothalamus are of similar magnitude than that of cortical areas. Incremental variations of electrode position on the head surface also influence which cortical regions are modulated. The high-resolution modeling predictions suggest that details of electrode montage influence current flow through superficial and deep structures. Finally we present laptop based methods for tPCS dose design using dominant frequency and spherical models. These modeling predictions and tools are the first step to advance rational and optimized use of tPCS and CES.

Targeted transcranial direct current stimulation for rehabilitation after stroke.

Transcranial direct current stimulation (tDCS) is being investigated as an adjunctive technique to behavioral rehabilitation treatment after stroke. The conventional "dosage", consisting of a large (25 cm(2)) anode over the target with the cathode over the contralateral hemisphere, has been previously shown to yield broadly distributed electric fields whose intensities at the target region are less than maximal. Here, we report the results of a systematic targeting procedure with small "high-definition" electrodes that was used in preparation for a pilot study on 8 stroke patients with chronic aphasia. We employ functional and anatomical magnetic resonance imagery (fMRI/MRI) to define a target and optimize (with respect to the electric field magnitude at the target) the electrode configuration, respectively, and demonstrate that electric field strengths in targeted cortex can be substantially increased (63%) over the conventional approach. The optimal montage exhibits significant variation across subjects as well as when perturbing the target location within a subject. However, for each displacement of the target co-ordinates, the algorithm is able to determine a montage which delivers a consistent amount of current to that location. These results demonstrate that MRI-based models of current flow yield maximal stimulation of target structures, and as such, may aid in reliably assessing the efficacy of tDCS in neuro-rehabilitation.

Effects of motivational interviewing intervention on blackouts among college freshmen.

PURPOSE: Alcohol and illicit drug abuse is a serious public health issue facing college students. This study examined the impact of motivational interviewing (MI) as an intervention on the rate of blackouts among freshmen who engaged in high-risk drinking and illicit drug use. DESIGN: A sample of 188 volunteer freshmen from a university were administered the Daily Drinking Questionnaire, the Rutgers Alcohol Problem Index, and the Government Performance and Results Act at baseline and again at 6 months postintervention. MI was applied at baseline and then again at 2 weeks, 3 months, and 6 months. METHODS: Generalized estimated equations and logistic regression models were used to determine associations between the rate of blackouts and time, ethnicity, gender, illicit drug use, and alcohol consumption. FINDINGS: At 6 months, the rate of blackouts decreased from 40% at baseline to 16% (p < .0001). The average number, time, and days of drinking and frequency of drug use also decreased significantly (p < .0001). An association between rate of blackouts and gender was observed, but not with ethnicity. CONCLUSIONS: MI had an impact on reducing alcohol consumption and the rate of blackouts among college freshmen who were engaging in high-risk drinking and illicit drug use. CLINICAL RELEVANCE: The findings support the importance of using MI with freshmen college students to decrease drinking and the associated negative consequences, including blackouts, which has particular relevance for advanced practice registered nurses, physicians, and community health nurses who conduct MI as an intervention with college students.

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.