Activation of primate frontal eye fields with a CMUT phased array system.

BACKGROUND: There are pushes toward non-invasive stimulation of neural tissues to prevent issues that arise from invasive brain recordings and stimulation. Transcranial Focused Ultrasound (TFUS) has been examined as a way to stimulate non-invasively, but previous studies have limitations in the application of TFUS. As a result, refinement is needed to improve stimulation results. NEW METHOD: We utilized a custom-built capacitive micromachined ultrasonic transducer (CMUT) that would send ultrasonic waves through skin and skull to targets located in the Frontal Eye Fields (FEF) region triangulated from co-registered MRI and CT scans while a non-human primate subject was performing a discrimination behavioral task. RESULTS: We observed that the stimulation immediately caused changes in the local field potential (LFP) signal that continued until stimulation ended, at which point there was higher voltage upon the cue for the animal to saccade. This co-incided with increases in activity in the alpha band during stimulation. The activity rebounded mid-way through our electrode-shank, indicating a specific point of stimulation along the shank. We observed different LFP signals for different stimulation targets, indicating the ability to"steer" the stimulation through the transducer. We also observed a bias in first saccades towards the opposite direction. CONCLUSIONS: In conclusion, we provide a new approach for non-invasive stimulation during performance of a behavioral task. With the ability to steer stimulation patterns and target using a large amount of transducers, the ability to provide non-invasive stimulation will be greatly improved for future clinical and research applications.

Short Duration Repetitive Transcranial Electrical Stimulation During Sleep Enhances Declarative Memory of Facts.

Transcranial electrical stimulation (tES) during sleep has been shown to successfully modulate memory consolidation. Here, we tested the effect of short duration repetitive tES (SDR-tES) during a daytime nap on the consolidation of declarative memory of facts in healthy individuals. We use a previously described approach to deliver the stimulation at regular intervals during non-rapid eye movement (NREM) sleep, specifically stage NREM2 and NREM3. Similar to previous studies using tES, we find enhanced memory performance compared to sham both after sleep and 48 h later. We also observed an increase in the proportion of time spent in NREM3 sleep and SDR-tES boosted the overall rate of slow oscillations (SOs) during NREM2/NREM3 sleep. Retrospective investigation of brain activity immediately preceding stimulation suggests that increases in the SO rate are more likely when stimulation is delivered during quiescent and asynchronous periods of activity in contrast to other closed-loop approaches which target phasic stimulation during ongoing SOs.

Closed-Loop Targeted Memory Reactivation during Sleep Improves Spatial Navigation.

Sounds associated with newly learned information that are replayed during non-rapid eye movement (NREM) sleep can improve recall in simple tasks. The mechanism for this improvement is presumed to be reactivation of the newly learned memory during sleep when consolidation takes place. We have developed an EEG-based closed-loop system to precisely deliver sensory stimulation at the time of down-state to up-state transitions during NREM sleep. Here, we demonstrate that applying this technology to participants performing a realistic navigation task in virtual reality results in a significant improvement in navigation efficiency after sleep that is accompanied by increases in the spectral power especially in the fast (12-15 Hz) sleep spindle band. Our results show promise for the application of sleep-based interventions to drive improvement in real-world tasks.

Combining Real-Time fMRI Neurofeedback Training of the DLPFC with N-Back Practice Results in Neuroplastic Effects Confined to the Neurofeedback Target Region.

In traditional fMRI, individuals respond to exogenous stimuli and are naïve to the effects of the stimuli on their neural activity patterns. Changes arising in the fMRI signal are analyzed post-hoc to elucidate the spatial and temporal activation of brain regions associated with the tasks performed. The advent of real-time fMRI has enabled a new method to systematically alter brain activity across space and time using neurofeedback training (NFT), providing a new tool to study internally-driven processes such as neuroplasticity. In this work, we combined n-back practice with fMRI-NFT of the left dorsolateral prefrontal cortex (DLPFC) to better understand the relationship between open- and closed-loop neuromodulation. FMRI data were acquired during both traditional n-back and NFT across five imaging sessions. Region-of-interest (ROI) and voxel-wise 2 × 2 within subjects ANOVAs were carried out to determine the effects of, and interaction between, training session and neuromodulation type. A main effect of training session was identified for only a single, highly focused cluster that shared spatial properties with the fMRI-NFT target region (left DLPFC). This finding indicates that combined open- and closed-loop neuroplastic enhancement techniques result in focal changes that are confined to the target area of NFT, and do not affect up- or down-stream network components that are normally engaged during working memory. Additionally, we identified a main effect of neuromodulation type for 15 clusters with significantly different activation between open- and closed-loop neuromodulation during training, 12 of which demonstrated higher activity during the open-loop neuromodulation. Our results, taken together with previous reports, indicate that fMRI-NFT combined with n-back practice leads to a highly focal volume exhibiting neuroplasticity without additional network effects.

Enhanced control of dorsolateral prefrontal cortex neurophysiology with real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback training and working memory practice.

Real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback can be used to train localized, conscious regulation of blood oxygen level-dependent (BOLD) signals. As a therapeutic technique, rt-fMRI neurofeedback reduces the symptoms of a variety of neurologic disorders. To date, few studies have investigated the use of self-regulation training using rt-fMRI neurofeedback to enhance cognitive performance. This work investigates the utility of rt-fMRI neurofeedback as a tool to enhance human cognition by training healthy individuals to consciously control activity in the left dorsolateral prefrontal cortex (DLPFC). A cohort of 18 healthy participants in the experimental group underwent rt-fMRI neurofeedback from the left DLPFC in five training sessions across two weeks while 7 participants in the control group underwent similar training outside the MRI and without rt-fMRI neurofeedback. Working memory (WM) performance was evaluated on two testing days separated by the five rt-fMRI neurofeedback sessions using two computerized tests. We investigated the ability to control the BOLD signal across training sessions and WM performance across the two testing days. The group with rt-fMRI neurofeedback demonstrated a significant increase in the ability to self-regulate the BOLD signal in the left DLPFC across sessions. WM performance showed differential improvement between testing days one and two across the groups with the highest increases observed in the rt-fMRI neurofeedback group. These results provide evidence that individuals can quickly gain the ability to consciously control the left DLPFC, and this training results in improvements of WM performance beyond that of training alone.

Reliable activation to novel stimuli predicts higher fluid intelligence.

The ability to reliably respond to stimuli could be an important biological determinant of differences in fluid intelligence (Gf). However, most electrophysiological studies of Gf employ event-related potential (ERP) measures that average brain activity over trials, and hence have limited power to quantify neural variability. Time-frequency analyses can capture cross-trial variation in the phase of neural activity, and thus can help address the importance of neural reliability to differences in Gf. This study recruited a community sample of healthy adults and measured inter-trial phase clustering (ITPC), total spectral power, and ERP amplitudes elicited by Repeated and Novel non-target stimuli during two visual oddball tasks. Condition effects, relations among the EEG measures, and relations with Gf were assessed. Early visual responses to Repeated stimuli elicited higher ITPC, yet only ITPC elicited by Novel stimuli was associated with Gf. Analyses of spectral power further highlighted the contribution of phase consistency to the findings. The link between Gf and reliable responding to changing inputs suggests an important role for flexible resource allocation in fluid intellectual skills.

High-order interactions observed in multi-task intrinsic networks are dominant indicators of aberrant brain function in schizophrenia.

Identifying the complex activity relationships present in rich, modern neuroimaging data sets remains a key challenge for neuroscience. The problem is hard because (a) the underlying spatial and temporal networks may be nonlinear and multivariate and (b) the observed data may be driven by numerous latent factors. Further, modern experiments often produce data sets containing multiple stimulus contexts or tasks processed by the same subjects. Fusing such multi-session data sets may reveal additional structure, but raises further statistical challenges. We present a novel analysis method for extracting complex activity networks from such multifaceted imaging data sets. Compared to previous methods, we choose a new point in the trade-off space, sacrificing detailed generative probability models and explicit latent variable inference in order to achieve robust estimation of multivariate, nonlinear group factors ("network clusters"). We apply our method to identify relationships of task-specific intrinsic networks in schizophrenia patients and control subjects from a large fMRI study. After identifying network-clusters characterized by within- and between-task interactions, we find significant differences between patient and control groups in interaction strength among networks. Our results are consistent with known findings of brain regions exhibiting deviations in schizophrenic patients. However, we also find high-order, nonlinear interactions that discriminate groups but that are not detected by linear, pairwise methods. We additionally identify high-order relationships that provide new insights into schizophrenia but that have not been found by traditional univariate or second-order methods. Overall, our approach can identify key relationships that are missed by existing analysis methods, without losing the ability to find relationships that are known to be important.

Acceleration of image analyst training with transcranial direct current stimulation.

Humans today are routinely and increasingly presented with vast quantities of data that challenge their capacity for efficient processing. To restore the balance between man and machine, it is worthwhile to explore new methods for enhancing or accelerating this capacity. This study was designed to investigate the efficacy of transcranial DC stimulation (tDCS) to reduce training time and increase proficiency in spatial recognition using a simulated synthetic aperture radar (SAR) task. Twenty-seven Air Force active duty members volunteered to participate in the study. Each participant was assigned to 1 of 3 stimulation groups and received two, 90-min training sessions on a target search and identification task using SAR imagery followed by a test. The tDCS anode was applied to site F10 according to the 10-20 electroencephalographic electrode convention while the cathode was placed on the contralateral bicep. Group 1 received anodal tDCS at 2 mA for 30 min in the first training session and sham tDCS in the second session. Group 2 received the stimulation conditions in the opposite order. Group 3 did not receive stimulation at all. Results showed that participants receiving training plus tDCS attained visual search accuracies ~25% higher than those provided with sham stimulation or no stimulation. However, a corresponding performance improvement was not found in the first training session for the change detection portion of the task. This indicates that experience with the imagery is important in the tDCS-elicited performance improvements in change detection.

Frontotemporal anatomical connectivity and working-relational memory performance predict everyday functioning in schizophrenia.

Hippocampal (relational memory) and prefrontal cortex (PFC; working memory) impairments have been found in patients with schizophrenia (SP), possibly due to a dysfunctional connection between structures. Neuroanatomical studies that describe reduced fractional anisotropy (FA) in the uncinate fasciculus support this idea. The dysconnection hypothesis in SP was investigated by examining frontotemporal anatomical connectivity (uncinate fasciculus FA) and PFC-hippocampal memory and their relationship with each other and everyday functioning. PFC-hippocampal memory was examined with two working-relational memory tasks: transverse patterning and a virtual Morris water task. SP exhibited a performance deficit on both tasks and had lower FA in bilateral uncinate fasciculus than healthy volunteers. Lower frontotemporal anatomical connectivity was related to lower working-relational memory performance, and both predicted worse everyday functioning.

TDCS guided using fMRI significantly accelerates learning to identify concealed objects.

The accurate identification of obscured and concealed objects in complex environments was an important skill required for survival during human evolution, and is required today for many forms of expertise. Here we used transcranial direct current stimulation (tDCS) guided using neuroimaging to increase learning rate in a novel, minimally guided discovery-learning paradigm. Ninety-six subjects identified threat-related objects concealed in naturalistic virtual surroundings used in real-world training. A variety of brain networks were found using functional magnetic resonance imaging (fMRI) data collected at different stages of learning, with two of these networks focused in right inferior frontal and right parietal cortex. Anodal 2.0 mA tDCS performed for 30 min over these regions in a series of single-blind, randomized studies resulted in significant improvements in learning and performance compared with 0.1 mA tDCS. This difference in performance increased to a factor of two after a one-hour delay. A dose-response effect of current strength on learning was also found. Taken together, these brain imaging and stimulation studies suggest that right frontal and parietal cortex are involved in learning to identify concealed objects in naturalistic surroundings. Furthermore, they suggest that the application of anodal tDCS over these regions can greatly increase learning, resulting in one of the largest effects on learning yet reported. The methods developed here may be useful to decrease the time required to attain expertise in a variety of settings.

Bilateral hippocampal dysfunction in schizophrenia.

The hippocampus has long been known to be important for memory, with the right hippocampus particularly implicated in nonverbal/visuo-spatial memory and the left in verbal/narrative or episodic memory. Despite this hypothesized lateralized functional difference, there has not been a single task that has been shown to activate both the right and left hippocampi differentially, dissociating the two, using neuroimaging. The transverse patterning (TP) task is a strong candidate for this purpose, as it has been shown in human and nonhuman animal studies to theoretically and empirically depend on the hippocampus. In TP, participants choose between stimuli presented in pairs, with the correct choice being a function of the specific pairing. In this project, TP was used to assess lateralized hippocampal function by varying its dependence on verbal material, with the goal of dissociating the two hippocampi. Magnetoencephalographic (MEG) data were collected while controls performed verbal and nonverbal versions of TP in order to verify and validate lateralized activation within the hippocampi. Schizophrenia patients were evaluated to determine whether they exhibited a lateralized hippocampal deficit. As hypothesized, patients' mean level of behavioral performance was poorer than controls' on both verbal and nonverbal TP. In contrast, patients had no decrement in performance on a verbal and nonverbal non-hippocampal-dependent matched control task. Also, controls but not patients showed more right hippocampal activation during nonverbal TP and more left hippocampal activation during verbal TP. These data demonstrate the capacity to assess lateralized hippocampal function and suggest a bilateral hippocampal behavioral and activation deficit in schizophrenia.

Effective connectivity analysis of fMRI and MEG data collected under identical paradigms.

Estimation of effective connectivity, a measure of the influence among brain regions, can potentially reveal valuable information about organization of brain networks. Effective connectivity is usually evaluated from the functional data of a single modality. In this paper we show why that may lead to incorrect conclusions about effective connectivity. In this paper we use Bayesian networks to estimate connectivity on two different modalities. We analyze structures of estimated effective connectivity networks using aggregate statistics from the field of complex networks. Our study is conducted on functional MRI and magnetoencephalography data collected from the same subjects under identical paradigms. Results showed some similarities but also revealed some striking differences in the conclusions one would make on the fMRI data compared with the MEG data and are strongly supportive of the use of multiple modalities in order to gain a more complete picture of how the brain is organized given the limited information one modality is able to provide.

Magnetoencephalographic and magnetic resonance spectroscopy evidence of regional functional abnormality in mesial temporal lobe epilepsy.

Mesial temporal lobe epilepsy (mTLE) with mesial temporal sclerosis (MTS) is a recognized epilepsy syndrome which is successfully treated with mesial temporal lobe resection. However, recent studies suggest that mTLE is more than a "focal" disease process. The objective of our study was to determine the presence and extent of functional abnormalities outside of a defined structural abnormality in epilepsy patients with mTLE. We used a prospective age-matched controlled design to study eight consecutive patients with MTS who were undergoing epilepsy surgery evaluation. Magnetoencephalography was used to localize the sources of electromagnetic abnormality. Proton magnetic resonance spectroscopy ((1)H-MRS) measured integrated peak areas for N-acetyl compounds (NAA) and choline-containing compounds (Cho) to determine regions of metabolic abnormality. All eight subjects had predominant electromagnetic abnormality in the temporal lobe ipsilateral to the MTS. All eight subjects had lower NAA/Cho ratios in the region of electromagnetic abnormality when compared to the homologous contralateral region (P < 0.001). Four subjects had predominant MEG spiking outside the mesial temporal region. Surgery-free outcome for the group with neuroimaging abnormalities outside of the medial temporal lobe is 50%. The region of maximal electromagnetic abnormality is outside the hippocampus in some patients with mTLE. These regions also demonstrate functional abnormalities. Our findings support the concept that mTLE is a more diffuse process than the hippocampal structural abnormality, which may impact surgical outcome.

MEG and fMRI Fusion for Non-Linear Estimation of Neural and BOLD Signal Changes.

The combined analysis of magnetoencephalography (MEG)/electroencephalography and functional magnetic resonance imaging (fMRI) measurements can lead to improvement in the description of the dynamical and spatial properties of brain activity. In this paper we empirically demonstrate this improvement using simulated and recorded task related MEG and fMRI activity. Neural activity estimates were derived using a dynamic Bayesian network with continuous real valued parameters by means of a sequential Monte Carlo technique. In synthetic data, we show that MEG and fMRI fusion improves estimation of the indirectly observed neural activity and smooths tracking of the blood oxygenation level dependent (BOLD) response. In recordings of task related neural activity the combination of MEG and fMRI produces a result with greater signal-to-noise ratio, that confirms the expectation arising from the nature of the experiment. The highly non-linear model of the BOLD response poses a difficult inference problem for neural activity estimation; computational requirements are also high due to the time and space complexity. We show that joint analysis of the data improves the system's behavior by stabilizing the differential equations system and by requiring fewer computational resources.

Schizophrenia diagnosis and anterior hippocampal volume make separate contributions to sensory gating.

Impaired P50 gating is thought to reflect a core deficit in schizophrenia, but the relevant neural network is not well understood. The present study used EEG and MEG to assess sensory gating and volumetric MRI to measure hippocampal volume to investigate relationships between them in 22 normal controls and 22 patients with schizophrenia. In the schizophrenia group, anterior but not posterior hippocampal volume was smaller, and both the P50 and M50 gating ratios were larger (worse) than in controls. Independent of group, left-hemisphere M50 gating ratio correlated negatively with left anterior hippocampal volume, and right-hemisphere M50 gating ratio correlated negatively with right anterior hippocampal volume. Schizophrenia diagnosis predicted M50 gating independent of hippocampal volume. These results are consistent with the finding that hippocampus is a critical part of a fronto-temporal circuit involved in auditory gating.

Superior temporal gyrus spectral abnormalities in schizophrenia.

Considerable evidence indicates early auditory stimulus processing abnormalities in schizophrenia, but the mechanisms are unclear. The present study examined oscillatory phenomena during a paired-click paradigm in the superior temporal gyrus (STG) as a possible core problem. The primary question addressed is whether first click and/or second click group differences in the time-domain evoked response in patients with schizophrenia are due to (1) group differences in the magnitude of poststimulus oscillatory activity, (2) group differences in poststimulus phase-locking, and/or (3) group differences in the magnitude of ongoing background oscillatory activity. Dense-array magnetoencephalography from 45 controls and 45 patients with schizophrenia produced left- and right-hemisphere STG 50- and 100-ms time-frequency evoked, phase-locking, and total power measures. Whereas first click 100-ms evoked theta and alpha abnormalities were observed bilaterally, evoked low beta-band differences were specific to the left hemisphere. Compared to controls, patients with schizophrenia showed more low-frequency phase variability, and the decreased 100-ms S1 evoked response observed in patients was best predicted by the STG phase-locking measure.

The relative influence of place and direction in the Morris water task.

Previous work from our laboratory has demonstrated that rats display a preference for directional responding over true place navigation in the Morris water task. The present study evaluated the range of situations in which this preference is observed and attempted to identify methods that favor navigation to the precise location of the escape platform in the room. A preference for directional responding over place navigation was observed in a wide range of procedures that included providing extensive training (Experiment 1), providing only platform placement experience in the absence of active swim training (Experiment 2), training navigation to multiple platform locations in a moving platform variant of the task (Experiment 3), and explicitly training navigation to a precise location in the room, versus navigation in a particular direction, regardless of the pool's position in the room (Experiments 4-5). A modest preference for navigation to the precise spatial location of the platform was observed when the pool wall was virtually eliminated as a source of control by filling it to the top with water (Experiment 6).

How do room and apparatus cues control navigation in the Morris water task? Evidence for distinct contributions to a movement vector.

The present study compared the relative influence of location and direction on navigation in the Morris water task. Rats were trained with a fixed hidden or cued platform, and probe trials were conducted with the pool repositioned such that the absolute spatial location of the platform was centered in the opposite quadrant of the pool. Rather than swimming to the platform location, rats swam in the direction that was reinforced during training, resulting in navigation to the relative location of the platform in the pool and search at the appropriate distance from the pool wall. Pool relocation tests revealed disruptions in cued navigation if the cued platform remained at the absolute location, whereas no disruption was observed if the platform remained at the relative location (same direction). The results indicate that direction holds greater influence than does location and further demonstrate that this observation is not altered by the amount of training or time on the platform. The authors propose that navigation in the water task involves a movement vector in which the distal cues and apparatus provide direction and distance information, respectively.

Impaired secondary somatosensory gating in patients with schizophrenia.

A large and growing literature has demonstrated a deficit in auditory gating in patients with schizophrenia. Although that deficit has been interpreted as a general gating problem, no deficit has been shown in other sensory modalities. Recent research in our laboratory has examined sensory gating effects in the somatosensory system showing no difference in gating of the primary somatosensory response between patients with schizophrenia and control subjects. This is consistent with recent structural studies showing no cortical structural abnormality in primary somatosensory area in schizophrenia. However, a significant decrease in cortical thickness and gray matter volume loss in secondary somatosensory cortex has recently been reported, suggesting this as a focus for impaired somatosensory gating. Thus, the current study was designed (1) to replicate previous work showing a lack of schizophrenia deficit in primary somatosensory cortex (SI) gating, and (2) to investigate a possible deficit in secondary somatosensory cortex (SII) gating. In a paired-pulse paradigm, dipolar sources were assessed in SI and SII contralateral to unilateral median nerve stimulation. Patients demonstrated no impairment in SI gating, but a robust gating deficit in SII, supporting the presence of cross modal gating deficits in schizophrenia.

Dynamic neural activity recorded from human amygdala during fear conditioning using magnetoencephalography.

Magnetoencephalography (MEG) was used to record the dynamics of amygdala neuronal population activity during fear conditioning in human participants. Activation during conditioning training was compared to habituation and extinction sessions. Conditioned stimuli (CS) were visually presented geometric figures, and unconditioned stimuli (US) were aversive white-noise bursts. The CS+ was paired with the US on 50% of presentations and the CS- was never paired. The precise temporal resolution of MEG allowed us to address the issue of whether the amygdala responds to the onset or offset of the CS+, and/or the expectation of the initiation or offset of the an omitted auditory US. Fear conditioning elicited differential amygdala activation for the unpaired CS+ compared to the CS-, extinction and habituation. This was especially robust in the right hemisphere at CS onset. The strongest peaks of amygdala activity occurred at an average of 270 ms in the right and 306 ms in the left hemisphere following unpaired CS+ onset, and following offset at 21 ms in the left and 161 ms in the right (corresponding to an interval of 108 ms and 248 ms after the anticipated onset of the US, respectively). However, the earliest peaks in this epoch preceded US onset in most subjects. Thus, the activity dynamics suggest that the amygdala both differentially responds to stimuli and anticipates the arrival of stimuli based on prior learning of contingencies. The amygdala also shows stimulus omission-related activation that could potentially provide feedback about experienced stimulus contingencies to modify future responding during learning and extinction.