Spatiotemporal patterns of sleep spindle activity in human anterior thalamus and cortex.

Sleep spindles (8 - 16 Hz) are transient electrophysiological events during non-rapid eye movement sleep. While sleep spindles are routinely observed in the cortex using scalp electroencephalography (EEG), recordings of their thalamic counterparts have not been widely studied in humans. Based on a few existing studies, it has been hypothesized that spindles occur as largely local phenomena. We investigated intra-thalamic and thalamocortical spindle co-occurrence, which may underlie thalamocortical communication. We obtained scalp EEG and thalamic recordings from 7 patients that received bilateral deep brain stimulation (DBS) electrodes to the anterior thalamus for the treatment of drug resistant focal epilepsy. Spindles were categorized into subtypes based on their main frequency (i.e., slow (10±2 Hz) or fast (14±2 Hz)) and their level of thalamic involvement (spanning one channel, or spreading uni- or bilaterally within the thalamus). For the first time, we contrasted observed spindle patterns with permuted data to estimate random spindle co-occurrence. We found that multichannel spindle patterns were systematically coordinated at the thalamic and thalamocortical level. Importantly, distinct topographical patterns of thalamocortical spindle overlap were associated with slow and fast subtypes of spindles. These observations provide further evidence for coordinated spindle activity in thalamocortical networks.

The Effects of Context and Attention on Spiking Activity in Human Early Visual Cortex.

Here we report the first quantitative analysis of spiking activity in human early visual cortex. We recorded multi-unit activity from two electrodes in area V2/V3 of a human patient implanted with depth electrodes as part of her treatment for epilepsy. We observed well-localized multi-unit receptive fields with tunings for contrast, orientation, spatial frequency, and size, similar to those reported in the macaque. We also observed pronounced gamma oscillations in the local-field potential that could be used to estimate the underlying spiking response properties. Spiking responses were modulated by visual context and attention. We observed orientation-tuned surround suppression: responses were suppressed by image regions with a uniform orientation and enhanced by orientation contrast. Additionally, responses were enhanced on regions that perceptually segregated from the background, indicating that neurons in the human visual cortex are sensitive to figure-ground structure. Spiking responses were also modulated by object-based attention. When the patient mentally traced a curve through the neurons' receptive fields, the accompanying shift of attention enhanced neuronal activity. These results demonstrate that the tuning properties of cells in the human early visual cortex are similar to those in the macaque and that responses can be modulated by both contextual factors and behavioral relevance. Our results, therefore, imply that the macaque visual system is an excellent model for the human visual cortex.

Characterizing object- and position-dependent response profiles to uni- and bilateral stimulus configurations in human higher visual cortex: a 7T fMRI study.

Visual scenes are initially processed via segregated neural pathways dedicated to either of the two visual hemifields. Although higher-order visual areas are generally believed to utilize invariant object representations (abstracted away from features such as stimulus position), recent findings suggest they retain more spatial information than previously thought. Here, we assessed the nature of such higher-order object representations in human cortex using high-resolution fMRI at 7T, supported by corroborative 3T data. We show that multi-voxel activation patterns in both the contra- and ipsilateral hemisphere can be exploited to successfully classify the object category of unilaterally presented stimuli. Moreover, robustly identified rank order-based response profiles demonstrated a strong contralateral bias which frequently outweighed object category preferences. Finally, we contrasted different combinatorial operations to predict the responses during bilateral stimulation conditions based on responses to their constituent unilateral elements. Results favored a max operation predominantly reflecting the contralateral stimuli. The current findings extend previous work by showing that configuration-dependent modulations in higher-order visual cortex responses as observed in single unit activity have a counterpart in human neural population coding. They furthermore corroborate the emerging view that position coding is a fundamental functional characteristic of ventral visual stream processing.

Behavioural interference at event boundaries reduces long-term memory performance in the virtual water maze task without affecting working memory performance.

Narrative episodic memory of movie clips can be retroactively impaired by presenting unrelated stimuli coinciding with event boundaries. This effect has been linked with rapid hippocampal processes triggered by the offset of the event, that are alternatively related either to memory consolidation or with working memory processes. Here we tested whether this effect extended to spatial memory, the temporal specificity and extent of the interference, and its effect on working- vs long-term memory. In three computerized adaptations of the Morris Water Maze, participants learned the location of an invisible target over three trials each. A second spatial navigation task was presented either immediately after finding the target, after a 10-s delay, or no second task was presented (control condition). A recall session, in which participants indicated the learned target location with 10 'pin-drop' trials for each condition, was performed after a 1-h or a 24-h break. Spatial memory was measured by the mean distance between pins and the true location. Results indicated that the immediate presentation of the second task led to worse memory performance, for both break durations, compared to the delayed condition. There was no difference in performance between the delayed presentation and the control condition. Despite this long-term memory effect, we found no difference in the rate of performance improvement during the learning session, indicating no effect of the second task on working memory. Our findings are in line with a rapid process, linked to the offset of an event, that is involved in the early stages of memory consolidation.

Posttraining transcranial magnetic stimulation of striate cortex disrupts consolidation early in visual skill learning.

Practice-induced improvements in skilled performance reflect "offline " consolidation processes extending beyond daily training sessions. According to visual learning theories, an early, fast learning phase driven by high-level areas is followed by a late, asymptotic learning phase driven by low-level, retinotopic areas when higher resolution is required. Thus, low-level areas would not contribute to learning and offline consolidation until late learning. Recent studies have challenged this notion, demonstrating modified responses to trained stimuli in primary visual cortex (V1) and offline activity after very limited training. However, the behavioral relevance of modified V1 activity for offline consolidation of visual skill memory in V1 after early training sessions remains unclear. Here, we used neuronavigated transcranial magnetic stimulation (TMS) directed to a trained retinotopic V1 location to test for behaviorally relevant consolidation in human low-level visual cortex. Applying TMS to the trained V1 location within 45 min of the first or second training session strongly interfered with learning, as measured by impaired performance the next day. The interference was conditional on task context and occurred only when training in the location targeted by TMS was followed by training in a second location before TMS. In this condition, high-level areas may become coupled to the second location and uncoupled from the previously trained low-level representation, thereby rendering consolidation vulnerable to interference. Our data show that, during the earliest phases of skill learning in the lowest-level visual areas, a behaviorally relevant form of consolidation exists of which the robustness is controlled by high-level, contextual factors.

On the feasibility of concurrent human TMS-EEG-fMRI measurements.

Simultaneously combining the complementary assets of EEG, functional MRI (fMRI), and transcranial magnetic stimulation (TMS) within one experimental session provides synergetic results, offering insights into brain function that go beyond the scope of each method when used in isolation. The steady increase of concurrent EEG-fMRI, TMS-EEG, and TMS-fMRI studies further underlines the added value of such multimodal imaging approaches. Whereas concurrent EEG-fMRI enables monitoring of brain-wide network dynamics with high temporal and spatial resolution, the combination with TMS provides insights in causal interactions within these networks. Thus the simultaneous use of all three methods would allow studying fast, spatially accurate, and distributed causal interactions in the perturbed system and its functional relevance for intact behavior. Concurrent EEG-fMRI, TMS-EEG, and TMS-fMRI experiments are already technically challenging, and the three-way combination of TMS-EEG-fMRI might yield additional difficulties in terms of hardware strain or signal quality. The present study explored the feasibility of concurrent TMS-EEG-fMRI studies by performing safety and quality assurance tests based on phantom and human data combining existing commercially available hardware. Results revealed that combined TMS-EEG-fMRI measurements were technically feasible, safe in terms of induced temperature changes, allowed functional MRI acquisition with comparable image quality as during concurrent EEG-fMRI or TMS-fMRI, and provided artifact-free EEG before and from 300 ms after TMS pulse application. Based on these empirical findings, we discuss the conceptual benefits of this novel complementary approach to investigate the working human brain and list a number of precautions and caveats to be heeded when setting up such multimodal imaging facilities with current hardware.

Tactile perceptual learning: learning curves and transfer to the contralateral finger.

Tactile perceptual learning has been shown to improve performance on tactile tasks, but there is no agreement about the extent of transfer to untrained skin locations. The lack of such transfer is often seen as a behavioral index of the contribution of early somatosensory brain regions. Moreover, the time course of improvements has never been described explicitly. Sixteen subjects were trained on the Ludvigh task (a tactile vernier task) on four subsequent days. On the fifth day, transfer of learning to the non-trained contralateral hand was tested. In five subjects, we explored to what extent training effects were retained approximately 1.5 years after the final training session, expecting to find long-term retention of learning effects after training. Results showed that tactile perceptual learning mainly occurred offline, between sessions. Training effects did not transfer initially, but became fully available to the untrained contralateral hand after a few additional training runs. After 1.5 years, training effects were not fully washed out and could be recuperated within a single training session. Interpreted in the light of theories of visual perceptual learning, these results suggest that tactile perceptual learning is not fundamentally different from visual perceptual learning, but might proceed at a slower pace due to procedural and task differences, thus explaining the apparent divergence in the amount of transfer and long-term retention.

Hippocampal activity in working memory tasks: sparse, yet relevant.

Recent studies suggest the hippocampus is involved in working memory (WM). Slotnick (this issue) critically reviewed relevant fMRI findings and concludes WM 'does not activate the hippocampus.' We extend Slotnick's review by discussing observations from human intracranial and lesion research. These studies do suggest hippocampal contributions to WM (beyond novelty encoding), which however are difficult to capture with conventional fMRI. Still, the advent of new fMRI techniques combined with a stronger emphasis on shared hippocampal mechanisms across short- and long-term memory pave an exciting path forward.

Deviant processing of letters and speech sounds as proximate cause of reading failure: a functional magnetic resonance imaging study of dyslexic children.

Learning to associate auditory information of speech sounds with visual information of letters is a first and critical step for becoming a skilled reader in alphabetic languages. Nevertheless, it remains largely unknown which brain areas subserve the learning and automation of such associations. Here, we employ functional magnetic resonance imaging to study letter-speech sound integration in children with and without developmental dyslexia. The results demonstrate that dyslexic children show reduced neural integration of letters and speech sounds in the planum temporale/Heschl sulcus and the superior temporal sulcus. While cortical responses to speech sounds in fluent readers were modulated by letter-speech sound congruency with strong suppression effects for incongruent letters, no such modulation was observed in the dyslexic readers. Whole-brain analyses of unisensory visual and auditory group differences additionally revealed reduced unisensory responses to letters in the fusiform gyrus in dyslexic children, as well as reduced activity for processing speech sounds in the anterior superior temporal gyrus, planum temporale/Heschl sulcus and superior temporal sulcus. Importantly, the neural integration of letters and speech sounds in the planum temporale/Heschl sulcus and the neural response to letters in the fusiform gyrus explained almost 40% of the variance in individual reading performance. These findings indicate that an interrelated network of visual, auditory and heteromodal brain areas contributes to the skilled use of letter-speech sound associations necessary for learning to read. By extending similar findings in adults, the data furthermore argue against the notion that reduced neural integration of letters and speech sounds in dyslexia reflect the consequence of a lifetime of reading struggle. Instead, they support the view that letter-speech sound integration is an emergent property of learning to read that develops inadequately in dyslexic readers, presumably as a result of a deviant interactive specialization of neural systems for processing auditory and visual linguistic inputs.

Continuous motor sequence learning: cortical efficiency gains accompanied by striatal functional reorganization.

The acquisition and generation of action sequences constitute essential elements of purposeful human behavior. However, there is still considerable debate on how experience-driven changes related to skill learning are expressed at the neural systems level. The current functional magnetic resonance imaging (fMRI) study focused on changes in the neural representation of continuous movement sequences as learning evolved. Behavioral and neural manifestations of nonvisual motor practice were studied both within the time frame of a single scanning session, as well as after several days of extended practice. Based on detailed behavioral recordings which enabled the continuous characterization of the ongoing learning process at the single subject level, sequence-specific decreases in activation throughout a learning-related network of cortical areas were identified. Furthermore, the spatial layout of this cortical network remained largely unchanged after extensive practice, although further decreases in activation levels could be observed as learning progressed. In contrast, the posterior part of the left putamen showed increased activation levels when an extensively trained sequence needed to be recalled. Overall, these findings imply that continuous motor sequence learning is mainly associated with more efficient processing in a network of consistently recruited cortical areas, together with co-occurring activation pattern changes at the subcortical level.

Nonvisual motor learning influences abstract action observation.

Neuroimaging studies have recently provided support for the existence of a human equivalent of the "mirror-neuron" system as first described in monkeys [1], involved in both the execution of movements as well as the observation and imitation of actions performed by others (e.g., [2-6]). A widely held conception concerning this system is that the understanding of observed actions is mediated by a covert simulation process [7]. In the present fMRI experiment, this simulation process was probed by asking subjects to discriminate between visually presented trajectories that either did or did not match previously performed but unseen continuous movement sequences. A specific network of learning-related premotor and parietal areas was found to be reactivated when participants were confronted with their movements' visual counterpart. Moreover, the strength of these reactivations was dependent on the observers' experience with executing the corresponding movement sequence. These findings provide further support for the emerging view that embodied simulations during action observation engage widespread activations in cortical motor regions beyond the classically defined mirror-neuron system. Furthermore, the obtained results extend previous work by showing experience-dependent perceptual modulations at the neural systems level based on nonvisual motor learning.

Concurrent human TMS-EEG-fMRI enables monitoring of oscillatory brain state-dependent gating of cortico-subcortical network activity.

Despite growing interest, the causal mechanisms underlying human neural network dynamics remain elusive. Transcranial Magnetic Stimulation (TMS) allows to noninvasively probe neural excitability, while concurrent fMRI can log the induced activity propagation through connected network nodes. However, this approach ignores ongoing oscillatory fluctuations which strongly affect network excitability and concomitant behavior. Here, we show that concurrent TMS-EEG-fMRI enables precise and direct monitoring of causal dependencies between oscillatory states and signal propagation throughout cortico-subcortical networks. To demonstrate the utility of this multimodal triad, we assessed how pre-TMS EEG power fluctuations influenced motor network activations induced by subthreshold TMS to right dorsal premotor cortex. In participants with adequate motor network reactivity, strong pre-TMS alpha power reduced TMS-evoked hemodynamic activations throughout the bilateral cortico-subcortical motor system (including striatum and thalamus), suggesting shunted network connectivity. Concurrent TMS-EEG-fMRI opens an exciting noninvasive avenue of subject-tailored network research into dynamic cognitive circuits and their dysfunction.

Combining Gamma With Alpha and Beta Power Modulation for Enhanced Cortical Mapping in Patients With Focal Epilepsy.

About one third of patients with epilepsy have seizures refractory to the medical treatment. Electrical stimulation mapping (ESM) is the gold standard for the identification of "eloquent" areas prior to resection of epileptogenic tissue. However, it is time-consuming and may cause undesired side effects. Broadband gamma activity (55-200 Hz) recorded with extraoperative electrocorticography (ECoG) during cognitive tasks may be an alternative to ESM but until now has not proven of definitive clinical value. Considering their role in cognition, the alpha (8-12 Hz) and beta (15-25 Hz) bands could further improve the identification of eloquent cortex. We compared gamma, alpha and beta activity, and their combinations for the identification of eloquent cortical areas defined by ESM. Ten patients with intractable focal epilepsy (age: 35.9 ± 9.1 years, range: 22-48, 8 females, 9 right handed) participated in a delayed-match-to-sample task, where syllable sounds were compared to visually presented letters. We used a generalized linear model (GLM) approach to find the optimal weighting of each band for predicting ESM-defined categories and estimated the diagnostic ability by calculating the area under the receiver operating characteristic (ROC) curve. Gamma activity increased more in eloquent than in non-eloquent areas, whereas alpha and beta power decreased more in eloquent areas. Diagnostic ability of each band was close to 0.7 for all bands but depended on multiple factors including the time period of the cognitive task, the location of the electrodes and the patient's degree of attention to the stimulus. We show that diagnostic ability can be increased by 3-5% by combining gamma and alpha and by 7.5-11% when gamma and beta were combined. We then show how ECoG power modulation from cognitive testing can be used to map the probability of eloquence in individual patients and how this probability map can be used in clinical settings to optimize ESM planning. We conclude that the combination of gamma and beta power modulation during cognitive testing can contribute to the identification of eloquent areas prior to ESM in patients with refractory focal epilepsy.

Resistance-based high resolution recording of predefined 2-dimensional pen trajectories in an fMRI setting.

The recent advent of functional magnetic resonance imaging (fMRI) as a readily accessible neuroimaging method has led to exciting new insights into the functioning of the human motor system. However, technical complications related to the fMRI scanner environment often limit the ability to measure the desired behavioral data reflecting the subjects' movements. In order to perform kinematic registrations of predefined complex two-dimensional movement patterns while scanning, a new MR-compatible setup has been developed. The method presented here allows the recording of detailed pen tracing data during concurrent functional image acquisition. Essentially, temporally high resolved resistance measurements are used to keep track of the covered distance across time, as applied here to the tracing of various mazes. In this way, the current setup adds the close monitoring of continuous tracing movements to the spectrum of behavioral data which can be successfully obtained in an fMRI setting.

Evaluating population receptive field estimation frameworks in terms of robustness and reproducibility.

Within vision research retinotopic mapping and the more general receptive field estimation approach constitute not only an active field of research in itself but also underlie a plethora of interesting applications. This necessitates not only good estimation of population receptive fields (pRFs) but also that these receptive fields are consistent across time rather than dynamically changing. It is therefore of interest to maximize the accuracy with which population receptive fields can be estimated in a functional magnetic resonance imaging (fMRI) setting. This, in turn, requires an adequate estimation framework providing the data for population receptive field mapping. More specifically, adequate decisions with regard to stimulus choice and mode of presentation need to be made. Additionally, it needs to be evaluated whether the stimulation protocol should entail mean luminance periods and whether it is advantageous to average the blood oxygenation level dependent (BOLD) signal across stimulus cycles or not. By systematically studying the effects of these decisions on pRF estimates in an empirical as well as simulation setting we come to the conclusion that a bar stimulus presented at random positions and interspersed with mean luminance periods is generally most favorable. Finally, using this optimal estimation framework we furthermore tested the assumption of temporal consistency of population receptive fields. We show that the estimation of pRFs from two temporally separated sessions leads to highly similar pRF parameters.

Modeling invariant object processing based on tight integration of simulated and empirical data in a Common Brain Space.

Recent advances in Computer Vision and Experimental Neuroscience provided insights into mechanisms underlying invariant object recognition. However, due to the different research aims in both fields models tended to evolve independently. A tighter integration between computational and empirical work may contribute to cross-fertilized development of (neurobiologically plausible) computational models and computationally defined empirical theories, which can be incrementally merged into a comprehensive brain model. After reviewing theoretical and empirical work on invariant object perception, this article proposes a novel framework in which neural network activity and measured neuroimaging data are interfaced in a common representational space. This enables direct quantitative comparisons between predicted and observed activity patterns within and across multiple stages of object processing, which may help to clarify how high-order invariant representations are created from low-level features. Given the advent of columnar-level imaging with high-resolution fMRI, it is time to capitalize on this new window into the brain and test which predictions of the various object recognition models are supported by this novel empirical evidence.

A real-time fMRI-based spelling device immediately enabling robust motor-independent communication.

Human communication entirely depends on the functional integrity of the neuromuscular system. This is devastatingly illustrated in clinical conditions such as the so-called locked-in syndrome (LIS), in which severely motor-disabled patients become incapable to communicate naturally--while being fully conscious and awake. For the last 20 years, research on motor-independent communication has focused on developing brain-computer interfaces (BCIs) implementing neuroelectric signals for communication (e.g., [2-7]), and BCIs based on electroencephalography (EEG) have already been applied successfully to concerned patients. However, not all patients achieve proficiency in EEG-based BCI control. Thus, more recently, hemodynamic brain signals have also been explored for BCI purposes. Here, we introduce the first spelling device based on fMRI. By exploiting spatiotemporal characteristics of hemodynamic responses, evoked by performing differently timed mental imagery tasks, our novel letter encoding technique allows translating any freely chosen answer (letter-by-letter) into reliable and differentiable single-trial fMRI signals. Most importantly, automated letter decoding in real time enables back-and-forth communication within a single scanning session. Because the suggested spelling device requires only little effort and pretraining, it is immediately operational and possesses high potential for clinical applications, both in terms of diagnostics and establishing short-term communication with nonresponsive and severely motor-impaired patients.

Another kind of 'BOLD Response': answering multiple-choice questions via online decoded single-trial brain signals.

The term 'locked-in'syndrome (LIS) describes a medical condition in which persons concerned are severely paralyzed and at the same time fully conscious and awake. The resulting anarthria makes it impossible for these patients to naturally communicate, which results in diagnostic as well as serious practical and ethical problems. Therefore, developing alternative, muscle-independent communication means is of prime importance. Such communication means can be realized via brain-computer interfaces (BCIs) circumventing the muscular system by using brain signals associated with preserved cognitive, sensory, and emotional brain functions. Primarily, BCIs based on electrophysiological measures have been developed and applied with remarkable success. Recently, also blood flow-based neuroimaging methods, such as functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS), have been explored in this context. After reviewing recent literature on the development of especially hemodynamically based BCIs, we introduce a highly reliable and easy-to-apply communication procedure that enables untrained participants to motor-independently and relatively effortlessly answer multiple-choice questions based on intentionally generated single-trial fMRI signals that can be decoded online. Our technique takes advantage of the participants' capability to voluntarily influence certain spatio-temporal aspects of the blood oxygenation level-dependent (BOLD) signal: source location (by using different mental tasks), signal onset and offset. We show that healthy participants are capable of hemodynamically encoding at least four distinct information units on a single-trial level without extensive pretraining and with little effort. Moreover, real-time data analysis based on simple multi-filter correlations allows for automated answer decoding with a high accuracy (94.9%) demonstrating the robustness of the presented method. Following our 'proof of concept', the next step will involve clinical trials with LIS patients, undertaken in close collaboration with their relatives and caretakers in order to elaborate individually tailored communication protocols. As our procedure can be easily transferred to MRI-equipped clinical sites, it may constitute a simple and effective possibility for online detection of residual consciousness and for LIS patients to communicate basic thoughts and needs in case no other alternative communication means are available (yet)--especially in the acute phase of the LIS. Future research may focus on further increasing the efficiency and accuracy of fMRI-based BCIs by implementing sophisticated data analysis methods (e.g., multivariate and independent component analysis) and neurofeedback training techniques. Finally, the presented BCI approach could be transferred to portable fNIRS systems as only this would enable hemodynamically based communication in daily life situations.