Joel Reithler

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.

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.

Multimodal transcranial magnetic stimulation: using concurrent neuroimaging to reveal the neural network dynamics of noninvasive brain stimulation

Since its introduction in the 1980s, Transcranial Magnetic Stimulation (TMS) has proven to be a versatile method to non-invasively study human brain function by reversibly altering ongoing neural processing. In addition, TMS has been explored as a therapeutic intervention in a number of neurological and neuropsychiatric conditions. However, our understanding of TMS-induced changes in neural activity patterns is still rather limited, particularly when it comes to changes in neural network dynamics beyond the cortical site directly targeted by TMS. In order to monitor both its local and remote neurophysiological effects, TMS has been combined with complementary neuroimaging methods that allow additional insights into how observed TMS effects at the behavioral level can be interpreted by taking into account the full scale of its impact throughout the brain. The current review provides a comprehensive overview of the existing multimodal TMS literature, covering studies in which TMS was combined with one of the three main neuroimaging modalities, namely Electroencephalography, Positron Emission Tomography, and functional Magnetic Resonance Imaging. Besides constituting a reflection of the status quo in this exciting multidisciplinary research field, this review additionally reveals both convergent and divergent observations across modalities that await corroboration or resolution, thereby further guiding ongoing basic research and providing useful constraints to optimize future clinical applications.

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.

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.

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.

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.

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.

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

ABSTRACT 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. HighlightsIpsilateral cortical activation patterns allow visual object category decoding.Contralateral bias frequently outweighs object category preferences.Representational overlap varies consistently across uni/bilateral stimulation.A ‘MAX’‐operation predicts bi‐ from unilateral stimulation responses.