Alejandro Blenkmann

Expectation and Attention in Hierarchical Auditory Prediction

Hierarchical predictive coding suggests that attention in humans emerges from increased precision in probabilistic inference, whereas expectation biases attention in favor of contextually anticipated stimuli. We test these notions within auditory perception by independently manipulating top-down expectation and attentional precision alongside bottom-up stimulus predictability. Our findings support an integrative interpretation of commonly observed electrophysiological signatures of neurodynamics, namely mismatch negativity (MMN), P300, and contingent negative variation (CNV), as manifestations along successive levels of predictive complexity. Early first-level processing indexed by the MMN was sensitive to stimulus predictability: here, attentional precision enhanced early responses, but explicit top-down expectation diminished it. This pattern was in contrast to later, second-level processing indexed by the P300: although sensitive to the degree of predictability, responses at this level were contingent on attentional engagement and in fact sharpened by top-down expectation. At the highest level, the drift of the CNV was a fine-grained marker of top-down expectation itself. Source reconstruction of high-density EEG, supported by intracranial recordings, implicated temporal and frontal regions differentially active at early and late levels. The cortical generators of the CNV suggested that it might be involved in facilitating the consolidation of context-salient stimuli into conscious perception. These results provide convergent empirical support to promising recent accounts of attention and expectation in predictive coding.

Motor-language coupling: direct evidence from early Parkinson’s disease and intracranial cortical recordings

Language and action systems are functionally coupled in the brain as demonstrated by converging evidence using Functional magnetic resonance imaging (fMRI), electroencephalography (EEG), transcranial magnetic stimulation (TMS), and lesion studies. In particular, this coupling has been demonstrated using the action-sentence compatibility effect (ACE) in which motor activity and language interact. The ACE task requires participants to listen to sentences that described actions typically performed with an open hand (e.g., clapping), a closed hand (e.g., hammering), or without any hand action (neutral); and to press a large button with either an open hand position or closed hand position immediately upon comprehending each sentence. The ACE is defined as a longer reaction time (RT) in the action-sentence incompatible conditions than in the compatible conditions. Here we investigated direct motor-language coupling in two novel and uniquely informative ways. First, we measured the behavioural ACE in patients with motor impairment (early Parkinsons disease - EPD), and second, in epileptic patients with direct electrocorticography (ECoG) recordings. In experiment 1, EPD participants with preserved general cognitive repertoire, showed a much diminished ACE relative to non-EPD volunteers. Moreover, a correlation between ACE performance and action-verb processing (kissing and dancing test - KDT) was observed. Direct cortical recordings (ECoG) in motor and language areas (experiment 2) demonstrated simultaneous bidirectional effects: motor preparation affected language processing (N400 at left inferior frontal gyrus and middle/superior temporal gyrus), and language processing affected activity in movement-related areas (motor potential at premotor and M1). Our findings show that the ACE paradigm requires ongoing integration of preserved motor and language coupling (abolished in EPD) and engages motor-temporal cortices in a bidirectional way. In addition, both experiments suggest the presence of a motor-language network which is not restricted to somatotopically defined brain areas. These results open new pathways in the fields of motor diseases, theoretical approaches to language understanding, and models of action-perception coupling.

Cortical deficits of emotional face processing in adults with ADHD: Its relation to social cognition and executive function

Although it has been shown that adults with attention-deficit hyperactivity disorder (ADHD) have impaired social cognition, no previous study has reported the brain correlates of face valence processing. This study looked for behavioral, neuropsychological, and electrophysiological markers of emotion processing for faces (N170) in adult ADHD compared to controls matched by age, gender, educational level, and handedness. We designed an event-related potential (ERP) study based on a dual valence task (DVT), in which faces and words were presented to test the effects of stimulus type (faces, words, or face-word stimuli) and valence (positive versus negative). Individual signatures of cognitive functioning in participants with ADHD and controls were assessed with a comprehensive neuropsychological evaluation, including executive functioning (EF) and theory of mind (ToM). Compared to controls, the adult ADHD group showed deficits in N170 emotion modulation for facial stimuli. These N170 impairments were observed in the absence of any deficit in facial structural processing, suggesting a specific ADHD impairment in early facial emotion modulation. The cortical current density mapping of N170 yielded a main neural source of N170 at posterior section of fusiform gyrus (maximum at left hemisphere for words and right hemisphere for faces and simultaneous stimuli). Neural generators of N170 (fusiform gyrus) were reduced in ADHD. In those patients, N170 emotion processing was associated with performance on an emotional inference ToM task, and N170 from simultaneous stimuli was associated with EF, especially working memory. This is the first report to reveal an adult ADHD-specific impairment in the cortical modulation of emotion for faces and an association between N170 cortical measures and ToM and EF.

Neural Processing of Emotional Facial and Semantic Expressions in Euthymic Bipolar Disorder (BD) and Its Association with Theory of Mind (ToM)

Background Adults with bipolar disorder (BD) have cognitive impairments that affect face processing and social cognition. However, it remains unknown whether these deficits in euthymic BD have impaired brain markers of emotional processing. Methodology/Principal Findings We recruited twenty six participants, 13 controls subjects with an equal number of euthymic BD participants. We used an event-related potential (ERP) assessment of a dual valence task (DVT), in which faces (angry and happy), words (pleasant and unpleasant), and face-word simultaneous combinations are presented to test the effects of the stimulus type (face vs word) and valence (positive vs. negative). All participants received clinical, neuropsychological and social cognition evaluations. ERP analysis revealed that both groups showed N170 modulation of stimulus type effects (face > word). BD patients exhibited reduced and enhanced N170 to facial and semantic valence, respectively. The neural source estimation of N170 was a posterior section of the fusiform gyrus (FG), including the face fusiform area (FFA). Neural generators of N170 for faces (FG and FFA) were reduced in BD. In these patients, N170 modulation was associated with social cognition (theory of mind). Conclusions/Significance This is the first report of euthymic BD exhibiting abnormal N170 emotional discrimination associated with theory of mind impairments.

Hierarchical Organization of Frontotemporal Networks for the Prediction of Stimuli across Multiple Dimensions

Brain function can be conceived as a hierarchy of generative models that optimizes predictions of sensory inputs and minimizes “surprise.” Each level of the hierarchy makes predictions of neural events at a lower level in the hierarchy, which returns a prediction error when these expectations are violated. We tested the generalization of this hypothesis to multiple sequential deviations, and we identified the most likely organization of the network that accommodates deviations in temporal structure of stimuli. Magnetoencephalography of healthy human participants during an auditory paradigm identified prediction error responses in bilateral primary auditory cortex, superior temporal gyrus, and lateral prefrontal cortex for deviation by frequency, intensity, location, duration, and silent gap. We examined the connectivity between cortical sources using a set of 21 generative models that embedded alternate hypotheses of frontotemporal network dynamics. Bayesian model selection provided evidence for two new features of functional network organization. First, an expectancy signal provided input to the prefrontal cortex bilaterally, related to the temporal structure of stimuli. Second, there are functionally significant lateral connections between superior temporal and/or prefrontal cortex. The results support a predictive coding hypothesis but go beyond previous work in demonstrating the generalization to multiple concurrent stimulus dimensions and the evidence for a temporal expectancy input at the higher level of the frontotemporal hierarchy. We propose that this framework for studying the brains response to unexpected events is not limited to simple sensory tasks but may also apply to the neurocognitive mechanisms of higher cognitive functions and their disorders.

Noninvasive approach to focal cortical dysplasias: clinical, EEG, and neuroimaging features.

Purpose. The main purpose is to define more accurately the epileptogenic zone (EZ) with noninvasive methods in those patients with MRI diagnosis of focal cortical dysplasia (FCD) and epilepsy who are candidates of epilepsy surgery. Methods. Twenty patients were evaluated prospectively between 2007 and 2010 with comprehensive clinical evaluation, video-electroencephalography, diffusion tensor imaging (DTI), and high-resolution EEG to localize the equivalent current dipole (ECD). Key Findings. In 11 cases with white matter asymmetries in DTI the ECDs were located next to lesion on MRI with mean distance of 14.63 millimeters with topographical correlation with the EZ. Significance. We could establish a hypothesis of EZ based on Video-EEG, high-resolution EEG, ECD method, MRI, and DTI. These results are consistent with the hypothesis that the EZ in the FCD is complex and is often larger than visible lesion in MRI.

Rapid and efficient localization of depth electrodes and cortical labeling using free and open source medical software in epilepsy surgery candidates

Depth intracranial electrodes (IEs) placement is one of the most used procedures to identify the epileptogenic zone (EZ) in surgical treatment of drug resistant epilepsy patients, about 20–30% of this population. IEs localization is therefore a critical issue defining the EZ and its relation with eloquent functional areas. That information is then used to target the resective surgery and has great potential to affect outcome. We designed a methodological procedure intended to avoid the need for highly specialized medical resources and reduce time to identify the anatomical location of IEs, during the first instances of intracranial EEG recordings. This workflow is based on established open source software; 3D Slicer and Freesurfer that uses MRI and Post-implant CT fusion for the localization of IEs and its relation with automatic labeled surrounding cortex. To test this hypothesis we assessed the time elapsed between the surgical implantation process and the final anatomical localization of IEs by means of our proposed method compared against traditional visual analysis of raw post-implant imaging in two groups of patients. All IEs were identified in the first 24 H (6–24 H) of implantation using our method in 4 patients of the first group. For the control group; all IEs were identified by experts with an overall time range of 36 h to 3 days using traditional visual analysis. It included (7 patients), 3 patients implanted with IEs and the same 4 patients from the first group. Time to localization was restrained in this group by the specialized personnel and the image quality available. To validate our method; we trained two inexperienced operators to assess the position of IEs contacts on four patients (5 IEs) using the proposed method. We quantified the discrepancies between operators and we also assessed the efficiency of our method to define the EZ comparing the findings against the results of traditional analysis.

Association between equivalent current dipole source localization and focal cortical dysplasia in epilepsy patients

We analysed the association between focal cortical dysplasia (FCD) visible in MRI and the location of equivalent current dipole (ECD) of single interictal scalp EEG spikes (IIS) in 11 epilepsy patients. We calculated several indicators of distance of ECDs to the FCD border. The results confirm some previous studies suggesting that the epileptogenic zone associated to the location of ECDs extends beyond the FCD visible in MRI. The analysis suggests the ECDs to be in a shell parallel to part of the FCD surface.

Convergent evidence for hierarchical prediction networks from human electrocorticography and magnetoencephalography

We propose that sensory inputs are processed in terms of optimised predictions and prediction error signals within hierarchical neurocognitive models. The combination of non-invasive brain imaging and generative network models has provided support for hierarchical frontotemporal interactions in oddball tasks, including recent identification of a temporal expectancy signal acting on prefrontal cortex. However, these studies are limited by the need to invert magnetoencephalographic or electroencephalographic sensor signals to localise activity from cortical ‘nodes’ in the network, or to infer neural responses from indirect measures such as the fMRI BOLD signal. To overcome this limitation, we examined frontotemporal interactions estimated from direct cortical recordings from two human participants with cortical electrode grids (electrocorticography – ECoG). Their frontotemporal network dynamics were compared to those identified by magnetoencephalography (MEG) in forty healthy adults. All participants performed the same auditory oddball task with standard tones interspersed with five deviant tone types. We normalised post-operative electrode locations to standardised anatomic space, to compare across modalities, and inverted the MEG to cortical sources using the estimated lead field from subject-specific head models. A mismatch negativity signal in frontal and temporal cortex was identified in all subjects. Generative models of the electrocorticographic and magnetoencephalographic data were separately compared using the free-energy estimate of the model evidence. Model comparison confirmed the same critical features of hierarchical frontotemporal networks in each patient as in the group-wise MEG analysis. These features included bilateral, feedforward and feedback frontotemporal modulated connectivity, in addition to an asymmetric expectancy driving input on left frontal cortex. The invasive ECoG provides an important step in construct validation of the use of neural generative models of MEG, which in turn enables generalisation to larger populations. Together, they give convergent evidence for the hierarchical interactions in frontotemporal networks for expectation and processing of sensory inputs.

iElectrodes: A Comprehensive Open-Source Toolbox for Depth and Subdural Grid Electrode Localization

The localization of intracranial electrodes is a fundamental step in the analysis of invasive electroencephalography (EEG) recordings in research and clinical practice. The conclusions reached from the analysis of these recordings rely on the accuracy of electrode localization in relationship to brain anatomy. However, currently available techniques for localizing electrodes from magnetic resonance (MR) and/or computerized tomography (CT) images are time consuming and/or limited to particular electrode types or shapes. Here we present iElectrodes, an open-source toolbox that provides robust and accurate semi-automatic localization of both subdural grids and depth electrodes. Using pre- and post-implantation images, the method takes 2–3 min to localize the coordinates in each electrode array and automatically number the electrodes. The proposed pre-processing pipeline allows one to work in a normalized space and to automatically obtain anatomical labels of the localized electrodes without neuroimaging experts. We validated the method with data from 22 patients implanted with a total of 1,242 electrodes. We show that localization distances were within 0.56 mm of those achieved by experienced manual evaluators. iElectrodes provided additional advantages in terms of robustness (even with severe perioperative cerebral distortions), speed (less than half the operator time compared to expert manual localization), simplicity, utility across multiple electrode types (surface and depth electrodes) and all brain regions.