Eeg

Founder and CEO of MINDIG, Rennes, France. Adjunct professor, Reykjavik University, Reykjavik, Iceland.

Beyond Homogeneity: Characterizing Brain Disorder Heterogeneity through EEG and Normative Modeling

Mahmoud Hassan

Oct 8, 2024

Electroencephalography (EEG) has been thoroughly studied for decades in psychiatry research. Yet its integration into clinical practice as a diagnostic/prognostic tool remains unachieved. We hypothesize that a key reason is the underlying patient's heterogeneity, overlooked in psychiatric EEG research relying on a case-control approach. We combine HD-EEG with normative modeling to quantify this heterogeneity using two well-established and extensively investigated EEG characteristics -spectral power and functional connectivity- across a cohort of 1674 patients with attention-deficit/hyperactivity disorder, autism spectrum disorder, learning disorder, or anxiety, and 560 matched controls. Normative models showed that deviations from population norms among patients were highly heterogeneous and frequency-dependent. Deviation spatial overlap across patients did not exceed 40% and 24% for spectral and connectivity, respectively. Considering individual deviations in patients has significantly enhanced comparative analysis, and the identification of patient-specific markers has demonstrated a correlation with clinical assessments, representing a crucial step towards attaining precision psychiatry through EEG.

Dianalund, Aarhus, Denmark

AI for routine EEG and beyond

Sandor Benizscky

May 29, 2024

Mass Eye and Ear, Harvard Medical School

Jan 18, 2023

Liad Mudrik/Walter Sinnott-Armstrong/Ivano Triggiani/Nick Byrd

A possible role of the posterior alpha as a railroad switcher between dorsal and ventral pathways

Jan 9, 2023

Suppose you are on your favorite touchscreen device consciously and deliberately deciding emails to read or delete. In other words, you are consciously and intentionally looking, tapping, and swiping. Now suppose that you are doing this while neuroscientists are recording your brain activity. Eventually, the neuroscientists are familiar enough with your brain activity and behavior that they run an experiment with subliminal cues which reveals that your looking, tapping, and swiping seem to be determined by a random switch in your brain. You are not aware of it, or its impact on your decisions or movements. Would these predictions undermine your sense of free will? Some have argued that it should. Although this inference from unreflective and/or random intention mechanisms to free will skepticism, may seem intuitive at first, there are already objections to it. So, even if this thought experiment is plausible, it may not actually undermine our sense of free will.

Aix Marseille Univ, Inserm, INS, Institut de Neurosciences des Systèmes

Motor contribution to auditory temporal predictions

Benjamin Morillon

Dec 13, 2022

Temporal predictions are fundamental instruments for facilitating sensory selection, allowing humans to exploit regularities in the world. Recent evidence indicates that the motor system instantiates predictive timing mechanisms, helping to synchronize temporal fluctuations of attention with the timing of events in a task-relevant stream, thus facilitating sensory selection. Accordingly, in the auditory domain auditory-motor interactions are observed during perception of speech and music, two temporally structured sensory streams. I will present a behavioral and neurophysiological account for this theory and will detail the parameters governing the emergence of this auditory-motor coupling, through a set of behavioral and magnetoencephalography (MEG) experiments.

Driving human visual cortex, visually and electrically

Dora Hermes Miller

Mayo Clinic, USA

Nov 15, 2022

The development of circuit-based therapeutics to treat neurological and neuropsychiatric diseases require detailed localization and understanding of electrophysiological signals in the human brain. Electrodes can record and stimulate circuits in many ways, and we often rely on non-invasive imaging methods to predict the location to implant electrodes. However, electrophysiological and imaging signals measure the underlying tissue in a fundamentally different manner. To integrate multimodal data and benefit from these complementary measurements, I will describe an approach that considers how different measurements integrate signals across the underlying tissue. I will show how this approach helps relate fMRI and intracranial EEG measurements and provides new insights into how electrical stimulation influences human brain networks.

Children's Hospital Los Angeles

Baby steps to breakthroughs in precision health in neurodevelopmental disorders

Shafali Spurling Jeste

Oct 25, 2022

Westfälischen Wilhelms-Universität (WWU) Münster

Disentangling neural correlates of consciousness and task relevance using EEG and fMRI

Torge Dellert

Oct 11, 2022

How does our brain generate consciousness, that is, the subjective experience of what it is like to see face or hear a sound? Do we become aware of a stimulus during early sensory processing or only later when information is shared in a wide-spread fronto-parietal network? Neural correlates of consciousness are typically identified by comparing brain activity when a constant stimulus (e.g., a face) is perceived versus not perceived. However, in most previous experiments, conscious perception was systematically confounded with post-perceptual processes such as decision-making and report. In this talk, I will present recent EEG and fMRI studies dissociating neural correlates of consciousness and task-related processing in visual and auditory perception. Our results suggest that consciousness emerges during early sensory processing, while late, fronto-parietal activity is associated with post-perceptual processes rather than awareness. These findings challenge predominant theories of consciousness and highlight the importance of considering task relevance as a confound across different neuroscientific methods, experimental paradigms and sensory modalities.

Dario Alejandro Gordillo Lopez

Do we measure what we think we are measuring?

EPFL

Jul 13, 2022

Tests used in the empirical sciences are often (implicitly) assumed to be representative of a target mechanism in the sense that similar tests should lead to similar results. In this talk, using resting-state electroencephalogram (EEG) as an example, I will argue that this assumption does not necessarily hold true. Typically EEG studies are conducted selecting one analysis method thought to be representative of the research question asked. Using multiple methods, we extracted a variety of features from a single resting-state EEG dataset and conducted correlational and case-control analyses. We found that many EEG features revealed a significant effect in the case-control analyses. Similarly, EEG features correlated significantly with cognitive tasks. However, when we compared these features pairwise, we did not find strong correlations. A number of explanations to these results will be discussed.

Binocular combination of light

Daniel H. Baker

University of York (USA)

Jul 13, 2022

The brain combines signals across the eyes. This process is well-characterized for the perceptual anatomical pathway through V1 that primarily codes contrast, where interocular normalization ensures that responses are approximately equal for monocular and binocular stimulation. But we have much less understanding of how luminance is combined binocularly, both in the cortex and in subcortical structures that govern pupil diameter. Here I will describe the results of experiments using a novel combined EEG and pupillometry paradigm to simultaneously index binocular combination of luminance flicker in parallel pathways. The results show evidence of a more linear process than for spatial contrast, that may reflect different operational constraints in distinct anatomical pathways.

Marcus Kaiser, Sarah Marzi, Giuseppe Gava, Gema Vera Gonzalez, Matteo Vinao-Carl, Sihao Lu, Hayriye Cagnan

Imperial Neurotechnology 2022 - Annual Research Symposium

Nottingham University, Imperial College, University of Oxford

Jul 4, 2022

A diverse mix of neurotechnology talks and posters from researchers at Imperial and beyond. Visit our event page to find out more. The event is in-person but talk sessions will be broadcast via Teams.

Functional segregation of rostral and caudal hippocampus in associative memory

Alicia Vorobiova

HSE University

Apr 6, 2022

It has long been established that the hippocampus plays a crucial role for episodic memory. As opposed to the modular approach, now it is generally assumed that being a complex structure, the HC performs multiplex interconnected functions, whose hierarchical organization provides basis for the higher cognitive functions such as semantics-based encoding and retrieval. However, the «where, when and how» properties of distinct memory aspects within and outside the HC are still under debate. Here we used a visual associative memory task as a probe to test the hypothesis about the differential involvement of the rostral and caudal portions of the human hippocampus in memory encoding, recognition and associative recall. In epilepsy patients implanted with stereo-EEG, we show that at retrieval the rostral HC is selectively active for recognition memory, whereas the caudal HC is selectively active for the associative memory. Low frequency desynchronization and high frequency synchronization characterize the temporal dynamic in encoding and retrieval. Therefore, we describe here anatomical segregation in the hippocampal contributions to associative and recognition memory.

Assistant Professor, University of Illinois, USA

The functional connectome across temporal scales

Sepideh Sadaghiani

Mar 29, 2022

The view of human brain function has drastically shifted over the last decade, owing to the observation that the majority of brain activity is intrinsic rather than driven by external stimuli or cognitive demands. Specifically, all brain regions continuously communicate in spatiotemporally organized patterns that constitute the functional connectome, with consequences for cognition and behavior. In this talk, I will argue that another shift is underway, driven by new insights from synergistic interrogation of the functional connectome using different acquisition methods. The human functional connectome is typically investigated with functional magnetic resonance imaging (fMRI) that relies on the indirect hemodynamic signal, thereby emphasizing very slow connectivity across brain regions. Conversely, more recent methodological advances demonstrate that fast connectivity within the whole-brain connectome can be studied with real-time methods such as electroencephalography (EEG). Our findings show that combining fMRI with scalp or intracranial EEG in humans, especially when recorded concurrently, paints a rich picture of neural communication across the connectome. Specifically, the connectome comprises both fast, oscillation-based connectivity observable with EEG, as well as extremely slow processes best captured by fMRI. While the fast and slow processes share an important degree of spatial organization, these processes unfold in a temporally independent manner. Our observations suggest that fMRI and EEG may be envisaged as capturing distinct aspects of functional connectivity, rather than intermodal measurements of the same phenomenon. Infraslow fluctuation-based and rapid oscillation-based connectivity of various frequency bands constitute multiple dynamic trajectories through a shared state space of discrete connectome configurations. The multitude of flexible trajectories may concurrently enable functional connectivity across multiple independent sets of distributed brain regions.

Giersch Lab, INSERM U1114

Neurocognitive mechanisms of enhanced implicit temporal processing in action video game players

Francois R. Foerster

Feb 22, 2022

Playing action video games involves both explicit (conscious) and implicit (non-conscious) expectations of timed events, such as the appearance of foes. While studies revealed that explicit attention skills are improved in action video game players (VGPs), their implicit skills remained untested. To this end, we investigated explicit and implicit temporal processing in VGPs and non-VGPs (control participants). In our variable foreperiod task, participants were immersed in a virtual reality and instructed to respond to a visual target appearing at variable delays after a cue. I will present behavioral, oculomotor and EEG data and discuss possible markers of the implicit passage of time and explicit temporal attention processing. All evidence indicates that VGPs have enhanced implicit skills to track the passage of time, which does not require conscious attention. Thus, action video game play may improve a temporal processing found altered in psychopathologies, such as schizophrenia. Could digital (game-based) interventions help remediate temporal processing deficits in psychiatric populations?

Do we reason differently about affectively charged analogies? Insights from EEG research

Yanick Leblanc-Sirois

Université Laval

Feb 9, 2022

Affectively charged analogies are commonly used in literature and art, but also in politics and argumentation. There are reasons to think we may process these analogies differently. Notably, analogical reasoning is a complex process that requires the use of cognitive resources, which are limited. In the presence of affectively charged content, some of these resources might be directed towards affective processing and away from analogical reasoning. To investigate this idea, I investigated effects of affective charge on differences in brain activity evoked by sound versus unsound analogies. The presentation will detail the methods and results for two such experiments, one in which participants saw analogies formed of neutral and negative words and one in which they were created by combining conditioned symbols. I will also briefly discuss future research aiming to investigate the effects of analogical reasoning on brain activity related to affective processing.

Cognitive Neuroscience Lab (Bits Pilani Goa Campus)

Multimodal framework and fusion of EEG, graph theory and sentiment analysis for the prediction and interpretation of consumer decision

Veeky Baths

Feb 2, 2022

The application of neuroimaging methods to marketing has recently gained lots of attention. In analyzing consumer behaviors, the inclusion of neuroimaging tools and methods is improving our understanding of consumer’s preferences. Human emotions play a significant role in decision making and critical thinking. Emotion classification using EEG data and machine learning techniques has been on the rise in the recent past. We evaluate different feature extraction techniques, feature selection techniques and propose the optimal set of features and electrodes for emotion recognition.Affective neuroscience research can help in detecting emotions when a consumer responds to an advertisement. Successful emotional elicitation is a verification of the effectiveness of an advertisement. EEG provides a cost effective alternative to measure advertisement effectiveness while eliminating several drawbacks of the existing market research tools which depend on self-reporting. We used Graph theoretical principles to differentiate brain connectivity graphs when a consumer likes a logo versus a consumer disliking a logo. The fusion of EEG and sentiment analysis can be a real game changer and this combination has the power and potential to provide innovative tools for market research.

Center for Mathematics, Computing and Cognition, Federal University of ABC

Neural correlates of temporal processing in humans

Andre M. Cravo

Jan 25, 2022

Estimating intervals is essential for adaptive behavior and decision-making. Although several theoretical models have been proposed to explain how the brain keeps track of time, there is still no evidence toward a single one. It is often hard to compare different models due to their overlap in behavioral predictions. For this reason, several studies have looked for neural signatures of temporal processing using methods such as electrophysiological recordings (EEG). However, for this strategy to work, it is essential to have consistent EEG markers of temporal processing. In this talk, I'll present results from several studies investigating how temporal information is encoded in the EEG signal. Specifically, across different experiments, we have investigated whether different neural signatures of temporal processing (such as the CNV, the LPC, and early ERPs): 1. Depend on the task to be executed (whether or not it is a temporal task or different types of temporal tasks); 2. Are encoding the physical duration of an interval or how much longer/shorter an interval is relative to a reference. Lastly, I will discuss how these results are consistent with recent proposals that approximate temporal processing with decisional models.

The Hebrew University of Jerusalem

Neural signature for accumulated evidence underlying temporal decisions

Nir Ofir

Dec 15, 2021

Cognitive models of timing often include a pacemaker analogue whose ticks are accumulated to form an internal representation of time, and a threshold that determines when a target duration has elapsed. However, clear EEG manifestations of these abstract components have not yet been identified. We measured the EEG of subjects while they performed a temporal bisection task in which they were requested to categorize visual stimuli as short or long in duration. We report an ERP component whose amplitude depends monotonically on the stimulus duration. The relation of the ERP amplitude and stimulus duration can be captured by a simple model, adapted from a known drift-diffusion model for time perception. It includes a noisy accumulator that starts with the stimulus onset and a threshold. If the threshold is reached during stimulus presentation, the stimulus is categorized as "long", otherwise the stimulus is categorized as "short". At the stimulus offset, a response proportional to the distance to the threshold is emitted. This simple model has two parameters that fit both the behavior and ERP amplitudes recorded in the task. Two subsequent experiments replicate and extend this finding to another modality (touch) as well as to different time ranges (subsecond and suprasecond), establishing the described ERP component as a useful handle on the cognitive processes involved in temporal decisions.

The organization of neural representations for control

David Badre

Brown University

Dec 9, 2021

Cognitive control allows us to think and behave flexibly based on our context and goals. Most theories of cognitive control propose a control representation that enables the same input to produce different outputs contingent on contextual factors. In this talk, I will focus on an important property of the control representation's neural code: its representational dimensionality. Dimensionality of a neural representation balances a basic separability/generalizability trade-off in neural computation. This tradeoff has important implications for cognitive control. In this talk, I will present initial evidence from fMRI and EEG showing that task representations in the human brain leverage both ends of this tradeoff during flexible behavior.

Max Planck Institute for Biological Cybernetics, Tübingen

Neurocognitive mechanisms of proactive temporal attention: challenging oscillatory and cortico-centered models

Assaf Breska

Dec 1, 2021

To survive in a rapidly dynamic world, the brain predicts the future state of the world and proactively adjusts perception, attention and action. A key to efficient interaction is to predict and prepare to not only “where” and “what” things will happen, but also to “when”. I will present studies in healthy and neurological populations that investigated the cognitive architecture and neural basis of temporal anticipation. First, influential ‘entrainment’ models suggest that anticipation in rhythmic contexts, e.g. music or biological motion, uniquely relies on alignment of attentional oscillations to external rhythms. Using computational modeling and EEG, I will show that cortical neural patterns previously associated with entrainment in fact overlap with interval timing mechanisms that are used in aperiodic contexts. Second, temporal prediction and attention have commonly been associated with cortical circuits. Studying neurological populations with subcortical degeneration, I will present data that point to a double dissociation between rhythm- and interval-based prediction in the cerebellum and basal ganglia, respectively, and will demonstrate a role for the cerebellum in attentional control of perceptual sensitivity in time. Finally, using EEG in neurodegenerative patients, I will demonstrate that the cerebellum controls temporal adjustment of cortico-striatal neural dynamics, and use computational modeling to identify cerebellar-controlled neural parameters. Altogether, these findings reveal functionally and neural context-specificity and subcortical contributions to temporal anticipation, revising our understanding of dynamic cognition.

Change of mind in rapid free-choice picking scenarios

Ariel Furstenberg

The Hebrew University

Nov 23, 2021

In a famous philosophical paradox, Buridan's ass perishes because he is equally hungry and thirsty, and cannot make up his mind whether to first drink or eat. We are faced daily with the need to pick between alternatives that are equally attractive (or not) to us. What are the processes that allow us to avoid paralysis and to rapidly select between such equal options when there are no preferences or rational reasons to rely on? One solution that was offered is that although on a higher cognitive level there is symmetry between the alternatives, on a neuronal level the symmetry does not maintain. What is the nature of this asymmetry of the neuronal level? In this talk I will present experiments addressing this important phenomenon using measures of human behavior, EEG, EMG and large scale neural network modeling, and discuss mechanisms involved in the process of intention formation and execution, in the face of alternatives to choose from. Specifically, I will show results revealing the temporal dynamics of rapid intention formation and, moreover, ‘change of intention’ in a free choice picking scenario, in which the alternatives are on a par for the participant. The results suggest that even in arbitrary choices, endogenous or exogenous biases that are present in the neural system for selecting one or another option may be implicitly overruled; thus creating an implicit and non-conscious ‘change of mind’. Finally, the question is raised: in what way do such rapid implicit ‘changes of mind’ help retain one’s self-control and free-will behavior?

University of Texas at San Antonio

Stem cell approaches to understand acquired and genetic epilepsies

Jenny Hsieh

Nov 16, 2021

The Hsieh lab focuses on the mechanisms that promote neural stem cell self-renewal and differentiation in embryonic and adult brain. Using mouse models, video-EEG monitoring, viral techniques, and imaging/electrophysiological approaches, we elucidated many of the key transcriptional/epigenetic regulators of adult neurogenesis and showed aberrant new neuron integration in adult rodent hippocampus contribute to circuit disruption and seizure development. Building on this work, I will present our recent studies describing how GABA-mediated Ca2+ activity regulates the production of aberrant adult-born granule cells. In a new direction of my laboratory, we are using human induced pluripotent stem cells and brain organoid models as approaches to understand brain development and disease. Mutations in one gene, Aristaless-related homeobox (ARX), are of considerable interest since they are known to cause a common spectrum of neurodevelopmental disorders including epilepsy, autism, and intellectual disability. We have generated cortical and subpallial organoids from patients with poly-alanine expansion mutations in ARX. To understand the nature of ARX mutations in the organoid system, we are currently performing cellular, molecular, and physiological analyses. I will present these data to gain a comprehensive picture of the effect of ARX mutations in brain development. Since we do not understand how human brain development is affected by ARX mutations that contribute to epilepsy, we believe these studies will allow us to understand the mechanism of pathogenesis of ARX mutations, which has the potential to impact the diagnosis and care of patients.

Conflict in Multisensory Perception

Salvador Soto.Faraco

Universitat Pompeu Fabra

Nov 10, 2021

Multisensory perception is often studied through the effects of inter-sensory conflict, such as in the McGurk effect, the Ventriloquist illusion, and the Rubber Hand Illusion. Moreover, Bayesian approaches to cue fusion and causal inference overwhelmingly draw on cross-modal conflict to measure and to model multisensory perception. Given the prevalence of conflict, it is remarkable that accounts of multisensory perception have so far neglected the theory of conflict monitoring and cognitive control, established about twenty years ago. I hope to make a case for the role of conflict monitoring and resolution during multisensory perception. To this end, I will present EEG and fMRI data showing that cross-modal conflict in speech, resulting in either integration or segregation, triggers neural mechanisms of conflict detection and resolution. I will also present data supporting a role of these mechanisms during perceptual conflict in general, using Binocular Rivalry, surrealistic imagery, and cinema. Based on this preliminary evidence, I will argue that it is worth considering the potential role of conflict in multisensory perception and its incorporation in a causal inference framework. Finally, I will raise some potential problems associated with this proposal.

Institute of Pharmacology and Toxicology, University of Zürich, Zürich, Switzerland; Sleep & Health Zurich, University Center of Competence, University of Zürich, Zürich, Switzerland

Will it keep me awake? Common caffeine intake habits and sleep in real life situations

Hans-Peter Landolt

Oct 21, 2021

Daily caffeine consumption and chronic sleep restriction are highly prevalent in society. It is well established that acute caffeine intake under controlled conditions enhances vigilance and promotes wakefulness but can also delay sleep initiation and reduce electroencephalographic (EEG) markers of sleep intensity, particularly in susceptible individuals. To investigate whether these effects are also present during chronic consumption of coffee/caffeine, we recently conducted several complementary studies. We examined whether repeated coffee intake in dose and timing mimicking ‘real world’ habits maintains simple and complex attentional processes during chronic sleep restriction, such as during a busy work week. We found in genetically caffeine-sensitive individuals that regular coffee (300 mg caffeine/day) benefits most attentional tasks for 3-4 days when compared to decaffeinated coffee. Genetic variants were also used in the population-based HypnoLaus cohort, to investigate whether habitual caffeine consumption causally affects time to fall asleep, number of awakenings during sleep, and EEG-derived sleep intensity. The multi-level statistical analyses consistently showed that sleep quality was virtually unaffected when >3 caffeine-containing beverages/day were compared to 0-3 beverages/day. This conclusion was further corroborated by quantifying the sleep EEG in the laboratory in habitual caffeine consumers. Compared to placebo, daily intake of 3 x 150 mg caffeine over 10 days did not strongly impair nocturnal sleep nor subjective sleep quality in good sleepers. Finally, we tested whether an engineered delayed, pulsatile-release caffeine formula can improve the quality of morning awakening in sleep-restricted volunteers. We found that 160 mg caffeine taken at bedtime ameliorated the quality of awakening, increased positive and reduced negative affect scores, and promoted sustained attention immediately upon scheduled wake-up. Such an approach could prevent over-night caffeine withdrawal and provide a proactive strategy to attenuate disabling sleep inertia. Taken together, the studies suggest that common coffee/caffeine intake habits can transiently attenuate detrimental consequences of reduced sleep virtually without disturbing subjective and objective markers of sleep quality. Nevertheless, coffee/caffeine consumption cannot compensate for chronic sleep restriction.

Kohn lab, Albert Einstein College of Medicine; Growth Intelligence, UK

- CANCELLED -

Selina Solomon

Oct 19, 2021

A recent formulation of predictive coding theory proposes that a subset of neurons in each cortical area encodes sensory prediction errors, the difference between predictions relayed from higher cortex and the sensory input. Here, we test for evidence of prediction error responses in spiking responses and local field potentials (LFP) recorded in primary visual cortex and area V4 of macaque monkeys, and in complementary electroencephalographic (EEG) scalp recordings in human participants. We presented a fixed sequence of visual stimuli on most trials, and violated the expected ordering on a small subset of trials. Under predictive coding theory, pattern-violating stimuli should trigger robust prediction errors, but we found that spiking, LFP and EEG responses to expected and pattern-violating stimuli were nearly identical. Our results challenge the assertion that a fundamental computational motif in sensory cortex is to signal prediction errors, at least those based on predictions derived from temporal patterns of visual stimulation.

Nuttida Rungratsameetaweemana

Neural dynamics of probabilistic information processing in humans and recurrent neural networks

Sejnowski lab, The Salk Institute

Oct 5, 2021

In nature, sensory inputs are often highly structured, and statistical regularities of these signals can be extracted to form expectation about future sensorimotor associations, thereby optimizing behavior. One of the fundamental questions in neuroscience concerns the neural computations that underlie these probabilistic sensorimotor processing. Through a recurrent neural network (RNN) model and human psychophysics and electroencephalography (EEG), the present study investigates circuit mechanisms for processing probabilistic structures of sensory signals to guide behavior. We first constructed and trained a biophysically constrained RNN model to perform a series of probabilistic decision-making tasks similar to paradigms designed for humans. Specifically, the training environment was probabilistic such that one stimulus was more probable than the others. We show that both humans and the RNN model successfully extract information about stimulus probability and integrate this knowledge into their decisions and task strategy in a new environment. Specifically, performance of both humans and the RNN model varied with the degree to which the stimulus probability of the new environment matched the formed expectation. In both cases, this expectation effect was more prominent when the strength of sensory evidence was low, suggesting that like humans, our RNNs placed more emphasis on prior expectation (top-down signals) when the available sensory information (bottom-up signals) was limited, thereby optimizing task performance. Finally, by dissecting the trained RNN model, we demonstrate how competitive inhibition and recurrent excitation form the basis for neural circuitry optimized to perform probabilistic information processing.

Interpreting the Mechanisms and Meaning of Sensorimotor Beta Rhythms with the Human Neocortical Neurosolver (HNN) Neural Modeling Software

Stephanie Jones

Brown University

Sep 7, 2021

Electro- and magneto-encephalography (EEG/MEG) are the leading methods to non-invasively record human neural dynamics with millisecond temporal resolution. However, it can be extremely difficult to infer the underlying cellular and circuit level origins of these macro-scale signals without simultaneous invasive recordings. This limits the translation of E/MEG into novel principles of information processing, or into new treatment modalities for neural pathologies. To address this need, we developed the Human Neocortical Neurosolver (HNN: https://hnn.brown/edu ), a new user-friendly neural modeling tool designed to help researchers and clinicians interpret human imaging data. A unique feature of HNN’s model is that it accounts for the biophysics generating the primary electric currents underlying such data, so simulation results are directly comparable to source localized data. HNN is being constructed with workflows of use to study some of the most commonly measured E/MEG signals including event related potentials, and low frequency brain rhythms. In this talk, I will give an overview of this new tool and describe an application to study the origin and meaning of 15-29Hz beta frequency oscillations, known to be important for sensory and motor function. Our data showed that in primary somatosensory cortex these oscillations emerge as transient high power ‘events’. Functionally relevant differences in averaged power reflected a difference in the number of high-power beta events per trial (“rate”), as opposed to changes in event amplitude or duration. These findings were consistent across detection and attention tasks in human MEG, and in local field potentials from mice performing a detection task. HNN modeling led to a new theory on the circuit origin of such beta events and suggested beta causally impacts perception through layer specific recruitment of cortical inhibition, with support from invasive recordings in animal models and high-resolution MEG in humans. In total, HNN provides an unpresented biophysically principled tool to link mechanism to meaning of human E/MEG signals.

Enhanced perception and cognition in deaf sign language users: EEG and behavioral evidence

Lorna Quandt

Gallaudet University

Aug 18, 2021

In this talk, Dr. Quandt will share results from behavioral and cognitive neuroscience studies from the past few years of her work in the Action & Brain Lab, an EEG lab at Gallaudet University, the world's premiere university for deaf and hard-of-hearing students. These results will center upon the question of how extensive knowledge of signed language changes, and in some cases enhances, people's perception and cognition. Evidence for this effect comes from studies of human biological motion using point light displays, self-report, and studies of action perception. Dr. Quandt will also discuss some of the lab's efforts in designing and testing a virtual reality environment in which users can learn American Sign Language from signing avatars (virtual humans).

Characterising the brain representations behind variations in real-world visual behaviour

Simon Faghel-Soubeyrand

Université de Montréal

Aug 4, 2021

Not all individuals are equally competent at recognizing the faces they interact with. Revealing how the brains of different individuals support variations in this ability is a crucial step to develop an understanding of real-world human visual behaviour. In this talk, I will present findings from a large high-density EEG dataset (>100k trials of participants processing various stimulus categories) and computational approaches which aimed to characterise the brain representations behind real-world proficiency of “super-recognizers”—individuals at the top of face recognition ability spectrum. Using decoding analysis of time-resolved EEG patterns, we predicted with high precision the trial-by-trial activity of super-recognizers participants, and showed that evidence for face recognition ability variations is disseminated along early, intermediate and late brain processing steps. Computational modeling of the underlying brain activity uncovered two representational signatures supporting higher face recognition ability—i) mid-level visual & ii) semantic computations. Both components were dissociable in brain processing-time (the first around the N170, the last around the P600) and levels of computations (the first emerging from mid-level layers of visual Convolutional Neural Networks, the last from a semantic model characterising sentence descriptions of images). I will conclude by presenting ongoing analyses from a well-known case of acquired prosopagnosia (PS) using similar computational modeling of high-density EEG activity.

Monash Biomedical Imaging

Understanding the role of prediction in sensory encoding

Jason Mattingley

Jul 28, 2021

At any given moment the brain receives more sensory information than it can use to guide adaptive behaviour, creating the need for mechanisms that promote efficient processing of incoming sensory signals. One way in which the brain might reduce its sensory processing load is to encode successive presentations of the same stimulus in a more efficient form, a process known as neural adaptation. Conversely, when a stimulus violates an expected pattern, it should evoke an enhanced neural response. Such a scheme for sensory encoding has been formalised in predictive coding theories, which propose that recent experience establishes expectations in the brain that generate prediction errors when violated. In this webinar, Professor Jason Mattingley will discuss whether the encoding of elementary visual features is modulated when otherwise identical stimuli are expected or unexpected based upon the history of stimulus presentation. In humans, EEG was employed to measure neural activity evoked by gratings of different orientations, and multivariate forward modelling was used to determine how orientation selectivity is affected for expected versus unexpected stimuli. In mice, two-photon calcium imaging was used to quantify orientation tuning of individual neurons in the primary visual cortex to expected and unexpected gratings. Results revealed enhanced orientation tuning to unexpected visual stimuli, both at the level of whole-brain responses and for individual visual cortex neurons. Professor Mattingley will discuss the implications of these findings for predictive coding theories of sensory encoding. Professor Jason Mattingley is a Laureate Fellow and Foundation Chair in Cognitive Neuroscience at The University of Queensland. His research is directed toward understanding the brain processes that support perception, selective attention and decision-making, in health and disease.

SeminarPsychologyRecording

Spatio-temporal large-scale organization of the trimodal connectome derived from concurrent EEG-fMRI and diffusion MRI

Jonathan Wirsich

University of Geneva

Jul 21, 2021

While time-averaged dynamics of brain functional connectivity are known to reflect the underlying structural connections, the exact relationship between large-scale function and structure remains an unsolved issue in network neuroscience. Large-scale networks are traditionally observed by correlation of fMRI timecourses, and connectivity of source-reconstructed electrophysiological measures are less prominent. Accessing the brain by using multimodal recordings combining EEG, fMRI and diffusion MRI (dMRI) can help to refine the understanding of the spatio-temporal organization of both static and dynamic brain connectivity. In this talk I will discuss our prior findings that whole-brain connectivity derived from source-reconstructed resting-state (rs) EEG is both linked to the rs-fMRI and dMRI connectome. The EEG connectome provides complimentary information to link function to structure as compared to an fMRI-only perspective. I will present an approach extending the multimodal data integration of concurrent rs-EEG-fMRI to the temporal domain by combining dynamic functional connectivity of both modalities to better understand the neural basis of functional connectivity dynamics. The close relationship between time-varying changes in EEG and fMRI whole-brain connectivity patterns provide evidence for spontaneous reconfigurations of the brain’s functional processing architecture. Finally, I will talk about data quality of connectivity derived from concurrent EEG-fMRI recordings and how the presented multimodal framework could be applied to better understand focal epilepsy. In summary this talk will give an overview of how to integrate large-scale EEG networks with MRI-derived brain structure and function. In conclusion EEG-based connectivity measures not only are closely linked to MRI-based measures of brain structure and function over different time-scales, but also provides complimentary information on the function of underlying brain organization.

Differential working memory functioning

Anja Leue

University of Kiel, Germany

Jul 20, 2021

The integrated conflict monitoring theory of Botvinick introduced cognitive demand into conflict monitoring research. We investigated effects of individual differences of cognitive demand and another determinant of conflict monitoring entitled reinforcement sensitivity on conflict monitoring. We showed evidence of differential variability of conflict monitoring intensity using the electroencephalogram (EEG), functional magnet resonance imaging (fMRI) and behavioral data. Our data suggest that individual differences of anxiety and reasoning ability are differentially related to the recruitment of proactive and reactive cognitive control (cf. Braver). Based on previous findings, the team of the Leue-Lab investigated new psychometric data on conflict monitoring and proactive-reactive cognitive control. Moreover, data of the Leue-Lab suggest the relevance of individual differences of conflict monitoring for the context of deception. In this respect, we plan new studies highlighting individual differences of the functioning of the Anterior Cingulate Cortex (ACC). Disentangling the role of individual differences in working memory-related cognitive demand, mental effort, and reinforcement-related processes opens new insights for cognitive-motivational approaches of information processing (Passcode to rewatch: 0R8v&m59).

Yulong Li, Christos Kapatos, Mary Ann Go, Sonja Hofer, Oscar Bates, Christian Wilms

Imperial Neurotechnology 2021 - Annual Research Symposium

Peking University, SERG Technologies, Imperial College, UCL, Scientifica Ltd

Jul 6, 2021

A diverse mix of neurotechnology talks from academic and industry colleagues plus presentations from our MRes Neurotechnology students. Visit our event page to find out more and register now!

Investigating visual recognition and the temporal lobes using electrophysiology and fast periodic visual stimulation

Angelique Volfart

University of Louvain

Jun 23, 2021

The ventral visual pathway extends from the occipital to the anterior temporal regions, and is specialized in giving meaning to objects and people that are perceived through vision. Numerous studies in functional magnetic resonance imaging have focused on the cerebral basis of visual recognition. However, this technique is susceptible to magnetic artefacts in ventral anterior temporal regions and it has led to an underestimation of the role of these regions within the ventral visual stream, especially with respect to face recognition and semantic representations. Moreover, there is an increasing need for implicit methods assessing these functions as explicit tasks lack specificity. In this talk, I will present three studies using fast periodic visual stimulation (FPVS) in combination with scalp and/or intracerebral EEG to overcome these limitations and provide high SNR in temporal regions. I will show that, beyond face recognition, FPVS can be extended to investigate semantic representations using a face-name association paradigm and a semantic categorisation paradigm with written words. These results shed new light on the role of temporal regions and demonstrate the high potential of the FPVS approach as a powerful electrophysiological tool to assess various cognitive functions in neurotypical and clinical populations.