scholarly journals Human Neocortical Neurosolver (HNN), a new software tool for interpreting the cellular and network origin of human MEG/EEG data

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Samuel A Neymotin ◽  
Dylan S Daniels ◽  
Blake Caldwell ◽  
Robert A McDougal ◽  
Nicholas T Carnevale ◽  
...  
Keyword(s):  
Graphical User Interface ◽  
Brain Activity ◽  
Event Related Potentials ◽  
Software Tool ◽  
Translational Neuroscience ◽  
Electrical Currents ◽  
Disease States ◽  
Neuroscience Research ◽  
Eeg Data ◽  
Related Potentials

Magneto- and electro-encephalography (MEG/EEG) non-invasively record human brain activity with millisecond resolution providing reliable markers of healthy and disease states. Relating these macroscopic signals to underlying cellular- and circuit-level generators is a limitation that constrains using MEG/EEG to reveal novel principles of information processing or to translate findings into new therapies for neuropathology. To address this problem, we built Human Neocortical Neurosolver (HNN, https://hnn.brown.edu) software. HNN has a graphical user interface designed to help researchers and clinicians interpret the neural origins of MEG/EEG. HNN’s core is a neocortical circuit model that accounts for biophysical origins of electrical currents generating MEG/EEG. Data can be directly compared to simulated signals and parameters easily manipulated to develop/test hypotheses on a signal’s origin. Tutorials teach users to simulate commonly measured signals, including event related potentials and brain rhythms. HNN’s ability to associate signals across scales makes it a unique tool for translational neuroscience research.

scholarly journals Human Neocortical Neurosolver (HNN): A new software tool for interpreting the cellular and network origin of human MEG/EEG data

2019 ◽  
Author(s):  
Samuel A Neymotin ◽  
Dylan S Daniels ◽  
Blake Caldwell ◽  
Robert A McDougal ◽  
Nicholas T Carnevale ◽  
...  
Keyword(s):  
Graphical User Interface ◽  
Brain Activity ◽  
Event Related Potentials ◽  
Software Tool ◽  
Translational Neuroscience ◽  
Electrical Currents ◽  
Disease States ◽  
Neuroscience Research ◽  
Eeg Data ◽  
Related Potentials

AbstractMagneto- and electro-encephalography (MEG/EEG) non-invasively record human brain activity with millisecond resolution providing reliable markers of healthy and disease states. Relating these macroscopic signals to underlying cellular- and circuit-level generators is a limitation that constrains using MEG/EEG to reveal novel principles of information processing or to translate findings into new therapies for neuropathology. To address this problem, we built Human Neocortical Neurosolver (HNN, https://hnn.brown.edu) software. HNN has a graphical user interface designed to help researchers and clinicians interpret the neural origins of MEG/EEG. HNN’s core is a neocortical circuit model that accounts for biophysical origins of electrical currents generating MEG/EEG. Data can be directly compared to simulated signals and parameters easily manipulated to develop/test hypotheses on a signal’s origin. Tutorials teach users to simulate commonly measured signals, including event related potentials and brain rhythms. HNN’s ability to associate signals across scales makes it a unique tool for translational neuroscience research.

scholarly journals Time-frequency analysis methods and their application in developmental EEG data

2021 ◽  
Author(s):  
Santiago Morales ◽  
Maureen Bowers
Keyword(s):  
Brain Activity ◽  
Event Related Potentials ◽  
Phase Lag ◽  
Phase Synchrony ◽  
Time Frequency ◽  
Use Of Time ◽  
Eeg Data ◽  
Related Potentials ◽  
Neurophysiological Mechanisms ◽  
The Fourier Transform

EEG provides a rich measure of brain activity that can be characterized as neuronal oscillations. However, most developmental EEG work to date has focused on analyzing EEG data as Event-Related Potentials (ERPs) or power based on the Fourier transform. While these measures have been productive, they do not leverage all the information contained within the EEG signal. Namely, ERP analyses ignore non-phase-locked signals and Fourier-based power analyses ignore temporal information. Time-frequency analyses can better characterize the oscillations contained in the EEG data. By separating power and phase information across different frequencies, time-frequency measures provide a closer interpretation of the neurophysiological mechanisms, facilitate translation across neurophysiology disciplines, and capture processes not observed by ERP or Fourier-based analyses (e.g., connectivity). Despite their unique contributions, a literature review of this journal reveals that time-frequency analyses of EEG are yet to be embraced by the developmental cognitive neuroscience field. This manuscript presents a conceptual introduction to time-frequency analyses for developmental researchers. To facilitate the use of time-frequency analyses, we include a tutorial of accessible scripts, based on Cohen (2014), to calculate time-frequency power (signal strength), inter-trial phase synchrony (signal consistency), and two types of phase-based connectivity (inter-channel phase synchrony and weighted phase lag index).

scholarly journals Real-time audio processing of real-life soundscapes for EEG analysis: ERPs based on natural sound onsets

2021 ◽  
Author(s):  
Daniel Hölle ◽  
Sarah Blum ◽  
Sven Kissner ◽  
Stefan Debener ◽  
Martin Georg Bleichner
Keyword(s):  
Auditory Processing ◽  
Brain Activity ◽  
Real Life ◽  
Event Related Potentials ◽  
Information Need ◽  
Sound Perception ◽  
Temporal Precision ◽  
Audio Features ◽  
Eeg Data ◽  
Related Potentials

With smartphone-based mobile electroencephalography (EEG), we can investigate sound perception beyond the lab. To understand sound perception in the real world, we need to relate naturally occurring sounds to EEG data. For this, EEG and audio information need to be synchronized precisely, only then it is possible to capture fast and transient evoked neural responses and relate them to individual sounds. We have developed Android applications (AFEx and Record-a) that allow for the concurrent acquisition of EEG data and audio features, i.e., sound onsets, average signal power (RMS) and power spectral density (PSD) on smartphone. In this paper, we evaluate these apps by computing event-related potentials (ERPs) evoked by everyday sounds. One participant listened to piano notes (played live by a pianist) and to a home-office soundscape. Timing tests showed that the temporal precision of the system is very good. We calculated ERPs to sound onsets and observed the typical P1-N1-P2 complex of auditory processing. Furthermore, we show how to relate information on loudness (RMS) and spectra (PSD) to brain activity. In future studies, we can use this system to study sound processing in everyday life.

scholarly journals Eliciting and Recording Event Related Potentials (ERPs) in Behaviourally Unresponsive Populations: A Retrospective Commentary on Critical Factors

2021 ◽  
Vol 11 (7) ◽  
pp. 835
Author(s):  
Alexander Rokos ◽  
Richard Mah ◽  
Rober Boshra ◽  
Amabilis Harrison ◽  
Tsee Leng Choy ◽  
...  
Keyword(s):  
Event Related Potentials ◽  
Stimulus Presentation ◽  
Event Related Potential ◽  
Critical Factors ◽  
Healthy Elderly ◽  
States Of Consciousness ◽  
Long Latency ◽  
Eeg Data ◽  
Related Potentials ◽  
The Relationship

A consistent limitation when designing event-related potential paradigms and interpreting results is a lack of consideration of the multivariate factors that affect their elicitation and detection in behaviorally unresponsive individuals. This paper provides a retrospective commentary on three factors that influence the presence and morphology of long-latency event-related potentials—the P3b and N400. We analyze event-related potentials derived from electroencephalographic (EEG) data collected from small groups of healthy youth and healthy elderly to illustrate the effect of paradigm strength and subject age; we analyze ERPs collected from an individual with severe traumatic brain injury to illustrate the effect of stimulus presentation speed. Based on these critical factors, we support that: (1) the strongest paradigms should be used to elicit event-related potentials in unresponsive populations; (2) interpretation of event-related potential results should account for participant age; and (3) speed of stimulus presentation should be slower in unresponsive individuals. The application of these practices when eliciting and recording event-related potentials in unresponsive individuals will help to minimize result interpretation ambiguity, increase confidence in conclusions, and advance the understanding of the relationship between long-latency event-related potentials and states of consciousness.

scholarly journals Anytime collaborative brain–computer interfaces for enhancing perceptual group decision-making

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Saugat Bhattacharyya ◽  
Davide Valeriani ◽  
Caterina Cinel ◽  
Luca Citi ◽  
Riccardo Poli
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Brain Activity ◽  
Event Related Potentials ◽  
Brain Computer Interfaces ◽  
Appearance Time ◽  
Perceptual Group ◽  
Computer Interfaces ◽  
Related Potentials

AbstractIn this paper we present, and test in two realistic environments, collaborative Brain-Computer Interfaces (cBCIs) that can significantly increase both the speed and the accuracy of perceptual group decision-making. The key distinguishing features of this work are: (1) our cBCIs combine behavioural, physiological and neural data in such a way as to be able to provide a group decision at any time after the quickest team member casts their vote, but the quality of a cBCI-assisted decision improves monotonically the longer the group decision can wait; (2) we apply our cBCIs to two realistic scenarios of military relevance (patrolling a dark corridor and manning an outpost at night where users need to identify any unidentified characters that appear) in which decisions are based on information conveyed through video feeds; and (3) our cBCIs exploit Event-Related Potentials (ERPs) elicited in brain activity by the appearance of potential threats but, uniquely, the appearance time is estimated automatically by the system (rather than being unrealistically provided to it). As a result of these elements, in the two test environments, groups assisted by our cBCIs make both more accurate and faster decisions than when individual decisions are integrated in more traditional manners.

Syntactically Based Sentence Processing Classes: Evidence from Event-Related Brain Potentials

1991 ◽  
Vol 3 (2) ◽  
pp. 151-165 ◽  
Author(s):  
Helen Neville ◽  
Janet L. Nicol ◽  
Andrew Barss ◽  
Kenneth I. Forster ◽  
Merrill F. Garrett
Keyword(s):  
Left Hemisphere ◽  
Sentence Processing ◽  
Brain Activity ◽  
Phrase Structure ◽  
Event Related Potentials ◽  
Negative Potential ◽  
Developmental Studies ◽  
Brain Potentials ◽  
Related Potentials ◽  
Theoretical Considerations

Theoretical considerations and diverse empirical data from clinical, psycholinguistic, and developmental studies suggest that language comprehension processes are decomposable into separate subsystems, including distinct systems for semantic and grammatical processing. Here we report that event-related potentials (ERPs) to syntactically well-formed but semantically anomalous sentences produced a pattern of brain activity that is distinct in timing and distribution from the patterns elicited by syntactically deviant sentences, and further, that different types of syntactic deviance produced distinct ERP patterns. Forty right-handed young adults read sentences presented at 2 words/sec while ERPs were recorded from over several positions between and within the hemispheres. Half of the sentences were semantically and grammatically acceptable and were controls for the remainder, which contained sentence medial words that violated (1) semantic expectations, (2) phrase structure rules, or (3) WH-movement constraints on Specificity and (4) Subjacency. As in prior research, the semantic anomalies produced a negative potential, N400, that was bilaterally distributed and was largest over posterior regions. The phrase structure violations enhanced the N125 response over anterior regions of the left hemisphere, and elicited a negative response (300-500 msec) over temporal and parietal regions of the left hemisphere. Violations of Specificity constraints produced a slow negative potential, evident by 125 msec, that was also largest over anterior regions of the left hemisphere. Violations of Subjacency constraints elicited a broadly and symmetrically distributed positivity that onset around 200 msec. The distinct timing and distribution of these effects provide biological support for theories that distinguish between these types of grammatical rules and constraints and more generally for the proposal that semantic and grammatical processes are distinct subsystems within the language faculty.

Frontal Brain Activity during Episodic and Semantic Retrieval: Insights from Event-Related Potentials

1999 ◽  
Vol 11 (6) ◽  
pp. 598-609 ◽  
Author(s):  
Charan Ranganath ◽  
Ken A. Paller
Keyword(s):  
Prefrontal Cortex ◽  
Memory Retrieval ◽  
Brain Activity ◽  
Novelty Detection ◽  
Event Related Potentials ◽  
Episodic Retrieval ◽  
Semantic Retrieval ◽  
Retrieval Task ◽  
Related Potentials ◽  
The Right

Previous neuropsychological and neuroimaging results have implicated the prefrontal cortex in memory retrieval, although its precise role is unclear. In the present study, we examined patterns of brain electrical activity during retrieval of episodic and semantic memories. In the episodic retrieval task, participants retrieved autobiographical memories in response to event cues. In the semantic retrieval task, participants generated exemplars in response to category cues. Novel sounds presented intermittently during memory retrieval elicited a series of brain potentials including one identifiable as the P3a potential. Based on prior research linking P3a with novelty detection and with the frontal lobes, we predicted that P3a would be reduced to the extent that novelty detection and memory retrieval interfere with each other. Results during episodic and semantic retrieval tasks were compared to results during a task in which subjects attended to the auditory stimuli. P3a amplitudes were reduced during episodic retrieval, particularly at right lateral frontal scalp locations. A similar but less lateralized pattern of frontal P3a reduction was observed during semantic retrieval. These findings support the notion that the right prefrontal cortex is engaged in the service of memory retrieval, particularly for episodic memories.

scholarly journals ERP CORE: An Open Resource for Human Event-Related Potential Research

2020 ◽  
Author(s):  
Emily S. Kappenman ◽  
Jaclyn Farrens ◽  
Wendy Zhang ◽  
Andrew X Stewart ◽  
Steven J Luck
Keyword(s):  
Data Processing ◽  
Brain Activity ◽  
A Priori ◽  
Event Related Potentials ◽  
Event Related Potential ◽  
Error Related Negativity ◽  
Wide Range ◽  
Experiment Control ◽  
Related Potentials

Event-related potentials (ERPs) are noninvasive measures of human brain activity that index a range of sensory, cognitive, affective, and motor processes. Despite their broad application across basic and clinical research, there is little standardization of ERP paradigms and analysis protocols across studies. To address this, we created ERP CORE (Compendium of Open Resources and Experiments), a set of optimized paradigms, experiment control scripts, data processing pipelines, and sample data (N = 40 neurotypical young adults) for seven widely used ERP components: N170, mismatch negativity (MMN), N2pc, N400, P3, lateralized readiness potential (LRP), and error-related negativity (ERN). This resource makes it possible for researchers to 1) employ standardized ERP paradigms in their research, 2) apply carefully designed analysis pipelines and use a priori selected parameters for data processing, 3) rigorously assess the quality of their data, and 4) test new analytic techniques with standardized data from a wide range of paradigms.

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