Cameron Higgins
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View article: Default Mode Network Detection using EEG in Real-time
Default Mode Network Detection using EEG in Real-time Open
Mental health disorders affect countless people worldwide and present a major challenge for mental health services, which are struggling with the demand on a global scale. Recent studies have indicated that activity of the brain’s Default …
View article: Large-scale cortical networks are organised in structured cycles
Large-scale cortical networks are organised in structured cycles Open
The brain needs to perform a diverse set of cognitive functions essential for survival, but it is unknown how it is organized to ensure that each of these functions is fulfilled within a reasonable period. One way in which this requirement…
View article: Reduced coupling between offline neural replay events and default mode network activation in schizophrenia
Reduced coupling between offline neural replay events and default mode network activation in schizophrenia Open
Schizophrenia is characterized by an abnormal resting state and default mode network brain activity. However, despite intense study, the mechanisms linking default mode network dynamics to neural computation remain elusive. During rest, se…
View article: Mixtures of large-scale dynamic functional brain network modes
Mixtures of large-scale dynamic functional brain network modes Open
Accurate temporal modelling of functional brain networks is essential in the quest for understanding how such networks facilitate cognition. Researchers are beginning to adopt time-varying analyses for electrophysiological data that captur…
View article: Spatiotemporally resolved multivariate pattern analysis for M/ <scp>EEG</scp>
Spatiotemporally resolved multivariate pattern analysis for M/ <span>EEG</span> Open
An emerging goal in neuroscience is tracking what information is represented in brain activity over time as a participant completes some task. While electroencephalography (EEG) and magnetoencephalography (MEG) offer millisecond temporal r…
View article: The relationship between frequency content and representational dynamics in the decoding of neurophysiological data
The relationship between frequency content and representational dynamics in the decoding of neurophysiological data Open
Decoding of high temporal resolution, stimulus-evoked neurophysiological data is increasingly used to test theories about how the brain processes information. However, a fundamental relationship between the frequency spectra of the neural …
View article: Brain stimulation boosts perceptual learning by altering sensory GABAergic plasticity and functional connectivity
Brain stimulation boosts perceptual learning by altering sensory GABAergic plasticity and functional connectivity Open
Interpreting cluttered scenes —a key skill for successfully interacting with our environment— relies on our ability to select relevant sensory signals while filtering out noise. Training is known to improve our ability to make these percep…
View article: Spatiotemporally Resolved Multivariate Pattern Analysis for M/EEG
Spatiotemporally Resolved Multivariate Pattern Analysis for M/EEG Open
An emerging goal in neuroscience is tracking what information is represented in brain activity over time as a participant completes some task. Whilst EEG and MEG offer millisecond temporal resolution of how activity patterns emerge and evo…
View article: Temporally delayed linear modelling (TDLM) measures replay in both animals and humans
Temporally delayed linear modelling (TDLM) measures replay in both animals and humans Open
There are rich structures in off-task neural activity which are hypothesized to reflect fundamental computations across a broad spectrum of cognitive functions. Here, we develop an analysis toolkit – temporal delayed linear modelling (TDLM…
View article: Author response: Temporally delayed linear modelling (TDLM) measures replay in both animals and humans
Author response: Temporally delayed linear modelling (TDLM) measures replay in both animals and humans Open
Article Figures and data Abstract Introduction Results Discussion Materials and methods Appendix 1 Appendix 2 Appendix 3 Appendix 4 Appendix 5 Data availability References Decision letter Author response Article and author information Metr…
View article: Replay bursts in humans coincide with activation of the default mode and parietal alpha networks
Replay bursts in humans coincide with activation of the default mode and parietal alpha networks Open
Our brains at rest spontaneously replay recently acquired information, but how this process is orchestrated to avoid interference with ongoing cognition is an open question. Here we investigated whether replay coincided with spontaneous pa…
View article: Replay bursts coincide with activation of the default mode and parietal alpha network
Replay bursts coincide with activation of the default mode and parietal alpha network Open
Our brains at rest spontaneously replay recently acquired information, but how this process is orchestrated to avoid interference with ongoing cognition is an open question. We investigated whether replay coincided with spontaneous pattern…
View article: Uncovering temporal structure in neural data with statistical machine learning models
Uncovering temporal structure in neural data with statistical machine learning models Open
Methods for analysing neural dynamics have predominantly focussed on resting state activity, typically using unsupervised models to infer the main modes of spontaneous variation in the absence of deliberately controlled experimental stimul…