Decoding dynamic brain patterns from evoked responses: A tutorial on multivariate pattern analysis applied to time series neuroimaging data
Multivariate pattern analysis (MVPA) or brain decoding methods have become standard
practice in analyzing fMRI data. Although decoding methods have been extensively applied …
practice in analyzing fMRI data. Although decoding methods have been extensively applied …
[HTML][HTML] Decoding cognition in neurodevelopmental, psychiatric and neurological conditions with multivariate pattern analysis of EEG data
Multivariate pattern analysis (MVPA) of electroencephalographic (EEG) data represents a
revolutionary approach to investigate how the brain encodes information. By considering …
revolutionary approach to investigate how the brain encodes information. By considering …
THINGS-data, a multimodal collection of large-scale datasets for investigating object representations in human brain and behavior
Understanding object representations requires a broad, comprehensive sampling of the
objects in our visual world with dense measurements of brain activity and behavior. Here …
objects in our visual world with dense measurements of brain activity and behavior. Here …
Distributed representations of behaviour-derived object dimensions in the human visual system
Object vision is commonly thought to involve a hierarchy of brain regions processing
increasingly complex image features, with high-level visual cortex supporting object …
increasingly complex image features, with high-level visual cortex supporting object …
Evidence that neural information flow is reversed between object perception and object reconstruction from memory
Remembering is a reconstructive process, yet little is known about how the reconstruction of
a memory unfolds in time in the human brain. Here, we used reaction times and EEG time …
a memory unfolds in time in the human brain. Here, we used reaction times and EEG time …
The representational dynamics of task and object processing in humans
Despite the importance of an observer's goals in determining how a visual object is
categorized, surprisingly little is known about how humans process the task context in which …
categorized, surprisingly little is known about how humans process the task context in which …
Recurrent neural networks can explain flexible trading of speed and accuracy in biological vision
Deep feedforward neural network models of vision dominate in both computational
neuroscience and engineering. The primate visual system, by contrast, contains abundant …
neuroscience and engineering. The primate visual system, by contrast, contains abundant …
[HTML][HTML] Decoding the brain: Neural representation and the limits of multivariate pattern analysis in cognitive neuroscience
Since its introduction, multivariate pattern analysis (MVPA), or 'neural decoding', has
transformed the field of cognitive neuroscience. Underlying its influence is a crucial …
transformed the field of cognitive neuroscience. Underlying its influence is a crucial …
Similarity-based fusion of MEG and fMRI reveals spatio-temporal dynamics in human cortex during visual object recognition
Every human cognitive function, such as visual object recognition, is realized in a complex
spatio-temporal activity pattern in the brain. Current brain imaging techniques in isolation …
spatio-temporal activity pattern in the brain. Current brain imaging techniques in isolation …
Visual representations: Insights from neural decoding
Patterns of brain activity contain meaningful information about the perceived world. Recent
decades have welcomed a new era in neural analyses, with computational techniques from …
decades have welcomed a new era in neural analyses, with computational techniques from …