Real-time decoding of covert attention in higher-order visual areas

ABSTRACT Brain‐computer‐interfaces (BCI) provide a means of using human brain activations to control devices for communication. Until now this has only been demonstrated in primary motor and sensory brain regions, using surgical implants or non‐invasive neuroimaging techniques. Here, we provide proof‐of‐principle for the use of higher‐order brain regions involved in complex cognitive processes such as attention. Using realtime fMRI, we implemented an online ‘winner‐takes‐all approach’ with quadrant‐specific parameter estimates, to achieve single‐block classification of brain activations. These were linked to the covert allocation of attention to real‐world images presented at 4‐quadrant locations. Accuracies in three target regions were significantly above chance, with individual decoding accuracies reaching upto 70%. By utilising higher order mental processes, ‘cognitive BCIs’ access varied and therefore more versatile information, potentially providing a platform for communication in patients who are unable to speak or move due to brain injury. HighlightsProof‐of‐principle of a ‘cognitive brain‐computer‐interface’ using realtime fMRI.Higher order visual brain regions used to decode the allocation of attention.Online single‐block classification of 4‐quadrant spatial attention to realworld images.Brain signal detection made more efficient by using ‘m‐sequences’.Higher order mental processes produce more information for communication interfaces.

• Publication year

  2018

• Venue

  NeuroImage

• Publication date

  2018-04-01

• Fields of study

  Medicine, Computer Science

• Identifiers
  DOI 10.1016/j.neuroimage.2017.12.019PMID 29247807PMCID 5864512
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

• Thought/translation

  2020cited by this paper
• Automated selection of brain regions for real-time fMRI brain–computer interfaces

  2017cited by this paper
• Direct Two-Dimensional Access to the Spatial Location of Covert Attention in Macaque Prefrontal Cortex.

  2016cited by this paper
• Brain-computer interfaces for dissecting cognitive processes underlying sensorimotor control.

  2016cited by this paper
• Current Challenges Facing the Translation of Brain Computer Interfaces from Preclinical Trials to Use in Human Patients

  2016cited by this paper
• Tracking the will to attend: Cortical activity indexes self-generated, voluntary shifts of attention

  2016cited by this paper
• DARPA-funded efforts in the development of novel brain–computer interface technologies

  2015cited by this paper
• Synaptic activity and Alzheimer's disease: a critical update

  2015cited by this paper
• Individual Differences in Temporal Selective Attention as Reflected in Pupil Dilation

  2015cited by this paper
• Closed-loop training of attention with real-time brain imaging

  2015cited by this paper
• Brain-Computer Interfaces

  2015cited by this paper
• Single trial decoding of visual attention from local field potentials in the primate lateral prefrontal cortex.

  2015cited by this paper
• Revealing neuronal function through microelectrode array recordings

  2015cited by this paper
• Evaluation of local field potential signals in decoding of visual attention

  2015cited by this paper
• DARPA-funded efforts in the development of novel brain-computer interface technologies.

  2015cited by this paper
• Single-Trial Decoding of Visual Attention from Local Field Potentials in the Primate Lateral Prefrontal Cortex Is Frequency-Dependent

  2015cited by this paper
• Brain-machine interfaces beyond neuroprosthetics.

  2015cited by this paper
• Decoding of Visual Attention from LFP Signals of Macaque MT

  2014cited by this paper
• DC-shifts in amplitude in-field generated by an oscillatory interference model of grid cell firing

  2014cited by this paper
• NIH Public Access

  2014cited by this paper
• A collaborative pipeline

  2014cited by this paper
• Selective visual attention to drive cognitive brain–machine interfaces: from concepts to neurofeedback and rehabilitation applications

  2014cited by this paper
• A hybrid method for the decoding of spatial attention using the MEG brain signals

  2014cited by this paper
• Cognitive-motor brain-machine interfaces.

  2014cited by this paper
• Mind over brain, brain over mind: cognitive causes and consequences of controlling brain activity

  2014cited by this paper
• Online decoding of object‐based attention using real‐time fMRI

  2014cited by this paper
• Top-down control.

  2014cited by this paper
• Dorsal and Ventral Attention Systems

  2014cited by this paper
• 7T fMRI reveals feasibility of covert visual attention-based brain-computer interfacing with signals obtained solely from cortical grey matter accessible by subdural surface electrodes.

  2013cited by this paper
• Prediction of brain-computer interface aptitude from individual brain structure

  2013cited by this paper
• Bottom-up and top-down attention are independent.

  2013cited by this paper
• Creating new functional circuits for action via brain-machine interfaces

  2013cited by this paper
• Dorsal and Ventral Attention Systems: Distinct Neural Circuits but Collaborative Roles

  2013cited by this paper
• Brain Computer Interface

  2013cited by this paper
• Brain Computer Interfacing

  2013cited by this paper
• Toward High Performance, Weakly Invasive Brain Computer Interfaces Using Selective Visual Attention

  2013cited by this paper
• Attention flexibly alters tuning for object categories.

  2013cited by this paper
• Covert Visuospatial Attention Orienting in a Brain-Computer Interface for Amyotrophic Lateral Sclerosis Patients

  2013cited by this paper
• Attention and P300-based BCI performance in people with amyotrophic lateral sclerosis

  2013cited by this paper
• Transfer of information by BMI.

  2013cited by this paper
• Top-down influences on visual processing

  2013cited by this paper
• Real-time decoding of the direction of covert visuospatial attention

  2012cited by this paper
• Navigation of a Telepresence Robot via Covert Visuospatial Attention and Real-Time fMRI

  2012cited by this paper
• Tracking cognitive fluctuations with multivoxel pattern time course (MVPTC) analysis.

  2012cited by this paper
• Cognitive signals for brain–machine interfaces in posterior parietal cortex include continuous 3D trajectory commands

  2012cited by this paper
• Brain-Computer Interfaces: Principles and Practice

  2012cited by this paper
• Decoding covert spatial attention using electrocorticographic (ECoG) signals in humans

  2012cited by this paper
• Neural interfaces for the brain and spinal cord—restoring motor function

  2012cited by this paper
• A real-time fMRI-based spelling device immediately enabling robust motor-independent communication.

  2012cited by this paper
• Mental Fatigue Affects Visual Selective Attention

  2012cited by this paper
• Signal quality and Bayesian signal processing in neurofeedback based on real-time fMRI

  2012cited by this paper
• Brain-computer interfacing using modulations of alpha activity induced by covert shifts of attention

  2011cited by this paper
• Encoding the identity and location of objects in human LOC

  2011cited by this paper
• Where do objects become scenes?

  2011cited by this paper
• Spatial coding and invariance in object-selective cortex.

  2011cited by this paper
• Training of goal-directed attention regulation enhances control over neural processing for individuals with brain injury.

  2011cited by this paper
• The neural basis of visual attention

  2011influential reference
• Visual attention: the past 25 years.

  2011cited by this paper
• Real-Time Decoding of Brain Responses to Visuospatial Attention Using 7T fMRI

  2011influential reference
• Mechanisms of top-down attention.

  2011cited by this paper
• Reversible large-scale modification of cortical networks during neuroprosthetic control

  2011cited by this paper
• The influence of alertness on spatial and nonspatial components of visual attention.

  2010cited by this paper
• Top-down control of visual attention.

  2010cited by this paper
• BCI control using 4 direction spatial visual attention and real-time fMRI at 7T

  2010cited by this paper
• Salience Representation in the Parietal and Frontal Cortex

  2010cited by this paper
• Covert attention allows for continuous control of brain–computer interfaces

  2010cited by this paper
• Brain–computer interfacing based on cognitive control

  2010cited by this paper
• Superior Parietal Cortex Is Critical for the Manipulation of Information in Working Memory

  2009cited by this paper
• fMRI based BCI control using spatial visual attention at 7T

  2009cited by this paper
• Decoding cognitive control in human parietal cortex

  2009cited by this paper
• The brain–computer interface cycle

  2009cited by this paper
• Brain–computer interface in paralysis

  2008cited by this paper
• Top-Down Control of Human Visual Cortex by Frontal and Parietal Cortex in Anticipatory Visual Spatial Attention

  2008cited by this paper
• Brain-computer interfaces in neurological rehabilitation.

  2008cited by this paper
• Cerebral Cortex doi:10.1093/cercor/bhm242 Retinotopy and Attention in Human Occipital, Temporal, Parietal, and Frontal Cortex

  2008influential reference
• The distribution of category and location information across object-selective regions in human visual cortex

  2008influential reference
• fMRI Brain-Computer Interface: A Tool for Neuroscientific Research and Treatment

  2007cited by this paper
• Brain–computer interface systems: progress and prospects

  2007cited by this paper
• From thought to action: the parietal cortex as a bridge between perception, action, and cognition.

  2007cited by this paper
• Brain states: top-down influences in sensory processing.

  2007cited by this paper
• Spatially selective representations of voluntary and stimulus-driven attentional priority in human occipital, parietal, and frontal cortex.

  2007cited by this paper
• Top-down biases win against focal attention in the fusiform face area

  2007cited by this paper
• Attentional modulation of repetition attenuation is anatomically dissociable for scenes and faces.

  2006cited by this paper
• Activity in the Lateral Intraparietal Area Predicts the Goal and Latency of Saccades in a Free-Viewing Visual Search Task

  2006cited by this paper
• Two Retinotopic Visual Areas in Human Lateral Occipital Cortex

  2006cited by this paper
• Testing anatomically specified hypotheses in functional imaging using cytoarchitectonic maps

  2006cited by this paper
• Brain-machine interfaces: past, present and future.

  2006cited by this paper
• P300-based brain computer interface: reliability and performance in healthy and paralysed participants.

  2006cited by this paper
• Difficulty of perceptual spatiotemporal integration modulates the neural activity of left inferior parietal cortex.

  2005cited by this paper
• A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data

  2005cited by this paper
• Visual spatial attention control in an independent brain-computer interface

  2005cited by this paper
• Independent Brain Computer Interface Control using Visual Spatial Attention-Dependent Modulations of Parieto-occipital Alpha

  2005cited by this paper
• Cortical visual areas in monkeys: location, topography, connections, columns, plasticity and cortical dynamics

  2005cited by this paper
• Self-regulation of local brain activity using real-time functional magnetic resonance imaging (fMRI).

  2004cited by this paper
• Brain^computer interface using fMRI: spatial navigation by thoughts

  2004cited by this paper
• Cognitive Control Signals for Neural Prosthetics

  2004cited by this paper
• Principles of a brain-computer interface (BCI) based on real-time functional magnetic resonance imaging (fMRI)

  2004cited by this paper
• Predictability of Brain-Computer Communication

  2004cited by this paper
• Left inferior parietal cortex integrates time and space during collision judgments.

  2003cited by this paper
• Transient neural activity in human parietal cortex during spatial attention shifts

  2002cited by this paper

• Progress in Non-Invasive Cognitive Brain-Computer Interface and Implications for Mind-Uploading

  2024influential citation
• Bridging Neuroscience and Minds: Exploring Collective Intelligence through Brain Duplication using AI

  2023cites this paper
• Non-invasive real-time access to spatial attention information from 3T fMRI BOLD signals

  2021cites this paper
• Modern Approaches to Augmenting the Brain Functions

  2021cites this paper
• Real-Time Decoding of Attentional States Using Closed-Loop EEG Neurofeedback

  2021cites this paper
• Single-Trial Decoding of Motion Direction During Visual Attention From Local Field Potential Signals

  2021cites this paper
• Modulating the interhemispheric activity balance in the intraparietal sulcus using real-time fMRI neurofeedback: Development and proof-of-concept

  2020cites this paper
• Functional Magnetic Resonance Imaging-Based Brain Computer Interfaces

  2020cites this paper
• Neural Engineering

  2020cites this paper
• Decoding the Temporal Dynamics of Covert Spatial Attention Using Multivariate EEG Analysis: Contributions of Raw Amplitude and Alpha Power

  2020cites this paper
• Brain–Computer Interfaces

  2020cites this paper
• A framework for closed-loop neurofeedback for real-time EEG decoding

  2019cites this paper
• Gedankenlesen aus der Hirnaktivität?

  2018cites this paper
• Brain–computer interaction for online enhancement of visuospatial attention performance

  2018cites this paper
• Automated selection of brain regions for real-time fMRI brain–computer interfaces

  2017cites this paper