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Probing of Brain States in Real-Time: Introducing the ConSole Environment.

Hartmann T, Schulz H, Weisz N - Front Psychol (2011)

Bottom Line: However such offline analyses are disadvantageous as they are correlational by drawing conclusions in a post hoc-manner and stimulus presentation is random with respect to the feature of interest.The software is also independent from the EEG/MEG system, as long as a driver can be written (currently two EEG systems are supported).Besides a general introduction, we present benchmark data regarding performance and validity of the calculations used, as well as three example applications of ConSole in different settings.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychology, Universität Konstanz Konstanz, Germany.

ABSTRACT
Recent years have seen huge advancements in the methods available and used in neuroscience employing EEG or MEG. However, the standard approach is to average a large number of trials for experimentally defined conditions in order to reduce intertrial-variability, i.e., treating it as a source of "noise." Yet it is now more and more accepted that trial-to-trial fluctuations bear functional significance, reflecting fluctuations of "brain states" that predispose perception and action. Such effects are often revealed in a pre-stimulus period, when comparing response variability to an invariant stimulus. However such offline analyses are disadvantageous as they are correlational by drawing conclusions in a post hoc-manner and stimulus presentation is random with respect to the feature of interest. A more direct test is to trigger stimulus presentation when the relevant feature is present. The current paper introduces Constance System for Online EEG (ConSole), a software package capable of analyzing ongoing EEG/MEG in real-time and presenting auditory and visual stimuli via internal routines. Stimulation via external devices (e.g., transcranial magnetic stimulation) or third-party software (e.g., PsyScope X) is possible by sending TTL-triggers. With ConSole it is thus possible to target the stimulation at specific brain states. In contrast to many available applications, ConSole is open-source. Its modular design enhances the power of the software as it can be easily adapted to new challenges and writing new experiments is an easy task. ConSole is already pre-equipped with modules performing standard signal processing steps. The software is also independent from the EEG/MEG system, as long as a driver can be written (currently two EEG systems are supported). Besides a general introduction, we present benchmark data regarding performance and validity of the calculations used, as well as three example applications of ConSole in different settings. ConSole can be downloaded at: http://console-kn.sf.net.

No MeSH data available.


Related in: MedlinePlus

(A) Screenshot of the patient's training screen. The fish takes 10 s to move from the left to the right of the screen. The first 5 s are the “baseline” period for the patient without any stimulation. In the second half, the patients were stimulated with a sound that resulted in an alpha desynchronization. The patient's task was then to increase temporal alpha power which was indicated by the height of the displayed fish. The patient was rewarded after the trial if the fish stayed above the target line for a sufficient amount of time. (B) Normalized alpha power of all subjects over all 10 sessions before and after neurofeedback training. Alpha power increased significantly within and between sessions. Error bars denote SE. (C) Distress rating of all subjects over all 10 sessions before and after neurofeedback training. Distress was reduced significantly within and between sessions. Error bars denote SE.
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Figure 5: (A) Screenshot of the patient's training screen. The fish takes 10 s to move from the left to the right of the screen. The first 5 s are the “baseline” period for the patient without any stimulation. In the second half, the patients were stimulated with a sound that resulted in an alpha desynchronization. The patient's task was then to increase temporal alpha power which was indicated by the height of the displayed fish. The patient was rewarded after the trial if the fish stayed above the target line for a sufficient amount of time. (B) Normalized alpha power of all subjects over all 10 sessions before and after neurofeedback training. Alpha power increased significantly within and between sessions. Error bars denote SE. (C) Distress rating of all subjects over all 10 sessions before and after neurofeedback training. Distress was reduced significantly within and between sessions. Error bars denote SE.

Mentions: Nine otherwise healthy patients (one female, mean age ± SD: 57 ± 8.8 years) suffering from chronic tinnitus were recruited via advertisements in the local newspaper. All patients were informed about the training and gave written consent. The procedure was approved by the local ethics committee. The patients took part in 10 session within 3 weeks. Each session consisted of one baseline measurement to calibrate the neurofeedback system, four training runs, and another baseline measurement after the training to assess changes in cortical activity within each session. In the training runs, patients were shown a feedback on a screen for 5 s without hearing a tone (see Figure 5A). They were instructed to consider this period as a baseline that showed how auditory areas of their brain behaved without any input. Afterward, patients were stimulated with a sound that was filtered to match their tinnitus sound as closely as possible. Because of the aforementioned effect, patients saw a decrease in alpha activity via the feedback. They were instructed that one possible strategy for increasing alpha activity was to ignore the sound. Baseline measurements before and after the training runs differed from those only by not providing feedback to the patients. The patients were instructed to passively listen to the sounds with eyes open.


Probing of Brain States in Real-Time: Introducing the ConSole Environment.

Hartmann T, Schulz H, Weisz N - Front Psychol (2011)

(A) Screenshot of the patient's training screen. The fish takes 10 s to move from the left to the right of the screen. The first 5 s are the “baseline” period for the patient without any stimulation. In the second half, the patients were stimulated with a sound that resulted in an alpha desynchronization. The patient's task was then to increase temporal alpha power which was indicated by the height of the displayed fish. The patient was rewarded after the trial if the fish stayed above the target line for a sufficient amount of time. (B) Normalized alpha power of all subjects over all 10 sessions before and after neurofeedback training. Alpha power increased significantly within and between sessions. Error bars denote SE. (C) Distress rating of all subjects over all 10 sessions before and after neurofeedback training. Distress was reduced significantly within and between sessions. Error bars denote SE.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3110935&req=5

Figure 5: (A) Screenshot of the patient's training screen. The fish takes 10 s to move from the left to the right of the screen. The first 5 s are the “baseline” period for the patient without any stimulation. In the second half, the patients were stimulated with a sound that resulted in an alpha desynchronization. The patient's task was then to increase temporal alpha power which was indicated by the height of the displayed fish. The patient was rewarded after the trial if the fish stayed above the target line for a sufficient amount of time. (B) Normalized alpha power of all subjects over all 10 sessions before and after neurofeedback training. Alpha power increased significantly within and between sessions. Error bars denote SE. (C) Distress rating of all subjects over all 10 sessions before and after neurofeedback training. Distress was reduced significantly within and between sessions. Error bars denote SE.
Mentions: Nine otherwise healthy patients (one female, mean age ± SD: 57 ± 8.8 years) suffering from chronic tinnitus were recruited via advertisements in the local newspaper. All patients were informed about the training and gave written consent. The procedure was approved by the local ethics committee. The patients took part in 10 session within 3 weeks. Each session consisted of one baseline measurement to calibrate the neurofeedback system, four training runs, and another baseline measurement after the training to assess changes in cortical activity within each session. In the training runs, patients were shown a feedback on a screen for 5 s without hearing a tone (see Figure 5A). They were instructed to consider this period as a baseline that showed how auditory areas of their brain behaved without any input. Afterward, patients were stimulated with a sound that was filtered to match their tinnitus sound as closely as possible. Because of the aforementioned effect, patients saw a decrease in alpha activity via the feedback. They were instructed that one possible strategy for increasing alpha activity was to ignore the sound. Baseline measurements before and after the training runs differed from those only by not providing feedback to the patients. The patients were instructed to passively listen to the sounds with eyes open.

Bottom Line: However such offline analyses are disadvantageous as they are correlational by drawing conclusions in a post hoc-manner and stimulus presentation is random with respect to the feature of interest.The software is also independent from the EEG/MEG system, as long as a driver can be written (currently two EEG systems are supported).Besides a general introduction, we present benchmark data regarding performance and validity of the calculations used, as well as three example applications of ConSole in different settings.

View Article: PubMed Central - PubMed

Affiliation: Department of Psychology, Universität Konstanz Konstanz, Germany.

ABSTRACT
Recent years have seen huge advancements in the methods available and used in neuroscience employing EEG or MEG. However, the standard approach is to average a large number of trials for experimentally defined conditions in order to reduce intertrial-variability, i.e., treating it as a source of "noise." Yet it is now more and more accepted that trial-to-trial fluctuations bear functional significance, reflecting fluctuations of "brain states" that predispose perception and action. Such effects are often revealed in a pre-stimulus period, when comparing response variability to an invariant stimulus. However such offline analyses are disadvantageous as they are correlational by drawing conclusions in a post hoc-manner and stimulus presentation is random with respect to the feature of interest. A more direct test is to trigger stimulus presentation when the relevant feature is present. The current paper introduces Constance System for Online EEG (ConSole), a software package capable of analyzing ongoing EEG/MEG in real-time and presenting auditory and visual stimuli via internal routines. Stimulation via external devices (e.g., transcranial magnetic stimulation) or third-party software (e.g., PsyScope X) is possible by sending TTL-triggers. With ConSole it is thus possible to target the stimulation at specific brain states. In contrast to many available applications, ConSole is open-source. Its modular design enhances the power of the software as it can be easily adapted to new challenges and writing new experiments is an easy task. ConSole is already pre-equipped with modules performing standard signal processing steps. The software is also independent from the EEG/MEG system, as long as a driver can be written (currently two EEG systems are supported). Besides a general introduction, we present benchmark data regarding performance and validity of the calculations used, as well as three example applications of ConSole in different settings. ConSole can be downloaded at: http://console-kn.sf.net.

No MeSH data available.


Related in: MedlinePlus