Coupling between intrinsic prefrontal HbO2 and central EEG beta power oscillations in the resting brain.

There is increasing interest in the intrinsic activity in the resting brain, especially that of ultraslow and slow oscillations. Using near-infrared spectroscopy (NIRS), electroencephalography (EEG), blood pressure (BP), respiration and heart rate recordings during 5 minutes of rest, combined with cross spectral and sliding cross correlation calculations, we identified a short-lasting coupling (duration [Formula: see text] s) between prefrontal oxyhemoglobin (HbO2) in the frequency band between 0.07 and 0.13 Hz and central EEG alpha and/or beta power oscillations in 8 of the 9 subjects investigated. The HbO2 peaks preceded the EEG band power peaks by 3.7 s in 6 subjects, with moderate or no coupling between BP and HbO2 oscillations. HbO2 and EEG band power oscillations were approximately in phase with BP oscillations in the 2 subjects with an extremely high coupling (squared coherence [Formula: see text]) between BP and HbO2 oscillation. No coupling was identified in one subject. These results indicate that slow precentral (de)oxyhemoglobin concentration oscillations during awake rest can be temporarily coupled with EEG fluctuations in sensorimotor areas and modulate the excitability level in the brains' motor areas, respectively. Therefore, this provides support for the idea that resting state networks fluctuate with frequencies of between 0.01 and 0.1 Hz (Mantini et.al. PNAS 2007)

The Hybrid BCI

Nowadays, everybody knows what a hybrid car is. A hybrid car normally has two engines to enhance energy efficiency and reduce CO2 output. Similarly, a hybrid brain-computer interface (BCI) is composed of two BCIs, or at least one BCI and another system. A hybrid BCI, like any BCI, must fulfill the following four criteria: (i) the device must rely on signals recorded directly from the brain; (ii) there must be at least one recordable brain signal that the user can intentionally modulate to effect goal-directed behaviour; (iii) real time processing; and (iv) the user must obtain feedback. This paper introduces hybrid BCIs that have already been published or are in development. We also introduce concepts for future work. We describe BCIs that classify two EEG patterns: one is the event-related (de)synchronisation (ERD, ERS) of sensorimotor rhythms, and the other is the steady-state visual evoked potential (SSVEP). Hybrid BCIs can either process their inputs simultaneously, or operate two systems sequentially, where the first system can act as a “brain switch”. For example, we describe a hybrid BCI that simultaneously combines ERD and SSVEP BCIs. We also describe a sequential hybrid BCI, in which subjects could use a brain switch to control an SSVEP-based hand orthosis. Subjects who used this hybrid BCI exhibited about half the false positives encountered while using the SSVEP BCI alone. A brain switch can also rely on hemodynamic changes measured through near-infrared spectroscopy (NIRS). Hybrid BCIs can also use one brain signal and a different type of input. This additional input can be an electrophysiological signal such as the heart rate, or a signal from an external device such as an eye tracking system

fNIRS for future use in auditory diagnostics

Functional near-infrared spectroscopy (fNIRS) is an emerging technique for the assessment of functional activity of the cerebral cortex. Recently fNIRS was also envisaged as a novel neuroimaging approach for measuring the auditory cortex (AC) activity in cochlear implant (CI) users. In the present study we report on initial measurements of AC activation due to spatial sound presentation with a first target to generate data for comparison with CI user and the future use in auditory diagnostics

The interplay of prefrontal and sensorimotor cortices during inhibitory control of learned motor behavior

In the present study inhibitory cortical mechanisms have been investigated during execution and inhibition of learned motor programs by means of multi-channel functional near infrared spectroscopy (fNIRS). fNIRS is an emerging non-invasive optical technique for the in-vivo assessment of cerebral oxygenation, concretely changes of oxygenated [oxy-Hb] and deoxygenated [deoxy-Hb] hemoglobin. Eleven healthy subjects executed or inhibited previous learned finger and foot movements indicated by a visual cue. The execution of finger/foot movements caused a typical activation pattern namely an increase of [oxy-Hb] and a decrease of [deoxy-Hb] whereas the inhibition of finger/foot movements caused a decrease of [oxy-Hb] and an increase of [deoxy-Hb] in the hand or foot representation area (left or medial somatosensory and primary motor cortex). Additionally an increase of [oxy-Hb] and a decrease of [deoxy-Hb] in the medial area of the anterior prefrontal cortex (APFC) during the inhibition of finger/foot movements were found. The results showed, that inhibition/execution of learned motor programs depends on an interplay of focal increases and decreases of neural activity in prefrontal and sensorimotor areas regardless of the effector. As far as we know, this is the first study investigating inhibitory processes of finger/foot movements by means of multi-channel fNIRS

For each subject, couplings are listed between, HbO2 and Hb, HbO2 and BP, and BP and RRI.

<p>Dominant frequencies (DFs), periods, phase shifts, and squared coherence values () are listed in each case. Subjects with a high coupling () are highlighted in grey.</p

Data from a representative subject (S8).

<p>From top to bottom: time series of BPdia (mmHg), RRI (ms), HbO2 (mM*mm), Hb (mM*mm), EEG band power (C4, 15–25 Hz), and respiration (a.u.) during 300 s of rest. Relationships between individual peaks are marked by stippled lines.</p

From top to bottom.

<p>cross correlation function (CCF) for the 150–250 s window, time courses of EEG log band power (Cz, 15–25 Hz) and HbO2 during 300 s of rest and CCF calculated from the total 300 s (5 minute) epoch. Subject S2. Note, the significant correlation (r = 0.49, , p<0.01) in the 100 s window and the non-significant correlation (r = 0.2) for the total 300 s.</p

Correlations between EEG and HbO2 for all subjects.

<p>For each subject 100 s windows, which exhibit significant correlation (r>0.3), and their corresponding delays, are listed in the 9–14 and 15–25 Hz frequency bands. In the last column the delays with the largest correlation are indicated. For subject’s S2 and S5 the second largest correlations are also marked. Mean delay ( SD) is calculated without subject’s S2 and S5. Subjects with a high coupling ( between HbO2 and BP are highlighted in grey.</p