Abstract perceptual choice signals during action-linked decisions in the human brain.

Humans can make abstract choices independent of motor actions. However, in laboratory tasks, choices are typically reported with an associated action. Consequentially, knowledge about the neural representation of abstract choices is sparse, and choices are often thought to evolve as motor intentions. Here, we show that in the human brain, perceptual choices are represented in an abstract, motor-independent manner, even when they are directly linked to an action. We measured MEG signals while participants made choices with known or unknown motor response mapping. Using multivariate decoding, we quantified stimulus, perceptual choice, and motor response information with distinct cortical distributions. Choice representations were invariant to whether the response mapping was known during stimulus presentation, and they occupied a distinct representational space from motor signals. As expected from an internal decision variable, they were informed by the stimuli, and their strength predicted decision confidence and accuracy. Our results demonstrate abstract neural choice signals that generalize to action-linked decisions, suggesting a general role of an abstract choice stage in human decision-making.

Stroop in motion: Neurodynamic modulation underlying interference control while sitting, standing, and walking.

There is conflicting evidence about how interference control in healthy adults is affected by walking as compared to standing or sitting. Although the Stroop paradigm is one of the best-studied paradigms to investigate interference control, the neurodynamics associated with the Stroop task during walking have never been studied. We investigated three Stroop tasks using variants with increasing interference levels - word-reading, ink-naming, and the switching of the two tasks, combined in a systematic dual-tasking fashion with three motor conditions - sitting, standing, and treadmill walking. Neurodynamics underlying interference control were recorded using the electroencephalogram. Worsened performance was observed for the incongruent compared to congruent trials and for the switching Stroop compared to the other two variants. The early frontocentral event-related potentials (ERPs) associated with executive functions (P2, N2) differentially signaled posture-related workloads, while the later stages of information processing indexed faster interference suppression and response selection in walking compared to static conditions. The early P2 and N2 components as well as frontocentral Theta and parietal Alpha power were sensitive to increasing workloads on the motor and cognitive systems. The distinction between the type of load (motor and cognitive) became evident only in the later posterior ERP components in which the amplitude non-uniformly reflected the relative attentional demand of a task. Our data suggest that walking might facilitate selective attention and interference control in healthy adults. Existing interpretations of ERP components recorded in stationary settings should be considered with care as they might not be directly transferable to mobile settings.

On the Influence of Aging on Classification Performance in the Visual EEG Oddball Paradigm Using Statistical and Temporal Features.

The utilization of a non-invasive electroencephalogram (EEG) as an input sensor is a common approach in the field of the brain-computer interfaces (BCI). However, the collected EEG data pose many challenges, one of which may be the age-related variability of event-related potentials (ERPs), which are often used as primary EEG BCI signal features. To assess the potential effects of aging, a sample of 27 young and 43 older healthy individuals participated in a visual oddball study, in which they passively viewed frequent stimuli among randomly occurring rare stimuli while being recorded with a 32-channel EEG set. Two types of EEG datasets were created to train the classifiers, one consisting of amplitude and spectral features in time and another with extracted time-independent statistical ERP features. Among the nine classifiers tested, linear classifiers performed best. Furthermore, we show that classification performance differs between dataset types. When temporal features were used, maximum individuals' performance scores were higher, had lower variance, and were less affected overall by within-class differences such as age. Finally, we found that the effect of aging on classification performance depends on the classifier and its internal feature ranking. Accordingly, performance will differ if the model favors features with large within-class differences. With this in mind, care must be taken in feature extraction and selection to find the correct features and consequently avoid potential age-related performance degradation in practice.

Neural Bases of Age-Related Sensorimotor Slowing in the Upper and Lower Limbs.

With advanced age, there is a loss of reaction speed that may contribute to an increased risk of tripping and falling. Avoiding falls and injuries requires awareness of the threat, followed by selection and execution of the appropriate motor response. Using event-related potentials (ERPs) and a simple visual reaction task (RT), the goal of our study was to distinguish sensory and motor processing in the upper- and lower-limbs while attempting to uncover the main cause of age-related behavioral slowing. Strength (amplitudes) as well as timing and speed (latencies) of various stages of stimulus- and motor-related processing were analyzed in 48 healthy individuals (young adults, n = 24, mean age = 34 years; older adults, n = 24, mean age = 67 years). The behavioral results showed a significant age-related slowing, where the younger compared to older adults exhibited shorter RTs for the upper- (222 vs. 255 ms; p = 0.006, respectively) and the lower limb (257 vs. 274 ms; p = 0.048, respectively) as well as lower variability in both modalities (p = 0.001). Using ERP indices, age-related slowing of visual stimulus processing was characterized by overall larger amplitudes with delayed latencies of endogenous potentials in older compared with younger adults. While no differences were found in the P1 component, the later components of recorded potentials for visual stimuli processing were most affected by age. This was characterized by increased N1 and P2 amplitudes and delayed P2 latencies in both upper and lower extremities. The analysis of motor-related cortical potentials (MRCPs) revealed stronger MRCP amplitude for upper- and a non-significant trend for lower limbs in older adults. The MRCP amplitude was smaller and peaked closer to the actual motor response for the upper- than for the lower limb in both age groups. There were longer MRCP onset latencies for lower- compared to upper-limb in younger adults, and a non-significant trend was seen in older adults. Multiple regression analyses showed that the onset of the MRCP peak consistently predicted reaction time across both age groups and limbs tested. However, MRCP rise time and P2 latency were also significant predictors of simple reaction time, but only in older adults and only for the upper limbs. Our study suggests that motor cortical processes contribute most strongly to the slowing of simple reaction time in advanced age. However, late-stage cortical processing related to sensory stimuli also appears to play a role in upper limb responses in the elderly. This process most likely reflects less efficient recruitment of neuronal resources required for the upper and lower extremity response task in older adults.

Review of the therapeutic neurofeedback method using electroencephalography: EEG Neurofeedback.

Electroencephalographic neurofeedback (EEG-NFB) represents a broadly used method that involves a real-time EEG signal measurement, immediate data processing with the extraction of the parameter(s) of interest, and feedback to the individual in a real-time. Using such a feedback loop, the individual may gain better control over the neurophysiological parameters, by inducing changes in brain functioning and, consequently, behavior. It is used as a complementary treatment for a variety of neuropsychological disorders and improvement of cognitive capabilities, creativity or relaxation in healthy subjects. In this review, various types of EEG-NFB training are described, including training of slow cortical potentials (SCPs) and frequency and coherence training, with their main results and potential limitations. Furthermore, some general concerns about EEG-NFB methodology are presented, which still need to be addressed by the NFB community. Due to the heterogeneity of research designs in EEG-NFB protocols, clear conclusions on the effectiveness of this method are difficult to draw. Despite that, there seems to be a well-defined path for the EEG-NFB research in the future, opening up possibilities for improvement.