Review of real brain-controlled wheelchairs

This paper presents a review of the state of the art regarding wheelchairs driven by a brain-computer interface (BCI). Using a brain-controlled wheelchair (BCW), disabled users could handle a wheelchair through their brain activity, granting autonomy to move through an experimental environment. A classification is established, based on the characteristics of the BCW, such as the type of electroencephalographic (EEG) signal used, the navigation system employed by the wheelchair, the task for the participants, or the metrics used to evaluate the performance. Furthermore, these factors are compared according to the type of signal used, in order to clarify the differences among them. Finally, the trend of current research in this field is discussed, as well as the challenges that should be solved in the future

An analysis of right-and left-brain thinkers and certain styles of learning

Includes bibliographical references

Quantitative morphology of human hippocampus early neuron development

Background: Previous findings in adults revealed significant hemispheric asymmetry in size of neuronal somata in hippocampal subfield CA2 (the “resistant sector”) with no age-related changes. Paucity of quantitative data on the developmental status of these “protected” neurons has led to the investigation of their morphology in comparison to neurons in adjacent subfield CA3, bilaterally. Methods: Bilateral coronal sections from postmortem hippocampus, 24 and 76 weeks postmenstrual age (gestational age plus postnatal age) were studied. The neurons were digitized and measured on a computer. Results: Soma size correlated positively and significantly with age in CA2 and CA3, bilaterally. CA2 somata were significantly larger (left 34%, right 32%) than adjacent CA3 somata. Variability in soma form or size increased appreciably with age, in both subfields, bilaterally, while variability in soma orientation was weakly correlated with brain growth. Conclusions: The results suggest that in early development there are similarities in hemispheric growth patterns in CA2 and CA3. Large CA2 soma size implies axonal connectivity to distantly located targets very early in development. The results have functional implications, including memory, to brain developmen

Consciousness operates beyond the timescale for discerning time intervals: implications for Q-mind theories and analysis of quantum decoherence in brain

This paper presents in details how the subjective time is constructed by the brain cortex via reading packets of information called "time labels", produced by the right basal ganglia that act as brain timekeeper. Psychophysiological experiments have measured the subjective "time quanta" to be 40 ms and show that consciousness operates beyond that scale - an important result having profound implications for the Q-mind theory. Although in most current mainstream biophysics research on cognitive processes, the brain is modelled as a neural network obeying classical physics, Penrose (1989, 1997) and others have argued that quantum mechanics may play an essential role, and that successful brain simulations can only be performed with a quantum computer. Tegmark (2000) showed that make-or-break issue for the quantum models of mind is whether the relevant degrees of freedom of the brain can be sufficiently isolated to retain their quantum coherence and tried to settle the issue with detailed calculations of the relevant decoherence rates. He concluded that the mind is classical rather than quantum system, however his reasoning is based on biological inconsistency. Here we present detailed exposition of molecular neurobiology and define the dynamical timescale of cognitive processes linked to consciousness to be 10-15 ps showing that macroscopic quantum coherent phenomena in brain are not ruled out, and even may provide insight in understanding life, information and consciousness

Steady-State movement related potentials for brain–computer interfacing

An approach for brain-computer interfacing (BCI) by analysis of steady-state movement related potentials (ssMRPs) produced during rhythmic finger movements is proposed in this paper. The neurological background of ssMRPs is briefly reviewed. Averaged ssMRPs represent the development of a lateralized rhythmic potential, and the energy of the EEG signals at the finger tapping frequency can be used for single-trial ssMRP classification. The proposed ssMRP-based BCI approach is tested using the classic Fisher's linear discriminant classifier. Moreover, the influence of the current source density transform on the performance of BCI system is investigated. The averaged correct classification rates (CCRs) as well as averaged information transfer rates (ITRs) for different sliding time windows are reported. Reliable single-trial classification rates of 88%-100% accuracy are achievable at relatively high ITRs. Furthermore, we have been able to achieve CCRs of up to 93% in classification of the ssMRPs recorded during imagined rhythmic finger movements. The merit of this approach is in the application of rhythmic cues for BCI, the relatively simple recording setup, and straightforward computations that make the real-time implementations plausible

Is implicit motor imagery a reliable strategy for a brain computer interface?

Explicit motor imagery (eMI) is a widely used brain computer interface (BCI) paradigm, but not everybody can accomplish this task. Here we propose a BCI based on implicit motor imagery (iMI). We compared classification accuracy between eMI and iMI of hands. Fifteen able bodied people were asked to judge the laterality of hand images presented on a computer screen in a lateral or medial orientation. This judgement task is known to require mental rotation of a person’s own hands which in turn is thought to involve iMI. The subjects were also asked to perform eMI of the hands. Their electroencephalography (EEG) was recorded. Linear classifiers were designed based on common spatial patterns. For discrimination between left and right hand the classifier achieved maximum of 81 ± 8% accuracy for eMI and 83 ± 3% for iMI. These results show that iMI can be used to achieve similar classification accuracy as eMI. Additional classification was performed between iMI in medial and lateral orientations of a single hand; the classifier achieved 81 ± 7% for the left and 78 ± 7% for the right hand which indicate distinctive spatial patterns of cortical activity for iMI of a single hand in different directions. These results suggest that a special brain computer interface based on iMI may be constructed, for people who cannot perform explicit imagination, for rehabilitation of movement or for treatment of bodily spatial neglect

The quick and the dead: when reaction beats intention

Everyday behaviour involves a trade-off between planned actions and reaction to environmental events.Evidence from neurophysiology, neurology and functional brain imaging suggests different neural bases for the control of different movement types. Here we develop a behavioural paradigm to test movement dynamics for intentional versus reaction movements and provide evidence for a ‘reactive advantage’ in movement execution, whereby the same action is executed faster in reaction to an opponent. We placed pairs of participants in competition with each other to make a series of button presses. Within subject analysis of movement times revealed a 10 per cent benefit for reactive actions. This was maintained when opponents performed dissimilar actions, and when participants competed against a computer, suggesting that the effect is not related to facilitation produced by action observation. Rather, faster ballistic movements may be a general property of reactive motor control, potentially providing a useful means of promoting survival