Let me decide!
Attention Orienting in P300-based Brain-Computer Interface for Patients with Amyotrophic Lateral Sclerosis
Marchetti Piccione Silvoni Priftis
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Dipartimento di Psicologia dello Sviluppo e della Socializzazione, Università di Padova, Italia - 2 IRCCS Ospedale San Camillo, Lido-Venezia, Italia - 3 Dipartimento di Psicologia Generale, Università di Padova, Italia
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Corresponding author: mauro.marchetti@unipd.it
1. Introduction
TRIAL TIMELINE Trial timeline Endogenous condition
SOA 2500 ms
Exogenous condition
Neurological diseases that affect the motor system may impair communication abilities of patients, as in the case of amyotrophic lateral sclerosis (ALS). This pathology might evolve in the completely locked-in syndrome (LIS), a condition in which patients remain conscious but cannot move their muscles. For instance, they may become unable to express their opinions and decisions on important questions regarding their clinical treatment or their living and biological wills. Brain-computer interfaces (BCIs) are communicative prostheses that utilise neurophysiological brain-signals (e.g., the P300) to control devices without muscular involvement (Figure 1), allowing ALS-LIS patients to communicate (Birbaumer, 2006). Several studies have shown that incomplete ALS-LIS patients can use a BCI that is based on the electroencephalogram (EEG) for communication. To date, however, none of the reported patients with complete ALS-LIS has been able to communicate using a BCI (Kubler & Birbaumer, 2008). In addition, the effects of cognitive mechanisms (i.e., executive functions, attention, memory, etc.) involved in brain signal elicitation in BCIs have not been investigated to date. We tested the effect of attention orienting on a P300-guided BCI, by comparing two visual interfaces which elicited Method different modalities of implicit attention orienting (exogenous vs. endogenous; Posner, 1980).
Initial situation: The blue-dot cursor, the central fixation point and four black and white target icons were displayed on a black screen
Figure 2 (*)
M.1,+ F.2 2 S. K.2,3
Classifying recorded epochs: - 200 Hz sampling - 0.15 Hz to 30 Hz bandpass filter - ICA decomposition
1st trial Endogenous Interface Random presentation of letters in the screen centre (A=“alto”, B=“basso”, D=“destra”, S=“sinistra”) each representing a direction, for 900 ms Exogenous Interface Random flashing of peripheral icons for 75 ms
Feedback: - Feature Extraction
- SVM classification: P300 present / absent
The cursor was moved according to the desired direction when the P300 was detected by the classifying system; otherwise the cursor was not moved
3. Results The main effect of Interface was significant for both Performance [F(1, 6) = 3.06, p < .01] and Communication speed [F(1, 6) = 7.36, p < .05], whereas neither the main effects of Group nor the interaction Interface by Group were significant. Planned contrast revealed that ALS patients showed higher Performance with the “endogenous” interface than with the “exogenous” interface (Figure 3), t(3) = -4.31, p < .05. Importantly, ALS patients’ responses did not differ statistically from those of healthy controls. PERFORMANCE
Signal Acquisition
Signal digitalization
Signal processing Feature extraction
Command to device
Classification algorithms
(%; 1 SEM)
Brain-Computer Interface System
Feedback (bit/min; 1 SEM)
Figure 1
COMMUNICATION SPEED
2. Methods Four ALS patients (mean age = 56.7; males = 3) and four matched healthy controls (mean age = 52.3; males = 3) performed 16 sessions with the abovementioned interfaces to move a virtual cursor towards icons representing activities of daily life. Brain waves were recorded on each trial (Figure 2) and were subsequently classified on-line using an ad-hoc three-step algorithm (Independent component analysis (ICA) -> extraction of 78 features -> support vector machine (SVM) classification). Each time the P300 was correctly classified, the cursor moved toward the target position. The dependent variables were: Performance, defined as the percentage of correctly classified epochs, and Communication Speed, defined as the quantity of information transmitted from the brain signal to the system, measured in bit/min. REFERENCES
Figure 3
4. Conclusions ALS patients are able to use endogenous attention orienting and, by doing so, they can increase their performance on a P300-guided BCI. Now more than ever, the ethical debate on critical clinical conditions, such as ALS-LIS, is open (Haselanger et al., 2009): who can legally decide for a compos-mentis but locked-in person on end-of-life questions? An efficient cognitive-based BCI may have the considerable ethical implication of “giving a voice” to ALS-LIS patients.
- Birbaumer, N. (2006). Brain-computer-interface research: Coming of age. Clinical Neurophysiology, 117, 479-483. - Kubler, A., & Birbaumer, N. (2008). Brain-computer interfaces and communication in paralysis: Extinction of goal directed thinking in completely paralysed patients? Clinical Neurophysiology, 119, 2658–2666. - Posner, M. I. (1980). Orienting of attention. Quarterly Journal of Experimental Psychology, 32, 3-25. - Haselager, P., Vlek, R., Hill, J., & Nijboer, F. (2009). A note on ethical aspects of BCI. Neural Networks, 22, 1352-1357. * Icons in Figure 2 are from Miceli, G., Laudanna, A., Burani, C., & Capasso, R. (1994). Batteria per l’analisi dei deficit afasici (B.A.D.A.). Roma: CEPSAG.