Attention Restraint, Working Memory Capacity, and Mind Wandering: Do Emotional Valence or Intentionality Matter?

Attention restraint appears to mediate the relationship between working memory capacity (WMC) and mind wandering (Kane et al., 2016). Prior work has identifed two dimensions of mind wandering—emotional valence and intentionality. However, less is known about how WMC and attention restraint correlate with these dimensions. Te current study examined the relationship between WMC, attention restraint, and mind wandering by emotional valence and intentionality. A confrmatory factor analysis demonstrated that WMC and attention restraint were strongly correlated, but only attention restraint was related to overall mind wandering, consistent with prior fndings. However, when examining the emotional valence of mind wandering, attention restraint and WMC were related to negatively and positively valenced, but not neutral, mind wandering. Attention restraint was also related to intentional but not unintentional mind wandering. Tese results suggest that WMC and attention restraint predict some, but not all, types of mind wandering

Intact prioritization of fearful faces during continuous flash suppression in psychopathy

Affective state recognition and in particular the identification of fear is known to be impaired in psychopathy. It is unclear, however, whether this reflects a deficit in basic perception (‘fear blindness’) or a deficit in later cognitive processing. To test for a perceptual deficit, 63 male incarcerated offenders, assessed with the Hare Psychopathy Checklist-Revised (PCL-R), and 59 age-matched control participants detected fearful, neutral, and happy facial expressions rendered invisible through continuous flash suppression (CFS), a strong interocular suppression technique. Consistent with previous CFS studies on children, student and community samples, fearful faces were detected faster than neutral faces, which were detected faster than happy faces. Detection of emotional faces was unimpaired in offenders, with strong evidence for a full-blown fear advantage. Moreover, the fear advantage was not reduced in the 20 offenders qualifying as psychopaths according to the PCL-R, and there was no correlation between the fear advantage and PCL-R scores in the 63 incarcerated offenders. These results show that basic visual detection of fearful faces is unimpaired in psychopathy. Deficits in the processing of fearful facial expressions in psychopathy may thus not reflect fear blindness, but impairments at later post-perceptual processing stages related to attention, memory, decision-making, or language

Objective neurophysiologic markers to aid assessment of prolonged disorders of consciousness (PDoC)

Clinical assessments of individuals with cognitive-motor dissociation (CMD) following brain injury are both challenging and error prone. Prior studies have shown that electroencephalographic or EEG-based brain computer interface protocols for motor-command following (MCF) and differences in the N1 and P3 components of auditory evoked potentials (AEPs) in response to an auditory oddball paradigm can provide a more accurate, quantitative assessment of children with CMD (Kim et al., 2022). This study investigates if these EEG measures would aid in the assessment of adults with prolonged disorders of consciousness (PDoC); and if brain-computer interface (BCI) protocols using motor-imagery decoding tasks or latencies of AEPs can improve cognitive assessments of individuals with PDoC.Methods: EEG data from nine individuals with PDoC, including cases of unresponsive wakefulness syndrome (UWS), minimally conscious state (MCS), and locked-in syndrome (LIS), were recorded using a 16-channel gNautilus system (g.tec). The MCF protocol included up to 12 sessions of 240 trials each. During the first six sessions, participants underwent training with and without feedback, to learn to consistently imagine moving one of two limbs, such as the left or right hand, in response to auditory cues. From the seventh session onward, this binary imagery task was associated with yes and no and applied in a closed question-and-answer task. Separately, the auditory oddball protocol included at least two sessions, approximately 10 days apart. Each session involved 2 five-minute sets of auditory stimuli: 340ms square-wave beeps at frequencies of 400 Hz (standard) or 575 Hz (deviant), along with various novel sounds, following a standard:deviant:novel ratio of 27:8:6 per set. Results: Mean N1 AEP latencies had significant group differences due to lower latencies for the LIS and MCS groups as compared to the UWS group (LIS v UWS – p &lt; 0.001; MCS v UWS – p = 0.005). Furthermore, mean AEP latencies were found to be negatively correlated with the mean of the decoding accuracies (DA) obtained from significant runs for each participant during the corresponding motor-imagery sessions (i.e., latencies decreased as DA increased, p = 0.011, one-tailed).Conclusion: The latency of the N1 AEP may aid the assessment of awareness in PDoC. The finding that N1 latencies are correlated with motor imagery DA across groups suggest that both movement-independent measures could be used complementarily to improve accuracy in detecting consciousness in adults with PDoC.<br/

Objective neurophysiologic markers to aid assessment of prolonged disorders of consciousness (PDoC)

Abstract: Clinical assessments of individuals with cognitive-motor dissociation (CMD) following brain injury are both challenging and error prone. Prior studies have shown that electroencephalographic or EEG-based brain-computer interface protocols for motor-command following (MCF) and differences in the N1 and P3 components of auditory evoked potentials (AEPs) in response to an auditory oddball paradigm, can provide a more accurate, quantitative assessment of children with CMD. This study investigates if these EEG measures would aid in the assessment of adults with prolonged disorders of consciousness (PDoC); and if brain-computer interface (BCI) protocols using motor-imagery decoding tasks or latencies of AEPs can improve cognitive assessments of individuals with PDoC. Methods: EEG data from nine individuals with PDoC, including cases of unresponsive wakefulness syndrome (UWS), minimally conscious state (MCS), and locked-in syndrome (LIS), were recorded using a 16-channel gNautilus system (g.tec). The MCF protocol included up to 12 sessions of 240 trials each. During the first six sessions, participants underwent training with and without feedback, to learn to consistently imagine moving one of two limbs, such as the left or right hand, in response to auditory cues. From the seventh session onward, this binary imagery task was associated with yes and no and applied in a closed question-and-answer task. Separately, the auditory oddball protocol included at least two sessions, approximately 10 days apart. Each session involved 2 five-minute sets of auditory stimuli: 340ms square-wave beeps at frequencies of 400 Hz (standard) or 575 Hz (deviant), along with various novel sounds, following a standard:deviant:novel ratio of 27:8:6 per set. Results: Mean N1 AEP latencies had significant group differences due to lower latencies for the LIS and MCS groups as compared to the UWS group (LIS v UWS - p &lt; 0.001; MCS v UWS - p = 0.005). Furthermore, mean AEP latencies were found to be negatively correlated with the mean of the decoding accuracies (DA) obtained from significant runs for each participant during the corresponding motor-imagery sessions (i.e., latencies decreased as DA increased, p = 0.011, one-tailed). Conclusion: The latency of the N1 AEP may aid the assessment of awareness in PDoC. The finding that N1 latencies are correlated with motor imagery DA across groups suggest that both movement-independent measures could be used complementarily to improve accuracy in detecting consciousness in adults with PDoC

Objective neurophysiologic markers to aid assessment of prolonged disorders of consciousness (PDoC)

Abstract: Clinical assessments of individuals with cognitive-motor dissociation (CMD) following brain injury are both challenging and error prone. Prior studies have shown that electroencephalographic or EEG-based brain-computer interface protocols for motor-command following (MCF) and differences in the N1 and P3 components of auditory evoked potentials (AEPs) in response to an auditory oddball paradigm, can provide a more accurate, quantitative assessment of children with CMD. This study investigates if these EEG measures would aid in the assessment of adults with prolonged disorders of consciousness (PDoC); and if brain-computer interface (BCI) protocols using motor-imagery decoding tasks or latencies of AEPs can improve cognitive assessments of individuals with PDoC. Methods: EEG data from nine individuals with PDoC, including cases of unresponsive wakefulness syndrome (UWS), minimally conscious state (MCS), and locked-in syndrome (LIS), were recorded using a 16-channel gNautilus system (g.tec). The MCF protocol included up to 12 sessions of 240 trials each. During the first six sessions, participants underwent training with and without feedback, to learn to consistently imagine moving one of two limbs, such as the left or right hand, in response to auditory cues. From the seventh session onward, this binary imagery task was associated with yes and no and applied in a closed question-and-answer task. Separately, the auditory oddball protocol included at least two sessions, approximately 10 days apart. Each session involved 2 five-minute sets of auditory stimuli: 340ms square-wave beeps at frequencies of 400 Hz (standard) or 575 Hz (deviant), along with various novel sounds, following a standard:deviant:novel ratio of 27:8:6 per set. Results: Mean N1 AEP latencies had significant group differences due to lower latencies for the LIS and MCS groups as compared to the UWS group (LIS v UWS - p &lt; 0.001; MCS v UWS - p = 0.005). Furthermore, mean AEP latencies were found to be negatively correlated with the mean of the decoding accuracies (DA) obtained from significant runs for each participant during the corresponding motor-imagery sessions (i.e., latencies decreased as DA increased, p = 0.011, one-tailed). Conclusion: The latency of the N1 AEP may aid the assessment of awareness in PDoC. The finding that N1 latencies are correlated with motor imagery DA across groups suggest that both movement-independent measures could be used complementarily to improve accuracy in detecting consciousness in adults with PDoC