Mind-wandering and Predictive Processes in Narcolepsy: a Putative Mechanism Through Covert REM Intrusions

Idiopathic Hypersomnia Clinical Trial

— NARCOWANDERING  

Official title:

Mind-wandering and Predictive Processes in Narcolepsy: a Putative Mechanism Through Covert REM Intrusions, the NarcoWandering Study

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT06457945
• Other study ID #: 69HCL24_0179
• Status: Not yet recruiting
• Phase: N/A
• Start date: June 15, 2024
• Est. completion date: June 15, 2026

Study information

• Verified date: May 2024
• Source: Hospices Civils de Lyon
• Contact: Laure PETER-DEREX, Professor
• Phone: +33 04 72 07 19 29
• Email: laure.peter-derex[@]chu-lyon.fr
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

Mind wandering is a state in which attention turns away from the external environment or current task to focus on internal thoughts (past experiences, future events, planned actions...). Humans are thought to spend at least one third of their waking lives in this state. Mind wandering can be assessed experimentally by investigating mental content during well-controlled tasks. In this case, task-unrelated thoughts likely to arise during tasks of varying cognitive demand are studied. Mind wandering (=task-unrelated thoughts) has a deleterious effect on cognitive performance in most paradigms, particularly those requiring sustained attention and executive control. However, this phenomenon could also have cognitive benefits, although knowledge on this issue remains limited. For example, it has been suggested that mind wandering could promote creativity, anticipation of future scenarios and prospective memory. In a recent behavioural study, we investigated the cost and benefit of mind wandering in an implicit visual-motor probabilistic learning task (ASRT - Alternating Serial Reaction Time Task). ASRT distinguishes between two fundamental processes: visuomotor performance and implicit statistical learning. While the former reflects visuo-spatial discrimination efficiency, the latter refers to the unintentional acquisition of probabilistic regularities of external inputs. Reduced visuo-spatial accuracy and faster but less accurate responses have been observed during periods of mind-wandering. On the other hand, mind-wandering was associated with enhanced statistical learning reflecting improved predictive processing.

Whereas the study of the neural correlates of mind-wandering is constantly growing, the mechanisms triggering mind-wandering are far from being unravelled, but may involve sleep pressure. Thus, the frequency of mind wandering tends to increase after sleep deprivation or during attention-demanding cognitive tasks, during which neurophysiological markers of local sleep appear. These markers of sleep during wakefulness are frequently observed in hypersomnolence disorders. They are generally defined by the appearance of slow waves (typical of slow wave sleep, SWS). Nevertheless, sleep intrusions during wakefulness may not be limited to non-rapid-eye-movement (NREM) sleep but also concern REM sleep. REM sleep is the sleep state when the most intense forms of dreaming occur, and could therefore be phenomenologically similar to the reverie of mind wandering. Thus, daytime mental wandering could be triggered by intrusions of REM sleep during wakefulness.

Patients with narcolepsy type 1 (NT1) exhibit frequent REM sleep onset during daytime wakefulness. The study of ASRT in this population therefore offers a unique opportunity to investigate the role of REM sleep intrusions in mind wandering. The hypothesis is that mind wandering would be observed more frequently during the ASRT task in NT1 patients (with REM sleep intrusions during wakefulness) than in patients with idiopathic hypersomnia (IH) (with NREM sleep intrusions during wakefulness) and patients with subjective hypersomnolence (little or no sleep intrusion). Furthermore, it could be possible that REM sleep-related mind wandering would be associated with impaired visuomotor performance in terms of accuracy, but improved predictive processing (probabilistic learning) compared to NREM sleep intrusions or no sleep intrusion during the task.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 180
• Est. completion date: June 15, 2026
• Est. primary completion date: June 15, 2026
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years to 65 Years

Eligibility

Inclusion Criteria:

• Patients with NT1 or IH diagnosis according to ICSD3-TR criteria (American Academy of Sleep, 2023)

• For patient with IH: with abnormal Mean Sleep Latency Test (MSLT) (mean latency = 8 min, = 1 SOREMp)

• Patients with subjective hypersomnolence without underlying cause (negative extensive work-up including actigraphy, PSG, MSLT, 24h bedrest, biological tests, MRI, psychiatric consultation; this allows to rule out sleep deprivation, irregular sleep/wake schedule, sleep apnea or other sleep disorders associated with sleep fragmentation, somatic/psychiatric causes of hypersomnolence, sedative substance intake). This type of "controls" have already been used in studies on hypersomnolence disorders.

Exclusion Criteria:

• Cognitive impairment not compatible with the task

• Treatment with antidepressant

• Other cause of hypersomnolence: untreated severe obstructive sleep apnea, sleep-wake circadian rhythm disorders, sleep deprivation, somatic/psychiatric causes of hypersomnolence, sedative substance intake

• Unstable medical or psychiatric condition

• Refusal to participate

Related Conditions & MeSH terms

• Disorders of Excessive Somnolence
• Hypersomnolence
• Idiopathic Hypersomnia
• Narcolepsy
• Narcolepsy Type 1

Intervention

Behavioral:
• ASRT
The task involves the presentation of a visual stimulus in one of four horizontal locations on the screen, and participants are instructed to indicate the location of the target stimulus by pressing the corresponding key on the keyboard. In case of correct response, the target stimulus disappears, and after a 120 ms interstimulus interval, the next stimulus appears. In case of an incorrect response, the target stimulus remains in place until the first correct response. The stimuli follow a probabilistic eight-element sequence, with pattern and random elements alternating with each other. Each participant will be assigned to one of 24 possible sequences throughout the task. The ASRT task will be composed of 25 blocks, with each block containing ten repetitions of the eight-element sequence. After each block, participants will have to take a short break and answer the thought probes before continuing. All patients will perform the task one time.
• Questionnaires
All patients will have to fill questionnaire at the beginning of the study Spontaneous and Deliberate Mind Wandering Scales (SDMWS) Epworth Sleepiness Scale Narcolepsy Severity Index Idiopathic Hypersomnia Severity Scale Hospital Anxiety and Depression scale Horne & Ostberg questionnaire Attention Deficit Hyperactivity Disorder (ADHD) auto-evaluation Pittsburgh Sleep Quality Index Insomnia Severity Index Psychotic-like experiences scale

Device:
• Electrophysiological recordings
A subset of patients in each arm will undergo polysomnography recording (EEG, EOG, EMG, ECG) during the ASRT

Locations

Country	Name	City	State
France	Hôpital de la Croix-Rousse	Lyon

Sponsors (1)

Lead Sponsor	Collaborator
Hospices Civils de Lyon

Country where clinical trial is conducted

France, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Difference in accuracy in responses between high-and low- probability trials during the ASRT	Statistical learning will be assessed by the difference in accuracy (percentage of correct location) in responses between high-and low probability trials during the ASRT in the 3 groups (NT1, IH, subjective sleepiness). Mean accuracy scores will be computed for each block for high-and low- probability trials, and the above learning indices will be extracted for each block.	At inclusion, during the ASRT
Primary	Difference in reaction time in responses between high-and low- probability trials during the ASRT	Statistical learning will be assessed by the difference in reaction time (in ms) in responses between high-and low probability trials during the ASRT in the 3 groups (NT1, IH, subjective sleepiness). Median reaction times will be computed for each block for high-and low- probability trials, and the above learning indices will be extracted for each block.	At inclusion, during the ASRT
Secondary	Subjective states of mind during the ASRT	Distribution of subjective states of mind (mind wandering, mind blanking, focus on task) assessed at the end of each block during the ASRT in the 3 groups (NT1, IH, subjective sleepiness)	At inclusion, at the end of each block of ASRT
Secondary	Neurophysiological patterns during the ASRT	Neurophysiological patterns (EEG, electro-oculography (EOG), electromyography (EMG), ECG to detect sleep intrusion: micro-REM and micro-NREM) will be assessed for each block during the ASRT in all patients and each group of patient (NT1, IH and subjective hypersomnolence) EEG features: spectral power (aperiodic and periodic components, relative and theta-delta/alpha-beta ratio vs pre-task baseline) and specific grapho-elements such as sawtooth waves, alpha bursts and beta oscillations; 2) EMG: muscle tone (% vs pre-task baseline), 3) EOG: presence and % slow vs rapid vs no eye movements, 4) ECG: heart rate, heart rate variability (SDNN, RMSSD), heartbeat evoked potentials)	At inclusion, during the ASRT
Secondary	Spontaneous and Deliberate Mind Wandering Scales (SDMWS) score		At inclusion
Secondary	Epworth Sleepiness Scale score	Subjective sleepiness will be assessed thnaks to Epworth Sleepiness Scale	At inclusion
Secondary	Dream recall frequency	Dream recall frequency (n/week, diary the week before the ASRT)	At inclusion
Secondary	Frequency of sleep-related hallucinations	Frequency of sleep-related hallucinations (nb/week, item of the Narcolepsy Severity Scale)	At inclusion
Secondary	Insomnia Severity Index score	Nighttime sleep quality assessed thanks to the Insomnia Severity Index.	At inclusion